Security Applications Of Computer Motion Detection

NASA Astrophysics Data System (ADS)

Bernat, Andrew P.; Nelan, Joseph; Riter, Stephen; Frankel, Harry

1987-05-01

An important area of application of computer vision is the detection of human motion in security systems. This paper describes the development of a computer vision system which can detect and track human movement across the international border between the United States and Mexico. Because of the wide range of environmental conditions, this application represents a stringent test of computer vision algorithms for motion detection and object identification. The desired output of this vision system is accurate, real-time locations for individual aliens and accurate statistical data as to the frequency of illegal border crossings. Because most detection and tracking routines assume rigid body motion, which is not characteristic of humans, new algorithms capable of reliable operation in our application are required. Furthermore, most current detection and tracking algorithms assume a uniform background against which motion is viewed - the urban environment along the US-Mexican border is anything but uniform. The system works in three stages: motion detection, object tracking and object identi-fication. We have implemented motion detection using simple frame differencing, maximum likelihood estimation, mean and median tests and are evaluating them for accuracy and computational efficiency. Due to the complex nature of the urban environment (background and foreground objects consisting of buildings, vegetation, vehicles, wind-blown debris, animals, etc.), motion detection alone is not sufficiently accurate. Object tracking and identification are handled by an expert system which takes shape, location and trajectory information as input and determines if the moving object is indeed representative of an illegal border crossing.

An ice-motion tracking system at the Alaska SAR facility

NASA Technical Reports Server (NTRS)

Kwok, Ronald; Curlander, John C.; Pang, Shirley S.; Mcconnell, Ross

1990-01-01

An operational system for extracting ice-motion information from synthetic aperture radar (SAR) imagery is being developed as part of the Alaska SAR Facility. This geophysical processing system (GPS) will derive ice-motion information by automated analysis of image sequences acquired by radars on the European ERS-1, Japanese ERS-1, and Canadian RADARSAT remote sensing satellites. The algorithm consists of a novel combination of feature-based and area-based techniques for the tracking of ice floes that undergo translation and rotation between imaging passes. The system performs automatic selection of the image pairs for input to the matching routines using an ice-motion estimator. It is designed to have a daily throughput of ten image pairs. A description is given of the GPS system, including an overview of the ice-motion-tracking algorithm, the system architecture, and the ice-motion products that will be available for distribution to geophysical data users.

SU-C-18A-02: Image-Based Camera Tracking: Towards Registration of Endoscopic Video to CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ingram, S; Rao, A; Wendt, R

Purpose: Endoscopic examinations are routinely performed on head and neck and esophageal cancer patients. However, these images are underutilized for radiation therapy because there is currently no way to register them to a CT of the patient. The purpose of this work is to develop a method to track the motion of an endoscope within a structure using images from standard clinical equipment. This method will be incorporated into a broader endoscopy/CT registration framework. Methods: We developed a software algorithm to track the motion of an endoscope within an arbitrary structure. We computed frame-to-frame rotation and translation of the cameramore » by tracking surface points across the video sequence and utilizing two-camera epipolar geometry. The resulting 3D camera path was used to recover the surrounding structure via triangulation methods. We tested this algorithm on a rigid cylindrical phantom with a pattern spray-painted on the inside. We did not constrain the motion of the endoscope while recording, and we did not constrain our measurements using the known structure of the phantom. Results: Our software algorithm can successfully track the general motion of the endoscope as it moves through the phantom. However, our preliminary data do not show a high degree of accuracy in the triangulation of 3D point locations. More rigorous data will be presented at the annual meeting. Conclusion: Image-based camera tracking is a promising method for endoscopy/CT image registration, and it requires only standard clinical equipment. It is one of two major components needed to achieve endoscopy/CT registration, the second of which is tying the camera path to absolute patient geometry. In addition to this second component, future work will focus on validating our camera tracking algorithm in the presence of clinical imaging features such as patient motion, erratic camera motion, and dynamic scene illumination.« less

Estimation of contour motion and deformation for nonrigid object tracking

NASA Astrophysics Data System (ADS)

Shao, Jie; Porikli, Fatih; Chellappa, Rama

2007-08-01

We present an algorithm for nonrigid contour tracking in heavily cluttered background scenes. Based on the properties of nonrigid contour movements, a sequential framework for estimating contour motion and deformation is proposed. We solve the nonrigid contour tracking problem by decomposing it into three subproblems: motion estimation, deformation estimation, and shape regulation. First, we employ a particle filter to estimate the global motion parameters of the affine transform between successive frames. Then we generate a probabilistic deformation map to deform the contour. To improve robustness, multiple cues are used for deformation probability estimation. Finally, we use a shape prior model to constrain the deformed contour. This enables us to retrieve the occluded parts of the contours and accurately track them while allowing shape changes specific to the given object types. Our experiments show that the proposed algorithm significantly improves the tracker performance.

Management of three-dimensional intrafraction motion through real-time DMLC tracking.

PubMed

Sawant, Amit; Venkat, Raghu; Srivastava, Vikram; Carlson, David; Povzner, Sergey; Cattell, Herb; Keall, Paul

2008-05-01

Tumor tracking using a dynamic multileaf collimator (DMLC) represents a promising approach for intrafraction motion management in thoracic and abdominal cancer radiotherapy. In this work, we develop, empirically demonstrate, and characterize a novel 3D tracking algorithm for real-time, conformal, intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT)-based radiation delivery to targets moving in three dimensions. The algorithm obtains real-time information of target location from an independent position monitoring system and dynamically calculates MLC leaf positions to account for changes in target position. Initial studies were performed to evaluate the geometric accuracy of DMLC tracking of 3D target motion. In addition, dosimetric studies were performed on a clinical linac to evaluate the impact of real-time DMLC tracking for conformal, step-and-shoot (S-IMRT), dynamic (D-IMRT), and VMAT deliveries to a moving target. The efficiency of conformal and IMRT delivery in the presence of tracking was determined. Results show that submillimeter geometric accuracy in all three dimensions is achievable with DMLC tracking. Significant dosimetric improvements were observed in the presence of tracking for conformal and IMRT deliveries to moving targets. A gamma index evaluation with a 3%-3 mm criterion showed that deliveries without DMLC tracking exhibit between 1.7 (S-IMRT) and 4.8 (D-IMRT) times more dose points that fail the evaluation compared to corresponding deliveries with tracking. The efficiency of IMRT delivery, as measured in the lab, was observed to be significantly lower in case of tracking target motion perpendicular to MLC leaf travel compared to motion parallel to leaf travel. Nevertheless, these early results indicate that accurate, real-time DMLC tracking of 3D tumor motion is feasible and can potentially result in significant geometric and dosimetric advantages leading to more effective management of intrafraction motion.

Binocular Vision-Based Position and Pose of Hand Detection and Tracking in Space

NASA Astrophysics Data System (ADS)

Jun, Chen; Wenjun, Hou; Qing, Sheng

After the study of image segmentation, CamShift target tracking algorithm and stereo vision model of space, an improved algorithm based of Frames Difference and a new space point positioning model were proposed, a binocular visual motion tracking system was constructed to verify the improved algorithm and the new model. The problem of the spatial location and pose of the hand detection and tracking have been solved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chao, M; Yuan, Y; Lo, Y

Purpose: To develop a novel strategy to extract the lung tumor motion from cone beam CT (CBCT) projections by an active contour model with interpolated respiration learned from diaphragm motion. Methods: Tumor tracking on CBCT projections was accomplished with the templates derived from planning CT (pCT). There are three major steps in the proposed algorithm: 1) The pCT was modified to form two CT sets: a tumor removed pCT and a tumor only pCT, the respective digitally reconstructed radiographs DRRtr and DRRto following the same geometry of the CBCT projections were generated correspondingly. 2) The DRRtr was rigidly registered withmore » the CBCT projections on the frame-by-frame basis. Difference images between CBCT projections and the registered DRRtr were generated where the tumor visibility was appreciably enhanced. 3) An active contour method was applied to track the tumor motion on the tumor enhanced projections with DRRto as templates to initialize the tumor tracking while the respiratory motion was compensated for by interpolating the diaphragm motion estimated by our novel constrained linear regression approach. CBCT and pCT from five patients undergoing stereotactic body radiotherapy were included in addition to scans from a Quasar phantom programmed with known motion. Manual tumor tracking was performed on CBCT projections and was compared to the automatic tracking to evaluate the algorithm accuracy. Results: The phantom study showed that the error between the automatic tracking and the ground truth was within 0.2mm. For the patients the discrepancy between the calculation and the manual tracking was between 1.4 and 2.2 mm depending on the location and shape of the lung tumor. Similar patterns were observed in the frequency domain. Conclusion: The new algorithm demonstrated the feasibility to track the lung tumor from noisy CBCT projections, providing a potential solution to better motion management for lung radiation therapy.« less

SU-F-303-11: Implementation and Applications of Rapid, SIFT-Based Cine MR Image Binning and Region Tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mazur, T; Wang, Y; Fischer-Valuck, B

2015-06-15

Purpose: To develop a novel and rapid, SIFT-based algorithm for assessing feature motion on cine MR images acquired during MRI-guided radiotherapy treatments. In particular, we apply SIFT descriptors toward both partitioning cine images into respiratory states and tracking regions across frames. Methods: Among a training set of images acquired during a fraction, we densely assign SIFT descriptors to pixels within the images. We cluster these descriptors across all frames in order to produce a dictionary of trackable features. Associating the best-matching descriptors at every frame among the training images to these features, we construct motion traces for the features. Wemore » use these traces to define respiratory bins for sorting images in order to facilitate robust pixel-by-pixel tracking. Instead of applying conventional methods for identifying pixel correspondences across frames we utilize a recently-developed algorithm that derives correspondences via a matching objective for SIFT descriptors. Results: We apply these methods to a collection of lung, abdominal, and breast patients. We evaluate the procedure for respiratory binning using target sites exhibiting high-amplitude motion among 20 lung and abdominal patients. In particular, we investigate whether these methods yield minimal variation between images within a bin by perturbing the resulting image distributions among bins. Moreover, we compare the motion between averaged images across respiratory states to 4DCT data for these patients. We evaluate the algorithm for obtaining pixel correspondences between frames by tracking contours among a set of breast patients. As an initial case, we track easily-identifiable edges of lumpectomy cavities that show minimal motion over treatment. Conclusions: These SIFT-based methods reliably extract motion information from cine MR images acquired during patient treatments. While we performed our analysis retrospectively, the algorithm lends itself to prospective motion assessment. Applications of these methods include motion assessment, identifying treatment windows for gating, and determining optimal margins for treatment.« less

Planning and delivery of four-dimensional radiation therapy with multileaf collimators

NASA Astrophysics Data System (ADS)

McMahon, Ryan L.

This study is an investigation of the application of multileaf collimators (MLCs) to the treatment of moving anatomy with external beam radiation therapy. First, a method for delivering intensity modulated radiation therapy (IMRT) to moving tumors is presented. This method uses an MLC control algorithm that calculates appropriate MLC leaf speeds in response to feedback from real-time imaging. The algorithm does not require a priori knowledge of a tumor's motion, and is based on the concept of self-correcting DMLC leaf trajectories . This gives the algorithm the distinct advantage of allowing for correction of DMLC delivery errors without interrupting delivery. The algorithm is first tested for the case of one-dimensional (1D) rigid tumor motion in the beam's eye view (BEV). For this type of motion, it is shown that the real-time tracking algorithm results in more accurate deliveries, with respect to delivered intensity, than those which ignore motion altogether. This is followed by an appropriate extension of the algorithm to two-dimensional (2D) rigid motion in the BEV. For this type of motion, it is shown that the 2D real-time tracking algorithm results in improved accuracy (in the delivered intensity) in comparison to deliveries which ignore tumor motion or only account for tumor motion which is aligned with MLC leaf travel. Finally, a method is presented for designing DMLC leaf trajectories which deliver a specified intensity over a moving tumor without overexposing critical structures which exhibit motion patterns that differ from that of the tumor. In addition to avoiding overexposure of critical organs, the method can, in the case shown, produce deliveries that are superior to anything achievable using stationary anatomy. In this regard, the method represents a systematic way to include anatomical motion as a degree of freedom in the optimization of IMRT while producing treatment plans that are deliverable with currently available technology. These results, combined with those related to the real-time MLC tracking algorithm, show that an MLC is a promising tool to investigate for the delivery of four-dimensional radiation therapy.

MRI-guided tumor tracking in lung cancer radiotherapy

NASA Astrophysics Data System (ADS)

Cerviño, Laura I.; Du, Jiang; Jiang, Steve B.

2011-07-01

Precise tracking of lung tumor motion during treatment delivery still represents a challenge in radiation therapy. Prototypes of MRI-linac hybrid systems are being created which have the potential of ionization-free real-time imaging of the tumor. This study evaluates the performance of lung tumor tracking algorithms in cine-MRI sagittal images from five healthy volunteers. Visible vascular structures were used as targets. Volunteers performed several series of regular and irregular breathing. Two tracking algorithms were implemented and evaluated: a template matching (TM) algorithm in combination with surrogate tracking using the diaphragm (surrogate was used when the maximum correlation between the template and the image in the search window was less than specified), and an artificial neural network (ANN) model based on the principal components of a region of interest that encompasses the target motion. The mean tracking error ē and the error at 95% confidence level e95 were evaluated for each model. The ANN model led to ē = 1.5 mm and e95 = 4.2 mm, while TM led to ē = 0.6 mm and e95 = 1.0 mm. An extra series was considered separately to evaluate the benefit of using surrogate tracking in combination with TM when target out-of-plane motion occurs. For this series, the mean error was 7.2 mm using only TM and 1.7 mm when the surrogate was used in combination with TM. Results show that, as opposed to tracking with other imaging modalities, ANN does not perform well in MR-guided tracking. TM, however, leads to highly accurate tracking. Out-of-plane motion could be addressed by surrogate tracking using the diaphragm, which can be easily identified in the images.

A Real-Time Position-Locating Algorithm for CCD-Based Sunspot Tracking

NASA Technical Reports Server (NTRS)

Taylor, Jaime R.

1996-01-01

NASA Marshall Space Flight Center's (MSFC) EXperimental Vector Magnetograph (EXVM) polarimeter measures the sun's vector magnetic field. These measurements are taken to improve understanding of the sun's magnetic field in the hopes to better predict solar flares. Part of the procedure for the EXVM requires image motion stabilization over a period of a few minutes. A high speed tracker can be used to reduce image motion produced by wind loading on the EXVM, fluctuations in the atmosphere and other vibrations. The tracker consists of two elements, an image motion detector and a control system. The image motion detector determines the image movement from one frame to the next and sends an error signal to the control system. For the ground based application to reduce image motion due to atmospheric fluctuations requires an error determination at the rate of at least 100 hz. It would be desirable to have an error determination rate of 1 kHz to assure that higher rate image motion is reduced and to increase the control system stability. Two algorithms are presented that are typically used for tracking. These algorithms are examined for their applicability for tracking sunspots, specifically their accuracy if only one column and one row of CCD pixels are used. To examine the accuracy of this method two techniques are used. One involves moving a sunspot image a known distance with computer software, then applying the particular algorithm to see how accurately it determines this movement. The second technique involves using a rate table to control the object motion, then applying the algorithms to see how accurately each determines the actual motion. Results from these two techniques are presented.

Motion control of the rabbit ankle joint with a flat interface nerve electrode.

PubMed

Park, Hyun-Joo; Durand, Dominique M

2015-12-01

A flat interface nerve electrode (FINE) has been shown to improve fascicular and subfascicular selectivity. A recently developed novel control algorithm for FINE was applied to motion control of the rabbit ankle. A 14-contact FINE was placed on the rabbit sciatic nerve (n = 8), and ankle joint motion was controlled for sinusoidal trajectories and filtered random trajectories. To this end, a real-time controller was implemented with a multiple-channel current stimulus isolator. The performance test results showed good tracking performance of rabbit ankle joint motion for filtered random trajectories and sinusoidal trajectories (0.5 Hz and 1.0 Hz) with <10% average root-mean-square (RMS) tracking error, whereas the average range of ankle joint motion was between -20.0 ± 9.3° and 18.1 ± 8.8°. The proposed control algorithm enables the use of a multiple-contact nerve electrode for motion trajectory tracking control of musculoskeletal systems. © 2015 Wiley Periodicals, Inc.

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caillet, V; Colvill, E; Royal North Shore Hospital, St Leonards, Sydney

2016-06-15

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physicalmore » experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use of either algorithm for clinical implementation.« less

Poster - 51: A tumor motion-compensating system with tracking and prediction – a proof-of-concept study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Kaiming; Teo, Peng; Kawalec, Philip

2016-08-15

Purpose: This work reports on the development of a mechanical slider system for the counter-steering of tumor motion in adaptive Radiation Therapy (RT). The tumor motion was tracked using a weighted optical flow algorithm and its position is being predicted with a neural network (NN). Methods: The components of the proposed mechanical counter-steering system includes: (1) an actuator which provides the tumor motion, (2) the motion detection using an optical flow algorithm, (3) motion prediction using a neural network, (4) a control module and (5) a mechanical slider to counter-steer the anticipated motion of the tumor phantom. An asymmetrical cosinemore » function and five patient traces (P1–P5) were used to evaluate the tracking of a 3D printed lung tumor. In the proposed mechanical counter-steering system, both actuator (Zaber NA14D60) and slider (Zaber A-BLQ0070-E01) were programed to move independently with LabVIEW and their positions were recorded by 2 potentiometers (ETI LCP12S-25). The accuracy of this counter-steering system is given by the difference between the two potentiometers. Results: The inherent accuracy of the system, measured using the cosine function, is −0.15 ± 0.06 mm. While the errors when tracking and prediction were included, is (0.04 ± 0.71) mm. Conclusion: A prototype tumor motion counter-steering system with tracking and prediction was implemented. The inherent errors are small in comparison to the tracking and prediction errors, which in turn are small in comparison to the magnitude of tumor motion. The results show that this system is suited for evaluating RT tracking and prediction.« less

Target motion tracking in MRI-guided transrectal robotic prostate biopsy.

PubMed

Tadayyon, Hadi; Lasso, Andras; Kaushal, Aradhana; Guion, Peter; Fichtinger, Gabor

2011-11-01

MRI-guided prostate needle biopsy requires compensation for organ motion between target planning and needle placement. Two questions are studied and answered in this paper: 1) is rigid registration sufficient in tracking the targets with an error smaller than the clinically significant size of prostate cancer and 2) what is the effect of the number of intraoperative slices on registration accuracy and speed? we propose multislice-to-volume registration algorithms for tracking the biopsy targets within the prostate. Three orthogonal plus additional transverse intraoperative slices are acquired in the approximate center of the prostate and registered with a high-resolution target planning volume. Both rigid and deformable scenarios were implemented. Both simulated and clinical MRI-guided robotic prostate biopsy data were used to assess tracking accuracy. average registration errors in clinical patient data were 2.6 mm for the rigid algorithm and 2.1 mm for the deformable algorithm. rigid tracking appears to be promising. Three tracking slices yield significantly high registration speed with an affordable error.

Multiple feature fusion via covariance matrix for visual tracking

NASA Astrophysics Data System (ADS)

Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Wang, Xin; Sun, Hui

2018-04-01

Aiming at the problem of complicated dynamic scenes in visual target tracking, a multi-feature fusion tracking algorithm based on covariance matrix is proposed to improve the robustness of the tracking algorithm. In the frame-work of quantum genetic algorithm, this paper uses the region covariance descriptor to fuse the color, edge and texture features. It also uses a fast covariance intersection algorithm to update the model. The low dimension of region covariance descriptor, the fast convergence speed and strong global optimization ability of quantum genetic algorithm, and the fast computation of fast covariance intersection algorithm are used to improve the computational efficiency of fusion, matching, and updating process, so that the algorithm achieves a fast and effective multi-feature fusion tracking. The experiments prove that the proposed algorithm can not only achieve fast and robust tracking but also effectively handle interference of occlusion, rotation, deformation, motion blur and so on.

Adaptive vehicle motion estimation and prediction

NASA Astrophysics Data System (ADS)

Zhao, Liang; Thorpe, Chuck E.

1999-01-01

Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.

Structure preserving clustering-object tracking via subgroup motion pattern segmentation

NASA Astrophysics Data System (ADS)

Fan, Zheyi; Zhu, Yixuan; Jiang, Jiao; Weng, Shuqin; Liu, Zhiwen

2018-01-01

Tracking clustering objects with similar appearances simultaneously in collective scenes is a challenging task in the field of collective motion analysis. Recent work on clustering-object tracking often suffers from poor tracking accuracy and terrible real-time performance due to the neglect or the misjudgment of the motion differences among objects. To address this problem, we propose a subgroup motion pattern segmentation framework based on a multilayer clustering structure and establish spatial constraints only among objects in the same subgroup, which entails having consistent motion direction and close spatial position. In addition, the subgroup segmentation results are updated dynamically because crowd motion patterns are changeable and affected by objects' destinations and scene structures. The spatial structure information combined with the appearance similarity information is used in the structure preserving object tracking framework to track objects. Extensive experiments conducted on several datasets containing multiple real-world crowd scenes validate the accuracy and the robustness of the presented algorithm for tracking objects in collective scenes.

A tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel independent brake from moderate driving to limit handling

NASA Astrophysics Data System (ADS)

Joa, Eunhyek; Park, Kwanwoo; Koh, Youngil; Yi, Kyongsu; Kim, Kilsoo

2018-04-01

This paper presents a tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel braking for enhanced performance from moderate driving to limit handling. The proposed algorithm adopted hierarchical structure: supervisor - desired motion tracking controller - optimisation-based control allocation. In the supervisor, by considering transient cornering characteristics, desired vehicle motion is calculated. In the desired motion tracking controller, in order to track desired vehicle motion, virtual control input is determined in the manner of sliding mode control. In the control allocation, virtual control input is allocated to minimise cost function. The cost function consists of two major parts. First part is a slip-based tyre friction utilisation quantification, which does not need a tyre force estimation. Second part is an allocation guideline, which guides optimally allocated inputs to predefined solution. The proposed algorithm has been investigated via simulation from moderate driving to limit handling scenario. Compared to Base and direct yaw moment control system, the proposed algorithm can effectively reduce tyre dissipation energy in the moderate driving situation. Moreover, the proposed algorithm enhances limit handling performance compared to Base and direct yaw moment control system. In addition to comparison with Base and direct yaw moment control, comparison the proposed algorithm with the control algorithm based on the known tyre force information has been conducted. The results show that the performance of the proposed algorithm is similar with that of the control algorithm with the known tyre force information.

Inertial Sensor-Based Touch and Shake Metaphor for Expressive Control of 3D Virtual Avatars

PubMed Central

Patil, Shashidhar; Chintalapalli, Harinadha Reddy; Kim, Dubeom; Chai, Youngho

2015-01-01

In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion control input device with a sensor fusion algorithm. The algorithm enables user hand motions to be tracked in 3D space via magnetic, angular rate, and gravity sensors. A quaternion-based complementary filter is implemented to reduce noise and drift. An algorithm based on dynamic time-warping is developed for efficient recognition of dynamic hand gestures with real-time automatic hand gesture segmentation. Our approach enables the recognition of gestures and estimates gesture variations for continuous interaction. We demonstrate the gesture expressivity using an interactive flexible gesture mapping interface for authoring and controlling a 3D virtual avatar and its motion by tracking user dynamic hand gestures. This synthesizes stylistic variations in a 3D virtual avatar, producing motions that are not present in the motion database using hand gesture sequences from a single inertial motion sensor. PMID:26094629

Marker-less multi-frame motion tracking and compensation in PET-brain imaging

NASA Astrophysics Data System (ADS)

Lindsay, C.; Mukherjee, J. M.; Johnson, K.; Olivier, P.; Song, X.; Shao, L.; King, M. A.

2015-03-01

In PET brain imaging, patient motion can contribute significantly to the degradation of image quality potentially leading to diagnostic and therapeutic problems. To mitigate the image artifacts resulting from patient motion, motion must be detected and tracked then provided to a motion correction algorithm. Existing techniques to track patient motion fall into one of two categories: 1) image-derived approaches and 2) external motion tracking (EMT). Typical EMT requires patients to have markers in a known pattern on a rigid too attached to their head, which are then tracked by expensive and bulky motion tracking camera systems or stereo cameras. This has made marker-based EMT unattractive for routine clinical application. Our main contributions are the development of a marker-less motion tracking system that uses lowcost, small depth-sensing cameras which can be installed in the bore of the imaging system. Our motion tracking system does not require anything to be attached to the patient and can track the rigid transformation (6-degrees of freedom) of the patient's head at a rate 60 Hz. We show that our method can not only be used in with Multi-frame Acquisition (MAF) PET motion correction, but precise timing can be employed to determine only the necessary frames needed for correction. This can speeds up reconstruction by eliminating the unnecessary subdivision of frames.

A Robust Random Forest-Based Approach for Heart Rate Monitoring Using Photoplethysmography Signal Contaminated by Intense Motion Artifacts.

PubMed

Ye, Yalan; He, Wenwen; Cheng, Yunfei; Huang, Wenxia; Zhang, Zhilin

2017-02-16

The estimation of heart rate (HR) based on wearable devices is of interest in fitness. Photoplethysmography (PPG) is a promising approach to estimate HR due to low cost; however, it is easily corrupted by motion artifacts (MA). In this work, a robust approach based on random forest is proposed for accurately estimating HR from the photoplethysmography signal contaminated by intense motion artifacts, consisting of two stages. Stage 1 proposes a hybrid method to effectively remove MA with a low computation complexity, where two MA removal algorithms are combined by an accurate binary decision algorithm whose aim is to decide whether or not to adopt the second MA removal algorithm. Stage 2 proposes a random forest-based spectral peak-tracking algorithm, whose aim is to locate the spectral peak corresponding to HR, formulating the problem of spectral peak tracking into a pattern classification problem. Experiments on the PPG datasets including 22 subjects used in the 2015 IEEE Signal Processing Cup showed that the proposed approach achieved the average absolute error of 1.65 beats per minute (BPM) on the 22 PPG datasets. Compared to state-of-the-art approaches, the proposed approach has better accuracy and robustness to intense motion artifacts, indicating its potential use in wearable sensors for health monitoring and fitness tracking.

An experimental comparison of online object-tracking algorithms

NASA Astrophysics Data System (ADS)

Wang, Qing; Chen, Feng; Xu, Wenli; Yang, Ming-Hsuan

2011-09-01

This paper reviews and evaluates several state-of-the-art online object tracking algorithms. Notwithstanding decades of efforts, object tracking remains a challenging problem due to factors such as illumination, pose, scale, deformation, motion blur, noise, and occlusion. To account for appearance change, most recent tracking algorithms focus on robust object representations and effective state prediction. In this paper, we analyze the components of each tracking method and identify their key roles in dealing with specific challenges, thereby shedding light on how to choose and design algorithms for different situations. We compare state-of-the-art online tracking methods including the IVT,1 VRT,2 FragT,3 BoostT,4 SemiT,5 BeSemiT,6 L1T,7 MILT,8 VTD9 and TLD10 algorithms on numerous challenging sequences, and evaluate them with different performance metrics. The qualitative and quantitative comparative results demonstrate the strength and weakness of these algorithms.

A mathematical model for computer image tracking.

PubMed

Legters, G R; Young, T Y

1982-06-01

A mathematical model using an operator formulation for a moving object in a sequence of images is presented. Time-varying translation and rotation operators are derived to describe the motion. A variational estimation algorithm is developed to track the dynamic parameters of the operators. The occlusion problem is alleviated by using a predictive Kalman filter to keep the tracking on course during severe occlusion. The tracking algorithm (variational estimation in conjunction with Kalman filter) is implemented to track moving objects with occasional occlusion in computer-simulated binary images.

Infrared measurement and composite tracking algorithm for air-breathing hypersonic vehicles

NASA Astrophysics Data System (ADS)

Zhang, Zhao; Gao, Changsheng; Jing, Wuxing

2018-03-01

Air-breathing hypersonic vehicles have capabilities of hypersonic speed and strong maneuvering, and thus pose a significant challenge to conventional tracking methodologies. To achieve desirable tracking performance for hypersonic targets, this paper investigates the problems related to measurement model design and tracking model mismatching. First, owing to the severe aerothermal effect of hypersonic motion, an infrared measurement model in near space is designed and analyzed based on target infrared radiation and an atmospheric model. Second, using information from infrared sensors, a composite tracking algorithm is proposed via a combination of the interactive multiple models (IMM) algorithm, fitting dynamics model, and strong tracking filter. During the procedure, the IMMs algorithm generates tracking data to establish a fitting dynamics model of the target. Then, the strong tracking unscented Kalman filter is employed to estimate the target states for suppressing the impact of target maneuvers. Simulations are performed to verify the feasibility of the presented composite tracking algorithm. The results demonstrate that the designed infrared measurement model effectively and continuously observes hypersonic vehicles, and the proposed composite tracking algorithm accurately and stably tracks these targets.

Fast leaf-fitting with generalized underdose/overdose constraints for real-time MLC tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moore, Douglas, E-mail: douglas.moore@utsouthwestern.edu; Sawant, Amit; Ruan, Dan

2016-01-15

Purpose: Real-time multileaf collimator (MLC) tracking is a promising approach to the management of intrafractional tumor motion during thoracic and abdominal radiotherapy. MLC tracking is typically performed in two steps: transforming a planned MLC aperture in response to patient motion and refitting the leaves to the newly generated aperture. One of the challenges of this approach is the inability to faithfully reproduce the desired motion-adapted aperture. This work presents an optimization-based framework with which to solve this leaf-fitting problem in real-time. Methods: This optimization framework is designed to facilitate the determination of leaf positions in real-time while accounting for themore » trade-off between coverage of the PTV and avoidance of organs at risk (OARs). Derived within this framework, an algorithm is presented that can account for general linear transformations of the planned MLC aperture, particularly 3D translations and in-plane rotations. This algorithm, together with algorithms presented in Sawant et al. [“Management of three-dimensional intrafraction motion through real-time DMLC tracking,” Med. Phys. 35, 2050–2061 (2008)] and Ruan and Keall [Presented at the 2011 IEEE Power Engineering and Automation Conference (PEAM) (2011) (unpublished)], was applied to apertures derived from eight lung intensity modulated radiotherapy plans subjected to six-degree-of-freedom motion traces acquired from lung cancer patients using the kilovoltage intrafraction monitoring system developed at the University of Sydney. A quality-of-fit metric was defined, and each algorithm was evaluated in terms of quality-of-fit and computation time. Results: This algorithm is shown to perform leaf-fittings of apertures, each with 80 leaf pairs, in 0.226 ms on average as compared to 0.082 and 64.2 ms for the algorithms of Sawant et al., Ruan, and Keall, respectively. The algorithm shows approximately 12% improvement in quality-of-fit over the Sawant et al. approach, while performing comparably to Ruan and Keall. Conclusions: This work improves upon the quality of the Sawant et al. approach, but does so without sacrificing run-time performance. In addition, using this framework allows for complex leaf-fitting strategies that can be used to account for PTV/OAR trade-off during real-time MLC tracking.« less

Robust object tracking techniques for vision-based 3D motion analysis applications

NASA Astrophysics Data System (ADS)

Knyaz, Vladimir A.; Zheltov, Sergey Y.; Vishnyakov, Boris V.

2016-04-01

Automated and accurate spatial motion capturing of an object is necessary for a wide variety of applications including industry and science, virtual reality and movie, medicine and sports. For the most part of applications a reliability and an accuracy of the data obtained as well as convenience for a user are the main characteristics defining the quality of the motion capture system. Among the existing systems for 3D data acquisition, based on different physical principles (accelerometry, magnetometry, time-of-flight, vision-based), optical motion capture systems have a set of advantages such as high speed of acquisition, potential for high accuracy and automation based on advanced image processing algorithms. For vision-based motion capture accurate and robust object features detecting and tracking through the video sequence are the key elements along with a level of automation of capturing process. So for providing high accuracy of obtained spatial data the developed vision-based motion capture system "Mosca" is based on photogrammetric principles of 3D measurements and supports high speed image acquisition in synchronized mode. It includes from 2 to 4 technical vision cameras for capturing video sequences of object motion. The original camera calibration and external orientation procedures provide the basis for high accuracy of 3D measurements. A set of algorithms as for detecting, identifying and tracking of similar targets, so for marker-less object motion capture is developed and tested. The results of algorithms' evaluation show high robustness and high reliability for various motion analysis tasks in technical and biomechanics applications.

Hand-writing motion tracking with vision-inertial sensor fusion: calibration and error correction.

PubMed

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J

2014-08-25

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model.

A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images.

PubMed

Yao, Libo; Liu, Yong; He, You

2018-06-22

The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In this paper, a novel ship-tracking method in GF-4 satellite sequential imagery is proposed. The algorithm has three stages. First, a local visual saliency map based on local peak signal-to-noise ratio (PSNR) is used to detect ships in a single frame of GF-4 satellite sequential images. Second, the accuracy positioning of each potential target is realized by a dynamic correction using the rational polynomial coefficients (RPCs) and automatic identification system (AIS) data of ships. Finally, an improved multiple hypotheses tracking (MHT) algorithm with amplitude information is used to track ships by further removing the false targets, and to estimate ships’ motion parameters. The algorithm has been tested using GF-4 sequential images and AIS data. The results of the experiment demonstrate that the algorithm achieves good tracking performance in GF-4 satellite sequential images and estimates the motion information of ships accurately.

Implementation of a state of the art automated system for the production of cloud/water vapor motion winds from geostationary satellites

NASA Technical Reports Server (NTRS)

Velden, Christopher

1995-01-01

The research objectives in this proposal were part of a continuing program at UW-CIMSS to develop and refine an automated geostationary satellite winds processing system which can be utilized in both research and operational environments. The majority of the originally proposed tasks were successfully accomplished, and in some cases the progress exceeded the original goals. Much of the research and development supported by this grant resulted in upgrades and modifications to the existing automated satellite winds tracking algorithm. These modifications were put to the test through case study demonstrations and numerical model impact studies. After being successfully demonstrated, the modifications and upgrades were implemented into the NESDIS algorithms in Washington DC, and have become part of the operational support. A major focus of the research supported under this grant attended to the continued development of water vapor tracked winds from geostationary observations. The fully automated UW-CIMSS tracking algorithm has been tuned to provide complete upper-tropospheric coverage from this data source, with data set quality close to that of operational cloud motion winds. Multispectral water vapor observations were collected and processed from several different geostationary satellites. The tracking and quality control algorithms were tuned and refined based on ground-truth comparisons and case studies involving impact on numerical model analyses and forecasts. The results have shown the water vapor motion winds are of good quality, complement the cloud motion wind data, and can have a positive impact in NWP on many meteorological scales.

Combined Feature Based and Shape Based Visual Tracker for Robot Navigation

NASA Technical Reports Server (NTRS)

Deans, J.; Kunz, C.; Sargent, R.; Park, E.; Pedersen, L.

2005-01-01

We have developed a combined feature based and shape based visual tracking system designed to enable a planetary rover to visually track and servo to specific points chosen by a user with centimeter precision. The feature based tracker uses invariant feature detection and matching across a stereo pair, as well as matching pairs before and after robot movement in order to compute an incremental 6-DOF motion at each tracker update. This tracking method is subject to drift over time, which can be compensated by the shape based method. The shape based tracking method consists of 3D model registration, which recovers 6-DOF motion given sufficient shape and proper initialization. By integrating complementary algorithms, the combined tracker leverages the efficiency and robustness of feature based methods with the precision and accuracy of model registration. In this paper, we present the algorithms and their integration into a combined visual tracking system.

Development of a Sunspot Tracking System

NASA Technical Reports Server (NTRS)

Taylor, Jaime R.

1998-01-01

Large solar flares produce a significant amount of energetic particles which pose a hazard for human activity in space. In the hope of understanding flare mechanisms and thus better predicting solar flares, NASA's Marshall Space Flight Center (MSFC) developed an experimental vector magnetograph (EXVM) polarimeter to measure the Sun's magnetic field. The EXVM will be used to perform ground-based solar observations and will provide a proof of concept for the design of a similar instrument for the Japanese Solar-B space mission. The EXVM typically operates for a period of several minutes. During this time there is image motion due to atmospheric fluctuation and telescope wind loading. To optimize the EXVM performance an image motion compensation device (sunspot tracker) is needed. The sunspot tracker consists of two parts, an image motion determination system and an image deflection system. For image motion determination a CCD or CID camera is used to digitize an image, than an algorithm is applied to determine the motion. This motion or error signal is sent to the image deflection system which moves the image back to its original location. Both of these systems are under development. Two algorithms are available for sunspot tracking which require the use of only one row and one column of image data. To implement these algorithms, two identical independent systems are being developed, one system for each axis of motion. Two CID cameras have been purchased; the data from each camera will be used to determine image motion for each direction. The error signal generated by the tracking algorithm will be sent to an image deflection system consisting of an actuator and a mirror constrained to move about one axis. Magnetostrictive actuators were chosen to move the mirror over piezoelectrics due to their larger driving force and larger range of motion. The actuator and mirror mounts are currently under development.

Accurate motion parameter estimation for colonoscopy tracking using a regression method

NASA Astrophysics Data System (ADS)

Liu, Jianfei; Subramanian, Kalpathi R.; Yoo, Terry S.

2010-03-01

Co-located optical and virtual colonoscopy images have the potential to provide important clinical information during routine colonoscopy procedures. In our earlier work, we presented an optical flow based algorithm to compute egomotion from live colonoscopy video, permitting navigation and visualization of the corresponding patient anatomy. In the original algorithm, motion parameters were estimated using the traditional Least Sum of squares(LS) procedure which can be unstable in the context of optical flow vectors with large errors. In the improved algorithm, we use the Least Median of Squares (LMS) method, a robust regression method for motion parameter estimation. Using the LMS method, we iteratively analyze and converge toward the main distribution of the flow vectors, while disregarding outliers. We show through three experiments the improvement in tracking results obtained using the LMS method, in comparison to the LS estimator. The first experiment demonstrates better spatial accuracy in positioning the virtual camera in the sigmoid colon. The second and third experiments demonstrate the robustness of this estimator, resulting in longer tracked sequences: from 300 to 1310 in the ascending colon, and 410 to 1316 in the transverse colon.

B-spline based image tracking by detection

NASA Astrophysics Data System (ADS)

Balaji, Bhashyam; Sithiravel, Rajiv; Damini, Anthony; Kirubarajan, Thiagalingam; Rajan, Sreeraman

2016-05-01

Visual image tracking involves the estimation of the motion of any desired targets in a surveillance region using a sequence of images. A standard method of isolating moving targets in image tracking uses background subtraction. The standard background subtraction method is often impacted by irrelevant information in the images, which can lead to poor performance in image-based target tracking. In this paper, a B-Spline based image tracking is implemented. The novel method models the background and foreground using the B-Spline method followed by a tracking-by-detection algorithm. The effectiveness of the proposed algorithm is demonstrated.

Enhancement of tracking performance in electro-optical system based on servo control algorithm

NASA Astrophysics Data System (ADS)

Choi, WooJin; Kim, SungSu; Jung, DaeYoon; Seo, HyoungKyu

2017-10-01

Modern electro-optical surveillance and reconnaissance systems require tracking capability to get exact images of target or to accurately direct the line of sight to target which is moving or still. This leads to the tracking system composed of image based tracking algorithm and servo control algorithm. In this study, we focus on the servo control function to minimize the overshoot in the tracking motion and do not miss the target. The scheme is to limit acceleration and velocity parameters in the tracking controller, depending on the target state information in the image. We implement the proposed techniques by creating a system model of DIRCM and simulate the same environment, validate the performance on the actual equipment.

MER-DIMES : a planetary landing application of computer vision

NASA Technical Reports Server (NTRS)

Cheng, Yang; Johnson, Andrew; Matthies, Larry

2005-01-01

During the Mars Exploration Rovers (MER) landings, the Descent Image Motion Estimation System (DIMES) was used for horizontal velocity estimation. The DIMES algorithm combines measurements from a descent camera, a radar altimeter and an inertial measurement unit. To deal with large changes in scale and orientation between descent images, the algorithm uses altitude and attitude measurements to rectify image data to level ground plane. Feature selection and tracking is employed in the rectified data to compute the horizontal motion between images. Differences of motion estimates are then compared to inertial measurements to verify correct feature tracking. DIMES combines sensor data from multiple sources in a novel way to create a low-cost, robust and computationally efficient velocity estimation solution, and DIMES is the first use of computer vision to control a spacecraft during planetary landing. In this paper, the detailed implementation of the DIMES algorithm and the results from the two landings on Mars are presented.

Technical Note: A novel leaf sequencing optimization algorithm which considers previous underdose and overdose events for MLC tracking radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wisotzky, Eric, E-mail: eric.wisotzky@charite.de, E-mail: eric.wisotzky@ipk.fraunhofer.de; O’Brien, Ricky; Keall, Paul J., E-mail: paul.keall@sydney.edu.au

2016-01-15

Purpose: Multileaf collimator (MLC) tracking radiotherapy is complex as the beam pattern needs to be modified due to the planned intensity modulation as well as the real-time target motion. The target motion cannot be planned; therefore, the modified beam pattern differs from the original plan and the MLC sequence needs to be recomputed online. Current MLC tracking algorithms use a greedy heuristic in that they optimize for a given time, but ignore past errors. To overcome this problem, the authors have developed and improved an algorithm that minimizes large underdose and overdose regions. Additionally, previous underdose and overdose events aremore » taken into account to avoid regions with high quantity of dose events. Methods: The authors improved the existing MLC motion control algorithm by introducing a cumulative underdose/overdose map. This map represents the actual projection of the planned tumor shape and logs occurring dose events at each specific regions. These events have an impact on the dose cost calculation and reduce recurrence of dose events at each region. The authors studied the improvement of the new temporal optimization algorithm in terms of the L1-norm minimization of the sum of overdose and underdose compared to not accounting for previous dose events. For evaluation, the authors simulated the delivery of 5 conformal and 14 intensity-modulated radiotherapy (IMRT)-plans with 7 3D patient measured tumor motion traces. Results: Simulations with conformal shapes showed an improvement of L1-norm up to 8.5% after 100 MLC modification steps. Experiments showed comparable improvements with the same type of treatment plans. Conclusions: A novel leaf sequencing optimization algorithm which considers previous dose events for MLC tracking radiotherapy has been developed and investigated. Reductions in underdose/overdose are observed for conformal and IMRT delivery.« less

Correlation between external and internal respiratory motion: a validation study.

PubMed

Ernst, Floris; Bruder, Ralf; Schlaefer, Alexander; Schweikard, Achim

2012-05-01

In motion-compensated image-guided radiotherapy, accurate tracking of the target region is required. This tracking process includes building a correlation model between external surrogate motion and the motion of the target region. A novel correlation method is presented and compared with the commonly used polynomial model. The CyberKnife system (Accuray, Inc., Sunnyvale/CA) uses a polynomial correlation model to relate externally measured surrogate data (optical fibres on the patient's chest emitting red light) to infrequently acquired internal measurements (X-ray data). A new correlation algorithm based on ɛ -Support Vector Regression (SVR) was developed. Validation and comparison testing were done with human volunteers using live 3D ultrasound and externally measured infrared light-emitting diodes (IR LEDs). Seven data sets (5:03-6:27 min long) were recorded from six volunteers. Polynomial correlation algorithms were compared to the SVR-based algorithm demonstrating an average increase in root mean square (RMS) accuracy of 21.3% (0.4 mm). For three signals, the increase was more than 29% and for one signal as much as 45.6% (corresponding to more than 1.5 mm RMS). Further analysis showed the improvement to be statistically significant. The new SVR-based correlation method outperforms traditional polynomial correlation methods for motion tracking. This method is suitable for clinical implementation and may improve the overall accuracy of targeted radiotherapy.

Siamese convolutional networks for tracking the spine motion

NASA Astrophysics Data System (ADS)

Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

2017-09-01

Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

Layered motion segmentation and depth ordering by tracking edges.

PubMed

Smith, Paul; Drummond, Tom; Cipolla, Roberto

2004-04-01

This paper presents a new Bayesian framework for motion segmentation--dividing a frame from an image sequence into layers representing different moving objects--by tracking edges between frames. Edges are found using the Canny edge detector, and the Expectation-Maximization algorithm is then used to fit motion models to these edges and also to calculate the probabilities of the edges obeying each motion model. The edges are also used to segment the image into regions of similar color. The most likely labeling for these regions is then calculated by using the edge probabilities, in association with a Markov Random Field-style prior. The identification of the relative depth ordering of the different motion layers is also determined, as an integral part of the process. An efficient implementation of this framework is presented for segmenting two motions (foreground and background) using two frames. It is then demonstrated how, by tracking the edges into further frames, the probabilities may be accumulated to provide an even more accurate and robust estimate, and segment an entire sequence. Further extensions are then presented to address the segmentation of more than two motions. Here, a hierarchical method of initializing the Expectation-Maximization algorithm is described, and it is demonstrated that the Minimum Description Length principle may be used to automatically select the best number of motion layers. The results from over 30 sequences (demonstrating both two and three motions) are presented and discussed.

Doppler-based motion compensation algorithm for focusing the signature of a rotorcraft.

PubMed

Goldman, Geoffrey H

2013-02-01

A computationally efficient algorithm was developed and tested to compensate for the effects of motion on the acoustic signature of a rotorcraft. For target signatures with large spectral peaks that vary slowly in amplitude and have near constant frequency, the time-varying Doppler shift can be tracked and then removed from the data. The algorithm can be used to preprocess data for classification, tracking, and nulling algorithms. The algorithm was tested on rotorcraft data. The average instantaneous frequency of the first harmonic of a rotorcraft was tracked with a fixed-lag smoother. Then, state space estimates of the frequency were used to calculate a time warping that removed the effect of a time-varying Doppler shift from the data. The algorithm was evaluated by analyzing the increase in the amplitude of the harmonics in the spectrum of a rotorcraft. The results depended upon the frequency of the harmonics and the processing interval duration. Under good conditions, the results for the fundamental frequency of the target (~11 Hz) almost achieved an estimated upper bound. The results for higher frequency harmonics had larger increases in the amplitude of the peaks, but significantly lower than the estimated upper bounds.

Hand-Writing Motion Tracking with Vision-Inertial Sensor Fusion: Calibration and Error Correction

PubMed Central

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J.

2014-01-01

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model. PMID:25157546

Optimum location of external markers using feature selection algorithms for real‐time tumor tracking in external‐beam radiotherapy: a virtual phantom study

PubMed Central

Nankali, Saber; Miandoab, Payam Samadi; Baghizadeh, Amin

2016-01-01

In external‐beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation‐based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two “Genetic” and “Ranker” searching procedures. The performance of these algorithms has been evaluated using four‐dimensional extended cardiac‐torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro‐fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F‐test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation‐based feature selection algorithm, in combination with a genetic search algorithm, proved to yield best performance accuracy for selecting optimum markers. PACS numbers: 87.55.km, 87.56.Fc PMID:26894358

Optimum location of external markers using feature selection algorithms for real-time tumor tracking in external-beam radiotherapy: a virtual phantom study.

PubMed

Nankali, Saber; Torshabi, Ahmad Esmaili; Miandoab, Payam Samadi; Baghizadeh, Amin

2016-01-08

In external-beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation-based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two "Genetic" and "Ranker" searching procedures. The performance of these algorithms has been evaluated using four-dimensional extended cardiac-torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro-fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F-test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation-based feature selection algorithm, in combination with a genetic search algorithm, proved to yield best performance accuracy for selecting optimum markers.

WE-AB-303-08: Direct Lung Tumor Tracking Using Short Imaging Arcs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shieh, C; Huang, C; Keall, P

2015-06-15

Purpose: Most current tumor tracking technologies rely on implanted markers, which suffer from potential toxicity of marker placement and mis-targeting due to marker migration. Several markerless tracking methods have been proposed: these are either indirect methods or have difficulties tracking lung tumors in most clinical cases due to overlapping anatomies in 2D projection images. We propose a direct lung tumor tracking algorithm robust to overlapping anatomies using short imaging arcs. Methods: The proposed algorithm tracks the tumor based on kV projections acquired within the latest six-degree imaging arc. To account for respiratory motion, an external motion surrogate is used tomore » select projections of the same phase within the latest arc. For each arc, the pre-treatment 4D cone-beam CT (CBCT) with tumor contours are used to estimate and remove the contribution to the integral attenuation from surrounding anatomies. The position of the tumor model extracted from 4D CBCT of the same phase is then optimized to match the processed projections using the conjugate gradient method. The algorithm was retrospectively validated on two kV scans of a lung cancer patient with implanted fiducial markers. This patient was selected as the tumor is attached to the mediastinum, representing a challenging case for markerless tracking methods. The tracking results were converted to expected marker positions and compared with marker trajectories obtained via direct marker segmentation (ground truth). Results: The root-mean-squared-errors of tracking were 0.8 mm and 0.9 mm in the superior-inferior direction for the two scans. Tracking error was found to be below 2 and 3 mm for 90% and 98% of the time, respectively. Conclusions: A direct lung tumor tracking algorithm robust to overlapping anatomies was proposed and validated on two scans of a lung cancer patient. Sub-millimeter tracking accuracy was observed, indicating the potential of this algorithm for real-time guidance applications.« less

A parallelizable real-time motion tracking algorithm with applications to ultrasonic strain imaging.

PubMed

Jiang, J; Hall, T J

2007-07-07

Ultrasound-based mechanical strain imaging systems utilize signals from conventional diagnostic ultrasound systems to image tissue elasticity contrast that provides new diagnostically valuable information. Previous works (Hall et al 2003 Ultrasound Med. Biol. 29 427, Zhu and Hall 2002 Ultrason. Imaging 24 161) demonstrated that uniaxial deformation with minimal elevation motion is preferred for breast strain imaging and real-time strain image feedback to operators is important to accomplish this goal. The work reported here enhances the real-time speckle tracking algorithm with two significant modifications. One fundamental change is that the proposed algorithm is a column-based algorithm (a column is defined by a line of data parallel to the ultrasound beam direction, i.e. an A-line), as opposed to a row-based algorithm (a row is defined by a line of data perpendicular to the ultrasound beam direction). Then, displacement estimates from its adjacent columns provide good guidance for motion tracking in a significantly reduced search region to reduce computational cost. Consequently, the process of displacement estimation can be naturally split into at least two separated tasks, computed in parallel, propagating outward from the center of the region of interest (ROI). The proposed algorithm has been implemented and optimized in a Windows system as a stand-alone ANSI C++ program. Results of preliminary tests, using numerical and tissue-mimicking phantoms, and in vivo tissue data, suggest that high contrast strain images can be consistently obtained with frame rates (10 frames s(-1)) that exceed our previous methods.

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

NASA Astrophysics Data System (ADS)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

Nonlinear Motion Tracking by Deep Learning Architecture

NASA Astrophysics Data System (ADS)

Verma, Arnav; Samaiya, Devesh; Gupta, Karunesh K.

2018-03-01

In the world of Artificial Intelligence, object motion tracking is one of the major problems. The extensive research is being carried out to track people in crowd. This paper presents a unique technique for nonlinear motion tracking in the absence of prior knowledge of nature of nonlinear path that the object being tracked may follow. We achieve this by first obtaining the centroid of the object and then using the centroid as the current example for a recurrent neural network trained using real-time recurrent learning. We have tweaked the standard algorithm slightly and have accumulated the gradient for few previous iterations instead of using just the current iteration as is the norm. We show that for a single object, such a recurrent neural network is highly capable of approximating the nonlinearity of its path.

Time-lapse microscopy and image processing for stem cell research: modeling cell migration

NASA Astrophysics Data System (ADS)

Gustavsson, Tomas; Althoff, Karin; Degerman, Johan; Olsson, Torsten; Thoreson, Ann-Catrin; Thorlin, Thorleif; Eriksson, Peter

2003-05-01

This paper presents hardware and software procedures for automated cell tracking and migration modeling. A time-lapse microscopy system equipped with a computer controllable motorized stage was developed. The performance of this stage was improved by incorporating software algorithms for stage motion displacement compensation and auto focus. The microscope is suitable for in-vitro stem cell studies and allows for multiple cell culture image sequence acquisition. This enables comparative studies concerning rate of cell splits, average cell motion velocity, cell motion as a function of cell sample density and many more. Several cell segmentation procedures are described as well as a cell tracking algorithm. Statistical methods for describing cell migration patterns are presented. In particular, the Hidden Markov Model (HMM) was investigated. Results indicate that if the cell motion can be described as a non-stationary stochastic process, then the HMM can adequately model aspects of its dynamic behavior.

Real Time Target Tracking in a Phantom Using Ultrasonic Imaging

NASA Astrophysics Data System (ADS)

Xiao, X.; Corner, G.; Huang, Z.

In this paper we present a real-time ultrasound image guidance method suitable for tracking the motion of tumors. A 2D ultrasound based motion tracking system was evaluated. A robot was used to control the focused ultrasound and position it at the target that has been segmented from a real-time ultrasound video. Tracking accuracy and precision were investigated using a lesion mimicking phantom. Experiments have been conducted and results show sufficient efficiency of the image guidance algorithm. This work could be developed as the foundation for combining the real time ultrasound imaging tracking and MRI thermometry monitoring non-invasive surgery.

Motion prediction in MRI-guided radiotherapy based on interleaved orthogonal cine-MRI

NASA Astrophysics Data System (ADS)

Seregni, M.; Paganelli, C.; Lee, D.; Greer, P. B.; Baroni, G.; Keall, P. J.; Riboldi, M.

2016-01-01

In-room cine-MRI guidance can provide non-invasive target localization during radiotherapy treatment. However, in order to cope with finite imaging frequency and system latencies between target localization and dose delivery, tumour motion prediction is required. This work proposes a framework for motion prediction dedicated to cine-MRI guidance, aiming at quantifying the geometric uncertainties introduced by this process for both tumour tracking and beam gating. The tumour position, identified through scale invariant features detected in cine-MRI slices, is estimated at high-frequency (25 Hz) using three independent predictors, one for each anatomical coordinate. Linear extrapolation, auto-regressive and support vector machine algorithms are compared against systems that use no prediction or surrogate-based motion estimation. Geometric uncertainties are reported as a function of image acquisition period and system latency. Average results show that the tracking error RMS can be decreased down to a [0.2; 1.2] mm range, for acquisition periods between 250 and 750 ms and system latencies between 50 and 300 ms. Except for the linear extrapolator, tracking and gating prediction errors were, on average, lower than those measured for surrogate-based motion estimation. This finding suggests that cine-MRI guidance, combined with appropriate prediction algorithms, could relevantly decrease geometric uncertainties in motion compensated treatments.

Precise Image-Based Motion Estimation for Autonomous Small Body Exploration

NASA Technical Reports Server (NTRS)

Johnson, Andrew Edie; Matthies, Larry H.

2000-01-01

We have developed and tested a software algorithm that enables onboard autonomous motion estimation near small bodies using descent camera imagery and laser altimetry. Through simulation and testing, we have shown that visual feature tracking can decrease uncertainty in spacecraft motion to a level that makes landing on small, irregularly shaped, bodies feasible. Possible future work will include qualification of the algorithm as a flight experiment for the Deep Space 4/Champollion comet lander mission currently under study at the Jet Propulsion Laboratory.

Novel true-motion estimation algorithm and its application to motion-compensated temporal frame interpolation.

PubMed

Dikbas, Salih; Altunbasak, Yucel

2013-08-01

In this paper, a new low-complexity true-motion estimation (TME) algorithm is proposed for video processing applications, such as motion-compensated temporal frame interpolation (MCTFI) or motion-compensated frame rate up-conversion (MCFRUC). Regular motion estimation, which is often used in video coding, aims to find the motion vectors (MVs) to reduce the temporal redundancy, whereas TME aims to track the projected object motion as closely as possible. TME is obtained by imposing implicit and/or explicit smoothness constraints on the block-matching algorithm. To produce better quality-interpolated frames, the dense motion field at interpolation time is obtained for both forward and backward MVs; then, bidirectional motion compensation using forward and backward MVs is applied by mixing both elegantly. Finally, the performance of the proposed algorithm for MCTFI is demonstrated against recently proposed methods and smoothness constraint optical flow employed by a professional video production suite. Experimental results show that the quality of the interpolated frames using the proposed method is better when compared with the MCFRUC techniques.

Evaluation of a video-based head motion tracking system for dedicated brain PET

NASA Astrophysics Data System (ADS)

Anishchenko, S.; Beylin, D.; Stepanov, P.; Stepanov, A.; Weinberg, I. N.; Schaeffer, S.; Zavarzin, V.; Shaposhnikov, D.; Smith, M. F.

2015-03-01

Unintentional head motion during Positron Emission Tomography (PET) data acquisition can degrade PET image quality and lead to artifacts. Poor patient compliance, head tremor, and coughing are examples of movement sources. Head motion due to patient non-compliance can be an issue with the rise of amyloid brain PET in dementia patients. To preserve PET image resolution and quantitative accuracy, head motion can be tracked and corrected in the image reconstruction algorithm. While fiducial markers can be used, a contactless approach is preferable. A video-based head motion tracking system for a dedicated portable brain PET scanner was developed. Four wide-angle cameras organized in two stereo pairs are used for capturing video of the patient's head during the PET data acquisition. Facial points are automatically tracked and used to determine the six degree of freedom head pose as a function of time. The presented work evaluated the newly designed tracking system using a head phantom and a moving American College of Radiology (ACR) phantom. The mean video-tracking error was 0.99±0.90 mm relative to the magnetic tracking device used as ground truth. Qualitative evaluation with the ACR phantom shows the advantage of the motion tracking application. The developed system is able to perform tracking with accuracy close to millimeter and can help to preserve resolution of brain PET images in presence of movements.

Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Shea, Tuathan P., E-mail: tuathan.oshea@icr.ac.uk; Bamber, Jeffrey C.; Harris, Emma J.

Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison withmore » normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking performance. A future study will investigate spatial uniformity of motion and its effect on the motion estimation errors.« less

The new approach for infrared target tracking based on the particle filter algorithm

NASA Astrophysics Data System (ADS)

Sun, Hang; Han, Hong-xia

2011-08-01

Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring, precision, and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection, the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure, but in order to capture the change of the state space, it need a certain amount of particles to ensure samples is enough, and this number will increase in accompany with dimension and increase exponentially, this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining", we expand the classic Mean Shift tracking framework .Based on the previous perspective, we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis, Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism, used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation, and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value .Last because of the gray and fusion target motion information, this approach also inhibit interference from the background, ultimately improve the stability and the real-time of the target track.

A proto-type design of a real-tissue phantom for the validation of deformation algorithms and 4D dose calculations

NASA Astrophysics Data System (ADS)

Szegedi, M.; Rassiah-Szegedi, P.; Fullerton, G.; Wang, B.; Salter, B.

2010-07-01

The purpose of this study is to design a real-tissue phantom for use in the validation of deformation algorithms. A phantom motion controller that runs sinusoidal and non-regular patient-based breathing pattern, via a piston, was applied to porcine liver tissue. It was regulated to simulate movement ranges similar to recorded implanted liver markers from patients. 4D CT was applied to analyze deformation. The suitability of various markers in the liver and the position reproducibility of markers and of reference points were studied. The similarity of marker motion pattern in the liver phantom and in real patients was evaluated. The viability of the phantom over time and its use with electro-magnetic tracking devices were also assessed. High contrast markers, such as carbon markers, implanted in the porcine liver produced less image artifacts on CT and were well visualized compared to metallic ones. The repositionability of markers was within a measurement accuracy of ±2 mm. Similar anatomical patient motions were reproducible up to elongations of 3 cm for a time period of at least 90 min. The phantom is compatible with electro-magnetic tracking devices and 4D CT. The phantom motion is reproducible and simulates realistic patient motion and deformation. The ability to carry out voxel-based tracking allows for the evaluation of deformation algorithms in a controlled environment with recorded patient traces. The phantom is compatible with all therapy devices clinically encountered in our department.

Feedback attitude sliding mode regulation control of spacecraft using arm motion

NASA Astrophysics Data System (ADS)

Shi, Ye; Liang, Bin; Xu, Dong; Wang, Xueqian; Xu, Wenfu

2013-09-01

The problem of spacecraft attitude regulation based on the reaction of arm motion has attracted extensive attentions from both engineering and academic fields. Most of the solutions of the manipulator’s motion tracking problem just achieve asymptotical stabilization performance, so that these controllers cannot realize precise attitude regulation because of the existence of non-holonomic constraints. Thus, sliding mode control algorithms are adopted to stabilize the tracking error with zero transient process. Due to the switching effects of the variable structure controller, once the tracking error reaches the designed hyper-plane, it will be restricted to this plane permanently even with the existence of external disturbances. Thus, precise attitude regulation can be achieved. Furthermore, taking the non-zero initial tracking errors and chattering phenomenon into consideration, saturation functions are used to replace sign functions to smooth the control torques. The relations between the upper bounds of tracking errors and the controller parameters are derived to reveal physical characteristic of the controller. Mathematical models of free-floating space manipulator are established and simulations are conducted in the end. The results show that the spacecraft’s attitude can be regulated to the position as desired by using the proposed algorithm, the steady state error is 0.000 2 rad. In addition, the joint tracking trajectory is smooth, the joint tracking errors converges to zero quickly with a satisfactory continuous joint control input. The proposed research provides a feasible solution for spacecraft attitude regulation by using arm motion, and improves the precision of the spacecraft attitude regulation.

Lung tumor tracking in fluoroscopic video based on optical flow

PubMed Central

Xu, Qianyi; Hamilton, Russell J.; Schowengerdt, Robert A.; Alexander, Brian; Jiang, Steve B.

2008-01-01

Respiratory gating and tumor tracking for dynamic multileaf collimator delivery require accurate and real-time localization of the lung tumor position during treatment. Deriving tumor position from external surrogates such as abdominal surface motion may have large uncertainties due to the intra- and interfraction variations of the correlation between the external surrogates and internal tumor motion. Implanted fiducial markers can be used to track tumors fluoroscopically in real time with sufficient accuracy. However, it may not be a practical procedure when implanting fiducials bronchoscopically. In this work, a method is presented to track the lung tumor mass or relevant anatomic features projected in fluoroscopic images without implanted fiducial markers based on an optical flow algorithm. The algorithm generates the centroid position of the tracked target and ignores shape changes of the tumor mass shadow. The tracking starts with a segmented tumor projection in an initial image frame. Then, the optical flow between this and all incoming frames acquired during treatment delivery is computed as initial estimations of tumor centroid displacements. The tumor contour in the initial frame is transferred to the incoming frames based on the average of the motion vectors, and its positions in the incoming frames are determined by fine-tuning the contour positions using a template matching algorithm with a small search range. The tracking results were validated by comparing with clinician determined contours on each frame. The position difference in 95% of the frames was found to be less than 1.4 pixels (∼0.7 mm) in the best case and 2.8 pixels (∼1.4 mm) in the worst case for the five patients studied. PMID:19175094

Lung tumor tracking in fluoroscopic video based on optical flow.

PubMed

Xu, Qianyi; Hamilton, Russell J; Schowengerdt, Robert A; Alexander, Brian; Jiang, Steve B

2008-12-01

Respiratory gating and tumor tracking for dynamic multileaf collimator delivery require accurate and real-time localization of the lung tumor position during treatment. Deriving tumor position from external surrogates such as abdominal surface motion may have large uncertainties due to the intra- and interfraction variations of the correlation between the external surrogates and internal tumor motion. Implanted fiducial markers can be used to track tumors fluoroscopically in real time with sufficient accuracy. However, it may not be a practical procedure when implanting fiducials bronchoscopically. In this work, a method is presented to track the lung tumor mass or relevant anatomic features projected in fluoroscopic images without implanted fiducial markers based on an optical flow algorithm. The algorithm generates the centroid position of the tracked target and ignores shape changes of the tumor mass shadow. The tracking starts with a segmented tumor projection in an initial image frame. Then, the optical flow between this and all incoming frames acquired during treatment delivery is computed as initial estimations of tumor centroid displacements. The tumor contour in the initial frame is transferred to the incoming frames based on the average of the motion vectors, and its positions in the incoming frames are determined by fine-tuning the contour positions using a template matching algorithm with a small search range. The tracking results were validated by comparing with clinician determined contours on each frame. The position difference in 95% of the frames was found to be less than 1.4 pixels (approximately 0.7 mm) in the best case and 2.8 pixels (approximately 1.4 mm) in the worst case for the five patients studied.

Human-like object tracking and gaze estimation with PKD android

PubMed Central

Wijayasinghe, Indika B.; Miller, Haylie L.; Das, Sumit K; Bugnariu, Nicoleta L.; Popa, Dan O.

2018-01-01

As the use of robots increases for tasks that require human-robot interactions, it is vital that robots exhibit and understand human-like cues for effective communication. In this paper, we describe the implementation of object tracking capability on Philip K. Dick (PKD) android and a gaze tracking algorithm, both of which further robot capabilities with regard to human communication. PKD's ability to track objects with human-like head postures is achieved with visual feedback from a Kinect system and an eye camera. The goal of object tracking with human-like gestures is twofold : to facilitate better human-robot interactions and to enable PKD as a human gaze emulator for future studies. The gaze tracking system employs a mobile eye tracking system (ETG; SensoMotoric Instruments) and a motion capture system (Cortex; Motion Analysis Corp.) for tracking the head orientations. Objects to be tracked are displayed by a virtual reality system, the Computer Assisted Rehabilitation Environment (CAREN; MotekForce Link). The gaze tracking algorithm converts eye tracking data and head orientations to gaze information facilitating two objectives: to evaluate the performance of the object tracking system for PKD and to use the gaze information to predict the intentions of the user, enabling the robot to understand physical cues by humans. PMID:29416193

Human-like object tracking and gaze estimation with PKD android

NASA Astrophysics Data System (ADS)

Wijayasinghe, Indika B.; Miller, Haylie L.; Das, Sumit K.; Bugnariu, Nicoleta L.; Popa, Dan O.

2016-05-01

As the use of robots increases for tasks that require human-robot interactions, it is vital that robots exhibit and understand human-like cues for effective communication. In this paper, we describe the implementation of object tracking capability on Philip K. Dick (PKD) android and a gaze tracking algorithm, both of which further robot capabilities with regard to human communication. PKD's ability to track objects with human-like head postures is achieved with visual feedback from a Kinect system and an eye camera. The goal of object tracking with human-like gestures is twofold: to facilitate better human-robot interactions and to enable PKD as a human gaze emulator for future studies. The gaze tracking system employs a mobile eye tracking system (ETG; SensoMotoric Instruments) and a motion capture system (Cortex; Motion Analysis Corp.) for tracking the head orientations. Objects to be tracked are displayed by a virtual reality system, the Computer Assisted Rehabilitation Environment (CAREN; MotekForce Link). The gaze tracking algorithm converts eye tracking data and head orientations to gaze information facilitating two objectives: to evaluate the performance of the object tracking system for PKD and to use the gaze information to predict the intentions of the user, enabling the robot to understand physical cues by humans.

Linearized motion estimation for articulated planes.

PubMed

Datta, Ankur; Sheikh, Yaser; Kanade, Takeo

2011-04-01

In this paper, we describe the explicit application of articulation constraints for estimating the motion of a system of articulated planes. We relate articulations to the relative homography between planes and show that these articulations translate into linearized equality constraints on a linear least-squares system, which can be solved efficiently using a Karush-Kuhn-Tucker system. The articulation constraints can be applied for both gradient-based and feature-based motion estimation algorithms and to illustrate this, we describe a gradient-based motion estimation algorithm for an affine camera and a feature-based motion estimation algorithm for a projective camera that explicitly enforces articulation constraints. We show that explicit application of articulation constraints leads to numerically stable estimates of motion. The simultaneous computation of motion estimates for all of the articulated planes in a scene allows us to handle scene areas where there is limited texture information and areas that leave the field of view. Our results demonstrate the wide applicability of the algorithm in a variety of challenging real-world cases such as human body tracking, motion estimation of rigid, piecewise planar scenes, and motion estimation of triangulated meshes.

On-track test of tilt control strategies for less motion sickness on tilting trains

NASA Astrophysics Data System (ADS)

Persson, Rickard; Kufver, Björn; Berg, Mats

2012-07-01

Carbody tilting is today a mature and inexpensive technology that permits higher train speeds in horizontal curves, thus shortening travel time. However, tilting trains run a greater risk of causing motion sickness than non-tilting ones. It is likely that the difference in motions between the two train types contributes to the observed difference in risk of motion sickness. Decreasing the risk of motion sickness has until now been equal to increasing the discomfort related to quasi-static lateral acceleration. But, there is a difference in time perception between discomfort caused by quasi-static quantities and motion sickness, which opens up for new solutions. One proposed strategy is to let the local track conditions influence the tilt and give each curve its own optimised tilt angle. This is made possible by new tilt algorithms, storing track data and using a positioning system to select the appropriate data. The present paper reports from on-track tests involving more than 100 test subjects onboard a tilting train. A technical approach is taken evaluating the effectiveness of the new tilt algorithms and the different requirements on quasi-static lateral acceleration and lateral jerk in relative terms. The evaluation verifies that the rms values important for motion sickness can be influenced without changing the requirements on quasi-static lateral acceleration and lateral jerk. The evaluation shows that reduced quantities of motions assumed to have a relation to motion sickness also lead to a reduction in experienced motion sickness. However, a limitation of applicability is found as the lowest risk of motion sickness was not recorded for the test case with motions closest to those of a non-tilting train. An optimal level of tilt, different from no tilt at all, is obtained. This non-linear relation has been observed by other researchers in laboratory tests.

A parallelizable real-time motion tracking algorithm with applications to ultrasonic strain imaging

NASA Astrophysics Data System (ADS)

Jiang, J.; Hall, T. J.

2007-07-01

Ultrasound-based mechanical strain imaging systems utilize signals from conventional diagnostic ultrasound systems to image tissue elasticity contrast that provides new diagnostically valuable information. Previous works (Hall et al 2003 Ultrasound Med. Biol. 29 427, Zhu and Hall 2002 Ultrason. Imaging 24 161) demonstrated that uniaxial deformation with minimal elevation motion is preferred for breast strain imaging and real-time strain image feedback to operators is important to accomplish this goal. The work reported here enhances the real-time speckle tracking algorithm with two significant modifications. One fundamental change is that the proposed algorithm is a column-based algorithm (a column is defined by a line of data parallel to the ultrasound beam direction, i.e. an A-line), as opposed to a row-based algorithm (a row is defined by a line of data perpendicular to the ultrasound beam direction). Then, displacement estimates from its adjacent columns provide good guidance for motion tracking in a significantly reduced search region to reduce computational cost. Consequently, the process of displacement estimation can be naturally split into at least two separated tasks, computed in parallel, propagating outward from the center of the region of interest (ROI). The proposed algorithm has been implemented and optimized in a Windows® system as a stand-alone ANSI C++ program. Results of preliminary tests, using numerical and tissue-mimicking phantoms, and in vivo tissue data, suggest that high contrast strain images can be consistently obtained with frame rates (10 frames s-1) that exceed our previous methods.

Markerless rat head motion tracking using structured light for brain PET imaging of unrestrained awake small animals

NASA Astrophysics Data System (ADS)

Miranda, Alan; Staelens, Steven; Stroobants, Sigrid; Verhaeghe, Jeroen

2017-03-01

Preclinical positron emission tomography (PET) imaging in small animals is generally performed under anesthesia to immobilize the animal during scanning. More recently, for rat brain PET studies, methods to perform scans of unrestrained awake rats are being developed in order to avoid the unwanted effects of anesthesia on the brain response. Here, we investigate the use of a projected structure stereo camera to track the motion of the rat head during the PET scan. The motion information is then used to correct the PET data. The stereo camera calculates a 3D point cloud representation of the scene and the tracking is performed by point cloud matching using the iterative closest point algorithm. The main advantage of the proposed motion tracking is that no intervention, e.g. for marker attachment, is needed. A manually moved microDerenzo phantom experiment and 3 awake rat [18F]FDG experiments were performed to evaluate the proposed tracking method. The tracking accuracy was 0.33 mm rms. After motion correction image reconstruction, the microDerenzo phantom was recovered albeit with some loss of resolution. The reconstructed FWHM of the 2.5 and 3 mm rods increased with 0.94 and 0.51 mm respectively in comparison with the motion-free case. In the rat experiments, the average tracking success rate was 64.7%. The correlation of relative brain regional [18F]FDG uptake between the anesthesia and awake scan reconstructions was increased from on average 0.291 (not significant) before correction to 0.909 (p  <  0.0001) after motion correction. Markerless motion tracking using structured light can be successfully used for tracking of the rat head for motion correction in awake rat PET scans.

Data fusion for target tracking and classification with wireless sensor network

NASA Astrophysics Data System (ADS)

Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

2016-10-01

In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

Pilot study on real-time motion detection in UAS video data by human observer and image exploitation algorithm

NASA Astrophysics Data System (ADS)

Hild, Jutta; Krüger, Wolfgang; Brüstle, Stefan; Trantelle, Patrick; Unmüßig, Gabriel; Voit, Michael; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2017-05-01

Real-time motion video analysis is a challenging and exhausting task for the human observer, particularly in safety and security critical domains. Hence, customized video analysis systems providing functions for the analysis of subtasks like motion detection or target tracking are welcome. While such automated algorithms relieve the human operators from performing basic subtasks, they impose additional interaction duties on them. Prior work shows that, e.g., for interaction with target tracking algorithms, a gaze-enhanced user interface is beneficial. In this contribution, we present an investigation on interaction with an independent motion detection (IDM) algorithm. Besides identifying an appropriate interaction technique for the user interface - again, we compare gaze-based and traditional mouse-based interaction - we focus on the benefit an IDM algorithm might provide for an UAS video analyst. In a pilot study, we exposed ten subjects to the task of moving target detection in UAS video data twice, once performing with automatic support, once performing without it. We compare the two conditions considering performance in terms of effectiveness (correct target selections). Additionally, we report perceived workload (measured using the NASA-TLX questionnaire) and user satisfaction (measured using the ISO 9241-411 questionnaire). The results show that a combination of gaze input and automated IDM algorithm provides valuable support for the human observer, increasing the number of correct target selections up to 62% and reducing workload at the same time.

Motion Field Estimation for a Dynamic Scene Using a 3D LiDAR

PubMed Central

Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

2014-01-01

This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively. PMID:25207868

Motion field estimation for a dynamic scene using a 3D LiDAR.

PubMed

Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

2014-09-09

This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively.

A Kinect-Based Real-Time Compressive Tracking Prototype System for Amphibious Spherical Robots

PubMed Central

Pan, Shaowu; Shi, Liwei; Guo, Shuxiang

2015-01-01

A visual tracking system is essential as a basis for visual servoing, autonomous navigation, path planning, robot-human interaction and other robotic functions. To execute various tasks in diverse and ever-changing environments, a mobile robot requires high levels of robustness, precision, environmental adaptability and real-time performance of the visual tracking system. In keeping with the application characteristics of our amphibious spherical robot, which was proposed for flexible and economical underwater exploration in 2012, an improved RGB-D visual tracking algorithm is proposed and implemented. Given the limited power source and computational capabilities of mobile robots, compressive tracking (CT), which is the effective and efficient algorithm that was proposed in 2012, was selected as the basis of the proposed algorithm to process colour images. A Kalman filter with a second-order motion model was implemented to predict the state of the target and select candidate patches or samples for the CT tracker. In addition, a variance ratio features shift (VR-V) tracker with a Kalman estimation mechanism was used to process depth images. Using a feedback strategy, the depth tracking results were used to assist the CT tracker in updating classifier parameters at an adaptive rate. In this way, most of the deficiencies of CT, including drift and poor robustness to occlusion and high-speed target motion, were partly solved. To evaluate the proposed algorithm, a Microsoft Kinect sensor, which combines colour and infrared depth cameras, was adopted for use in a prototype of the robotic tracking system. The experimental results with various image sequences demonstrated the effectiveness, robustness and real-time performance of the tracking system. PMID:25856331

A Kinect-based real-time compressive tracking prototype system for amphibious spherical robots.

PubMed

Pan, Shaowu; Shi, Liwei; Guo, Shuxiang

2015-04-08

A visual tracking system is essential as a basis for visual servoing, autonomous navigation, path planning, robot-human interaction and other robotic functions. To execute various tasks in diverse and ever-changing environments, a mobile robot requires high levels of robustness, precision, environmental adaptability and real-time performance of the visual tracking system. In keeping with the application characteristics of our amphibious spherical robot, which was proposed for flexible and economical underwater exploration in 2012, an improved RGB-D visual tracking algorithm is proposed and implemented. Given the limited power source and computational capabilities of mobile robots, compressive tracking (CT), which is the effective and efficient algorithm that was proposed in 2012, was selected as the basis of the proposed algorithm to process colour images. A Kalman filter with a second-order motion model was implemented to predict the state of the target and select candidate patches or samples for the CT tracker. In addition, a variance ratio features shift (VR-V) tracker with a Kalman estimation mechanism was used to process depth images. Using a feedback strategy, the depth tracking results were used to assist the CT tracker in updating classifier parameters at an adaptive rate. In this way, most of the deficiencies of CT, including drift and poor robustness to occlusion and high-speed target motion, were partly solved. To evaluate the proposed algorithm, a Microsoft Kinect sensor, which combines colour and infrared depth cameras, was adopted for use in a prototype of the robotic tracking system. The experimental results with various image sequences demonstrated the effectiveness, robustness and real-time performance of the tracking system.

Active contour-based visual tracking by integrating colors, shapes, and motions.

PubMed

Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

2013-05-01

In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

A robust motion estimation system for minimal invasive laparoscopy

NASA Astrophysics Data System (ADS)

Marcinczak, Jan Marek; von Öhsen, Udo; Grigat, Rolf-Rainer

2012-02-01

Laparoscopy is a reliable imaging method to examine the liver. However, due to the limited field of view, a lot of experience is required from the surgeon to interpret the observed anatomy. Reconstruction of organ surfaces provide valuable additional information to the surgeon for a reliable diagnosis. Without an additional external tracking system the structure can be recovered from feature correspondences between different frames. In laparoscopic images blurred frames, specular reflections and inhomogeneous illumination make feature tracking a challenging task. We propose an ego-motion estimation system for minimal invasive laparoscopy that can cope with specular reflection, inhomogeneous illumination and blurred frames. To obtain robust feature correspondence, the approach combines SIFT and specular reflection segmentation with a multi-frame tracking scheme. The calibrated five-point algorithm is used with the MSAC robust estimator to compute the motion of the endoscope from multi-frame correspondence. The algorithm is evaluated using endoscopic videos of a phantom. The small incisions and the rigid endoscope limit the motion in minimal invasive laparoscopy. These limitations are considered in our evaluation and are used to analyze the accuracy of pose estimation that can be achieved by our approach. The endoscope is moved by a robotic system and the ground truth motion is recorded. The evaluation on typical endoscopic motion gives precise results and demonstrates the practicability of the proposed pose estimation system.

Motion correction for improved estimation of heart rate using a visual spectrum camera

NASA Astrophysics Data System (ADS)

Tarbox, Elizabeth A.; Rios, Christian; Kaur, Balvinder; Meyer, Shaun; Hirt, Lauren; Tran, Vy; Scott, Kaitlyn; Ikonomidou, Vasiliki

2017-05-01

Heart rate measurement using a visual spectrum recording of the face has drawn interest over the last few years as a technology that can have various health and security applications. In our previous work, we have shown that it is possible to estimate the heart beat timing accurately enough to perform heart rate variability analysis for contactless stress detection. However, a major confounding factor in this approach is the presence of movement, which can interfere with the measurements. To mitigate the effects of movement, in this work we propose the use of face detection and tracking based on the Karhunen-Loewe algorithm in order to counteract measurement errors introduced by normal subject motion, as expected during a common seated conversation setting. We analyze the requirements on image acquisition for the algorithm to work, and its performance under different ranges of motion, changes of distance to the camera, as well and the effect of illumination changes due to different positioning with respect to light sources on the acquired signal. Our results suggest that the effect of face tracking on visual-spectrum based cardiac signal estimation depends on the amplitude of the motion. While for larger-scale conversation-induced motion it can significantly improve estimation accuracy, with smaller-scale movements, such as the ones caused by breathing or talking without major movement errors in facial tracking may interfere with signal estimation. Overall, employing facial tracking is a crucial step in adapting this technology to real-life situations with satisfactory results.

An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors

PubMed Central

Li, Jian; Wei, Xinguo; Zhang, Guangjun

2017-01-01

Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method. PMID:28825684

An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors.

PubMed

Li, Jian; Wei, Xinguo; Zhang, Guangjun

2017-08-21

Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method.

Visual servoing for a US-guided therapeutic HIFU system by coagulated lesion tracking: a phantom study.

PubMed

Seo, Joonho; Koizumi, Norihiro; Funamoto, Takakazu; Sugita, Naohiko; Yoshinaka, Kiyoshi; Nomiya, Akira; Homma, Yukio; Matsumoto, Yoichiro; Mitsuishi, Mamoru

2011-06-01

Applying ultrasound (US)-guided high-intensity focused ultrasound (HIFU) therapy for kidney tumours is currently very difficult, due to the unclearly observed tumour area and renal motion induced by human respiration. In this research, we propose new methods by which to track the indistinct tumour area and to compensate the respiratory tumour motion for US-guided HIFU treatment. For tracking indistinct tumour areas, we detect the US speckle change created by HIFU irradiation. In other words, HIFU thermal ablation can coagulate tissue in the tumour area and an intraoperatively created coagulated lesion (CL) is used as a spatial landmark for US visual tracking. Specifically, the condensation algorithm was applied to robust and real-time CL speckle pattern tracking in the sequence of US images. Moreover, biplanar US imaging was used to locate the three-dimensional position of the CL, and a three-actuator system drives the end-effector to compensate for the motion. Finally, we tested the proposed method by using a newly devised phantom model that enables both visual tracking and a thermal response by HIFU irradiation. In the experiment, after generation of the CL in the phantom kidney, the end-effector successfully synchronized with the phantom motion, which was modelled by the captured motion data for the human kidney. The accuracy of the motion compensation was evaluated by the error between the end-effector and the respiratory motion, the RMS error of which was approximately 2 mm. This research shows that a HIFU-induced CL provides a very good landmark for target motion tracking. By using the CL tracking method, target motion compensation can be realized in the US-guided robotic HIFU system. Copyright © 2011 John Wiley & Sons, Ltd.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal.

PubMed

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D; Hubbi, Basil; Liu, Xuan

2015-11-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal

PubMed Central

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D.; Hubbi, Basil; Liu, Xuan

2015-01-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue. PMID:26600996

Magnetic Resonance Imaging–Guided versus Surrogate-Based Motion Tracking in Liver Radiation Therapy: A Prospective Comparative Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paganelli, Chiara, E-mail: chiara.paganelli@polimi.it; Seregni, Matteo; Fattori, Giovanni

Purpose: This study applied automatic feature detection on cine–magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials: In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each featuremore » was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results: An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions: Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.« less

Precise Image-Based Motion Estimation for Autonomous Small Body Exploration

NASA Technical Reports Server (NTRS)

Johnson, Andrew E.; Matthies, Larry H.

1998-01-01

Space science and solar system exploration are driving NASA to develop an array of small body missions ranging in scope from near body flybys to complete sample return. This paper presents an algorithm for onboard motion estimation that will enable the precision guidance necessary for autonomous small body landing. Our techniques are based on automatic feature tracking between a pair of descent camera images followed by two frame motion estimation and scale recovery using laser altimetry data. The output of our algorithm is an estimate of rigid motion (attitude and position) and motion covariance between frames. This motion estimate can be passed directly to the spacecraft guidance and control system to enable rapid execution of safe and precise trajectories.

Multi-Complementary Model for Long-Term Tracking

PubMed Central

Zhang, Deng; Zhang, Junchang; Xia, Chenyang

2018-01-01

In recent years, video target tracking algorithms have been widely used. However, many tracking algorithms do not achieve satisfactory performance, especially when dealing with problems such as object occlusions, background clutters, motion blur, low illumination color images, and sudden illumination changes in real scenes. In this paper, we incorporate an object model based on contour information into a Staple tracker that combines the correlation filter model and color model to greatly improve the tracking robustness. Since each model is responsible for tracking specific features, the three complementary models combine for more robust tracking. In addition, we propose an efficient object detection model with contour and color histogram features, which has good detection performance and better detection efficiency compared to the traditional target detection algorithm. Finally, we optimize the traditional scale calculation, which greatly improves the tracking execution speed. We evaluate our tracker on the Object Tracking Benchmarks 2013 (OTB-13) and Object Tracking Benchmarks 2015 (OTB-15) benchmark datasets. With the OTB-13 benchmark datasets, our algorithm is improved by 4.8%, 9.6%, and 10.9% on the success plots of OPE, TRE and SRE, respectively, in contrast to another classic LCT (Long-term Correlation Tracking) algorithm. On the OTB-15 benchmark datasets, when compared with the LCT algorithm, our algorithm achieves 10.4%, 12.5%, and 16.1% improvement on the success plots of OPE, TRE, and SRE, respectively. At the same time, it needs to be emphasized that, due to the high computational efficiency of the color model and the object detection model using efficient data structures, and the speed advantage of the correlation filters, our tracking algorithm could still achieve good tracking speed. PMID:29425170

A GPU-Accelerated 3-D Coupled Subsample Estimation Algorithm for Volumetric Breast Strain Elastography.

PubMed

Peng, Bo; Wang, Yuqi; Hall, Timothy J; Jiang, Jingfeng

2017-04-01

Our primary objective of this paper was to extend a previously published 2-D coupled subsample tracking algorithm for 3-D speckle tracking in the framework of ultrasound breast strain elastography. In order to overcome heavy computational cost, we investigated the use of a graphic processing unit (GPU) to accelerate the 3-D coupled subsample speckle tracking method. The performance of the proposed GPU implementation was tested using a tissue-mimicking phantom and in vivo breast ultrasound data. The performance of this 3-D subsample tracking algorithm was compared with the conventional 3-D quadratic subsample estimation algorithm. On the basis of these evaluations, we concluded that the GPU implementation of this 3-D subsample estimation algorithm can provide high-quality strain data (i.e., high correlation between the predeformation and the motion-compensated postdeformation radio frequency echo data and high contrast-to-noise ratio strain images), as compared with the conventional 3-D quadratic subsample algorithm. Using the GPU implementation of the 3-D speckle tracking algorithm, volumetric strain data can be achieved relatively fast (approximately 20 s per volume [2.5 cm ×2.5 cm ×2.5 cm]).

Models for the Effects of G-seat Cuing on Roll-axis Tracking Performance

NASA Technical Reports Server (NTRS)

Levison, W. H.; Mcmillan, G. R.; Martin, E. A.

1984-01-01

Including whole-body motion in a flight simulator improves performance for a variety of tasks requiring a pilot to compensate for the effects of unexpected disturbances. A possible mechanism for this improvement is that whole-body motion provides high derivative vehicle state information whic allows the pilot to generate more lead in responding to the external disturbances. During development of motion simulating algorithms for an advanced g-cuing system it was discovered that an algorithm based on aircraft roll acceleration producted little or no performance improvement. On the other hand, algorithms based on roll position or roll velocity produced performance equivalent to whole-body motion. The analysis and modeling conducted at both the sensory system and manual control performance levels to explain the above results are described.

Using Passive Sensing to Estimate Relative Energy Expenditure for Eldercare Monitoring

PubMed Central

2012-01-01

This paper describes ongoing work in analyzing sensor data logged in the homes of seniors. An estimation of relative energy expenditure is computed using motion density from passive infrared motion sensors mounted in the environment. We introduce a new algorithm for detecting visitors in the home using motion sensor data and a set of fuzzy rules. The visitor algorithm, as well as a previous algorithm for identifying time-away-from-home (TAFH), are used to filter the logged motion sensor data. Thus, the energy expenditure estimate uses data collected only when the resident is home alone. Case studies are included from TigerPlace, an Aging in Place community, to illustrate how the relative energy expenditure estimate can be used to track health conditions over time. PMID:25266777

Trajectory Control of Rendezvous with Maneuver Target Spacecraft

NASA Technical Reports Server (NTRS)

Zhou, Zhinqiang

2012-01-01

In this paper, a nonlinear trajectory control algorithm of rendezvous with maneuvering target spacecraft is presented. The disturbance forces on the chaser and target spacecraft and the thrust forces on the chaser spacecraft are considered in the analysis. The control algorithm developed in this paper uses the relative distance and relative velocity between the target and chaser spacecraft as the inputs. A general formula of reference relative trajectory of the chaser spacecraft to the target spacecraft is developed and applied to four different proximity maneuvers, which are in-track circling, cross-track circling, in-track spiral rendezvous and cross-track spiral rendezvous. The closed-loop differential equations of the proximity relative motion with the control algorithm are derived. It is proven in the paper that the tracking errors between the commanded relative trajectory and the actual relative trajectory are bounded within a constant region determined by the control gains. The prediction of the tracking errors is obtained. Design examples are provided to show the implementation of the control algorithm. The simulation results show that the actual relative trajectory tracks the commanded relative trajectory tightly. The predicted tracking errors match those calculated in the simulation results. The control algorithm developed in this paper can also be applied to interception of maneuver target spacecraft and relative trajectory control of spacecraft formation flying.

A new method for tracking organ motion on diagnostic ultrasound images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kubota, Yoshiki, E-mail: y-kubota@gunma-u.ac.jp; Matsumura, Akihiko, E-mail: matchan.akihiko@gunma-u.ac.jp; Fukahori, Mai, E-mail: fukahori@nirs.go.jp

2014-09-15

Purpose: Respiratory-gated irradiation is effective in reducing the margins of a target in the case of abdominal organs, such as the liver, that change their position as a result of respiratory motion. However, existing technologies are incapable of directly measuring organ motion in real-time during radiation beam delivery. Hence, the authors proposed a novel quantitative organ motion tracking method involving the use of diagnostic ultrasound images; it is noninvasive and does not entail radiation exposure. In the present study, the authors have prospectively evaluated this proposed method. Methods: The method involved real-time processing of clinical ultrasound imaging data rather thanmore » organ monitoring; it comprised a three-dimensional ultrasound device, a respiratory sensing system, and two PCs for data storage and analysis. The study was designed to evaluate the effectiveness of the proposed method by tracking the gallbladder in one subject and a liver vein in another subject. To track a moving target organ, the method involved the control of a region of interest (ROI) that delineated the target. A tracking algorithm was used to control the ROI, and a large number of feature points and an error correction algorithm were used to achieve long-term tracking of the target. Tracking accuracy was assessed in terms of how well the ROI matched the center of the target. Results: The effectiveness of using a large number of feature points and the error correction algorithm in the proposed method was verified by comparing it with two simple tracking methods. The ROI could capture the center of the target for about 5 min in a cross-sectional image with changing position. Indeed, using the proposed method, it was possible to accurately track a target with a center deviation of 1.54 ± 0.9 mm. The computing time for one frame image using our proposed method was 8 ms. It is expected that it would be possible to track any soft-tissue organ or tumor with large deformations and changing cross-sectional position using this method. Conclusions: The proposed method achieved real-time processing and continuous tracking of the target organ for about 5 min. It is expected that our method will enable more accurate radiation treatment than is the case using indirect observational methods, such as the respiratory sensor method, because of direct visualization of the tumor. Results show that this tracking system facilitates safe treatment in clinical practice.« less

Motion-compensated speckle tracking via particle filtering

NASA Astrophysics Data System (ADS)

Liu, Lixin; Yagi, Shin-ichi; Bian, Hongyu

2015-07-01

Recently, an improved motion compensation method that uses the sum of absolute differences (SAD) has been applied to frame persistence utilized in conventional ultrasonic imaging because of its high accuracy and relative simplicity in implementation. However, high time consumption is still a significant drawback of this space-domain method. To seek for a more accelerated motion compensation method and verify if it is possible to eliminate conventional traversal correlation, motion-compensated speckle tracking between two temporally adjacent B-mode frames based on particle filtering is discussed. The optimal initial density of particles, the least number of iterations, and the optimal transition radius of the second iteration are analyzed from simulation results for the sake of evaluating the proposed method quantitatively. The speckle tracking results obtained using the optimized parameters indicate that the proposed method is capable of tracking the micromotion of speckle throughout the region of interest (ROI) that is superposed with global motion. The computational cost of the proposed method is reduced by 25% compared with that of the previous algorithm and further improvement is necessary.

Repurposing the Microsoft Kinect for Windows v2 for external head motion tracking for brain PET.

PubMed

Noonan, P J; Howard, J; Hallett, W A; Gunn, R N

2015-11-21

Medical imaging systems such as those used in positron emission tomography (PET) are capable of spatial resolutions that enable the imaging of small, functionally important brain structures. However, the quality of data from PET brain studies is often limited by subject motion during acquisition. This is particularly challenging for patients with neurological disorders or with dynamic research studies that can last 90 min or more. Restraining head movement during the scan does not eliminate motion entirely and can be unpleasant for the subject. Head motion can be detected and measured using a variety of techniques that either use the PET data itself or an external tracking system. Advances in computer vision arising from the video gaming industry could offer significant benefits when re-purposed for medical applications. A method for measuring rigid body type head motion using the Microsoft Kinect v2 is described with results presenting  ⩽0.5 mm spatial accuracy. Motion data is measured in real-time at 30 Hz using the KinectFusion algorithm. Non-rigid motion is detected using the residual alignment energy data of the KinectFusion algorithm allowing for unreliable motion to be discarded. Motion data is aligned to PET listmode data using injected pulse sequences into the PET/CT gantry allowing for correction of rigid body motion. Pilot data from a clinical dynamic PET/CT examination is shown.

Repurposing the Microsoft Kinect for Windows v2 for external head motion tracking for brain PET

NASA Astrophysics Data System (ADS)

Noonan, P. J.; Howard, J.; Hallett, W. A.; Gunn, R. N.

2015-11-01

Medical imaging systems such as those used in positron emission tomography (PET) are capable of spatial resolutions that enable the imaging of small, functionally important brain structures. However, the quality of data from PET brain studies is often limited by subject motion during acquisition. This is particularly challenging for patients with neurological disorders or with dynamic research studies that can last 90 min or more. Restraining head movement during the scan does not eliminate motion entirely and can be unpleasant for the subject. Head motion can be detected and measured using a variety of techniques that either use the PET data itself or an external tracking system. Advances in computer vision arising from the video gaming industry could offer significant benefits when re-purposed for medical applications. A method for measuring rigid body type head motion using the Microsoft Kinect v2 is described with results presenting  ⩽0.5 mm spatial accuracy. Motion data is measured in real-time at 30 Hz using the KinectFusion algorithm. Non-rigid motion is detected using the residual alignment energy data of the KinectFusion algorithm allowing for unreliable motion to be discarded. Motion data is aligned to PET listmode data using injected pulse sequences into the PET/CT gantry allowing for correction of rigid body motion. Pilot data from a clinical dynamic PET/CT examination is shown.

4D ultrasound speckle tracking of intra-fraction prostate motion: a phantom-based comparison with x-ray fiducial tracking using CyberKnife

NASA Astrophysics Data System (ADS)

O'Shea, Tuathan P.; Garcia, Leo J.; Rosser, Karen E.; Harris, Emma J.; Evans, Philip M.; Bamber, Jeffrey C.

2014-04-01

This study investigates the use of a mechanically-swept 3D ultrasound (3D-US) probe for soft-tissue displacement monitoring during prostate irradiation, with emphasis on quantifying the accuracy relative to CyberKnife® x-ray fiducial tracking. An US phantom, implanted with x-ray fiducial markers was placed on a motion platform and translated in 3D using five real prostate motion traces acquired using the Calypso system. Motion traces were representative of all types of motion as classified by studying Calypso data for 22 patients. The phantom was imaged using a 3D swept linear-array probe (to mimic trans-perineal imaging) and, subsequently, the kV x-ray imaging system on CyberKnife. A 3D cross-correlation block-matching algorithm was used to track speckle in the ultrasound data. Fiducial and US data were each compared with known phantom displacement. Trans-perineal 3D-US imaging could track superior-inferior (SI) and anterior-posterior (AP) motion to ≤0.81 mm root-mean-square error (RMSE) at a 1.7 Hz volume rate. The maximum kV x-ray tracking RMSE was 0.74 mm, however the prostate motion was sampled at a significantly lower imaging rate (mean: 0.04 Hz). Initial elevational (right-left RL) US displacement estimates showed reduced accuracy but could be improved (RMSE <2.0 mm) using a correlation threshold in the ultrasound tracking code to remove erroneous inter-volume displacement estimates. Mechanically-swept 3D-US can track the major components of intra-fraction prostate motion accurately but exhibits some limitations. The largest US RMSE was for elevational (RL) motion. For the AP and SI axes, accuracy was sub-millimetre. It may be feasible to track prostate motion in 2D only. 3D-US also has the potential to improve high tracking accuracy for all motion types. It would be advisable to use US in conjunction with a small (˜2.0 mm) centre-of-mass displacement threshold in which case it would be possible to take full advantage of the accuracy and high imaging rate capability.

Nearly automatic motion capture system for tracking octopus arm movements in 3D space.

PubMed

Zelman, Ido; Galun, Meirav; Akselrod-Ballin, Ayelet; Yekutieli, Yoram; Hochner, Binyamin; Flash, Tamar

2009-08-30

Tracking animal movements in 3D space is an essential part of many biomechanical studies. The most popular technique for human motion capture uses markers placed on the skin which are tracked by a dedicated system. However, this technique may be inadequate for tracking animal movements, especially when it is impossible to attach markers to the animal's body either because of its size or shape or because of the environment in which the animal performs its movements. Attaching markers to an animal's body may also alter its behavior. Here we present a nearly automatic markerless motion capture system that overcomes these problems and successfully tracks octopus arm movements in 3D space. The system is based on three successive tracking and processing stages. The first stage uses a recently presented segmentation algorithm to detect the movement in a pair of video sequences recorded by two calibrated cameras. In the second stage, the results of the first stage are processed to produce 2D skeletal representations of the moving arm. Finally, the 2D skeletons are used to reconstruct the octopus arm movement as a sequence of 3D curves varying in time. Motion tracking, segmentation and reconstruction are especially difficult problems in the case of octopus arm movements because of the deformable, non-rigid structure of the octopus arm and the underwater environment in which it moves. Our successful results suggest that the motion-tracking system presented here may be used for tracking other elongated objects.

Accurate Heart Rate Monitoring During Physical Exercises Using PPG.

PubMed

Temko, Andriy

2017-09-01

The challenging task of heart rate (HR) estimation from the photoplethysmographic (PPG) signal, during intensive physical exercises, is tackled in this paper. The study presents a detailed analysis of a novel algorithm (WFPV) that exploits a Wiener filter to attenuate the motion artifacts, a phase vocoder to refine the HR estimate and user-adaptive post-processing to track the subject physiology. Additionally, an offline version of the HR estimation algorithm that uses Viterbi decoding is designed for scenarios that do not require online HR monitoring (WFPV+VD). The performance of the HR estimation systems is rigorously compared with existing algorithms on the publically available database of 23 PPG recordings. On the whole dataset of 23 PPG recordings, the algorithms result in average absolute errors of 1.97 and 1.37 BPM in the online and offline modes, respectively. On the test dataset of 10 PPG recordings which were most corrupted with motion artifacts, WFPV has an error of 2.95 BPM on its own and 2.32 BPM in an ensemble with two existing algorithms. The error rate is significantly reduced when compared with the state-of-the art PPG-based HR estimation methods. The proposed system is shown to be accurate in the presence of strong motion artifacts and in contrast to existing alternatives has very few free parameters to tune. The algorithm has a low computational cost and can be used for fitness tracking and health monitoring in wearable devices. The MATLAB implementation of the algorithm is provided online.

SU-G-BRA-08: Diaphragm Motion Tracking Based On KV CBCT Projections with a Constrained Linear Regression Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, J; Chao, M

2016-06-15

Purpose: To develop a novel strategy to extract the respiratory motion of the thoracic diaphragm from kilovoltage cone beam computed tomography (CBCT) projections by a constrained linear regression optimization technique. Methods: A parabolic function was identified as the geometric model and was employed to fit the shape of the diaphragm on the CBCT projections. The search was initialized by five manually placed seeds on a pre-selected projection image. Temporal redundancies, the enabling phenomenology in video compression and encoding techniques, inherent in the dynamic properties of the diaphragm motion together with the geometrical shape of the diaphragm boundary and the associatedmore » algebraic constraint that significantly reduced the searching space of viable parabolic parameters was integrated, which can be effectively optimized by a constrained linear regression approach on the subsequent projections. The innovative algebraic constraints stipulating the kinetic range of the motion and the spatial constraint preventing any unphysical deviations was able to obtain the optimal contour of the diaphragm with minimal initialization. The algorithm was assessed by a fluoroscopic movie acquired at anteriorposterior fixed direction and kilovoltage CBCT projection image sets from four lung and two liver patients. The automatic tracing by the proposed algorithm and manual tracking by a human operator were compared in both space and frequency domains. Results: The error between the estimated and manual detections for the fluoroscopic movie was 0.54mm with standard deviation (SD) of 0.45mm, while the average error for the CBCT projections was 0.79mm with SD of 0.64mm for all enrolled patients. The submillimeter accuracy outcome exhibits the promise of the proposed constrained linear regression approach to track the diaphragm motion on rotational projection images. Conclusion: The new algorithm will provide a potential solution to rendering diaphragm motion and ultimately improving tumor motion management for radiation therapy of cancer patients.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rottmann, J; Berbeco, R; Keall, P

Purpose: To maximize normal tissue sparing for treatments requiring motion encompassing margins. Motion mitigation techniques including DMLC or couch tracking can freeze tumor motion within the treatment aperture potentially allowing for smaller treatment margins and thus better sparing of normal tissue. To enable for a safe application of this concept in the clinic we propose adapting margins dynamically in real-time during radiotherapy delivery based on personalized tumor localization confidence. To demonstrate technical feasibility we present a phantom study. Methods: We utilize a realistic anthropomorphic dynamic thorax phantom with a lung tumor model embedded close to the spine. The tumor, amore » 3D-printout of a patient's GTV, is moved 15mm peak-to-peak by diaphragm compression and monitored by continuous EPID imaging in real-time. Two treatment apertures are created for each beam, one representing ITV -based and the other GTV-based margin expansion. A soft tissue localization (STiL) algorithm utilizing the continuous EPID images is employed to freeze tumor motion within the treatment aperture by means of DMLC tracking. Depending on a tracking confidence measure (TCM), the treatment aperture is adjusted between the ITV and the GTV leaf. Results: We successfully demonstrate real-time personalized margin adjustment in a phantom study. We measured a system latency of about 250 ms which we compensated by utilizing a respiratory motion prediction algorithm (ridge regression). With prediction in place we observe tracking accuracies better than 1mm. For TCM=0 (as during startup) an ITV-based treatment aperture is chosen, for TCM=1 a GTV-based aperture and for 0« less

A motion algorithm to extract physical and motion parameters of mobile targets from cone-beam computed tomographic images.

PubMed

Alsbou, Nesreen; Ahmad, Salahuddin; Ali, Imad

2016-05-17

A motion algorithm has been developed to extract length, CT number level and motion amplitude of a mobile target from cone-beam CT (CBCT) images. The algorithm uses three measurable parameters: Apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm are tested with mobile targets having different well-known sizes that are made from tissue-equivalent gel which is inserted into a thorax phantom. The phantom moves sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0-20 mm. Using this motion algorithm, three unknown parameters are extracted that include: Length of the target, CT number level, speed or motion amplitude for the mobile targets from CBCT images. The motion algorithm solves for the three unknown parameters using measured length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agrees with the measured lengths which are dependent on the target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, the target length and motion amplitude. Motion frequency and phase do not affect the elongation and CT number distribution of the mobile target and could not be determined. A motion algorithm has been developed to extract three parameters that include length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement of motion tracking and sorting of the images into different breathing phases. The motion model developed here works well for tumors that have simple shapes, high contrast relative to surrounding tissues and move nearly in regular motion pattern that can be approximated with a simple sinusoidal function. This algorithm has potential applications in diagnostic CT imaging and radiotherapy in terms of motion management.

Vision-based measurement for rotational speed by improving Lucas-Kanade template tracking algorithm.

PubMed

Guo, Jie; Zhu, Chang'an; Lu, Siliang; Zhang, Dashan; Zhang, Chunyu

2016-09-01

Rotational angle and speed are important parameters for condition monitoring and fault diagnosis of rotating machineries, and their measurement is useful in precision machining and early warning of faults. In this study, a novel vision-based measurement algorithm is proposed to complete this task. A high-speed camera is first used to capture the video of the rotational object. To extract the rotational angle, the template-based Lucas-Kanade algorithm is introduced to complete motion tracking by aligning the template image in the video sequence. Given the special case of nonplanar surface of the cylinder object, a nonlinear transformation is designed for modeling the rotation tracking. In spite of the unconventional and complex form, the transformation can realize angle extraction concisely with only one parameter. A simulation is then conducted to verify the tracking effect, and a practical tracking strategy is further proposed to track consecutively the video sequence. Based on the proposed algorithm, instantaneous rotational speed (IRS) can be measured accurately and efficiently. Finally, the effectiveness of the proposed algorithm is verified on a brushless direct current motor test rig through the comparison with results obtained by the microphone. Experimental results demonstrate that the proposed algorithm can extract accurately rotational angles and can measure IRS with the advantage of noncontact and effectiveness.

Internal Motion Estimation by Internal-external Motion Modeling for Lung Cancer Radiotherapy.

PubMed

Chen, Haibin; Zhong, Zichun; Yang, Yiwei; Chen, Jiawei; Zhou, Linghong; Zhen, Xin; Gu, Xuejun

2018-02-27

The aim of this study is to develop an internal-external correlation model for internal motion estimation for lung cancer radiotherapy. Deformation vector fields that characterize the internal-external motion are obtained by respectively registering the internal organ meshes and external surface meshes from the 4DCT images via a recently developed local topology preserved non-rigid point matching algorithm. A composite matrix is constructed by combing the estimated internal phasic DVFs with external phasic and directional DVFs. Principle component analysis is then applied to the composite matrix to extract principal motion characteristics, and generate model parameters to correlate the internal-external motion. The proposed model is evaluated on a 4D NURBS-based cardiac-torso (NCAT) synthetic phantom and 4DCT images from five lung cancer patients. For tumor tracking, the center of mass errors of the tracked tumor are 0.8(±0.5)mm/0.8(±0.4)mm for synthetic data, and 1.3(±1.0)mm/1.2(±1.2)mm for patient data in the intra-fraction/inter-fraction tracking, respectively. For lung tracking, the percent errors of the tracked contours are 0.06(±0.02)/0.07(±0.03) for synthetic data, and 0.06(±0.02)/0.06(±0.02) for patient data in the intra-fraction/inter-fraction tracking, respectively. The extensive validations have demonstrated the effectiveness and reliability of the proposed model in motion tracking for both the tumor and the lung in lung cancer radiotherapy.

Accumulative Difference Image Protocol for Particle Tracking in Fluorescence Microscopy Tested in Mouse Lymphonodes

PubMed Central

Villa, Carlo E.; Caccia, Michele; Sironi, Laura; D'Alfonso, Laura; Collini, Maddalena; Rivolta, Ilaria; Miserocchi, Giuseppe; Gorletta, Tatiana; Zanoni, Ivan; Granucci, Francesca; Chirico, Giuseppe

2010-01-01

The basic research in cell biology and in medical sciences makes large use of imaging tools mainly based on confocal fluorescence and, more recently, on non-linear excitation microscopy. Substantially the aim is the recognition of selected targets in the image and their tracking in time. We have developed a particle tracking algorithm optimized for low signal/noise images with a minimum set of requirements on the target size and with no a priori knowledge of the type of motion. The image segmentation, based on a combination of size sensitive filters, does not rely on edge detection and is tailored for targets acquired at low resolution as in most of the in-vivo studies. The particle tracking is performed by building, from a stack of Accumulative Difference Images, a single 2D image in which the motion of the whole set of the particles is coded in time by a color level. This algorithm, tested here on solid-lipid nanoparticles diffusing within cells and on lymphocytes diffusing in lymphonodes, appears to be particularly useful for the cellular and the in-vivo microscopy image processing in which few a priori assumption on the type, the extent and the variability of particle motions, can be done. PMID:20808918

Accumulative difference image protocol for particle tracking in fluorescence microscopy tested in mouse lymphonodes.

PubMed

Villa, Carlo E; Caccia, Michele; Sironi, Laura; D'Alfonso, Laura; Collini, Maddalena; Rivolta, Ilaria; Miserocchi, Giuseppe; Gorletta, Tatiana; Zanoni, Ivan; Granucci, Francesca; Chirico, Giuseppe

2010-08-17

The basic research in cell biology and in medical sciences makes large use of imaging tools mainly based on confocal fluorescence and, more recently, on non-linear excitation microscopy. Substantially the aim is the recognition of selected targets in the image and their tracking in time. We have developed a particle tracking algorithm optimized for low signal/noise images with a minimum set of requirements on the target size and with no a priori knowledge of the type of motion. The image segmentation, based on a combination of size sensitive filters, does not rely on edge detection and is tailored for targets acquired at low resolution as in most of the in-vivo studies. The particle tracking is performed by building, from a stack of Accumulative Difference Images, a single 2D image in which the motion of the whole set of the particles is coded in time by a color level. This algorithm, tested here on solid-lipid nanoparticles diffusing within cells and on lymphocytes diffusing in lymphonodes, appears to be particularly useful for the cellular and the in-vivo microscopy image processing in which few a priori assumption on the type, the extent and the variability of particle motions, can be done.

Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery.

PubMed

Rottmann, Joerg; Keall, Paul; Berbeco, Ross

2013-09-01

To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient. 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps. Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm. The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time.

The performance of matched-field track-before-detect methods using shallow-water Pacific data.

PubMed

Tantum, Stacy L; Nolte, Loren W; Krolik, Jeffrey L; Harmanci, Kerem

2002-07-01

Matched-field track-before-detect processing, which extends the concept of matched-field processing to include modeling of the source dynamics, has recently emerged as a promising approach for maintaining the track of a moving source. In this paper, optimal Bayesian and minimum variance beamforming track-before-detect algorithms which incorporate a priori knowledge of the source dynamics in addition to the underlying uncertainties in the ocean environment are presented. A Markov model is utilized for the source motion as a means of capturing the stochastic nature of the source dynamics without assuming uniform motion. In addition, the relationship between optimal Bayesian track-before-detect processing and minimum variance track-before-detect beamforming is examined, revealing how an optimal tracking philosophy may be used to guide the modification of existing beamforming techniques to incorporate track-before-detect capabilities. Further, the benefits of implementing an optimal approach over conventional methods are illustrated through application of these methods to shallow-water Pacific data collected as part of the SWellEX-1 experiment. The results show that incorporating Markovian dynamics for the source motion provides marked improvement in the ability to maintain target track without the use of a uniform velocity hypothesis.

An algorithm of adaptive scale object tracking in occlusion

NASA Astrophysics Data System (ADS)

Zhao, Congmei

2017-05-01

Although the correlation filter-based trackers achieve the competitive results both on accuracy and robustness, there are still some problems in handling scale variations, object occlusion, fast motions and so on. In this paper, a multi-scale kernel correlation filter algorithm based on random fern detector was proposed. The tracking task was decomposed into the target scale estimation and the translation estimation. At the same time, the Color Names features and HOG features were fused in response level to further improve the overall tracking performance of the algorithm. In addition, an online random fern classifier was trained to re-obtain the target after the target was lost. By comparing with some algorithms such as KCF, DSST, TLD, MIL, CT and CSK, experimental results show that the proposed approach could estimate the object state accurately and handle the object occlusion effectively.

Performance Evaluation Within CASE_ATTI of MHT and JVC Association Algorithms for COMDAT TD

DTIC Science & Technology

2007-05-01

les résultats du travail effectué dans le cadre de l’analyse de sensibilité des algorithmes uti- lisés dans COMDAT, comparativement à ceux...is also very important in tracking system. Neverthe- less, tracking performance with even the best designed filter may become very degraded in the...for completeness. 2.2 IMM Some practical model of target motion is assumed for the design of the Kalman filter. This target kinematics model is

Autonomous & Adaptive Oceanographic Feature Tracking on Board Autonomous Underwater Vehicles

DTIC Science & Technology

2015-02-01

44 3.6 Tracking the Marine ermocline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.6.1 ermocline Definition ...intelligent autonomy algorithms to adapt the vehicle’s motion to changes in the environment, effectively seeking out and tracking an oceanographic...interface, H is the mean water depth, and f is the Coriolis parameter (twice the earth’s angular velocity about its vertical axis) [38]. at is, the

A GPU-accelerated 3D Coupled Sub-sample Estimation Algorithm for Volumetric Breast Strain Elastography

PubMed Central

Peng, Bo; Wang, Yuqi; Hall, Timothy J; Jiang, Jingfeng

2017-01-01

Our primary objective of this work was to extend a previously published 2D coupled sub-sample tracking algorithm for 3D speckle tracking in the framework of ultrasound breast strain elastography. In order to overcome heavy computational cost, we investigated the use of a graphic processing unit (GPU) to accelerate the 3D coupled sub-sample speckle tracking method. The performance of the proposed GPU implementation was tested using a tissue-mimicking (TM) phantom and in vivo breast ultrasound data. The performance of this 3D sub-sample tracking algorithm was compared with the conventional 3D quadratic sub-sample estimation algorithm. On the basis of these evaluations, we concluded that the GPU implementation of this 3D sub-sample estimation algorithm can provide high-quality strain data (i.e. high correlation between the pre- and the motion-compensated post-deformation RF echo data and high contrast-to-noise ratio strain images), as compared to the conventional 3D quadratic sub-sample algorithm. Using the GPU implementation of the 3D speckle tracking algorithm, volumetric strain data can be achieved relatively fast (approximately 20 seconds per volume [2.5 cm × 2.5 cm × 2.5 cm]). PMID:28166493

Dictionary learning-based spatiotemporal regularization for 3D dense speckle tracking

NASA Astrophysics Data System (ADS)

Lu, Allen; Zontak, Maria; Parajuli, Nripesh; Stendahl, John C.; Boutagy, Nabil; Eberle, Melissa; O'Donnell, Matthew; Sinusas, Albert J.; Duncan, James S.

2017-03-01

Speckle tracking is a common method for non-rigid tissue motion analysis in 3D echocardiography, where unique texture patterns are tracked through the cardiac cycle. However, poor tracking often occurs due to inherent ultrasound issues, such as image artifacts and speckle decorrelation; thus regularization is required. Various methods, such as optical flow, elastic registration, and block matching techniques have been proposed to track speckle motion. Such methods typically apply spatial and temporal regularization in a separate manner. In this paper, we propose a joint spatiotemporal regularization method based on an adaptive dictionary representation of the dense 3D+time Lagrangian motion field. Sparse dictionaries have good signal adaptive and noise-reduction properties; however, they are prone to quantization errors. Our method takes advantage of the desirable noise suppression, while avoiding the undesirable quantization error. The idea is to enforce regularization only on the poorly tracked trajectories. Specifically, our method 1.) builds data-driven 4-dimensional dictionary of Lagrangian displacements using sparse learning, 2.) automatically identifies poorly tracked trajectories (outliers) based on sparse reconstruction errors, and 3.) performs sparse reconstruction of the outliers only. Our approach can be applied on dense Lagrangian motion fields calculated by any method. We demonstrate the effectiveness of our approach on a baseline block matching speckle tracking and evaluate performance of the proposed algorithm using tracking and strain accuracy analysis.

Robust tracking of a virtual electrode on a coronary sinus catheter for atrial fibrillation ablation procedures

NASA Astrophysics Data System (ADS)

Wu, Wen; Chen, Terrence; Strobel, Norbert; Comaniciu, Dorin

2012-02-01

Catheter tracking in X-ray fluoroscopic images has become more important in interventional applications for atrial fibrillation (AF) ablation procedures. It provides real-time guidance for the physicians and can be used as reference for motion compensation applications. In this paper, we propose a novel approach to track a virtual electrode (VE), which is a non-existing electrode on the coronary sinus (CS) catheter at a more proximal location than any real electrodes. Successful tracking of the VE can provide more accurate motion information than tracking of real electrodes. To achieve VE tracking, we first model the CS catheter as a set of electrodes which are detected by our previously published learning-based approach.1 The tracked electrodes are then used to generate the hypotheses for tracking the VE. Model-based hypotheses are fused and evaluated by a Bayesian framework. Evaluation has been conducted on a database of clinical AF ablation data including challenging scenarios such as low signal-to-noise ratio (SNR), occlusion and nonrigid deformation. Our approach obtains 0.54mm median error and 90% of evaluated data have errors less than 1.67mm. The speed of our tracking algorithm reaches 6 frames-per-second on most data. Our study on motion compensation shows that using the VE as reference provides a good point to detect non-physiological catheter motion during the AF ablation procedures.2

Real time eye tracking using Kalman extended spatio-temporal context learning

NASA Astrophysics Data System (ADS)

Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu

2017-06-01

Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

Reliable motion detection of small targets in video with low signal-to-clutter ratios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nichols, S.A.; Naylor, R.B.

1995-07-01

Studies show that vigilance decreases rapidly after several minutes when human operators are required to search live video for infrequent intrusion detections. Therefore, there is a need for systems which can automatically detect targets in live video and reserve the operator`s attention for assessment only. Thus far, automated systems have not simultaneously provided adequate detection sensitivity, false alarm suppression, and ease of setup when used in external, unconstrained environments. This unsatisfactory performance can be exacerbated by poor video imagery with low contrast, high noise, dynamic clutter, image misregistration, and/or the presence of small, slow, or erratically moving targets. This papermore » describes a highly adaptive video motion detection and tracking algorithm which has been developed as part of Sandia`s Advanced Exterior Sensor (AES) program. The AES is a wide-area detection and assessment system for use in unconstrained exterior security applications. The AES detection and tracking algorithm provides good performance under stressing data and environmental conditions. Features of the algorithm include: reliable detection with negligible false alarm rate of variable velocity targets having low signal-to-clutter ratios; reliable tracking of targets that exhibit motion that is non-inertial, i.e., varies in direction and velocity; automatic adaptation to both infrared and visible imagery with variable quality; and suppression of false alarms caused by sensor flaws and/or cutouts.« less

Multi-object tracking of human spermatozoa

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; Østergaard, Jakob; Johansen, Peter; de Bruijne, Marleen

2008-03-01

We propose a system for tracking of human spermatozoa in phase-contrast microscopy image sequences. One of the main aims of a computer-aided sperm analysis (CASA) system is to automatically assess sperm quality based on spermatozoa motility variables. In our case, the problem of assessing sperm quality is cast as a multi-object tracking problem, where the objects being tracked are the spermatozoa. The system combines a particle filter and Kalman filters for robust motion estimation of the spermatozoa tracks. Further, the combinatorial aspect of assigning observations to labels in the particle filter is formulated as a linear assignment problem solved using the Hungarian algorithm on a rectangular cost matrix, making the algorithm capable of handling missing or spurious observations. The costs are calculated using hidden Markov models that express the plausibility of an observation being the next position in the track history of the particle labels. Observations are extracted using a scale-space blob detector utilizing the fact that the spermatozoa appear as bright blobs in a phase-contrast microscope. The output of the system is the complete motion track of each of the spermatozoa. Based on these tracks, different CASA motility variables can be computed, for example curvilinear velocity or straight-line velocity. The performance of the system is tested on three different phase-contrast image sequences of varying complexity, both by visual inspection of the estimated spermatozoa tracks and by measuring the mean squared error (MSE) between the estimated spermatozoa tracks and manually annotated tracks, showing good agreement.

Robust tracking and quantification of C. elegans body shape and locomotion through coiling, entanglement, and omega bends

PubMed Central

Roussel, Nicolas; Sprenger, Jeff; Tappan, Susan J; Glaser, Jack R

2014-01-01

The behavior of the well-characterized nematode, Caenorhabditis elegans (C. elegans), is often used to study the neurologic control of sensory and motor systems in models of health and neurodegenerative disease. To advance the quantification of behaviors to match the progress made in the breakthroughs of genetics, RNA, proteins, and neuronal circuitry, analysis must be able to extract subtle changes in worm locomotion across a population. The analysis of worm crawling motion is complex due to self-overlap, coiling, and entanglement. Using current techniques, the scope of the analysis is typically restricted to worms to their non-occluded, uncoiled state which is incomplete and fundamentally biased. Using a model describing the worm shape and crawling motion, we designed a deformable shape estimation algorithm that is robust to coiling and entanglement. This model-based shape estimation algorithm has been incorporated into a framework where multiple worms can be automatically detected and tracked simultaneously throughout the entire video sequence, thereby increasing throughput as well as data validity. The newly developed algorithms were validated against 10 manually labeled datasets obtained from video sequences comprised of various image resolutions and video frame rates. The data presented demonstrate that tracking methods incorporated in WormLab enable stable and accurate detection of these worms through coiling and entanglement. Such challenging tracking scenarios are common occurrences during normal worm locomotion. The ability for the described approach to provide stable and accurate detection of C. elegans is critical to achieve unbiased locomotory analysis of worm motion. PMID:26435884

Effectiveness of an automatic tracking software in underwater motion analysis.

PubMed

Magalhaes, Fabrício A; Sawacha, Zimi; Di Michele, Rocco; Cortesi, Matteo; Gatta, Giorgio; Fantozzi, Silvia

2013-01-01

Tracking of markers placed on anatomical landmarks is a common practice in sports science to perform the kinematic analysis that interests both athletes and coaches. Although different software programs have been developed to automatically track markers and/or features, none of them was specifically designed to analyze underwater motion. Hence, this study aimed to evaluate the effectiveness of a software developed for automatic tracking of underwater movements (DVP), based on the Kanade-Lucas-Tomasi feature tracker. Twenty-one video recordings of different aquatic exercises (n = 2940 markers' positions) were manually tracked to determine the markers' center coordinates. Then, the videos were automatically tracked using DVP and a commercially available software (COM). Since tracking techniques may produce false targets, an operator was instructed to stop the automatic procedure and to correct the position of the cursor when the distance between the calculated marker's coordinate and the reference one was higher than 4 pixels. The proportion of manual interventions required by the software was used as a measure of the degree of automation. Overall, manual interventions were 10.4% lower for DVP (7.4%) than for COM (17.8%). Moreover, when examining the different exercise modes separately, the percentage of manual interventions was 5.6% to 29.3% lower for DVP than for COM. Similar results were observed when analyzing the type of marker rather than the type of exercise, with 9.9% less manual interventions for DVP than for COM. In conclusion, based on these results, the developed automatic tracking software presented can be used as a valid and useful tool for underwater motion analysis. Key PointsThe availability of effective software for automatic tracking would represent a significant advance for the practical use of kinematic analysis in swimming and other aquatic sports.An important feature of automatic tracking software is to require limited human interventions and supervision, thus allowing short processing time.When tracking underwater movements, the degree of automation of the tracking procedure is influenced by the capability of the algorithm to overcome difficulties linked to the small target size, the low image quality and the presence of background clutters.The newly developed feature-tracking algorithm has shown a good automatic tracking effectiveness in underwater motion analysis with significantly smaller percentage of required manual interventions when compared to a commercial software.

A Novel Method for Tracking Individuals of Fruit Fly Swarms Flying in a Laboratory Flight Arena.

PubMed

Cheng, Xi En; Qian, Zhi-Ming; Wang, Shuo Hong; Jiang, Nan; Guo, Aike; Chen, Yan Qiu

2015-01-01

The growing interest in studying social behaviours of swarming fruit flies, Drosophila melanogaster, has heightened the need for developing tools that provide quantitative motion data. To achieve such a goal, multi-camera three-dimensional tracking technology is the key experimental gateway. We have developed a novel tracking system for tracking hundreds of fruit flies flying in a confined cubic flight arena. In addition to the proposed tracking algorithm, this work offers additional contributions in three aspects: body detection, orientation estimation, and data validation. To demonstrate the opportunities that the proposed system offers for generating high-throughput quantitative motion data, we conducted experiments on five experimental configurations. We also performed quantitative analysis on the kinematics and the spatial structure and the motion patterns of fruit fly swarms. We found that there exists an asymptotic distance between fruit flies in swarms as the population density increases. Further, we discovered the evidence for repulsive response when the distance between fruit flies approached the asymptotic distance. Overall, the proposed tracking system presents a powerful method for studying flight behaviours of fruit flies in a three-dimensional environment.

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

PubMed

Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng

2018-01-01

Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

SU-E-J-112: The Impact of Cine EPID Image Acquisition Frame Rate On Markerless Soft-Tissue Tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yip, S; Rottmann, J; Berbeco, R

2014-06-01

Purpose: Although reduction of the cine EPID acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor auto-tracking results. The impact of motion blurring and image noise on the tracking performance was investigated. Methods: Phantom and patient images were acquired at a frame rate of 12.87Hz on an AS1000 portal imager. Low frame rate images were obtained by continuous frame averaging. A previously validated tracking algorithm was employed for auto-tracking. The difference between the programmed and auto-tracked positions of a Las Vegas phantommore » moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at eleven field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise were correlated with δ using Pearson correlation coefficient (R). Results: For both phantom and patient studies, the auto-tracking errors increased at frame rates lower than 4.29Hz. Above 4.29Hz, changes in errors were negligible with δ<1.60mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R=0.94) and patient studies (R=0.72). Moderate to poor correlation was found between image noise and tracking error with R -0.58 and -0.19 for both studies, respectively. Conclusion: An image acquisition frame rate of at least 4.29Hz is recommended for cine EPID tracking. Motion blurring in images with frame rates below 4.39Hz can substantially reduce the accuracy of auto-tracking. This work is supported in part by the Varian Medical Systems, Inc.« less

Hybrid markerless tracking of complex articulated motion in golf swings.

PubMed

Fung, Sim Kwoh; Sundaraj, Kenneth; Ahamed, Nizam Uddin; Kiang, Lam Chee; Nadarajah, Sivadev; Sahayadhas, Arun; Ali, Md Asraf; Islam, Md Anamul; Palaniappan, Rajkumar

2014-04-01

Sports video tracking is a research topic that has attained increasing attention due to its high commercial potential. A number of sports, including tennis, soccer, gymnastics, running, golf, badminton and cricket have been utilised to display the novel ideas in sports motion tracking. The main challenge associated with this research concerns the extraction of a highly complex articulated motion from a video scene. Our research focuses on the development of a markerless human motion tracking system that tracks the major body parts of an athlete straight from a sports broadcast video. We proposed a hybrid tracking method, which consists of a combination of three algorithms (pyramidal Lucas-Kanade optical flow (LK), normalised correlation-based template matching and background subtraction), to track the golfer's head, body, hands, shoulders, knees and feet during a full swing. We then match, track and map the results onto a 2D articulated human stick model to represent the pose of the golfer over time. Our work was tested using two video broadcasts of a golfer, and we obtained satisfactory results. The current outcomes of this research can play an important role in enhancing the performance of a golfer, provide vital information to sports medicine practitioners by providing technically sound guidance on movements and should assist to diminish the risk of golfing injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.

Higher-Order Motion Inputs For Visual Figure Tracking: Control Algorithms and Neural Circuits

DTIC Science & Technology

2015-05-30

3 3 Accomplishments / New Findings .......................................................................................... 3 3.1...Posters: ........................................................................ 51 6.2 Consultative and advisory functions ...53 7 New Discoveries, Inventions, or Patent Disclosures

Simultaneous glacier surface elevation and flow velocity mapping from cross-track pushbroom satellite Imagery

NASA Astrophysics Data System (ADS)

Noh, M. J.; Howat, I. M.

2017-12-01

Glaciers and ice sheets are changing rapidly. Digital Elevation Models (DEMs) and Velocity Maps (VMs) obtained from repeat satellite imagery provide critical measurements of changes in glacier dynamics and mass balance over large, remote areas. DEMs created from stereopairs obtained during the same satellite pass through sensor re-pointing (i.e. "in-track stereo") have been most commonly used. In-track stereo has the advantage of minimizing the time separation and, thus, surface motion between image acquisitions, so that the ice surface can be assumed motionless in when collocating pixels between image pairs. Since the DEM extraction process assumes that all motion between collocated pixels is due to parallax or sensor model error, significant ice motion results in DEM quality loss or failure. In-track stereo, however, puts a greater demand on satellite tasking resources and, therefore, is much less abundant than single-scan imagery. Thus, if ice surface motion can be mitigated, the ability to extract surface elevation measurements from pairs of repeat single-scan "cross-track" imagery would greatly increase the extent and temporal resolution of ice surface change. Additionally, the ice motion measured by the DEM extraction process would itself provide a useful velocity measurement. We develop a novel algorithm for generating high-quality DEMs and VMs from cross-track image pairs without any prior information using the Surface Extraction from TIN-based Searchspace Minimization (SETSM) algorithm and its sensor model bias correction capabilities. Using a test suite of repeat, single-scan imagery from WorldView and QuickBird sensors collected over fast-moving outlet glaciers, we develop a method by which RPC biases between images are first calculated and removed over ice-free surfaces. Subpixel displacements over the ice are then constrained and used to correct the parallax estimate. Initial tests yield DEM results with the same quality as in-track stereo for cases where snowfall has not occurred between the two images and when the images have similar ground sample distances. The resulting velocity map also closely matches independent measurements.

Lateral Motion and Bending of Microtubules Studied with a New Single-Filament Tracking Routine in Living Cells

PubMed Central

Pallavicini, Carla; Levi, Valeria; Wetzler, Diana E.; Angiolini, Juan F.; Benseñor, Lorena; Despósito, Marcelo A.; Bruno, Luciana

2014-01-01

The cytoskeleton is involved in numerous cellular processes such as migration, division, and contraction and provides the tracks for transport driven by molecular motors. Therefore, it is very important to quantify the mechanical behavior of the cytoskeletal filaments to get a better insight into cell mechanics and organization. It has been demonstrated that relevant mechanical properties of microtubules can be extracted from the analysis of their motion and shape fluctuations. However, tracking individual filaments in living cells is extremely complex due, for example, to the high and heterogeneous background. We introduce a believed new tracking algorithm that allows recovering the coordinates of fluorescent microtubules with ∼9 nm precision in in vitro conditions. To illustrate potential applications of this algorithm, we studied the curvature distributions of fluorescent microtubules in living cells. By performing a Fourier analysis of the microtubule shapes, we found that the curvatures followed a thermal-like distribution as previously reported with an effective persistence length of ∼20 μm, a value significantly smaller than that measured in vitro. We also verified that the microtubule-associated protein XTP or the depolymerization of the actin network do not affect this value; however, the disruption of intermediate filaments decreased the persistence length. Also, we recovered trajectories of microtubule segments in actin or intermediate filament-depleted cells, and observed a significant increase of their motion with respect to untreated cells showing that these filaments contribute to the overall organization of the microtubule network. Moreover, the analysis of trajectories of microtubule segments in untreated cells showed that these filaments presented a slower but more directional motion in the cortex with respect to the perinuclear region, and suggests that the tracking routine would allow mapping the microtubule dynamical organization in cells. PMID:24940780

Detection and tracking of human targets in indoor and urban environments using through-the-wall radar sensors

NASA Astrophysics Data System (ADS)

Radzicki, Vincent R.; Boutte, David; Taylor, Paul; Lee, Hua

2017-05-01

Radar based detection of human targets behind walls or in dense urban environments is an important technical challenge with many practical applications in security, defense, and disaster recovery. Radar reflections from a human can be orders of magnitude weaker than those from objects encountered in urban settings such as walls, cars, or possibly rubble after a disaster. Furthermore, these objects can act as secondary reflectors and produce multipath returns from a person. To mitigate these issues, processing of radar return data needs to be optimized for recognizing human motion features such as walking, running, or breathing. This paper presents a theoretical analysis on the modulation effects human motion has on the radar waveform and how high levels of multipath can distort these motion effects. From this analysis, an algorithm is designed and optimized for tracking human motion in heavily clutter environments. The tracking results will be used as the fundamental detection/classification tool to discriminate human targets from others by identifying human motion traits such as predictable walking patterns and periodicity in breathing rates. The theoretical formulations will be tested against simulation and measured data collected using a low power, portable see-through-the-wall radar system that could be practically deployed in real-world scenarios. Lastly, the performance of the algorithm is evaluated in a series of experiments where both a single person and multiple people are moving in an indoor, cluttered environment.

A novel vehicle tracking algorithm based on mean shift and active contour model in complex environment

NASA Astrophysics Data System (ADS)

Cai, Lei; Wang, Lin; Li, Bo; Zhang, Libao; Lv, Wen

2017-06-01

Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can't be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, Mean-Shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. Meanwhile, the outline information is used to aid tracking algorithm to improve it.

Context-specific selection of algorithms for recursive feature tracking in endoscopic image using a new methodology.

PubMed

Selka, F; Nicolau, S; Agnus, V; Bessaid, A; Marescaux, J; Soler, L

2015-03-01

In minimally invasive surgery, the tracking of deformable tissue is a critical component for image-guided applications. Deformation of the tissue can be recovered by tracking features using tissue surface information (texture, color,...). Recent work in this field has shown success in acquiring tissue motion. However, the performance evaluation of detection and tracking algorithms on such images are still difficult and are not standardized. This is mainly due to the lack of ground truth data on real data. Moreover, in order to avoid supplementary techniques to remove outliers, no quantitative work has been undertaken to evaluate the benefit of a pre-process based on image filtering, which can improve feature tracking robustness. In this paper, we propose a methodology to validate detection and feature tracking algorithms, using a trick based on forward-backward tracking that provides an artificial ground truth data. We describe a clear and complete methodology to evaluate and compare different detection and tracking algorithms. In addition, we extend our framework to propose a strategy to identify the best combinations from a set of detector, tracker and pre-process algorithms, according to the live intra-operative data. Experimental results have been performed on in vivo datasets and show that pre-process can have a strong influence on tracking performance and that our strategy to find the best combinations is relevant for a reasonable computation cost. Copyright © 2014 Elsevier Ltd. All rights reserved.

SU-E-J-150: Four-Dimensional Cone-Beam CT Algorithm by Extraction of Physical and Motion Parameter of Mobile Targets Retrospective to Image Reconstruction with Motion Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ali, I; Ahmad, S; Alsbou, N

Purpose: To develop 4D-cone-beam CT (CBCT) algorithm by motion modeling that extracts actual length, CT numbers level and motion amplitude of a mobile target retrospective to image reconstruction by motion modeling. Methods: The algorithm used three measurable parameters: apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine actual length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm were tested with mobile targets that with different well-known sizes made from tissue-equivalent gel which was inserted into a thorax phantom. The phantom moved sinusoidally in one-direction to simulatemore » respiratory motion using eight amplitudes ranging 0–20mm. Results: Using this 4D-CBCT algorithm, three unknown parameters were extracted that include: length of the target, CT number level, speed or motion amplitude for the mobile targets retrospective to image reconstruction. The motion algorithms solved for the three unknown parameters using measurable apparent length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on the actual target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, actual target length and motion amplitude. Motion frequency and phase did not affect the elongation and CT number distribution of the mobile target and could not be determined. Conclusion: A 4D-CBCT motion algorithm was developed to extract three parameters that include actual length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement to motion tracking and sorting of the images into different breathing phases which has potential applications in diagnostic CT imaging and radiotherapy.« less

Motion tracking in the liver: Validation of a method based on 4D ultrasound using a nonrigid registration technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vijayan, Sinara, E-mail: sinara.vijayan@ntnu.no; Klein, Stefan; Hofstad, Erlend Fagertun

Purpose: Treatments like radiotherapy and focused ultrasound in the abdomen require accurate motion tracking, in order to optimize dosage delivery to the target and minimize damage to critical structures and healthy tissues around the target. 4D ultrasound is a promising modality for motion tracking during such treatments. In this study, the authors evaluate the accuracy of motion tracking in the liver based on deformable registration of 4D ultrasound images. Methods: The offline analysis was performed using a nonrigid registration algorithm that was specifically designed for motion estimation from dynamic imaging data. The method registers the entire 4D image data sequencemore » in a groupwise optimization fashion, thus avoiding a bias toward a specifically chosen reference time point. Three healthy volunteers were scanned over several breathing cycles (12 s) from three different positions and angles on the abdomen; a total of nine 4D scans for the three volunteers. Well-defined anatomic landmarks were manually annotated in all 96 time frames for assessment of the automatic algorithm. The error of the automatic motion estimation method was compared with interobserver variability. The authors also performed experiments to investigate the influence of parameters defining the deformation field flexibility and evaluated how well the method performed with a lower temporal resolution in order to establish the minimum frame rate required for accurate motion estimation. Results: The registration method estimated liver motion with an error of 1 mm (75% percentile over all datasets), which was lower than the interobserver variability of 1.4 mm. The results were only slightly dependent on the degrees of freedom of the deformation model. The registration error increased to 2.8 mm with an eight times lower temporal resolution. Conclusions: The authors conclude that the methodology was able to accurately track the motion of the liver in the 4D ultrasound data. The authors believe that the method has potential in interventions on moving abdominal organs such as MR or ultrasound guided focused ultrasound therapy and radiotherapy, pending the method is enabled to run in real-time. The data and the annotations used for this study are made publicly available for those who would like to test other methods on 4D liver ultrasound data.« less

Automatic Tracking Algorithm in Coaxial Near-Infrared Laser Ablation Endoscope for Fetus Surgery

NASA Astrophysics Data System (ADS)

Hu, Yan; Yamanaka, Noriaki; Masamune, Ken

2014-07-01

This article reports a stable vessel object tracking method for the treatment of twin-to-twin transfusion syndrome based on our previous 2 DOF endoscope. During the treatment of laser coagulation, it is necessary to focus on the exact position of the target object, however it moves by the mother's respiratory motion and still remains a challenge to obtain and track the position precisely. In this article, an algorithm which uses features from accelerated segment test (FAST) to extract the features and optical flow as the object tracking method, is proposed to deal with above problem. Further, we experimentally simulate the movement due to the mother's respiration, and the results of position errors and similarity verify the effectiveness of the proposed tracking algorithm for laser ablation endoscopy in-vitro and under water considering two influential factors. At average, the errors are about 10 pixels and the similarity over 0.92 are obtained in the experiments.

An error-based micro-sensor capture system for real-time motion estimation

NASA Astrophysics Data System (ADS)

Yang, Lin; Ye, Shiwei; Wang, Zhibo; Huang, Zhipei; Wu, Jiankang; Kong, Yongmei; Zhang, Li

2017-10-01

A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacement in real life activities. In the proposed filter algorithm, the gyroscope bias error, orientation error and magnetic disturbance error are estimated and compensated, significantly reducing the orientation estimation error due to sensor noise and drift. Displacement estimation, especially for activities such as jumping, has been the challenge in micro-sensor motion capture. An adaptive gait phase detection algorithm has been developed to accommodate accurate displacement estimation in different types of activities. The performance of this system is benchmarked with respect to the results of VICON optical capture system. The experimental results have demonstrated effectiveness of the system in daily activities tracking, with estimation error 0.16 ± 0.06 m for normal walking and 0.13 ± 0.11 m for jumping motions. Research supported by the National Natural Science Foundation of China (Nos. 61431017, 81272166).

Bounded Kalman filter method for motion-robust, non-contact heart rate estimation

PubMed Central

Prakash, Sakthi Kumar Arul; Tucker, Conrad S.

2018-01-01

The authors of this work present a real-time measurement of heart rate across different lighting conditions and motion categories. This is an advancement over existing remote Photo Plethysmography (rPPG) methods that require a static, controlled environment for heart rate detection, making them impractical for real-world scenarios wherein a patient may be in motion, or remotely connected to a healthcare provider through telehealth technologies. The algorithm aims to minimize motion artifacts such as blurring and noise due to head movements (uniform, random) by employing i) a blur identification and denoising algorithm for each frame and ii) a bounded Kalman filter technique for motion estimation and feature tracking. A case study is presented that demonstrates the feasibility of the algorithm in non-contact estimation of the pulse rate of subjects performing everyday head and body movements. The method in this paper outperforms state of the art rPPG methods in heart rate detection, as revealed by the benchmarked results. PMID:29552419

Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery

PubMed Central

Rottmann, Joerg; Keall, Paul; Berbeco, Ross

2013-01-01

Purpose: To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient. Methods: 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps. Results: Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm. Conclusions: The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time. PMID:24007146

SU-D-210-05: The Accuracy of Raw and B-Mode Image Data for Ultrasound Speckle Tracking in Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Shea, T; Bamber, J; Harris, E

Purpose: For ultrasound speckle tracking there is some evidence that the envelope-detected signal (the main step in B-mode image formation) may be more accurate than raw ultrasound data for tracking larger inter-frame tissue motion. This study investigates the accuracy of raw radio-frequency (RF) versus non-logarithmic compressed envelope-detected (B-mode) data for ultrasound speckle tracking in the context of image-guided radiation therapy. Methods: Transperineal ultrasound RF data was acquired (with a 7.5 MHz linear transducer operating at a 12 Hz frame rate) from a speckle phantom moving with realistic intra-fraction prostate motion derived from a commercial tracking system. A normalised cross-correlation templatemore » matching algorithm was used to track speckle motion at the focus using (i) the RF signal and (ii) the B-mode signal. A range of imaging rates (0.5 to 12 Hz) were simulated by decimating the imaging sequences, therefore simulating larger to smaller inter-frame displacements. Motion estimation accuracy was quantified by comparison with known phantom motion. Results: The differences between RF and B-mode motion estimation accuracy (2D mean and 95% errors relative to ground truth displacements) were less than 0.01 mm for stable and persistent motion types and 0.2 mm for transient motion for imaging rates of 0.5 to 12 Hz. The mean correlation for all motion types and imaging rates was 0.851 and 0.845 for RF and B-mode data, respectively. Data type is expected to have most impact on axial (Superior-Inferior) motion estimation. Axial differences were <0.004 mm for stable and persistent motion and <0.3 mm for transient motion (axial mean errors were lowest for B-mode in all cases). Conclusions: Using the RF or B-mode signal for speckle motion estimation is comparable for translational prostate motion. B-mode image formation may involve other signal-processing steps which also influence motion estimation accuracy. A similar study for respiratory-induced motion would also be prudent. This work is support by Cancer Research UK Programme Grant C33589/A19727.« less

Optical head tracking for functional magnetic resonance imaging using structured light.

PubMed

Zaremba, Andrei A; MacFarlane, Duncan L; Tseng, Wei-Che; Stark, Andrew J; Briggs, Richard W; Gopinath, Kaundinya S; Cheshkov, Sergey; White, Keith D

2008-07-01

An accurate motion-tracking technique is needed to compensate for subject motion during functional magnetic resonance imaging (fMRI) procedures. Here, a novel approach to motion metrology is discussed. A structured light pattern specifically coded for digital signal processing is positioned onto a fiduciary of the patient. As the patient undergoes spatial transformations in 6 DoF (degrees of freedom), a high-resolution CCD camera captures successive images for analysis on a computing platform. A high-speed image processing algorithm is used to calculate spatial transformations in a time frame commensurate with patient movements (10-100 ms) and with a precision of at least 0.5 microm for translations and 0.1 deg for rotations.

Moving Object Detection Using a Parallax Shift Vector Algorithm

NASA Astrophysics Data System (ADS)

Gural, Peter S.; Otto, Paul R.; Tedesco, Edward F.

2018-07-01

There are various algorithms currently in use to detect asteroids from ground-based observatories, but they are generally restricted to linear or mildly curved movement of the target object across the field of view. Space-based sensors in high inclination, low Earth orbits can induce significant parallax in a collected sequence of images, especially for objects at the typical distances of asteroids in the inner solar system. This results in a highly nonlinear motion pattern of the asteroid across the sensor, which requires a more sophisticated search pattern for detection processing. Both the classical pattern matching used in ground-based asteroid search and the more sensitive matched filtering and synthetic tracking techniques, can be adapted to account for highly complex parallax motion. A new shift vector generation methodology is discussed along with its impacts on commonly used detection algorithms, processing load, and responsiveness to asteroid track reporting. The matched filter, template generator, and pattern matcher source code for the software described herein are available via GitHub.

SU-E-T-465: Dose Calculation Method for Dynamic Tumor Tracking Using a Gimbal-Mounted Linac

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sugimoto, S; Inoue, T; Kurokawa, C

Purpose: Dynamic tumor tracking using the gimbal-mounted linac (Vero4DRT, Mitsubishi Heavy Industries, Ltd., Japan) has been available when respiratory motion is significant. The irradiation accuracy of the dynamic tumor tracking has been reported to be excellent. In addition to the irradiation accuracy, a fast and accurate dose calculation algorithm is needed to validate the dose distribution in the presence of respiratory motion because the multiple phases of it have to be considered. A modification of dose calculation algorithm is necessary for the gimbal-mounted linac due to the degrees of freedom of gimbal swing. The dose calculation algorithm for the gimbalmore » motion was implemented using the linear transformation between coordinate systems. Methods: The linear transformation matrices between the coordinate systems with and without gimbal swings were constructed using the combination of translation and rotation matrices. The coordinate system where the radiation source is at the origin and the beam axis along the z axis was adopted. The transformation can be divided into the translation from the radiation source to the gimbal rotation center, the two rotations around the center relating to the gimbal swings, and the translation from the gimbal center to the radiation source. After operating the transformation matrix to the phantom or patient image, the dose calculation can be performed as the no gimbal swing. The algorithm was implemented in the treatment planning system, PlanUNC (University of North Carolina, NC). The convolution/superposition algorithm was used. The dose calculations with and without gimbal swings were performed for the 3 × 3 cm{sup 2} field with the grid size of 5 mm. Results: The calculation time was about 3 minutes per beam. No significant additional time due to the gimbal swing was observed. Conclusions: The dose calculation algorithm for the finite gimbal swing was implemented. The calculation time was moderate.« less

PROMO – Real-time Prospective Motion Correction in MRI using Image-based Tracking

PubMed Central

White, Nathan; Roddey, Cooper; Shankaranarayanan, Ajit; Han, Eric; Rettmann, Dan; Santos, Juan; Kuperman, Josh; Dale, Anders

2010-01-01

Artifacts caused by patient motion during scanning remain a serious problem in most MRI applications. The prospective motion correction technique attempts to address this problem at its source by keeping the measurement coordinate system fixed with respect to the patient throughout the entire scan process. In this study, a new image-based approach for prospective motion correction is described, which utilizes three orthogonal 2D spiral navigator acquisitions (SP-Navs) along with a flexible image-based tracking method based on the Extended Kalman Filter (EKF) algorithm for online motion measurement. The SP-Nav/EKF framework offers the advantages of image-domain tracking within patient-specific regions-of-interest and reduced sensitivity to off-resonance-induced corruption of rigid-body motion estimates. The performance of the method was tested using offline computer simulations and online in vivo head motion experiments. In vivo validation results covering a broad range of staged head motions indicate a steady-state error of the SP-Nav/EKF motion estimates of less than 10 % of the motion magnitude, even for large compound motions that included rotations over 15 degrees. A preliminary in vivo application in 3D inversion recovery spoiled gradient echo (IR-SPGR) and 3D fast spin echo (FSE) sequences demonstrates the effectiveness of the SP-Nav/EKF framework for correcting 3D rigid-body head motion artifacts prospectively in high-resolution 3D MRI scans. PMID:20027635

Ground Simulation of an Autonomous Satellite Rendezvous and Tracking System Using Dual Robotic Systems

NASA Technical Reports Server (NTRS)

Trube, Matthew J.; Hyslop, Andrew M.; Carignan, Craig R.; Easley, Joseph W.

2012-01-01

A hardware-in-the-loop ground system was developed for simulating a robotic servicer spacecraft tracking a target satellite at short range. A relative navigation sensor package "Argon" is mounted on the end-effector of a Fanuc 430 manipulator, which functions as the base platform of the robotic spacecraft servicer. Machine vision algorithms estimate the pose of the target spacecraft, mounted on a Rotopod R-2000 platform, relay the solution to a simulation of the servicer spacecraft running in "Freespace", which performs guidance, navigation and control functions, integrates dynamics, and issues motion commands to a Fanuc platform controller so that it tracks the simulated servicer spacecraft. Results will be reviewed for several satellite motion scenarios at different ranges. Key words: robotics, satellite, servicing, guidance, navigation, tracking, control, docking.

An Integrated Processing Strategy for Mountain Glacier Motion Monitoring Based on SAR Images

NASA Astrophysics Data System (ADS)

Ruan, Z.; Yan, S.; Liu, G.; LV, M.

2017-12-01

Mountain glacier dynamic variables are important parameters in studies of environment and climate change in High Mountain Asia. Due to the increasing events of abnormal glacier-related hazards, research of monitoring glacier movements has attracted more interest during these years. Glacier velocities are sensitive and changing fast under complex conditions of high mountain regions, which implies that analysis of glacier dynamic changes requires comprehensive and frequent observations with relatively high accuracy. Synthetic aperture radar (SAR) has been successfully exploited to detect glacier motion in a number of previous studies, usually with pixel-tracking and interferometry methods. However, the traditional algorithms applied to mountain glacier regions are constrained by the complex terrain and diverse glacial motion types. Interferometry techniques are prone to fail in mountain glaciers because of their narrow size and the steep terrain, while pixel-tracking algorithm, which is more robust in high mountain areas, is subject to accuracy loss. In order to derive glacier velocities continually and efficiently, we propose a modified strategy to exploit SAR data information for mountain glaciers. In our approach, we integrate a set of algorithms for compensating non-glacial-motion-related signals which exist in the offset values retrieved by sub-pixel cross-correlation of SAR image pairs. We exploit modified elastic deformation model to remove the offsets associated with orbit and sensor attitude, and for the topographic residual offset we utilize a set of operations including DEM-assisted compensation algorithm and wavelet-based algorithm. At the last step of the flow, an integrated algorithm combining phase and intensity information of SAR images will be used to improve regional motion results failed in cross-correlation related processing. The proposed strategy is applied to the West Kunlun Mountain and Muztagh Ata region in western China using ALOS/PALSAR data. The results show that the strategy can effectively improve the accuracy of velocity estimation by reducing the mean and standard deviation values from 0.32 m and 0.4 m to 0.16 m. It is proved to be highly appropriate for monitoring glacier motion over a widely varying range of ice velocities with a relatively high accuracy.

Cascade and parallel combination (CPC) of adaptive filters for estimating heart rate during intensive physical exercise from photoplethysmographic signal

PubMed Central

Islam, Mohammad Tariqul; Tanvir Ahmed, Sk.; Zabir, Ishmam; Shahnaz, Celia

2018-01-01

Photoplethysmographic (PPG) signal is getting popularity for monitoring heart rate in wearable devices because of simplicity of construction and low cost of the sensor. The task becomes very difficult due to the presence of various motion artefacts. In this study, an algorithm based on cascade and parallel combination (CPC) of adaptive filters is proposed in order to reduce the effect of motion artefacts. First, preliminary noise reduction is performed by averaging two channel PPG signals. Next in order to reduce the effect of motion artefacts, a cascaded filter structure consisting of three cascaded adaptive filter blocks is developed where three-channel accelerometer signals are used as references to motion artefacts. To further reduce the affect of noise, a scheme based on convex combination of two such cascaded adaptive noise cancelers is introduced, where two widely used adaptive filters namely recursive least squares and least mean squares filters are employed. Heart rates are estimated from the noise reduced PPG signal in spectral domain. Finally, an efficient heart rate tracking algorithm is designed based on the nature of the heart rate variability. The performance of the proposed CPC method is tested on a widely used public database. It is found that the proposed method offers very low estimation error and a smooth heart rate tracking with simple algorithmic approach. PMID:29515812

Vehicle tracking in wide area motion imagery from an airborne platform

NASA Astrophysics Data System (ADS)

van Eekeren, Adam W. M.; van Huis, Jasper R.; Eendebak, Pieter T.; Baan, Jan

2015-10-01

Airborne platforms, such as UAV's, with Wide Area Motion Imagery (WAMI) sensors can cover multiple square kilometers and produce large amounts of video data. Analyzing all data for information need purposes becomes increasingly labor-intensive for an image analyst. Furthermore, the capacity of the datalink in operational areas may be inadequate to transfer all data to the ground station. Automatic detection and tracking of people and vehicles enables to send only the most relevant footage to the ground station and assists the image analysts in effective data searches. In this paper, we propose a method for detecting and tracking vehicles in high-resolution WAMI images from a moving airborne platform. For the vehicle detection we use a cascaded set of classifiers, using an Adaboost training algorithm on Haar features. This detector works on individual images and therefore does not depend on image motion stabilization. For the vehicle tracking we use a local template matching algorithm. This approach has two advantages. In the first place, it does not depend on image motion stabilization and it counters the inaccuracy of the GPS data that is embedded in the video data. In the second place, it can find matches when the vehicle detector would miss a certain detection. This results in long tracks even when the imagery is of low frame-rate. In order to minimize false detections, we also integrate height information from a 3D reconstruction that is created from the same images. By using the locations of buildings and roads, we are able to filter out false detections and increase the performance of the tracker. In this paper we show that the vehicle tracks can also be used to detect more complex events, such as traffic jams and fast moving vehicles. This enables the image analyst to do a faster and more effective search of the data.

Motion-Blur-Free High-Speed Video Shooting Using a Resonant Mirror

PubMed Central

Inoue, Michiaki; Gu, Qingyi; Takaki, Takeshi; Ishii, Idaku; Tajima, Kenji

2017-01-01

This study proposes a novel concept of actuator-driven frame-by-frame intermittent tracking for motion-blur-free video shooting of fast-moving objects. The camera frame and shutter timings are controlled for motion blur reduction in synchronization with a free-vibration-type actuator vibrating with a large amplitude at hundreds of hertz so that motion blur can be significantly reduced in free-viewpoint high-frame-rate video shooting for fast-moving objects by deriving the maximum performance of the actuator. We develop a prototype of a motion-blur-free video shooting system by implementing our frame-by-frame intermittent tracking algorithm on a high-speed video camera system with a resonant mirror vibrating at 750 Hz. It can capture 1024 × 1024 images of fast-moving objects at 750 fps with an exposure time of 0.33 ms without motion blur. Several experimental results for fast-moving objects verify that our proposed method can reduce image degradation from motion blur without decreasing the camera exposure time. PMID:29109385

2D/3D Visual Tracker for Rover Mast

NASA Technical Reports Server (NTRS)

Bajracharya, Max; Madison, Richard W.; Nesnas, Issa A.; Bandari, Esfandiar; Kunz, Clayton; Deans, Matt; Bualat, Maria

2006-01-01

A visual-tracker computer program controls an articulated mast on a Mars rover to keep a designated feature (a target) in view while the rover drives toward the target, avoiding obstacles. Several prior visual-tracker programs have been tested on rover platforms; most require very small and well-estimated motion between consecutive image frames a requirement that is not realistic for a rover on rough terrain. The present visual-tracker program is designed to handle large image motions that lead to significant changes in feature geometry and photometry between frames. When a point is selected in one of the images acquired from stereoscopic cameras on the mast, a stereo triangulation algorithm computes a three-dimensional (3D) location for the target. As the rover moves, its body-mounted cameras feed images to a visual-odometry algorithm, which tracks two-dimensional (2D) corner features and computes their old and new 3D locations. The algorithm rejects points, the 3D motions of which are inconsistent with a rigid-world constraint, and then computes the apparent change in the rover pose (i.e., translation and rotation). The mast pan and tilt angles needed to keep the target centered in the field-of-view of the cameras (thereby minimizing the area over which the 2D-tracking algorithm must operate) are computed from the estimated change in the rover pose, the 3D position of the target feature, and a model of kinematics of the mast. If the motion between the consecutive frames is still large (i.e., 3D tracking was unsuccessful), an adaptive view-based matching technique is applied to the new image. This technique uses correlation-based template matching, in which a feature template is scaled by the ratio between the depth in the original template and the depth of pixels in the new image. This is repeated over the entire search window and the best correlation results indicate the appropriate match. The program could be a core for building application programs for systems that require coordination of vision and robotic motion.

In vivo validation of patellofemoral kinematics during overground gait and stair ascent.

PubMed

Pitcairn, Samuel; Lesniak, Bryson; Anderst, William

2018-06-18

The patellofemoral (PF) joint is a common site for non-specific anterior knee pain. The pathophysiology of patellofemoral pain may be related to abnormal motion of the patella relative to the femur, leading to increased stress at the patellofemoral joint. Patellofemoral motion cannot be accurately measured using conventional motion capture. The aim of this study was to determine the accuracy of a biplane radiography system for measuring in vivo PF motion during walking and stair ascent. Four subjects had three 1.0 mm diameter tantalum beads implanted into the patella. Participants performed three trials each of over ground walking and stair ascent while biplane radiographs were collected at 100 Hz. Patella motion was tracked using radiostereophotogrammetric analysis (RSA) as a "gold standard", and compared to a volumetric CT model-based tracking algorithm that matched digitally reconstructed radiographs to the original biplane radiographs. The average RMS difference between the RSA and model-based tracking was 0.41 mm and 1.97° when there was no obstruction from the contralateral leg. These differences increased by 34% and 40%, respectively, when the patella was at least partially obstructed by the contralateral leg. The average RMS difference in patellofemoral joint space between tracking methods was 0.9 mm or less. Previous validations of biplane radiographic systems have estimated tracking accuracy by moving cadaveric knees through simulated motions. These validations were unable to replicate in vivo kinematics, including patella motion due to muscle activation, and failed to assess the imaging and tracking challenges related to contralateral limb obstruction. By replicating the muscle contraction, movement velocity, joint range of motion, and obstruction of the patella by the contralateral limb, the present study provides a realistic estimate of patellofemoral tracking accuracy for future in vivo studies. Copyright © 2018 Elsevier B.V. All rights reserved.

Remote Safety Monitoring for Elderly Persons Based on Omni-Vision Analysis

PubMed Central

Xiang, Yun; Tang, Yi-ping; Ma, Bao-qing; Yan, Hang-chen; Jiang, Jun; Tian, Xu-yuan

2015-01-01

Remote monitoring service for elderly persons is important as the aged populations in most developed countries continue growing. To monitor the safety and health of the elderly population, we propose a novel omni-directional vision sensor based system, which can detect and track object motion, recognize human posture, and analyze human behavior automatically. In this work, we have made the following contributions: (1) we develop a remote safety monitoring system which can provide real-time and automatic health care for the elderly persons and (2) we design a novel motion history or energy images based algorithm for motion object tracking. Our system can accurately and efficiently collect, analyze, and transfer elderly activity information and provide health care in real-time. Experimental results show that our technique can improve the data analysis efficiency by 58.5% for object tracking. Moreover, for the human posture recognition application, the success rate can reach 98.6% on average. PMID:25978761

A low cost real-time motion tracking approach using webcam technology.

PubMed

Krishnan, Chandramouli; Washabaugh, Edward P; Seetharaman, Yogesh

2015-02-05

Physical therapy is an important component of gait recovery for individuals with locomotor dysfunction. There is a growing body of evidence that suggests that incorporating a motor learning task through visual feedback of movement trajectory is a useful approach to facilitate therapeutic outcomes. Visual feedback is typically provided by recording the subject's limb movement patterns using a three-dimensional motion capture system and displaying it in real-time using customized software. However, this approach can seldom be used in the clinic because of the technical expertise required to operate this device and the cost involved in procuring a three-dimensional motion capture system. In this paper, we describe a low cost two-dimensional real-time motion tracking approach using a simple webcam and an image processing algorithm in LabVIEW Vision Assistant. We also evaluated the accuracy of this approach using a high precision robotic device (Lokomat) across various walking speeds. Further, the reliability and feasibility of real-time motion-tracking were evaluated in healthy human participants. The results indicated that the measurements from the webcam tracking approach were reliable and accurate. Experiments on human subjects also showed that participants could utilize the real-time kinematic feedback generated from this device to successfully perform a motor learning task while walking on a treadmill. These findings suggest that the webcam motion tracking approach is a feasible low cost solution to perform real-time movement analysis and training. Copyright © 2014 Elsevier Ltd. All rights reserved.

A low cost real-time motion tracking approach using webcam technology

PubMed Central

Krishnan, Chandramouli; Washabaugh, Edward P.; Seetharaman, Yogesh

2014-01-01

Physical therapy is an important component of gait recovery for individuals with locomotor dysfunction. There is a growing body of evidence that suggests that incorporating a motor learning task through visual feedback of movement trajectory is a useful approach to facilitate therapeutic outcomes. Visual feedback is typically provided by recording the subject’s limb movement patterns using a three-dimensional motion capture system and displaying it in real-time using customized software. However, this approach can seldom be used in the clinic because of the technical expertise required to operate this device and the cost involved in procuring a three-dimensional motion capture system. In this paper, we describe a low cost two-dimensional real-time motion tracking approach using a simple webcam and an image processing algorithm in LabVIEW Vision Assistant. We also evaluated the accuracy of this approach using a high precision robotic device (Lokomat) across various walking speeds. Further, the reliability and feasibility of real-time motion-tracking were evaluated in healthy human participants. The results indicated that the measurements from the webcam tracking approach were reliable and accurate. Experiments on human subjects also showed that participants could utilize the real-time kinematic feedback generated from this device to successfully perform a motor learning task while walking on a treadmill. These findings suggest that the webcam motion tracking approach is a feasible low cost solution to perform real-time movement analysis and training. PMID:25555306

TH-AB-202-01: Daily Lung Tumor Motion Characterization On EPIDs Using a Markerless Tiling Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rozario, T; University of Texas at Dallas, Richardson, TX; Chiu, T

Purpose: Tracking lung tumor motion in real time allows for target dose escalation while simultaneously reducing dose to sensitive structures, thus increasing local control without increasing toxicity. We present a novel intra-fractional markerless lung tumor tracking algorithm using MV treatment beam images acquired during treatment delivery. Strong signals superimposed on the tumor significantly reduced the soft tissue resolution; while different imaging modalities involved introduce global imaging discrepancies. This reduced the comparison accuracies. A simple yet elegant Tiling algorithm is reported to overcome the aforementioned issues. Methods: MV treatment beam images were acquired continuously in beam’s eye view (BEV) by anmore » electronic portal imaging device (EPID) during treatment and analyzed to obtain tumor positions on every frame. Every frame of the MV image was simulated by a composite of two components with separate digitally reconstructed radiographs (DRRs): all non-moving structures and the tumor. This Titling algorithm divides the global composite DRR and the corresponding MV projection into sub-images called tiles. Rigid registration is performed independently on tile-pairs in order to improve local soft tissue resolution. This enables the composite DRR to be transformed accurately to match the MV projection and attain a high correlation value through a pixel-based linear transformation. The highest cumulative correlation for all tile-pairs achieved over a user-defined search range indicates the 2-D coordinates of the tumor location on the MV projection. Results: This algorithm was successfully applied to cine-mode BEV images acquired during two SBRT plans delivered five times with different motion patterns to each of two phantoms. Approximately 15000 beam’s eye view images were analyzed and tumor locations were successfully identified on every projection with a maximum/average error of 1.8 mm / 1.0 mm. Conclusion: Despite the presence of strong anatomical signal overlapping with tumor images, this markerless detection algorithm accurately tracks intrafractional lung tumor motions. This project is partially supported by an Elekta research grant.« less

WE-G-213CD-06: Implementation of Real-Time Tumor Tracking Using Robotic Couch.

PubMed

Buzurovic, I; Yu, Y; Podder, T

2012-06-01

The purpose of this study was to present a novel method for real- time tumor tracking using a commercially available robotic treatment couch, and to evaluate tumor tracking accuracy. Commercially available robotic couches are capable of positioning patients with high level of accuracy; however, currently there is no provision for compensating tumor motion using these systems. Elekta's existing commercial couch (PreciseTM Table) was used without changing its design. To establish the real-time couch motion for tracking, a novel control system was developed and implemented. The tabletop could be moved in horizontal plane (laterally and longitudinally) using two Maxon-24V motors with gearbox combination. Vertical motion was obtained using robust 70V-Rockwell Automation motor. For vertical motor position sensing, we used Model 755A-Accu- Coder encoder. Two Baumer-ITD_01_4mm shaft encoders were used for the lateral and longitudinal motions of the couch. Motors were connected to the Advance Motion Controls (AMC) amplifiers: for the vertical motion, motor AMC-20A20-INV amplifier was used, and two AMC-Z6A8 amplifiers were applied for the lateral and longitudinal couch motions. The Galil DMC-4133 controller was connected to standard PC computer using USB port. The system had two independent power supplies: Galil PSR-12- 24-12A, 24vdc power supply with diodes for controller and 24vdc motors and amplifiers, and Galil-PS300W72 72vdc power supply for vertical motion. Control algorithms were developed for position and velocity adjustment. The system was tested for real-time tracking in the range of 50mm in all 3 directions (superior-inferior, lateral, anterior- posterior). Accuracies were 0.15, 0.20, and 0.18mm, respectively. Repeatability of the desired motion was within ± 0.2mm. Experimental results of couch tracking show feasibility of real-time tumor tracking with high level of accuracy (within sub-millimeter range). This tracking technique potentially offers a simple and effective method to minimize healthy tissues irradiation.Acknowledgement: Study supported by Elekta,Ltd. Study supported by Elekta, Ltd. © 2012 American Association of Physicists in Medicine.

Collaborative real-time motion video analysis by human observer and image exploitation algorithms

NASA Astrophysics Data System (ADS)

Hild, Jutta; Krüger, Wolfgang; Brüstle, Stefan; Trantelle, Patrick; Unmüßig, Gabriel; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2015-05-01

Motion video analysis is a challenging task, especially in real-time applications. In most safety and security critical applications, a human observer is an obligatory part of the overall analysis system. Over the last years, substantial progress has been made in the development of automated image exploitation algorithms. Hence, we investigate how the benefits of automated video analysis can be integrated suitably into the current video exploitation systems. In this paper, a system design is introduced which strives to combine both the qualities of the human observer's perception and the automated algorithms, thus aiming to improve the overall performance of a real-time video analysis system. The system design builds on prior work where we showed the benefits for the human observer by means of a user interface which utilizes the human visual focus of attention revealed by the eye gaze direction for interaction with the image exploitation system; eye tracker-based interaction allows much faster, more convenient, and equally precise moving target acquisition in video images than traditional computer mouse selection. The system design also builds on prior work we did on automated target detection, segmentation, and tracking algorithms. Beside the system design, a first pilot study is presented, where we investigated how the participants (all non-experts in video analysis) performed in initializing an object tracking subsystem by selecting a target for tracking. Preliminary results show that the gaze + key press technique is an effective, efficient, and easy to use interaction technique when performing selection operations on moving targets in videos in order to initialize an object tracking function.

A Novel Method for Tracking Individuals of Fruit Fly Swarms Flying in a Laboratory Flight Arena

PubMed Central

Cheng, Xi En; Qian, Zhi-Ming; Wang, Shuo Hong; Jiang, Nan; Guo, Aike; Chen, Yan Qiu

2015-01-01

The growing interest in studying social behaviours of swarming fruit flies, Drosophila melanogaster, has heightened the need for developing tools that provide quantitative motion data. To achieve such a goal, multi-camera three-dimensional tracking technology is the key experimental gateway. We have developed a novel tracking system for tracking hundreds of fruit flies flying in a confined cubic flight arena. In addition to the proposed tracking algorithm, this work offers additional contributions in three aspects: body detection, orientation estimation, and data validation. To demonstrate the opportunities that the proposed system offers for generating high-throughput quantitative motion data, we conducted experiments on five experimental configurations. We also performed quantitative analysis on the kinematics and the spatial structure and the motion patterns of fruit fly swarms. We found that there exists an asymptotic distance between fruit flies in swarms as the population density increases. Further, we discovered the evidence for repulsive response when the distance between fruit flies approached the asymptotic distance. Overall, the proposed tracking system presents a powerful method for studying flight behaviours of fruit flies in a three-dimensional environment. PMID:26083385

Feature-aided multiple target tracking in the image plane

NASA Astrophysics Data System (ADS)

Brown, Andrew P.; Sullivan, Kevin J.; Miller, David J.

2006-05-01

Vast quantities of EO and IR data are collected on airborne platforms (manned and unmanned) and terrestrial platforms (including fixed installations, e.g., at street intersections), and can be exploited to aid in the global war on terrorism. However, intelligent preprocessing is required to enable operator efficiency and to provide commanders with actionable target information. To this end, we have developed an image plane tracker which automatically detects and tracks multiple targets in image sequences using both motion and feature information. The effects of platform and camera motion are compensated via image registration, and a novel change detection algorithm is applied for accurate moving target detection. The contiguous pixel blob on each moving target is segmented for use in target feature extraction and model learning. Feature-based target location measurements are used for tracking through move-stop-move maneuvers, close target spacing, and occlusion. Effective clutter suppression is achieved using joint probabilistic data association (JPDA), and confirmed target tracks are indicated for further processing or operator review. In this paper we describe the algorithms implemented in the image plane tracker and present performance results obtained with video clips from the DARPA VIVID program data collection and from a miniature unmanned aerial vehicle (UAV) flight.

Airborne target tracking algorithm against oppressive decoys in infrared imagery

NASA Astrophysics Data System (ADS)

Sun, Xiechang; Zhang, Tianxu

2009-10-01

This paper presents an approach for tracking airborne target against oppressive infrared decoys. Oppressive decoy lures infrared guided missile by its high infrared radiation. Traditional tracking algorithms have degraded stability even come to tracking failure when airborne target continuously throw out many decoys. The proposed approach first determines an adaptive tracking window. The center of the tracking window is set at a predicted target position which is computed based on uniform motion model. Different strategies are applied for determination of tracking window size according to target state. The image within tracking window is segmented and multi features of candidate targets are extracted. The most similar candidate target is associated to the tracking target by using a decision function, which calculates a weighted sum of normalized feature differences between two comparable targets. Integrated intensity ratio of association target and tracking target, and target centroid are examined to estimate target state in the presence of decoys. The tracking ability and robustness of proposed approach has been validated by processing available real-world and simulated infrared image sequences containing airborne targets and oppressive decoys.

Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

NASA Astrophysics Data System (ADS)

Bal, A.; Alam, M. S.; Aslan, M. S.

2006-05-01

Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

Fast Compressive Tracking.

PubMed

Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

2014-10-01

It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

Motion correction of PET brain images through deconvolution: I. Theoretical development and analysis in software simulations

NASA Astrophysics Data System (ADS)

Faber, T. L.; Raghunath, N.; Tudorascu, D.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. Existing correction methods that use known patient motion obtained from tracking devices either require multi-frame acquisitions, detailed knowledge of the scanner, or specialized reconstruction algorithms. A deconvolution algorithm has been developed that alleviates these drawbacks by using the reconstructed image to estimate the original non-blurred image using maximum likelihood estimation maximization (MLEM) techniques. A high-resolution digital phantom was created by shape-based interpolation of the digital Hoffman brain phantom. Three different sets of 20 movements were applied to the phantom. For each frame of the motion, sinograms with attenuation and three levels of noise were simulated and then reconstructed using filtered backprojection. The average of the 20 frames was considered the motion blurred image, which was restored with the deconvolution algorithm. After correction, contrast increased from a mean of 2.0, 1.8 and 1.4 in the motion blurred images, for the three increasing amounts of movement, to a mean of 2.5, 2.4 and 2.2. Mean error was reduced by an average of 55% with motion correction. In conclusion, deconvolution can be used for correction of motion blur when subject motion is known.

Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity.

PubMed

Aghayee, Samira; Winkowski, Daniel E; Bowen, Zachary; Marshall, Erin E; Harrington, Matt J; Kanold, Patrick O; Losert, Wolfgang

2017-01-01

The application of 2-photon laser scanning microscopy (TPLSM) techniques to measure the dynamics of cellular calcium signals in populations of neurons is an extremely powerful technique for characterizing neural activity within the central nervous system. The use of TPLSM on awake and behaving subjects promises new insights into how neural circuit elements cooperatively interact to form sensory perceptions and generate behavior. A major challenge in imaging such preparations is unavoidable animal and tissue movement, which leads to shifts in the imaging location (jitter). The presence of image motion can lead to artifacts, especially since quantification of TPLSM images involves analysis of fluctuations in fluorescence intensities for each neuron, determined from small regions of interest (ROIs). Here, we validate a new motion correction approach to compensate for motion of TPLSM images in the superficial layers of auditory cortex of awake mice. We use a nominally uniform fluorescent signal as a secondary signal to complement the dynamic signals from genetically encoded calcium indicators. We tested motion correction for single plane time lapse imaging as well as multiplane (i.e., volume) time lapse imaging of cortical tissue. Our procedure of motion correction relies on locating the brightest neurons and tracking their positions over time using established techniques of particle finding and tracking. We show that our tracking based approach provides subpixel resolution without compromising speed. Unlike most established methods, our algorithm also captures deformations of the field of view and thus can compensate e.g., for rotations. Object tracking based motion correction thus offers an alternative approach for motion correction, one that is well suited for real time spike inference analysis and feedback control, and for correcting for tissue distortions.

Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity

PubMed Central

Aghayee, Samira; Winkowski, Daniel E.; Bowen, Zachary; Marshall, Erin E.; Harrington, Matt J.; Kanold, Patrick O.; Losert, Wolfgang

2017-01-01

The application of 2-photon laser scanning microscopy (TPLSM) techniques to measure the dynamics of cellular calcium signals in populations of neurons is an extremely powerful technique for characterizing neural activity within the central nervous system. The use of TPLSM on awake and behaving subjects promises new insights into how neural circuit elements cooperatively interact to form sensory perceptions and generate behavior. A major challenge in imaging such preparations is unavoidable animal and tissue movement, which leads to shifts in the imaging location (jitter). The presence of image motion can lead to artifacts, especially since quantification of TPLSM images involves analysis of fluctuations in fluorescence intensities for each neuron, determined from small regions of interest (ROIs). Here, we validate a new motion correction approach to compensate for motion of TPLSM images in the superficial layers of auditory cortex of awake mice. We use a nominally uniform fluorescent signal as a secondary signal to complement the dynamic signals from genetically encoded calcium indicators. We tested motion correction for single plane time lapse imaging as well as multiplane (i.e., volume) time lapse imaging of cortical tissue. Our procedure of motion correction relies on locating the brightest neurons and tracking their positions over time using established techniques of particle finding and tracking. We show that our tracking based approach provides subpixel resolution without compromising speed. Unlike most established methods, our algorithm also captures deformations of the field of view and thus can compensate e.g., for rotations. Object tracking based motion correction thus offers an alternative approach for motion correction, one that is well suited for real time spike inference analysis and feedback control, and for correcting for tissue distortions. PMID:28860973

MR-assisted PET Motion Correction for eurological Studies in an Integrated MR-PET Scanner

PubMed Central

Catana, Ciprian; Benner, Thomas; van der Kouwe, Andre; Byars, Larry; Hamm, Michael; Chonde, Daniel B.; Michel, Christian J.; El Fakhri, Georges; Schmand, Matthias; Sorensen, A. Gregory

2011-01-01

Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MR data can be used for motion tracking. In this work, a novel data processing and rigid-body motion correction (MC) algorithm for the MR-compatible BrainPET prototype scanner is described and proof-of-principle phantom and human studies are presented. Methods To account for motion, the PET prompts and randoms coincidences as well as the sensitivity data are processed in the line or response (LOR) space according to the MR-derived motion estimates. After sinogram space rebinning, the corrected data are summed and the motion corrected PET volume is reconstructed from these sinograms and the attenuation and scatter sinograms in the reference position. The accuracy of the MC algorithm was first tested using a Hoffman phantom. Next, human volunteer studies were performed and motion estimates were obtained using two high temporal resolution MR-based motion tracking techniques. Results After accounting for the physical mismatch between the two scanners, perfectly co-registered MR and PET volumes are reproducibly obtained. The MR output gates inserted in to the PET list-mode allow the temporal correlation of the two data sets within 0.2 s. The Hoffman phantom volume reconstructed processing the PET data in the LOR space was similar to the one obtained processing the data using the standard methods and applying the MC in the image space, demonstrating the quantitative accuracy of the novel MC algorithm. In human volunteer studies, motion estimates were obtained from echo planar imaging and cloverleaf navigator sequences every 3 seconds and 20 ms, respectively. Substantially improved PET images with excellent delineation of specific brain structures were obtained after applying the MC using these MR-based estimates. Conclusion A novel MR-based MC algorithm was developed for the integrated MR-PET scanner. High temporal resolution MR-derived motion estimates (obtained while simultaneously acquiring anatomical or functional MR data) can be used for PET MC. An MR-based MC has the potential to improve PET as a quantitative method, increasing its reliability and reproducibility which could benefit a large number of neurological applications. PMID:21189415

Operational space trajectory tracking control of robot manipulators endowed with a primary controller of synthetic joint velocity.

PubMed

Moreno-Valenzuela, Javier; González-Hernández, Luis

2011-01-01

In this paper, a new control algorithm for operational space trajectory tracking control of robot arms is introduced. The new algorithm does not require velocity measurement and is based on (1) a primary controller which incorporates an algorithm to obtain synthesized velocity from joint position measurements and (2) a secondary controller which computes the desired joint acceleration and velocity required to achieve operational space motion control. The theory of singularly perturbed systems is crucial for the analysis of the closed-loop system trajectories. In addition, the practical viability of the proposed algorithm is explored through real-time experiments in a two degrees-of-freedom horizontal planar direct-drive arm. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive learning compressive tracking based on Markov location prediction

NASA Astrophysics Data System (ADS)

Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

2017-03-01

Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

A biomechanical modeling guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction

NASA Astrophysics Data System (ADS)

Huang, Xiaokun; Zhang, You; Wang, Jing

2017-03-01

Four-dimensional (4D) cone-beam computed tomography (CBCT) enables motion tracking of anatomical structures and removes artifacts introduced by motion. However, the imaging time/dose of 4D-CBCT is substantially longer/higher than traditional 3D-CBCT. We previously developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, to reconstruct high-quality 4D-CBCT from limited number of projections to reduce the imaging time/dose. However, the accuracy of SMEIR is limited in reconstructing low-contrast regions with fine structure details. In this study, we incorporate biomechanical modeling into the SMEIR algorithm (SMEIR-Bio), to improve the reconstruction accuracy at low-contrast regions with fine details. The efficacy of SMEIR-Bio is evaluated using 11 lung patient cases and compared to that of the original SMEIR algorithm. Qualitative and quantitative comparisons showed that SMEIR-Bio greatly enhances the accuracy of reconstructed 4D-CBCT volume in low-contrast regions, which can potentially benefit multiple clinical applications including the treatment outcome analysis.

Enhanced object-based tracking algorithm for convective rain storms and cells

NASA Astrophysics Data System (ADS)

Muñoz, Carlos; Wang, Li-Pen; Willems, Patrick

2018-03-01

This paper proposes a new object-based storm tracking algorithm, based upon TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting). TITAN is a widely-used convective storm tracking algorithm but has limitations in handling small-scale yet high-intensity storm entities due to its single-threshold identification approach. It also has difficulties to effectively track fast-moving storms because of the employed matching approach that largely relies on the overlapping areas between successive storm entities. To address these deficiencies, a number of modifications are proposed and tested in this paper. These include a two-stage multi-threshold storm identification, a new formulation for characterizing storm's physical features, and an enhanced matching technique in synergy with an optical-flow storm field tracker, as well as, according to these modifications, a more complex merging and splitting scheme. High-resolution (5-min and 529-m) radar reflectivity data for 18 storm events over Belgium are used to calibrate and evaluate the algorithm. The performance of the proposed algorithm is compared with that of the original TITAN. The results suggest that the proposed algorithm can better isolate and match convective rainfall entities, as well as to provide more reliable and detailed motion estimates. Furthermore, the improvement is found to be more significant for higher rainfall intensities. The new algorithm has the potential to serve as a basis for further applications, such as storm nowcasting and long-term stochastic spatial and temporal rainfall generation.

Control of joint motion simulators for biomechanical research

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Glass, K.

1992-01-01

The authors present a hierarchical adaptive algorithm for controlling upper extremity human joint motion simulators. A joint motion simulator is a computer-controlled, electromechanical system which permits the application of forces to the tendons of a human cadaver specimen in such a way that the cadaver joint under study achieves a desired motion in a physiologic manner. The proposed control scheme does not require knowledge of the cadaver specimen dynamic model, and solves on-line the indeterminate problem which arises because human joints typically possess more actuators than degrees of freedom. Computer simulation results are given for an elbow/forearm system and wrist/hand system under hierarchical control. The results demonstrate that any desired normal joint motion can be accurately tracked with the proposed algorithm. These simulation results indicate that the controller resolved the indeterminate problem redundancy in a physiologic manner, and show that the control scheme was robust to parameter uncertainty and to sensor noise.

New algorithms for motion error detection of numerical control machine tool by laser tracking measurement on the basis of GPS principle.

PubMed

Wang, Jindong; Chen, Peng; Deng, Yufen; Guo, Junjie

2018-01-01

As a three-dimensional measuring instrument, the laser tracker is widely used in industrial measurement. To avoid the influence of angle measurement error on the overall measurement accuracy, the multi-station and time-sharing measurement with a laser tracker is introduced on the basis of the global positioning system (GPS) principle in this paper. For the proposed method, how to accurately determine the coordinates of each measuring point by using a large amount of measured data is a critical issue. Taking detecting motion error of a numerical control machine tool, for example, the corresponding measurement algorithms are investigated thoroughly. By establishing the mathematical model of detecting motion error of a machine tool with this method, the analytical algorithm concerning on base station calibration and measuring point determination is deduced without selecting the initial iterative value in calculation. However, when the motion area of the machine tool is in a 2D plane, the coefficient matrix of base station calibration is singular, which generates a distortion result. In order to overcome the limitation of the original algorithm, an improved analytical algorithm is also derived. Meanwhile, the calibration accuracy of the base station with the improved algorithm is compared with that with the original analytical algorithm and some iterative algorithms, such as the Gauss-Newton algorithm and Levenberg-Marquardt algorithm. The experiment further verifies the feasibility and effectiveness of the improved algorithm. In addition, the different motion areas of the machine tool have certain influence on the calibration accuracy of the base station, and the corresponding influence of measurement error on the calibration result of the base station depending on the condition number of coefficient matrix are analyzed.

New algorithms for motion error detection of numerical control machine tool by laser tracking measurement on the basis of GPS principle

NASA Astrophysics Data System (ADS)

Wang, Jindong; Chen, Peng; Deng, Yufen; Guo, Junjie

2018-01-01

As a three-dimensional measuring instrument, the laser tracker is widely used in industrial measurement. To avoid the influence of angle measurement error on the overall measurement accuracy, the multi-station and time-sharing measurement with a laser tracker is introduced on the basis of the global positioning system (GPS) principle in this paper. For the proposed method, how to accurately determine the coordinates of each measuring point by using a large amount of measured data is a critical issue. Taking detecting motion error of a numerical control machine tool, for example, the corresponding measurement algorithms are investigated thoroughly. By establishing the mathematical model of detecting motion error of a machine tool with this method, the analytical algorithm concerning on base station calibration and measuring point determination is deduced without selecting the initial iterative value in calculation. However, when the motion area of the machine tool is in a 2D plane, the coefficient matrix of base station calibration is singular, which generates a distortion result. In order to overcome the limitation of the original algorithm, an improved analytical algorithm is also derived. Meanwhile, the calibration accuracy of the base station with the improved algorithm is compared with that with the original analytical algorithm and some iterative algorithms, such as the Gauss-Newton algorithm and Levenberg-Marquardt algorithm. The experiment further verifies the feasibility and effectiveness of the improved algorithm. In addition, the different motion areas of the machine tool have certain influence on the calibration accuracy of the base station, and the corresponding influence of measurement error on the calibration result of the base station depending on the condition number of coefficient matrix are analyzed.

Automated identification and tracking of polar-cap plasma patches at solar minimum

NASA Astrophysics Data System (ADS)

Burston, R.; Hodges, K.; Astin, I.; Jayachandran, P. T.

2014-03-01

A method of automatically identifying and tracking polar-cap plasma patches, utilising data inversion and feature-tracking methods, is presented. A well-established and widely used 4-D ionospheric imaging algorithm, the Multi-Instrument Data Assimilation System (MIDAS), inverts slant total electron content (TEC) data from ground-based Global Navigation Satellite System (GNSS) receivers to produce images of the free electron distribution in the polar-cap ionosphere. These are integrated to form vertical TEC maps. A flexible feature-tracking algorithm, TRACK, previously used extensively in meteorological storm-tracking studies is used to identify and track maxima in the resulting 2-D data fields. Various criteria are used to discriminate between genuine patches and "false-positive" maxima such as the continuously moving day-side maximum, which results from the Earth's rotation rather than plasma motion. Results for a 12-month period at solar minimum, when extensive validation data are available, are presented. The method identifies 71 separate structures consistent with patch motion during this time. The limitations of solar minimum and the consequent small number of patches make climatological inferences difficult, but the feasibility of the method for patches larger than approximately 500 km in scale is demonstrated and a larger study incorporating other parts of the solar cycle is warranted. Possible further optimisation of discrimination criteria, particularly regarding the definition of a patch in terms of its plasma concentration enhancement over the surrounding background, may improve results.

Figure–ground discrimination behavior in Drosophila. I. Spatial organization of wing-steering responses

PubMed Central

Fox, Jessica L.; Aptekar, Jacob W.; Zolotova, Nadezhda M.; Shoemaker, Patrick A.; Frye, Mark A.

2014-01-01

The behavioral algorithms and neural subsystems for visual figure–ground discrimination are not sufficiently described in any model system. The fly visual system shares structural and functional similarity with that of vertebrates and, like vertebrates, flies robustly track visual figures in the face of ground motion. This computation is crucial for animals that pursue salient objects under the high performance requirements imposed by flight behavior. Flies smoothly track small objects and use wide-field optic flow to maintain flight-stabilizing optomotor reflexes. The spatial and temporal properties of visual figure tracking and wide-field stabilization have been characterized in flies, but how the two systems interact spatially to allow flies to actively track figures against a moving ground has not. We took a systems identification approach in flying Drosophila and measured wing-steering responses to velocity impulses of figure and ground motion independently. We constructed a spatiotemporal action field (STAF) – the behavioral analog of a spatiotemporal receptive field – revealing how the behavioral impulse responses to figure tracking and concurrent ground stabilization vary for figure motion centered at each location across the visual azimuth. The figure tracking and ground stabilization STAFs show distinct spatial tuning and temporal dynamics, confirming the independence of the two systems. When the figure tracking system is activated by a narrow vertical bar moving within the frontal field of view, ground motion is essentially ignored despite comprising over 90% of the total visual input. PMID:24198267

Robotized High Intensity Focused Ultrasound (HIFU) system for treatment of mobile organs using motion tracking by ultrasound imaging: An in vitro study.

PubMed

Chanel, Laure-Anais; Nageotte, Florent; Vappou, Jonathan; Luo, Jianwen; Cuvillon, Loic; de Mathelin, Michel

2015-01-01

High Intensity Focused Ultrasound (HIFU) therapy is a very promising method for ablation of solid tumors. However, intra-abdominal organ motion, principally due to breathing, is a substantial limitation that results in incorrect tumor targeting. The objective of this work is to develop an all-in-one robotized HIFU system that can compensate motion in real-time during HIFU treatment. To this end, an ultrasound visual servoing scheme working at 20 Hz was designed. It relies on the motion estimation by using a fast ultrasonic speckle tracking algorithm and on the use of an interleaved imaging/HIFU sonication sequence for avoiding ultrasonic wave interferences. The robotized HIFU system was tested on a sample of chicken breast undergoing a vertical sinusoidal motion at 0.25 Hz. Sonications with and without motion compensation were performed in order to assess the effect of motion compensation on thermal lesions induced by HIFU. Motion was reduced by more than 80% thanks to this ultrasonic visual servoing system.

Dynamical simulation priors for human motion tracking.

PubMed

Vondrak, Marek; Sigal, Leonid; Jenkins, Odest Chadwicke

2013-01-01

We propose a simulation-based dynamical motion prior for tracking human motion from video in presence of physical ground-person interactions. Most tracking approaches to date have focused on efficient inference algorithms and/or learning of prior kinematic motion models; however, few can explicitly account for the physical plausibility of recovered motion. Here, we aim to recover physically plausible motion of a single articulated human subject. Toward this end, we propose a full-body 3D physical simulation-based prior that explicitly incorporates a model of human dynamics into the Bayesian filtering framework. We consider the motion of the subject to be generated by a feedback “control loop” in which Newtonian physics approximates the rigid-body motion dynamics of the human and the environment through the application and integration of interaction forces, motor forces, and gravity. Interaction forces prevent physically impossible hypotheses, enable more appropriate reactions to the environment (e.g., ground contacts), and are produced from detected human-environment collisions. Motor forces actuate the body, ensure that proposed pose transitions are physically feasible, and are generated using a motion controller. For efficient inference in the resulting high-dimensional state space, we utilize an exemplar-based control strategy that reduces the effective search space of motor forces. As a result, we are able to recover physically plausible motion of human subjects from monocular and multiview video. We show, both quantitatively and qualitatively, that our approach performs favorably with respect to Bayesian filtering methods with standard motion priors.

Topography-Dependent Motion Compensation: Application to UAVSAR Data

NASA Technical Reports Server (NTRS)

Jones, Cathleen E.; Hensley, Scott; Michel, Thierry

2009-01-01

The UAVSAR L-band synthetic aperture radar system has been designed for repeat track interferometry in support of Earth science applications that require high-precision measurements of small surface deformations over timescales from hours to years. Conventional motion compensation algorithms, which are based upon assumptions of a narrow beam and flat terrain, yield unacceptably large errors in areas with even moderate topographic relief, i.e., in most areas of interest. This often limits the ability to achieve sub-centimeter surface change detection over significant portions of an acquired scene. To reduce this source of error in the interferometric phase, we have implemented an advanced motion compensation algorithm that corrects for the scene topography and radar beam width. Here we discuss the algorithm used, its implementation in the UAVSAR data processor, and the improvement in interferometric phase and correlation achieved in areas with significant topographic relief.

SU-E-T-562: Motion Tracking Optimization for Conformal Arc Radiotherapy Plans: A QUASAR Phantom Based Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Z; Wang, I; Yao, R

Purpose: This study is to use plan parameters optimization (Dose rate, collimator angle, couch angle, initial starting phase) to improve the performance of conformal arc radiotherapy plans with motion tracking by increasing the plan performance score (PPS). Methods: Two types of 3D conformal arc plans were created based on QUASAR respiratory motion phantom with spherical and cylindrical targets. Sinusoidal model was applied to the MLC leaves to generate motion tracking plans. A MATLAB program was developed to calculate PPS of each plan (ranges from 0–1) and optimize plan parameters. We first selected the dose rate for motion tracking plans andmore » then used simulated annealing algorithm to search for the combination of the other parameters that resulted in the plan of the maximal PPS. The optimized motion tracking plan was delivered by Varian Truebeam Linac. In-room cameras and stopwatch were used for starting phase selection and synchronization between phantom motion and plan delivery. Gaf-EBT2 dosimetry films were used to measure the dose delivered to the target in QUASAR phantom. Dose profiles and Truebeam trajectory log files were used for plan delivery performance evaluation. Results: For spherical target, the maximal PPS (PPSsph) of the optimized plan was 0.79: (Dose rate: 500MU/min, Collimator: 90°, Couch: +10°, starting phase: 0.83π). For cylindrical target, the maximal PPScyl was 0.75 (Dose rate: 300MU/min, Collimator: 87°, starting phase: 0.97π) with couch at 0°. Differences of dose profiles between motion tracking plans (with the maximal and the minimal PPS) and 3D conformal plans were as follows: PPSsph=0.79: %ΔFWHM: 8.9%, %Dmax: 3.1%; PPSsph=0.52: %ΔFWHM: 10.4%, %Dmax: 6.1%. PPScyl=0.75: %ΔFWHM: 4.7%, %Dmax: 3.6%; PPScyl=0.42: %ΔFWHM: 12.5%, %Dmax: 9.6%. Conclusion: By achieving high plan performance score through parameters optimization, we can improve target dose conformity of motion tracking plan by decreasing total MLC leaf travel distance and leaf speed.« less

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Hua, E-mail: huli@radonc.wustl.edu; Chen, Hsin

Purpose: For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Methods: Considering the complex H&N structures andmore » ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28%  ±  1.46%) and margin error (0.49  ±  0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. Conclusions: The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.« less

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy.

PubMed

Li, Hua; Chen, Hsin-Chen; Dolly, Steven; Li, Harold; Fischer-Valuck, Benjamin; Victoria, James; Dempsey, James; Ruan, Su; Anastasio, Mark; Mazur, Thomas; Gach, Michael; Kashani, Rojano; Green, Olga; Rodriguez, Vivian; Gay, Hiram; Thorstad, Wade; Mutic, Sasa

2016-08-01

For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Considering the complex H&N structures and ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28%  ±  1.46%) and margin error (0.49  ±  0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.

Nonlinear automatic landing control of unmanned aerial vehicles on moving platforms via a 3D laser radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hervas, Jaime Rubio; Tang, Hui; Reyhanoglu, Mahmut

2014-12-10

This paper presents a motion tracking and control system for automatically landing Unmanned Aerial Vehicles (UAVs) on an oscillating platform using Laser Radar (LADAR) observations. The system itself is assumed to be mounted on a ship deck. A full nonlinear mathematical model is first introduced for the UAV. The ship motion is characterized by a Fourier transform based method which includes a realistic characterization of the sea waves. LADAR observation models are introduced and an algorithm to process those observations for yielding the relative state between the vessel and the UAV is presented, from which the UAV's state relative tomore » an inertial frame can be obtained and used for feedback purposes. A sliding mode control algorithm is derived for tracking a landing trajectory defined by a set of desired waypoints. An extended Kalman filter (EKF) is proposed to account for process and observation noises in the design of a state estimator. The effectiveness of the control algorithm is illustrated through a simulation example.« less

Markerless motion estimation for motion-compensated clinical brain imaging

NASA Astrophysics Data System (ADS)

Kyme, Andre Z.; Se, Stephen; Meikle, Steven R.; Fulton, Roger R.

2018-05-01

Motion-compensated brain imaging can dramatically reduce the artifacts and quantitative degradation associated with voluntary and involuntary subject head motion during positron emission tomography (PET), single photon emission computed tomography (SPECT) and computed tomography (CT). However, motion-compensated imaging protocols are not in widespread clinical use for these modalities. A key reason for this seems to be the lack of a practical motion tracking technology that allows for smooth and reliable integration of motion-compensated imaging protocols in the clinical setting. We seek to address this problem by investigating the feasibility of a highly versatile optical motion tracking method for PET, SPECT and CT geometries. The method requires no attached markers, relying exclusively on the detection and matching of distinctive facial features. We studied the accuracy of this method in 16 volunteers in a mock imaging scenario by comparing the estimated motion with an accurate marker-based method used in applications such as image guided surgery. A range of techniques to optimize performance of the method were also studied. Our results show that the markerless motion tracking method is highly accurate (<2 mm discrepancy against a benchmarking system) on an ethnically diverse range of subjects and, moreover, exhibits lower jitter and estimation of motion over a greater range than some marker-based methods. Our optimization tests indicate that the basic pose estimation algorithm is very robust but generally benefits from rudimentary background masking. Further marginal gains in accuracy can be achieved by accounting for non-rigid motion of features. Efficiency gains can be achieved by capping the number of features used for pose estimation provided that these features adequately sample the range of head motion encountered in the study. These proof-of-principle data suggest that markerless motion tracking is amenable to motion-compensated brain imaging and holds good promise for a practical implementation in clinical PET, SPECT and CT systems.

Motion tracing system for ultrasound guided HIFU

NASA Astrophysics Data System (ADS)

Xiao, Xu; Jiang, Tingyi; Corner, George; Huang, Zhihong

2017-03-01

One main limitation in HIFU treatment is the abdominal movement in liver and kidney caused by respiration. The study has set up a tracking model which mainly compromises of a target carrying box and a motion driving balloon. A real-time B-mode ultrasound guidance method suitable for tracking of the abdominal organ motion in 2D was established and tested. For the setup, the phantoms mimicking moving organs are carefully prepared with agar surrounding round-shaped egg-white as the target of focused ultrasound ablation. Physiological phantoms and animal tissues are driven moving reciprocally along the main axial direction of the ultrasound image probe with slightly motion perpendicular to the axial direction. The moving speed and range could be adjusted by controlling the inflation and deflation speed and amount of the balloon driven by a medical ventilator. A 6-DOF robotic arm was used to position the focused ultrasound transducer. The overall system was trying to estimate to simulate the actual movement caused by human respiration. HIFU ablation experiments using phantoms and animal organs were conducted to test the tracking effect. Ultrasound strain elastography was used to post estimate the efficiency of the tracking algorithms and system. In moving state, the axial size of the lesion (perpendicular to the movement direction) are averagely 4mm, which is one third larger than the lesion got when the target was not moving. This presents the possibility of developing a low-cost real-time method of tracking organ motion during HIFU treatment in liver or kidney.

Lateral motion and bending of microtubules studied with a new single-filament tracking routine in living cells.

PubMed

Pallavicini, Carla; Levi, Valeria; Wetzler, Diana E; Angiolini, Juan F; Benseñor, Lorena; Despósito, Marcelo A; Bruno, Luciana

2014-06-17

The cytoskeleton is involved in numerous cellular processes such as migration, division, and contraction and provides the tracks for transport driven by molecular motors. Therefore, it is very important to quantify the mechanical behavior of the cytoskeletal filaments to get a better insight into cell mechanics and organization. It has been demonstrated that relevant mechanical properties of microtubules can be extracted from the analysis of their motion and shape fluctuations. However, tracking individual filaments in living cells is extremely complex due, for example, to the high and heterogeneous background. We introduce a believed new tracking algorithm that allows recovering the coordinates of fluorescent microtubules with ∼9 nm precision in in vitro conditions. To illustrate potential applications of this algorithm, we studied the curvature distributions of fluorescent microtubules in living cells. By performing a Fourier analysis of the microtubule shapes, we found that the curvatures followed a thermal-like distribution as previously reported with an effective persistence length of ∼20 μm, a value significantly smaller than that measured in vitro. We also verified that the microtubule-associated protein XTP or the depolymerization of the actin network do not affect this value; however, the disruption of intermediate filaments decreased the persistence length. Also, we recovered trajectories of microtubule segments in actin or intermediate filament-depleted cells, and observed a significant increase of their motion with respect to untreated cells showing that these filaments contribute to the overall organization of the microtubule network. Moreover, the analysis of trajectories of microtubule segments in untreated cells showed that these filaments presented a slower but more directional motion in the cortex with respect to the perinuclear region, and suggests that the tracking routine would allow mapping the microtubule dynamical organization in cells. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A hybrid approach to estimate the complex motions of clouds in sky images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peng, Zhenzhou; Yu, Dantong; Huang, Dong

Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

A hybrid approach to estimate the complex motions of clouds in sky images

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2016-09-14

Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

KiT: a MATLAB package for kinetochore tracking.

PubMed

Armond, Jonathan W; Vladimirou, Elina; McAinsh, Andrew D; Burroughs, Nigel J

2016-06-15

During mitosis, chromosomes are attached to the mitotic spindle via large protein complexes called kinetochores. The motion of kinetochores throughout mitosis is intricate and automated quantitative tracking of their motion has already revealed many surprising facets of their behaviour. Here, we present 'KiT' (Kinetochore Tracking)-an easy-to-use, open-source software package for tracking kinetochores from live-cell fluorescent movies. KiT supports 2D, 3D and multi-colour movies, quantification of fluorescence, integrated deconvolution, parallel execution and multiple algorithms for particle localization. KiT is free, open-source software implemented in MATLAB and runs on all MATLAB supported platforms. KiT can be downloaded as a package from http://www.mechanochemistry.org/mcainsh/software.php The source repository is available at https://bitbucket.org/jarmond/kit and under continuing development. Supplementary data are available at Bioinformatics online. jonathan.armond@warwick.ac.uk. © The Author 2016. Published by Oxford University Press.

Predictive local receptive fields based respiratory motion tracking for motion-adaptive radiotherapy.

PubMed

Yubo Wang; Tatinati, Sivanagaraja; Liyu Huang; Kim Jeong Hong; Shafiq, Ghufran; Veluvolu, Kalyana C; Khong, Andy W H

2017-07-01

Extracranial robotic radiotherapy employs external markers and a correlation model to trace the tumor motion caused by the respiration. The real-time tracking of tumor motion however requires a prediction model to compensate the latencies induced by the software (image data acquisition and processing) and hardware (mechanical and kinematic) limitations of the treatment system. A new prediction algorithm based on local receptive fields extreme learning machines (pLRF-ELM) is proposed for respiratory motion prediction. All the existing respiratory motion prediction methods model the non-stationary respiratory motion traces directly to predict the future values. Unlike these existing methods, the pLRF-ELM performs prediction by modeling the higher-level features obtained by mapping the raw respiratory motion into the random feature space of ELM instead of directly modeling the raw respiratory motion. The developed method is evaluated using the dataset acquired from 31 patients for two horizons in-line with the latencies of treatment systems like CyberKnife. Results showed that pLRF-ELM is superior to that of existing prediction methods. Results further highlight that the abstracted higher-level features are suitable to approximate the nonlinear and non-stationary characteristics of respiratory motion for accurate prediction.

Detection of obstacles on runway using Ego-Motion compensation and tracking of significant features

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar (Principal Investigator); Camps, Octavia (Principal Investigator); Gandhi, Tarak; Devadiga, Sadashiva

1996-01-01

This report describes a method for obstacle detection on a runway for autonomous navigation and landing of an aircraft. Detection is done in the presence of extraneous features such as tiremarks. Suitable features are extracted from the image and warping using approximately known camera and plane parameters is performed in order to compensate ego-motion as far as possible. Residual disparity after warping is estimated using an optical flow algorithm. Features are tracked from frame to frame so as to obtain more reliable estimates of their motion. Corrections are made to motion parameters with the residual disparities using a robust method, and features having large residual disparities are signaled as obstacles. Sensitivity analysis of the procedure is also studied. Nelson's optical flow constraint is proposed to separate moving obstacles from stationary ones. A Bayesian framework is used at every stage so that the confidence in the estimates can be determined.

Ultrasound thermography: A new temperature reconstruction model and in vivo results

NASA Astrophysics Data System (ADS)

Bayat, Mahdi; Ballard, John R.; Ebbini, Emad S.

2017-03-01

The recursive echo strain filter (RESF) model is presented as a new echo shift-based ultrasound temperature estimation model. The model is shown to have an infinite impulse response (IIR) filter realization of a differentitor-integrator operator. This model is then used for tracking sub-therapeutic temperature changes due to high intensity focused ultrasound (HIFU) shots in the hind limb of the Copenhagen rats in vivo. In addition to the reconstruction filter, a motion compensation method is presented which takes advantage of the deformation field outside the region of interest to correct the motion errors during temperature tracking. The combination of the RESF model and motion compensation algorithm is shown to greatly enhance the accuracy of the in vivo temperature estimation using ultrasound echo shifts.

4D Cone-beam CT reconstruction using a motion model based on principal component analysis

PubMed Central

Staub, David; Docef, Alen; Brock, Robert S.; Vaman, Constantin; Murphy, Martin J.

2011-01-01

Purpose: To provide a proof of concept validation of a novel 4D cone-beam CT (4DCBCT) reconstruction algorithm and to determine the best methods to train and optimize the algorithm. Methods: The algorithm animates a patient fan-beam CT (FBCT) with a patient specific parametric motion model in order to generate a time series of deformed CTs (the reconstructed 4DCBCT) that track the motion of the patient anatomy on a voxel by voxel scale. The motion model is constrained by requiring that projections cast through the deformed CT time series match the projections of the raw patient 4DCBCT. The motion model uses a basis of eigenvectors that are generated via principal component analysis (PCA) of a training set of displacement vector fields (DVFs) that approximate patient motion. The eigenvectors are weighted by a parameterized function of the patient breathing trace recorded during 4DCBCT. The algorithm is demonstrated and tested via numerical simulation. Results: The algorithm is shown to produce accurate reconstruction results for the most complicated simulated motion, in which voxels move with a pseudo-periodic pattern and relative phase shifts exist between voxels. The tests show that principal component eigenvectors trained on DVFs from a novel 2D/3D registration method give substantially better results than eigenvectors trained on DVFs obtained by conventionally registering 4DCBCT phases reconstructed via filtered backprojection. Conclusions: Proof of concept testing has validated the 4DCBCT reconstruction approach for the types of simulated data considered. In addition, the authors found the 2D/3D registration approach to be our best choice for generating the DVF training set, and the Nelder-Mead simplex algorithm the most robust optimization routine. PMID:22149852

A nowcasting technique based on application of the particle filter blending algorithm

NASA Astrophysics Data System (ADS)

Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai

2017-10-01

To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.

Local characterization of hindered Brownian motion by using digital video microscopy and 3D particle tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dettmer, Simon L.; Keyser, Ulrich F.; Pagliara, Stefano

In this article we present methods for measuring hindered Brownian motion in the confinement of complex 3D geometries using digital video microscopy. Here we discuss essential features of automated 3D particle tracking as well as diffusion data analysis. By introducing local mean squared displacement-vs-time curves, we are able to simultaneously measure the spatial dependence of diffusion coefficients, tracking accuracies and drift velocities. Such local measurements allow a more detailed and appropriate description of strongly heterogeneous systems as opposed to global measurements. Finite size effects of the tracking region on measuring mean squared displacements are also discussed. The use of thesemore » methods was crucial for the measurement of the diffusive behavior of spherical polystyrene particles (505 nm diameter) in a microfluidic chip. The particles explored an array of parallel channels with different cross sections as well as the bulk reservoirs. For this experiment we present the measurement of local tracking accuracies in all three axial directions as well as the diffusivity parallel to the channel axis while we observed no significant flow but purely Brownian motion. Finally, the presented algorithm is suitable also for tracking of fluorescently labeled particles and particles driven by an external force, e.g., electrokinetic or dielectrophoretic forces.« less

Cell Membrane Tracking in Living Brain Tissue Using Differential Interference Contrast Microscopy.

PubMed

Lee, John; Kolb, Ilya; Forest, Craig R; Rozell, Christopher J

2018-04-01

Differential interference contrast (DIC) microscopy is widely used for observing unstained biological samples that are otherwise optically transparent. Combining this optical technique with machine vision could enable the automation of many life science experiments; however, identifying relevant features under DIC is challenging. In particular, precise tracking of cell boundaries in a thick ( ) slice of tissue has not previously been accomplished. We present a novel deconvolution algorithm that achieves the state-of-the-art performance at identifying and tracking these membrane locations. Our proposed algorithm is formulated as a regularized least squares optimization that incorporates a filtering mechanism to handle organic tissue interference and a robust edge-sparsity regularizer that integrates dynamic edge tracking capabilities. As a secondary contribution, this paper also describes new community infrastructure in the form of a MATLAB toolbox for accurately simulating DIC microscopy images of in vitro brain slices. Building on existing DIC optics modeling, our simulation framework additionally contributes an accurate representation of interference from organic tissue, neuronal cell-shapes, and tissue motion due to the action of the pipette. This simulator allows us to better understand the image statistics (to improve algorithms), as well as quantitatively test cell segmentation and tracking algorithms in scenarios, where ground truth data is fully known.

Adaptive and accelerated tracking-learning-detection

NASA Astrophysics Data System (ADS)

Guo, Pengyu; Li, Xin; Ding, Shaowen; Tian, Zunhua; Zhang, Xiaohu

2013-08-01

An improved online long-term visual tracking algorithm, named adaptive and accelerated TLD (AA-TLD) based on Tracking-Learning-Detection (TLD) which is a novel tracking framework has been introduced in this paper. The improvement focuses on two aspects, one is adaption, which makes the algorithm not dependent on the pre-defined scanning grids by online generating scale space, and the other is efficiency, which uses not only algorithm-level acceleration like scale prediction that employs auto-regression and moving average (ARMA) model to learn the object motion to lessen the detector's searching range and the fixed number of positive and negative samples that ensures a constant retrieving time, but also CPU and GPU parallel technology to achieve hardware acceleration. In addition, in order to obtain a better effect, some TLD's details are redesigned, which uses a weight including both normalized correlation coefficient and scale size to integrate results, and adjusts distance metric thresholds online. A contrastive experiment on success rate, center location error and execution time, is carried out to show a performance and efficiency upgrade over state-of-the-art TLD with partial TLD datasets and Shenzhou IX return capsule image sequences. The algorithm can be used in the field of video surveillance to meet the need of real-time video tracking.

A High-Speed Vision-Based Sensor for Dynamic Vibration Analysis Using Fast Motion Extraction Algorithms.

PubMed

Zhang, Dashan; Guo, Jie; Lei, Xiujun; Zhu, Changan

2016-04-22

The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features.

Real-time tracking of respiratory-induced tumor motion by dose-rate regulation

NASA Astrophysics Data System (ADS)

Han-Oh, Yeonju Sarah

We have developed a novel real-time tumor-tracking technology, called Dose-Rate-Regulated Tracking (DRRT), to compensate for tumor motion caused by breathing. Unlike other previously proposed tumor-tracking methods, this new method uses a preprogrammed dynamic multileaf collimator (MLC) sequence in combination with real-time dose-rate control. This new scheme circumvents the technical challenge in MLC-based tumor tracking, that is to control the MLC motion in real time, based on real-time detected tumor motion. The preprogrammed MLC sequence describes the movement of the tumor, as a function of breathing phase, amplitude, or tidal volume. The irregularity of tumor motion during treatment is handled by real-time regulation of the dose rate, which effectively speeds up or slows down the delivery of radiation as needed. This method is based on the fact that all of the parameters in dynamic radiation delivery, including MLC motion, are enslaved to the cumulative dose, which, in turn, can be accelerated or decelerated by varying the dose rate. Because commercially available MLC systems do not allow the MLC delivery sequence to be modified in real time based on the patient's breathing signal, previously proposed tumor-tracking techniques using a MLC cannot be readily implemented in the clinic today. By using a preprogrammed MLC sequence to handle the required motion, the task for real-time control is greatly simplified. We have developed and tested the pre- programmed MLC sequence and the dose-rate regulation algorithm using lung-cancer patients breathing signals. It has been shown that DRRT can track the tumor with an accuracy of less than 2 mm for a latency of the DRRT system of less than 0.35 s. We also have evaluated the usefulness of guided breathing for DRRT. Since DRRT by its very nature can compensate for breathing-period changes, guided breathing was shown to be unnecessary for real-time tracking when using DRRT. Finally, DRRT uses the existing dose-rate control system that is provided for current linear accelerators. Therefore, DRRT can be achieved with minimal modification of existing technology, and this can shorten substantially the time necessary to establish DRRT in clinical practice.

The impact of cine EPID image acquisition frame rate on markerless soft-tissue tracking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yip, Stephen, E-mail: syip@lroc.harvard.edu; Rottmann, Joerg; Berbeco, Ross

2014-06-15

Purpose: Although reduction of the cine electronic portal imaging device (EPID) acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor autotracking results. The impact of motion blurring and image noise on the tracking performance was investigated. Methods: Phantom and patient images were acquired at a frame rate of 12.87 Hz with an amorphous silicon portal imager (AS1000, Varian Medical Systems, Palo Alto, CA). The maximum frame rate of 12.87 Hz is imposed by the EPID. Low frame rate images were obtained bymore » continuous frame averaging. A previously validated tracking algorithm was employed for autotracking. The difference between the programmed and autotracked positions of a Las Vegas phantom moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at 11 field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise are correlated with δ using Pearson correlation coefficient (R). Results: For both phantom and patient studies, the autotracking errors increased at frame rates lower than 4.29 Hz. Above 4.29 Hz, changes in errors were negligible withδ < 1.60 mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R = 0.94) and patient studies (R = 0.72). Moderate to poor correlation was found between image noise and tracking error with R −0.58 and −0.19 for both studies, respectively. Conclusions: Cine EPID image acquisition at the frame rate of at least 4.29 Hz is recommended. Motion blurring in the images with frame rates below 4.29 Hz can significantly reduce the accuracy of autotracking.« less

A Globally Optimal Particle Tracking Technique for Stereo Imaging Velocimetry Experiments

NASA Technical Reports Server (NTRS)

McDowell, Mark

2008-01-01

An important phase of any Stereo Imaging Velocimetry experiment is particle tracking. Particle tracking seeks to identify and characterize the motion of individual particles entrained in a fluid or air experiment. We analyze a cylindrical chamber filled with water and seeded with density-matched particles. In every four-frame sequence, we identify a particle track by assigning a unique track label for each camera image. The conventional approach to particle tracking is to use an exhaustive tree-search method utilizing greedy algorithms to reduce search times. However, these types of algorithms are not optimal due to a cascade effect of incorrect decisions upon adjacent tracks. We examine the use of a guided evolutionary neural net with simulated annealing to arrive at a globally optimal assignment of tracks. The net is guided both by the minimization of the search space through the use of prior limiting assumptions about valid tracks and by a strategy which seeks to avoid high-energy intermediate states which can trap the net in a local minimum. A stochastic search algorithm is used in place of back-propagation of error to further reduce the chance of being trapped in an energy well. Global optimization is achieved by minimizing an objective function, which includes both track smoothness and particle-image utilization parameters. In this paper we describe our model and present our experimental results. We compare our results with a nonoptimizing, predictive tracker and obtain an average increase in valid track yield of 27 percent

Object Tracking and Target Reacquisition Based on 3-D Range Data for Moving Vehicles

PubMed Central

Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

2013-01-01

In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle component analysis (PCA) of shape information is proposed. In the proposed method, if the target disappears out of frame, shape similarity energy is used to detect target candidates that match a template shape learned online from previously observed frames. Thus, we require no a priori knowledge of the target’s shape. Experimental results show the practical applicability and robustness of the proposed algorithm in realistic tracking scenarios. PMID:21486717

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera.

PubMed

Ci, Wenyan; Huang, Yingping

2016-10-17

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera's 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg-Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade-Lucas-Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method.

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

PubMed Central

Ci, Wenyan; Huang, Yingping

2016-01-01

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera’s 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg–Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade–Lucas–Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method. PMID:27763508

Automatic motion correction of clinical shoulder MR images

NASA Astrophysics Data System (ADS)

Manduca, Armando; McGee, Kiaran P.; Welch, Edward B.; Felmlee, Joel P.; Ehman, Richard L.

1999-05-01

A technique for the automatic correction of motion artifacts in MR images was developed. The algorithm uses only the raw (complex) data from the MR scanner, and requires no knowledge of the patient motion during the acquisition. It operates by searching over the space of possible patient motions and determining the motion which, when used to correct the image, optimizes the image quality. The performance of this algorithm was tested in coronal images of the rotator cuff in a series of 144 patients. A four observer comparison of the autocorrelated images with the uncorrected images demonstrated that motion artifacts were significantly reduced in 48% of the cases. The improvements in image quality were similar to those achieved with a previously reported navigator echo-based adaptive motion correction. The results demonstrate that autocorrelation is a practical technique for retrospectively reducing motion artifacts in a demanding clinical MRI application. It achieves performance comparable to a navigator based correction technique, which is significant because autocorrection does not require an imaging sequence that has been modified to explicitly track motion during acquisition. The approach is flexible and should be readily extensible to other types of MR acquisitions that are corrupted by global motion.

Technical aspects of real time positron emission tracking for gated radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chamberland, Marc; Xu, Tong, E-mail: txu@physics.carleton.ca; McEwen, Malcolm R.

2016-02-15

Purpose: Respiratory motion can lead to treatment errors in the delivery of radiotherapy treatments. Respiratory gating can assist in better conforming the beam delivery to the target volume. We present a study of the technical aspects of a real time positron emission tracking system for potential use in gated radiotherapy. Methods: The tracking system, called PeTrack, uses implanted positron emission markers and position sensitive gamma ray detectors to track breathing motion in real time. PeTrack uses an expectation–maximization algorithm to track the motion of fiducial markers. A normalized least mean squares adaptive filter predicts the location of the markers amore » short time ahead to account for system response latency. The precision and data collection efficiency of a prototype PeTrack system were measured under conditions simulating gated radiotherapy. The lung insert of a thorax phantom was translated in the inferior–superior direction with regular sinusoidal motion and simulated patient breathing motion (maximum amplitude of motion ±10 mm, period 4 s). The system tracked the motion of a {sup 22}Na fiducial marker (0.34 MBq) embedded in the lung insert every 0.2 s. The position of the was marker was predicted 0.2 s ahead. For sinusoidal motion, the equation used to model the motion was fitted to the data. The precision of the tracking was estimated as the standard deviation of the residuals. Software was also developed to communicate with a Linac and toggle beam delivery. In a separate experiment involving a Linac, 500 monitor units of radiation were delivered to the phantom with a 3 × 3 cm photon beam and with 6 and 10 MV accelerating potential. Radiochromic films were inserted in the phantom to measure spatial dose distribution. In this experiment, the period of motion was set to 60 s to account for beam turn-on latency. The beam was turned off when the marker moved outside of a 5-mm gating window. Results: The precision of the tracking in the IS direction was 0.53 mm for a sinusoidally moving target, with an average count rate ∼250 cps. The average prediction error was 1.1 ± 0.6 mm when the marker moved according to irregular patient breathing motion. Across all beam deliveries during the radiochromic film measurements, the average prediction error was 0.8 ± 0.5 mm. The maximum error was 2.5 mm and the 95th percentile error was 1.5 mm. Clear improvement of the dose distribution was observed between gated and nongated deliveries. The full-width at halfmaximum of the dose profiles of gated deliveries differed by 3 mm or less than the static reference dose distribution. Monitoring of the beam on/off times showed synchronization with the location of the marker within the latency of the system. Conclusions: PeTrack can track the motion of internal fiducial positron emission markers with submillimeter precision. The system can be used to gate the delivery of a Linac beam based on the position of a moving fiducial marker. This highlights the potential of the system for use in respiratory-gated radiotherapy.« less

MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner.

PubMed

Catana, Ciprian; Benner, Thomas; van der Kouwe, Andre; Byars, Larry; Hamm, Michael; Chonde, Daniel B; Michel, Christian J; El Fakhri, Georges; Schmand, Matthias; Sorensen, A Gregory

2011-01-01

Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MRI data can be used for motion tracking. In this work, a novel algorithm for data processing and rigid-body motion correction (MC) for the MRI-compatible BrainPET prototype scanner is described, and proof-of-principle phantom and human studies are presented. To account for motion, the PET prompt and random coincidences and sensitivity data for postnormalization were processed in the line-of-response (LOR) space according to the MRI-derived motion estimates. The processing time on the standard BrainPET workstation is approximately 16 s for each motion estimate. After rebinning in the sinogram space, the motion corrected data were summed, and the PET volume was reconstructed using the attenuation and scatter sinograms in the reference position. The accuracy of the MC algorithm was first tested using a Hoffman phantom. Next, human volunteer studies were performed, and motion estimates were obtained using 2 high-temporal-resolution MRI-based motion-tracking techniques. After accounting for the misalignment between the 2 scanners, perfectly coregistered MRI and PET volumes were reproducibly obtained. The MRI output gates inserted into the PET list-mode allow the temporal correlation of the 2 datasets within 0.2 ms. The Hoffman phantom volume reconstructed by processing the PET data in the LOR space was similar to the one obtained by processing the data using the standard methods and applying the MC in the image space, demonstrating the quantitative accuracy of the procedure. In human volunteer studies, motion estimates were obtained from echo planar imaging and cloverleaf navigator sequences every 3 s and 20 ms, respectively. Motion-deblurred PET images, with excellent delineation of specific brain structures, were obtained using these 2 MRI-based estimates. An MRI-based MC algorithm was implemented for an integrated MR-PET scanner. High-temporal-resolution MRI-derived motion estimates (obtained while simultaneously acquiring anatomic or functional MRI data) can be used for PET MC. An MRI-based MC method has the potential to improve PET image quality, increasing its reliability, reproducibility, and quantitative accuracy, and to benefit many neurologic applications.

Non-iterative double-frame 2D/3D particle tracking velocimetry

NASA Astrophysics Data System (ADS)

Fuchs, Thomas; Hain, Rainer; Kähler, Christian J.

2017-09-01

In recent years, the detection of individual particle images and their tracking over time to determine the local flow velocity has become quite popular for planar and volumetric measurements. Particle tracking velocimetry has strong advantages compared to the statistical analysis of an ensemble of particle images by means of cross-correlation approaches, such as particle image velocimetry. Tracking individual particles does not suffer from spatial averaging and therefore bias errors can be avoided. Furthermore, the spatial resolution can be increased up to the sub-pixel level for mean fields. A maximization of the spatial resolution for instantaneous measurements requires high seeding concentrations. However, it is still challenging to track particles at high seeding concentrations, if no time series is available. Tracking methods used under these conditions are typically very complex iterative algorithms, which require expert knowledge due to the large number of adjustable parameters. To overcome these drawbacks, a new non-iterative tracking approach is introduced in this letter, which automatically analyzes the motion of the neighboring particles without requiring to specify any parameters, except for the displacement limits. This makes the algorithm very user friendly and also offers unexperienced users to use and implement particle tracking. In addition, the algorithm enables measurements of high speed flows using standard double-pulse equipment and estimates the flow velocity reliably even at large particle image densities.

Influence of ultrasound speckle tracking strategies for motion and strain estimation.

PubMed

Curiale, Ariel H; Vegas-Sánchez-Ferrero, Gonzalo; Aja-Fernández, Santiago

2016-08-01

Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system. Copyright © 2016 Elsevier B.V. All rights reserved.

Experimental verification of a two-dimensional respiratory motion compensation system with ultrasound tracking technique in radiation therapy.

PubMed

Ting, Lai-Lei; Chuang, Ho-Chiao; Liao, Ai-Ho; Kuo, Chia-Chun; Yu, Hsiao-Wei; Zhou, Yi-Liang; Tien, Der-Chi; Jeng, Shiu-Chen; Chiou, Jeng-Fong

2018-05-01

This study proposed respiratory motion compensation system (RMCS) combined with an ultrasound image tracking algorithm (UITA) to compensate for respiration-induced tumor motion during radiotherapy, and to address the problem of inaccurate radiation dose delivery caused by respiratory movement. This study used an ultrasound imaging system to monitor respiratory movements combined with the proposed UITA and RMCS for tracking and compensation of the respiratory motion. Respiratory motion compensation was performed using prerecorded human respiratory motion signals and also sinusoidal signals. A linear accelerator was used to deliver radiation doses to GAFchromic EBT3 dosimetry film, and the conformity index (CI), root-mean-square error, compensation rate (CR), and planning target volume (PTV) were used to evaluate the tracking and compensation performance of the proposed system. Human respiratory pattern signals were captured using the UITA and compensated by the RMCS, which yielded CR values of 34-78%. In addition, the maximum coronal area of the PTV ranged from 85.53 mm 2 to 351.11 mm 2 (uncompensated), which reduced to from 17.72 mm 2 to 66.17 mm 2 after compensation, with an area reduction ratio of up to 90%. In real-time monitoring of the respiration compensation state, the CI values for 85% and 90% isodose areas increased to 0.7 and 0.68, respectively. The proposed UITA and RMCS can reduce the movement of the tracked target relative to the LINAC in radiation therapy, thereby reducing the required size of the PTV margin and increasing the effect of the radiation dose received by the treatment target. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

The star identification, pointing and tracking system of UVSTAR, an attached payload instrument system for the Shuttle Hitchhiker-M platform

NASA Technical Reports Server (NTRS)

Decarlo, Francesco; Stalio, Roberto; Trampus, Paolo; Broadfoot, A. Lyle; Sandel, Bill R.; Sicuranza, Giovanni

1993-01-01

We describe an algorithm for star identification and pointing/tracking of a spaceborne electro-optical system and simulation analyses to test the algorithm. The algorithm will be implemented in the guiding system of UVSTAR, a spectrographic telescope for observations of astronomical and planetary sources operating in the 500-1250 A waveband at approximately 1 A resolution. The experiment is an attached payload and will fly as a Hitchhiker-M payload on the Shuttle. UVSTAR includes capabilities for independent target acquisition and tracking. The spectrograph package has internal gimbals that allow angular movement of plus or minus 3 deg from the central position. Rotation about the azimuth axis (parallel to the Shuttle z axis) and elevation axis (parallel to the Shuttle x axis) will actively position the field of view to center the target of interest in the fields of the spectrographs. The algorithm is based on an on-board catalog of stars. To identify star fields, the algorithm compares the positions of stars recorded by the guiding imager to positions computed from the on-board catalog. When the field has been identified, its position within the guiding imager field of view can be used to compute the pointing corrections necessary to point to a target of interest. In tracking mode, the software uses the past history to predict the quasi-periodic attitude control motions of the shuttle and sends pointing commands to cancel the motion and stabilize UVSTAR on the target. The guiding imager (guider) will have an 80-mm focal length and f/1.4 optics giving a field of view of 6 deg x 4.5 deg using a 385 x 288 pixel intensified CCD. It will be capable of providing high accuracy (better than 2 arc-sec) attitude determination from coarse (6 deg x 4.5 deg) initial knowledge of the pointing direction; and of pointing toward the target. It will also be capable of tracking at the same high accuracy with a processing time of less than a few hundredths of a second.

A Probability-Based Algorithm Using Image Sensors to Track the LED in a Vehicle Visible Light Communication System.

PubMed

Huynh, Phat; Do, Trong-Hop; Yoo, Myungsik

2017-02-10

This paper proposes a probability-based algorithm to track the LED in vehicle visible light communication systems using a camera. In this system, the transmitters are the vehicles' front and rear LED lights. The receivers are high speed cameras that take a series of images of the LEDs. ThedataembeddedinthelightisextractedbyfirstdetectingthepositionoftheLEDsintheseimages. Traditionally, LEDs are detected according to pixel intensity. However, when the vehicle is moving, motion blur occurs in the LED images, making it difficult to detect the LEDs. Particularly at high speeds, some frames are blurred at a high degree, which makes it impossible to detect the LED as well as extract the information embedded in these frames. The proposed algorithm relies not only on the pixel intensity, but also on the optical flow of the LEDs and on statistical information obtained from previous frames. Based on this information, the conditional probability that a pixel belongs to a LED is calculated. Then, the position of LED is determined based on this probability. To verify the suitability of the proposed algorithm, simulations are conducted by considering the incidents that can happen in a real-world situation, including a change in the position of the LEDs at each frame, as well as motion blur due to the vehicle speed.

Four-dimensional (4D) tracking of high-temperature microparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhehui, E-mail: zwang@lanl.gov; Liu, Q.; Waganaar, W.

High-speed tracking of hot and molten microparticles in motion provides rich information about burning plasmas in magnetic fusion. An exploding-wire apparatus is used to produce moving high-temperature metallic microparticles and to develop four-dimensional (4D) or time-resolved 3D particle tracking techniques. The pinhole camera model and algorithms developed for computer vision are used for scene calibration and 4D reconstructions. 3D positions and velocities are then derived for different microparticles. Velocity resolution approaches 0.1 m/s by using the local constant velocity approximation.

Four-dimensional (4D) tracking of high-temperature microparticles

NASA Astrophysics Data System (ADS)

Wang, Zhehui; Liu, Q.; Waganaar, W.; Fontanese, J.; James, D.; Munsat, T.

2016-11-01

High-speed tracking of hot and molten microparticles in motion provides rich information about burning plasmas in magnetic fusion. An exploding-wire apparatus is used to produce moving high-temperature metallic microparticles and to develop four-dimensional (4D) or time-resolved 3D particle tracking techniques. The pinhole camera model and algorithms developed for computer vision are used for scene calibration and 4D reconstructions. 3D positions and velocities are then derived for different microparticles. Velocity resolution approaches 0.1 m/s by using the local constant velocity approximation.

Four-dimensional (4D) tracking of high-temperature microparticles

DOE PAGES

Wang, Zhehui; Liu, Qiuguang; Waganaar, Bill; ...

2016-07-08

High-speed tracking of hot and molten microparticles in motion provides rich information about burning plasmas in magnetic fusion. An exploding-wire apparatus is used to produce moving high-temperature metallic microparticles and to develop four-dimensional (4D) or time-resolved 3D particle tracking techniques. The pinhole camera model and algorithms developed for computer vision are used for scene calibration and 4D reconstructions. 3D positions and velocities are then derived for different microparticles. As a result, velocity resolution approaches 0.1 m/s by using the local constant velocity approximation.

Four-dimensional (4D) tracking of high-temperature microparticles.

PubMed

Wang, Zhehui; Liu, Q; Waganaar, W; Fontanese, J; James, D; Munsat, T

2016-11-01

High-speed tracking of hot and molten microparticles in motion provides rich information about burning plasmas in magnetic fusion. An exploding-wire apparatus is used to produce moving high-temperature metallic microparticles and to develop four-dimensional (4D) or time-resolved 3D particle tracking techniques. The pinhole camera model and algorithms developed for computer vision are used for scene calibration and 4D reconstructions. 3D positions and velocities are then derived for different microparticles. Velocity resolution approaches 0.1 m/s by using the local constant velocity approximation.

Tracking features in retinal images of adaptive optics confocal scanning laser ophthalmoscope using KLT-SIFT algorithm

PubMed Central

Li, Hao; Lu, Jing; Shi, Guohua; Zhang, Yudong

2010-01-01

With the use of adaptive optics (AO), high-resolution microscopic imaging of living human retina in the single cell level has been achieved. In an adaptive optics confocal scanning laser ophthalmoscope (AOSLO) system, with a small field size (about 1 degree, 280 μm), the motion of the eye severely affects the stabilization of the real-time video images and results in significant distortions of the retina images. In this paper, Scale-Invariant Feature Transform (SIFT) is used to abstract stable point features from the retina images. Kanade-Lucas-Tomasi(KLT) algorithm is applied to track the features. With the tracked features, the image distortion in each frame is removed by the second-order polynomial transformation, and 10 successive frames are co-added to enhance the image quality. Features of special interest in an image can also be selected manually and tracked by KLT. A point on a cone is selected manually, and the cone is tracked from frame to frame. PMID:21258443

Fire flame detection based on GICA and target tracking

NASA Astrophysics Data System (ADS)

Rong, Jianzhong; Zhou, Dechuang; Yao, Wei; Gao, Wei; Chen, Juan; Wang, Jian

2013-04-01

To improve the video fire detection rate, a robust fire detection algorithm based on the color, motion and pattern characteristics of fire targets was proposed, which proved a satisfactory fire detection rate for different fire scenes. In this fire detection algorithm: (a) a rule-based generic color model was developed based on analysis on a large quantity of flame pixels; (b) from the traditional GICA (Geometrical Independent Component Analysis) model, a Cumulative Geometrical Independent Component Analysis (C-GICA) model was developed for motion detection without static background and (c) a BP neural network fire recognition model based on multi-features of the fire pattern was developed. Fire detection tests on benchmark fire video clips of different scenes have shown the robustness, accuracy and fast-response of the algorithm.

Multiple hypothesis tracking for cluttered biological image sequences.

PubMed

Chenouard, Nicolas; Bloch, Isabelle; Olivo-Marin, Jean-Christophe

2013-11-01

In this paper, we present a method for simultaneously tracking thousands of targets in biological image sequences, which is of major importance in modern biology. The complexity and inherent randomness of the problem lead us to propose a unified probabilistic framework for tracking biological particles in microscope images. The framework includes realistic models of particle motion and existence and of fluorescence image features. For the track extraction process per se, the very cluttered conditions motivate the adoption of a multiframe approach that enforces tracking decision robustness to poor imaging conditions and to random target movements. We tackle the large-scale nature of the problem by adapting the multiple hypothesis tracking algorithm to the proposed framework, resulting in a method with a favorable tradeoff between the model complexity and the computational cost of the tracking procedure. When compared to the state-of-the-art tracking techniques for bioimaging, the proposed algorithm is shown to be the only method providing high-quality results despite the critically poor imaging conditions and the dense target presence. We thus demonstrate the benefits of advanced Bayesian tracking techniques for the accurate computational modeling of dynamical biological processes, which is promising for further developments in this domain.

Kassiopeia: a modern, extensible C++ particle tracking package

DOE Office of Scientific and Technical Information (OSTI.GOV)

Furse, Daniel; Groh, Stefan; Trost, Nikolaus

The Kassiopeia particle tracking framework is an object-oriented software package using modern C++ techniques, written originally to meet the needs of the KATRIN collaboration. Kassiopeia features a new algorithmic paradigm for particle tracking simulations which targets experiments containing complex geometries and electromagnetic fields, with high priority put on calculation efficiency, customizability, extensibility, and ease-of-use for novice programmers. To solve Kassiopeia's target physics problem the software is capable of simulating particle trajectories governed by arbitrarily complex differential equations of motion, continuous physics processes that may in part be modeled as terms perturbing that equation of motion, stochastic processes that occur inmore » flight such as bulk scattering and decay, and stochastic surface processes occurring at interfaces, including transmission and reflection effects. This entire set of computations takes place against the backdrop of a rich geometry package which serves a variety of roles, including initialization of electromagnetic field simulations and the support of state-dependent algorithm-swapping and behavioral changes as a particle's state evolves. Thanks to the very general approach taken by Kassiopeia it can be used by other experiments facing similar challenges when calculating particle trajectories in electromagnetic fields. It is publicly available at https://github.com/KATRIN-Experiment/Kassiopeia.« less

Kassiopeia: a modern, extensible C++ particle tracking package

DOE PAGES

Furse, Daniel; Groh, Stefan; Trost, Nikolaus; ...

2017-05-16

The Kassiopeia particle tracking framework is an object-oriented software package using modern C++ techniques, written originally to meet the needs of the KATRIN collaboration. Kassiopeia features a new algorithmic paradigm for particle tracking simulations which targets experiments containing complex geometries and electromagnetic fields, with high priority put on calculation efficiency, customizability, extensibility, and ease-of-use for novice programmers. To solve Kassiopeia's target physics problem the software is capable of simulating particle trajectories governed by arbitrarily complex differential equations of motion, continuous physics processes that may in part be modeled as terms perturbing that equation of motion, stochastic processes that occur inmore » flight such as bulk scattering and decay, and stochastic surface processes occurring at interfaces, including transmission and reflection effects. This entire set of computations takes place against the backdrop of a rich geometry package which serves a variety of roles, including initialization of electromagnetic field simulations and the support of state-dependent algorithm-swapping and behavioral changes as a particle's state evolves. Thanks to the very general approach taken by Kassiopeia it can be used by other experiments facing similar challenges when calculating particle trajectories in electromagnetic fields. It is publicly available at https://github.com/KATRIN-Experiment/Kassiopeia.« less

Kassiopeia: a modern, extensible C++ particle tracking package

NASA Astrophysics Data System (ADS)

Furse, Daniel; Groh, Stefan; Trost, Nikolaus; Babutzka, Martin; Barrett, John P.; Behrens, Jan; Buzinsky, Nicholas; Corona, Thomas; Enomoto, Sanshiro; Erhard, Moritz; Formaggio, Joseph A.; Glück, Ferenc; Harms, Fabian; Heizmann, Florian; Hilk, Daniel; Käfer, Wolfgang; Kleesiek, Marco; Leiber, Benjamin; Mertens, Susanne; Oblath, Noah S.; Renschler, Pascal; Schwarz, Johannes; Slocum, Penny L.; Wandkowsky, Nancy; Wierman, Kevin; Zacher, Michael

2017-05-01

The Kassiopeia particle tracking framework is an object-oriented software package using modern C++ techniques, written originally to meet the needs of the KATRIN collaboration. Kassiopeia features a new algorithmic paradigm for particle tracking simulations which targets experiments containing complex geometries and electromagnetic fields, with high priority put on calculation efficiency, customizability, extensibility, and ease-of-use for novice programmers. To solve Kassiopeia's target physics problem the software is capable of simulating particle trajectories governed by arbitrarily complex differential equations of motion, continuous physics processes that may in part be modeled as terms perturbing that equation of motion, stochastic processes that occur in flight such as bulk scattering and decay, and stochastic surface processes occurring at interfaces, including transmission and reflection effects. This entire set of computations takes place against the backdrop of a rich geometry package which serves a variety of roles, including initialization of electromagnetic field simulations and the support of state-dependent algorithm-swapping and behavioral changes as a particle’s state evolves. Thanks to the very general approach taken by Kassiopeia it can be used by other experiments facing similar challenges when calculating particle trajectories in electromagnetic fields. It is publicly available at https://github.com/KATRIN-Experiment/Kassiopeia.

Model identification and vision-based H∞ position control of 6-DoF cable-driven parallel robots

NASA Astrophysics Data System (ADS)

Chellal, R.; Cuvillon, L.; Laroche, E.

2017-04-01

This paper presents methodologies for the identification and control of 6-degrees of freedom (6-DoF) cable-driven parallel robots (CDPRs). First a two-step identification methodology is proposed to accurately estimate the kinematic parameters independently and prior to the dynamic parameters of a physics-based model of CDPRs. Second, an original control scheme is developed, including a vision-based position controller tuned with the H∞ methodology and a cable tension distribution algorithm. The position is controlled in the operational space, making use of the end-effector pose measured by a motion-tracking system. A four-block H∞ design scheme with adjusted weighting filters ensures good trajectory tracking and disturbance rejection properties for the CDPR system, which is a nonlinear-coupled MIMO system with constrained states. The tension management algorithm generates control signals that maintain the cables under feasible tensions. The paper makes an extensive review of the available methods and presents an extension of one of them. The presented methodologies are evaluated by simulations and experimentally on a redundant 6-DoF INCA 6D CDPR with eight cables, equipped with a motion-tracking system.

Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments

PubMed Central

Jiang, Yanhua; Xiong, Guangming; Chen, Huiyan; Lee, Dah-Jye

2014-01-01

This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC) scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments. PMID:25256109

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zawisza, I; Yan, H; Yin, F

Purpose: To assure that tumor motion is within the radiation field during high-dose and high-precision radiosurgery, real-time imaging and surrogate monitoring are employed. These methods are useful in providing real-time tumor/surrogate motion but no future information is available. In order to anticipate future tumor/surrogate motion and track target location precisely, an algorithm is developed and investigated for estimating surrogate motion multiple-steps ahead. Methods: The study utilized a one-dimensional surrogate motion signal divided into three components: (a) training component containing the primary data including the first frame to the beginning of the input subsequence; (b) input subsequence component of the surrogatemore » signal used as input to the prediction algorithm: (c) output subsequence component is the remaining signal used as the known output of the prediction algorithm for validation. The prediction algorithm consists of three major steps: (1) extracting subsequences from training component which best-match the input subsequence according to given criterion; (2) calculating weighting factors from these best-matched subsequence; (3) collecting the proceeding parts of the subsequences and combining them together with assigned weighting factors to form output. The prediction algorithm was examined for several patients, and its performance is assessed based on the correlation between prediction and known output. Results: Respiratory motion data was collected for 20 patients using the RPM system. The output subsequence is the last 50 samples (∼2 seconds) of a surrogate signal, and the input subsequence was 100 (∼3 seconds) frames prior to the output subsequence. Based on the analysis of correlation coefficient between predicted and known output subsequence, the average correlation is 0.9644±0.0394 and 0.9789±0.0239 for equal-weighting and relative-weighting strategies, respectively. Conclusion: Preliminary results indicate that the prediction algorithm is effective in estimating surrogate motion multiple-steps in advance. Relative-weighting method shows better prediction accuracy than equal-weighting method. More parameters of this algorithm are under investigation.« less

Implementation of a sensor guided flight algorithm for target tracking by small UAS

NASA Astrophysics Data System (ADS)

Collins, Gaemus E.; Stankevitz, Chris; Liese, Jeffrey

2011-06-01

Small xed-wing UAS (SUAS) such as Raven and Unicorn have limited power, speed, and maneuverability. Their missions can be dramatically hindered by environmental conditions (wind, terrain), obstructions (buildings, trees) blocking clear line of sight to a target, and/or sensor hardware limitations (xed stare, limited gimbal motion, lack of zoom). Toyon's Sensor Guided Flight (SGF) algorithm was designed to account for SUAS hardware shortcomings and enable long-term tracking of maneuvering targets by maintaining persistent eyes-on-target. SGF was successfully tested in simulation with high-delity UAS, sensor, and environment models, but real- world ight testing with 60 Unicorn UAS revealed surprising second order challenges that were not highlighted by the simulations. This paper describes the SGF algorithm, our rst round simulation results, our second order discoveries from ight testing, and subsequent improvements that were made to the algorithm.

Real-time tracking using stereo and motion: Visual perception for space robotics

NASA Technical Reports Server (NTRS)

Nishihara, H. Keith; Thomas, Hans; Huber, Eric; Reid, C. Ann

1994-01-01

The state-of-the-art in computing technology is rapidly attaining the performance necessary to implement many early vision algorithms at real-time rates. This new capability is helping to accelerate progress in vision research by improving our ability to evaluate the performance of algorithms in dynamic environments. In particular, we are becoming much more aware of the relative stability of various visual measurements in the presence of camera motion and system noise. This new processing speed is also allowing us to raise our sights toward accomplishing much higher-level processing tasks, such as figure-ground separation and active object tracking, in real-time. This paper describes a methodology for using early visual measurements to accomplish higher-level tasks; it then presents an overview of the high-speed accelerators developed at Teleos to support early visual measurements. The final section describes the successful deployment of a real-time vision system to provide visual perception for the Extravehicular Activity Helper/Retriever robotic system in tests aboard NASA's KC135 reduced gravity aircraft.

A general-purpose framework to simulate musculoskeletal system of human body: using a motion tracking approach.

PubMed

Ehsani, Hossein; Rostami, Mostafa; Gudarzi, Mohammad

2016-02-01

Computation of muscle force patterns that produce specified movements of muscle-actuated dynamic models is an important and challenging problem. This problem is an undetermined one, and then a proper optimization is required to calculate muscle forces. The purpose of this paper is to develop a general model for calculating all muscle activation and force patterns in an arbitrary human body movement. For this aim, the equations of a multibody system forward dynamics, which is considered for skeletal system of the human body model, is derived using Lagrange-Euler formulation. Next, muscle contraction dynamics is added to this model and forward dynamics of an arbitrary musculoskeletal system is obtained. For optimization purpose, the obtained model is used in computed muscle control algorithm, and a closed-loop system for tracking desired motions is derived. Finally, a popular sport exercise, biceps curl, is simulated by using this algorithm and the validity of the obtained results is evaluated via EMG signals.

Feature-based respiratory motion tracking in native fluoroscopic sequences for dynamic roadmaps during minimally invasive procedures in the thorax and abdomen

NASA Astrophysics Data System (ADS)

Wagner, Martin G.; Laeseke, Paul F.; Schubert, Tilman; Slagowski, Jordan M.; Speidel, Michael A.; Mistretta, Charles A.

2017-03-01

Fluoroscopic image guidance for minimally invasive procedures in the thorax and abdomen suffers from respiratory and cardiac motion, which can cause severe subtraction artifacts and inaccurate image guidance. This work proposes novel techniques for respiratory motion tracking in native fluoroscopic images as well as a model based estimation of vessel deformation. This would allow compensation for respiratory motion during the procedure and therefore simplify the workflow for minimally invasive procedures such as liver embolization. The method first establishes dynamic motion models for both the contrast-enhanced vasculature and curvilinear background features based on a native (non-contrast) and a contrast-enhanced image sequence acquired prior to device manipulation, under free breathing conditions. The model of vascular motion is generated by applying the diffeomorphic demons algorithm to an automatic segmentation of the subtraction sequence. The model of curvilinear background features is based on feature tracking in the native sequence. The two models establish the relationship between the respiratory state, which is inferred from curvilinear background features, and the vascular morphology during that same respiratory state. During subsequent fluoroscopy, curvilinear feature detection is applied to determine the appropriate vessel mask to display. The result is a dynamic motioncompensated vessel mask superimposed on the fluoroscopic image. Quantitative evaluation of the proposed methods was performed using a digital 4D CT-phantom (XCAT), which provides realistic human anatomy including sophisticated respiratory and cardiac motion models. Four groups of datasets were generated, where different parameters (cycle length, maximum diaphragm motion and maximum chest expansion) were modified within each image sequence. Each group contains 4 datasets consisting of the initial native and contrast enhanced sequences as well as a sequence, where the respiratory motion is tracked. The respiratory motion tracking error was between 1.00 % and 1.09 %. The estimated dynamic vessel masks yielded a Sørensen-Dice coefficient between 0.94 and 0.96. Finally, the accuracy of the vessel contours was measured in terms of the 99th percentile of the error, which ranged between 0.64 and 0.96 mm. The presented results show that the approach is feasible for respiratory motion tracking and compensation and could therefore considerably improve the workflow of minimally invasive procedures in the thorax and abdomen

Beam-induced motion correction for sub-megadalton cryo-EM particles.

PubMed

Scheres, Sjors Hw

2014-08-13

In electron cryo-microscopy (cryo-EM), the electron beam that is used for imaging also causes the sample to move. This motion blurs the images and limits the resolution attainable by single-particle analysis. In a previous Research article (Bai et al., 2013) we showed that correcting for this motion by processing movies from fast direct-electron detectors allowed structure determination to near-atomic resolution from 35,000 ribosome particles. In this Research advance article, we show that an improved movie processing algorithm is applicable to a much wider range of specimens. The new algorithm estimates straight movement tracks by considering multiple particles that are close to each other in the field of view, and models the fall-off of high-resolution information content by radiation damage in a dose-dependent manner. Application of the new algorithm to four data sets illustrates its potential for significantly improving cryo-EM structures, even for particles that are smaller than 200 kDa. Copyright © 2014, Scheres.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petasecca, M., E-mail: marcop@uow.edu.au; Newall, M. K.; Aldosari, A. H.

Purpose: Spatial and temporal resolutions are two of the most important features for quality assurance instrumentation of motion adaptive radiotherapy modalities. The goal of this work is to characterize the performance of the 2D high spatial resolution monolithic silicon diode array named “MagicPlate-512” for quality assurance of stereotactic body radiation therapy (SBRT) and stereotactic radiosurgery (SRS) combined with a dynamic multileaf collimator (MLC) tracking technique for motion compensation. Methods: MagicPlate-512 is used in combination with the movable platform HexaMotion and a research version of radiofrequency tracking system Calypso driving MLC tracking software. The authors reconstruct 2D dose distributions of smallmore » field square beams in three modalities: in static conditions, mimicking the temporal movement pattern of a lung tumor and tracking the moving target while the MLC compensates almost instantaneously for the tumor displacement. Use of Calypso in combination with MagicPlate-512 requires a proper radiofrequency interference shielding. Impact of the shielding on dosimetry has been simulated by GEANT4 and verified experimentally. Temporal and spatial resolutions of the dosimetry system allow also for accurate verification of segments of complex stereotactic radiotherapy plans with identification of the instant and location where a certain dose is delivered. This feature allows for retrospective temporal reconstruction of the delivery process and easy identification of error in the tracking or the multileaf collimator driving systems. A sliding MLC wedge combined with the lung motion pattern has been measured. The ability of the MagicPlate-512 (MP512) in 2D dose mapping in all three modes of operation was benchmarked by EBT3 film. Results: Full width at half maximum and penumbra of the moving and stationary dose profiles measured by EBT3 film and MagicPlate-512 confirm that motion has a significant impact on the dose distribution. Motion, no motion, and motion with MLC tracking profiles agreed within 1 and 0.4 mm, respectively, for all field sizes tested. Use of electromagnetic tracking system generates a fluctuation of the detector baseline up to 10% of the full scale signal requiring a proper shielding strategy. MagicPlate-512 is also able to reconstruct the dose variation pulse-by-pulse in each pixel of the detector. An analysis of the dose transients with motion and motion with tracking shows that the tracking feedback algorithm used for this experiment can compensate effectively only the effect of the slower transient components. The fast changing components of the organ motion can contribute only to discrepancy of the order of 15% in penumbral region while the slower components can change the dose profile up to 75% of the expected dose. Conclusions: MagicPlate-512 is shown to be, potentially, a valid alternative to film or 2D ionizing chambers for quality assurance dosimetry in SRS or SBRT. Its high spatial and temporal resolutions allow for accurate reconstruction of the profile in any conditions with motion and with tracking of the motion. It shows excellent performance to reconstruct the dose deposition in real time or retrospectively as a function of time for detailed analysis of the effect of motion in a specific pixel or area of interest.« less

EVA Robotic Assistant Project: Platform Attitude Prediction

NASA Technical Reports Server (NTRS)

Nickels, Kevin M.

2003-01-01

The Robotic Systems Technology Branch is currently working on the development of an EVA Robotic Assistant under the sponsorship of the Surface Systems Thrust of the NASA Cross Enterprise Technology Development Program (CETDP). This will be a mobile robot that can follow a field geologist during planetary surface exploration, carry his tools and the samples that he collects, and provide video coverage of his activity. Prior experiments have shown that for such a robot to be useful it must be able to follow the geologist at walking speed over any terrain of interest. Geologically interesting terrain tends to be rough rather than smooth. The commercial mobile robot that was recently purchased as an initial testbed for the EVA Robotic Assistant Project, an ATRV Jr., is capable of faster than walking speed outside but it has no suspension. Its wheels with inflated rubber tires are attached to axles that are connected directly to the robot body. Any angular motion of the robot produced by driving over rough terrain will directly affect the pointing of the on-board stereo cameras. The resulting image motion is expected to make tracking of the geologist more difficult. This will either require the tracker to search a larger part of the image to find the target from frame to frame or to search mechanically in pan and tilt whenever the image motion is large enough to put the target outside the image in the next frame. This project consists of the design and implementation of a Kalman filter that combines the output of the angular rate sensors and linear accelerometers on the robot to estimate the motion of the robot base. The motion of the stereo camera pair mounted on the robot that results from this motion as the robot drives over rough terrain is then straightforward to compute. The estimates may then be used, for example, to command the robot s on-board pan-tilt unit to compensate for the camera motion induced by the base movement. This has been accomplished in two ways: first, a standalone head stabilizer has been implemented and second, the estimates have been used to influence the search algorithm of the stereo tracking algorithm. Studies of the image motion of a tracked object indicate that the image motion of objects is suppressed while the robot crossing rough terrain. This work expands the range of speed and surface roughness over which the robot should be able to track and follow a field geologist and accept arm gesture commands from the geologist.

EVA: laparoscopic instrument tracking based on Endoscopic Video Analysis for psychomotor skills assessment.

PubMed

Oropesa, Ignacio; Sánchez-González, Patricia; Chmarra, Magdalena K; Lamata, Pablo; Fernández, Alvaro; Sánchez-Margallo, Juan A; Jansen, Frank Willem; Dankelman, Jenny; Sánchez-Margallo, Francisco M; Gómez, Enrique J

2013-03-01

The EVA (Endoscopic Video Analysis) tracking system is a new system for extracting motions of laparoscopic instruments based on nonobtrusive video tracking. The feasibility of using EVA in laparoscopic settings has been tested in a box trainer setup. EVA makes use of an algorithm that employs information of the laparoscopic instrument's shaft edges in the image, the instrument's insertion point, and the camera's optical center to track the three-dimensional position of the instrument tip. A validation study of EVA comprised a comparison of the measurements achieved with EVA and the TrEndo tracking system. To this end, 42 participants (16 novices, 22 residents, and 4 experts) were asked to perform a peg transfer task in a box trainer. Ten motion-based metrics were used to assess their performance. Construct validation of the EVA has been obtained for seven motion-based metrics. Concurrent validation revealed that there is a strong correlation between the results obtained by EVA and the TrEndo for metrics, such as path length (ρ = 0.97), average speed (ρ = 0.94), or economy of volume (ρ = 0.85), proving the viability of EVA. EVA has been successfully validated in a box trainer setup, showing the potential of endoscopic video analysis to assess laparoscopic psychomotor skills. The results encourage further implementation of video tracking in training setups and image-guided surgery.

Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images

NASA Technical Reports Server (NTRS)

Mcconnell, Ross; Kober, Wolfgang; Kwok, Ronald; Curlander, John C.; Pang, Shirley S.

1991-01-01

The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.

Cerebral palsy characterization by estimating ocular motion

NASA Astrophysics Data System (ADS)

González, Jully; Atehortúa, Angélica; Moncayo, Ricardo; Romero, Eduardo

2017-11-01

Cerebral palsy (CP) is a large group of motion and posture disorders caused during the fetal or infant brain development. Sensorial impairment is commonly found in children with CP, i.e., between 40-75 percent presents some form of vision problems or disabilities. An automatic characterization of the cerebral palsy is herein presented by estimating the ocular motion during a gaze pursuing task. Specifically, After automatically detecting the eye location, an optical flow algorithm tracks the eye motion following a pre-established visual assignment. Subsequently, the optical flow trajectories are characterized in the velocity-acceleration phase plane. Differences are quantified in a small set of patients between four to ten years.

Data-Driven Based Asynchronous Motor Control for Printing Servo Systems

NASA Astrophysics Data System (ADS)

Bian, Min; Guo, Qingyun

Modern digital printing equipment aims to the environmental-friendly industry with high dynamic performances and control precision and low vibration and abrasion. High performance motion control system of printing servo systems was required. Control system of asynchronous motor based on data acquisition was proposed. Iterative learning control (ILC) algorithm was studied. PID control was widely used in the motion control. However, it was sensitive to the disturbances and model parameters variation. The ILC applied the history error data and present control signals to approximate the control signal directly in order to fully track the expect trajectory without the system models and structures. The motor control algorithm based on the ILC and PID was constructed and simulation results were given. The results show that data-driven control method is effective dealing with bounded disturbances for the motion control of printing servo systems.

A full field, 3-D velocimeter for microgravity crystallization experiments

NASA Technical Reports Server (NTRS)

Brodkey, Robert S.; Russ, Keith M.

1991-01-01

The programming and algorithms needed for implementing a full-field, 3-D velocimeter for laminar flow systems and the appropriate hardware to fully implement this ultimate system are discussed. It appears that imaging using a synched pair of video cameras and digitizer boards with synched rails for camera motion will provide a viable solution to the laminar tracking problem. The algorithms given here are simple, which should speed processing. On a heavily loaded VAXstation 3100 the particle identification can take 15 to 30 seconds, with the tracking taking less than one second. It seeems reasonable to assume that four image pairs can thus be acquired and analyzed in under one minute.

A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor

PubMed Central

González, Diego; Botella, Guillermo; Meyer-Baese, Uwe; García, Carlos; Sanz, Concepción; Prieto-Matías, Manuel; Tirado, Francisco

2012-01-01

This work presents the implementation of a matching-based motion estimation sensor on a Field Programmable Gate Array (FPGA) and NIOS II microprocessor applying a C to Hardware (C2H) acceleration paradigm. The design, which involves several matching algorithms, is mapped using Very Large Scale Integration (VLSI) technology. These algorithms, as well as the hardware implementation, are presented here together with an extensive analysis of the resources needed and the throughput obtained. The developed low-cost system is practical for real-time throughput and reduced power consumption and is useful in robotic applications, such as tracking, navigation using an unmanned vehicle, or as part of a more complex system. PMID:23201989

A High-Speed Target-Free Vision-Based Sensor for Bus Rapid Transit Viaduct Vibration Measurements Using CMT and ORB Algorithms.

PubMed

Hu, Qijun; He, Songsheng; Wang, Shilong; Liu, Yugang; Zhang, Zutao; He, Leping; Wang, Fubin; Cai, Qijie; Shi, Rendan; Yang, Yuan

2017-06-06

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable.

A High-Speed Target-Free Vision-Based Sensor for Bus Rapid Transit Viaduct Vibration Measurements Using CMT and ORB Algorithms

PubMed Central

Hu, Qijun; He, Songsheng; Wang, Shilong; Liu, Yugang; Zhang, Zutao; He, Leping; Wang, Fubin; Cai, Qijie; Shi, Rendan; Yang, Yuan

2017-01-01

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable. PMID:28587275

Alternatives to an extended Kalman Filter for target image tracking

NASA Astrophysics Data System (ADS)

Leuthauser, P. R.

1981-12-01

Four alternative filters are compared to an extended Kalman filter (EKF) algorithm for tracking a distributed (elliptical) source target in a closed loop tracking problem, using outputs from a forward looking (FLIR) sensor as measurements. These were (1) an EKF with (second order) bias correction term, (2) a constant gain EKF, (3) a constant gain EKF with bias correction term, and (4) a statistically linearized filter. Estimates are made of both actual target motion and of apparent motion due to atmospheric jitter. These alternative designs are considered specifically to address some of the significant biases exhibited by an EKF due to initial acquisition difficulties, unmodelled maneuvering by the target, low signal-to-noise ratio, and real world conditions varying significantly from those assumed in the filter design (robustness). Filter performance was determined with a Monte Carlo study under both ideal and non ideal conditions for tracking targets on a constant velocity cross range path, and during constant acceleration turns of 5G, 10G, and 20G.

3-D model-based vehicle tracking.

PubMed

Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

2005-10-01

This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

Moving object detection and tracking in videos through turbulent medium

NASA Astrophysics Data System (ADS)

Halder, Kalyan Kumar; Tahtali, Murat; Anavatti, Sreenatha G.

2016-06-01

This paper addresses the problem of identifying and tracking moving objects in a video sequence having a time-varying background. This is a fundamental task in many computer vision applications, though a very challenging one because of turbulence that causes blurring and spatiotemporal movements of the background images. Our proposed approach involves two major steps. First, a moving object detection algorithm that deals with the detection of real motions by separating the turbulence-induced motions using a two-level thresholding technique is used. In the second step, a feature-based generalized regression neural network is applied to track the detected objects throughout the frames in the video sequence. The proposed approach uses the centroid and area features of the moving objects and creates the reference regions instantly by selecting the objects within a circle. Simulation experiments are carried out on several turbulence-degraded video sequences and comparisons with an earlier method confirms that the proposed approach provides a more effective tracking of the targets.

The Accuracy of Conventional 2D Video for Quantifying Upper Limb Kinematics in Repetitive Motion Occupational Tasks

PubMed Central

Chen, Chia-Hsiung; Azari, David; Hu, Yu Hen; Lindstrom, Mary J.; Thelen, Darryl; Yen, Thomas Y.; Radwin, Robert G.

2015-01-01

Objective Marker-less 2D video tracking was studied as a practical means to measure upper limb kinematics for ergonomics evaluations. Background Hand activity level (HAL) can be estimated from speed and duty cycle. Accuracy was measured using a cross correlation template-matching algorithm for tracking a region of interest on the upper extremities. Methods Ten participants performed a paced load transfer task while varying HAL (2, 4, and 5) and load (2.2 N, 8.9 N and 17.8 N). Speed and acceleration measured from 2D video were compared against ground truth measurements using 3D infrared motion capture. Results The median absolute difference between 2D video and 3D motion capture was 86.5 mm/s for speed, and 591 mm/s2 for acceleration, and less than 93 mm/s for speed and 656 mm/s2 for acceleration when camera pan and tilt were within ±30 degrees. Conclusion Single-camera 2D video had sufficient accuracy (< 100 mm/s) for evaluating HAL. Practitioner Summary This study demonstrated that 2D video tracking had sufficient accuracy to measure HAL for ascertaining the American Conference of Government Industrial Hygienists Threshold Limit Value® for repetitive motion when the camera is located within ±30 degrees off the plane of motion when compared against 3D motion capture for a simulated repetitive motion task. PMID:25978764

A dynamic model-based approach to motion and deformation tracking of prosthetic valves from biplane x-ray images.

PubMed

Wagner, Martin G; Hatt, Charles R; Dunkerley, David A P; Bodart, Lindsay E; Raval, Amish N; Speidel, Michael A

2018-04-16

Transcatheter aortic valve replacement (TAVR) is a minimally invasive procedure in which a prosthetic heart valve is placed and expanded within a defective aortic valve. The device placement is commonly performed using two-dimensional (2D) fluoroscopic imaging. Within this work, we propose a novel technique to track the motion and deformation of the prosthetic valve in three dimensions based on biplane fluoroscopic image sequences. The tracking approach uses a parameterized point cloud model of the valve stent which can undergo rigid three-dimensional (3D) transformation and different modes of expansion. Rigid elements of the model are individually rotated and translated in three dimensions to approximate the motions of the stent. Tracking is performed using an iterative 2D-3D registration procedure which estimates the model parameters by minimizing the mean-squared image values at the positions of the forward-projected model points. Additionally, an initialization technique is proposed, which locates clusters of salient features to determine the initial position and orientation of the model. The proposed algorithms were evaluated based on simulations using a digital 4D CT phantom as well as experimentally acquired images of a prosthetic valve inside a chest phantom with anatomical background features. The target registration error was 0.12 ± 0.04 mm in the simulations and 0.64 ± 0.09 mm in the experimental data. The proposed algorithm could be used to generate 3D visualization of the prosthetic valve from two projections. In combination with soft-tissue sensitive-imaging techniques like transesophageal echocardiography, this technique could enable 3D image guidance during TAVR procedures. © 2018 American Association of Physicists in Medicine.

Proton radiography and fluoroscopy of lung tumors: A Monte Carlo study using patient-specific 4DCT phantoms

PubMed Central

Han, Bin; Xu, X. George; Chen, George T. Y.

2011-01-01

Purpose: Monte Carlo methods are used to simulate and optimize a time-resolved proton range telescope (TRRT) in localization of intrafractional and interfractional motions of lung tumor and in quantification of proton range variations. Methods: The Monte Carlo N-Particle eXtended (MCNPX) code with a particle tracking feature was employed to evaluate the TRRT performance, especially in visualizing and quantifying proton range variations during respiration. Protons of 230 MeV were tracked one by one as they pass through position detectors, patient 4DCT phantom, and finally scintillator detectors that measured residual ranges. The energy response of the scintillator telescope was investigated. Mass density and elemental composition of tissues were defined for 4DCT data. Results: Proton water equivalent length (WEL) was deduced by a reconstruction algorithm that incorporates linear proton track and lateral spatial discrimination to improve the image quality. 4DCT data for three patients were used to visualize and measure tumor motion and WEL variations. The tumor trajectories extracted from the WEL map were found to be within ∼1 mm agreement with direct 4DCT measurement. Quantitative WEL variation studies showed that the proton radiograph is a good representation of WEL changes from entrance to distal of the target. Conclusions:MCNPX simulation results showed that TRRT can accurately track the motion of the tumor and detect the WEL variations. Image quality was optimized by choosing proton energy, testing parameters of image reconstruction algorithm, and comparing to ground truth 4DCT. The future study will demonstrate the feasibility of using the time resolved proton radiography as an imaging tool for proton treatments of lung tumors. PMID:21626923

A motion-compensated image filter for low-dose fluoroscopy in a real-time tumor-tracking radiotherapy system

PubMed Central

Miyamoto, Naoki; Ishikawa, Masayori; Sutherland, Kenneth; Suzuki, Ryusuke; Matsuura, Taeko; Toramatsu, Chie; Takao, Seishin; Nihongi, Hideaki; Shimizu, Shinichi; Umegaki, Kikuo; Shirato, Hiroki

2015-01-01

In the real-time tumor-tracking radiotherapy system, a surrogate fiducial marker inserted in or near the tumor is detected by fluoroscopy to realize respiratory-gated radiotherapy. The imaging dose caused by fluoroscopy should be minimized. In this work, an image processing technique is proposed for tracing a moving marker in low-dose imaging. The proposed tracking technique is a combination of a motion-compensated recursive filter and template pattern matching. The proposed image filter can reduce motion artifacts resulting from the recursive process based on the determination of the region of interest for the next frame according to the current marker position in the fluoroscopic images. The effectiveness of the proposed technique and the expected clinical benefit were examined by phantom experimental studies with actual tumor trajectories generated from clinical patient data. It was demonstrated that the marker motion could be traced in low-dose imaging by applying the proposed algorithm with acceptable registration error and high pattern recognition score in all trajectories, although some trajectories were not able to be tracked with the conventional spatial filters or without image filters. The positional accuracy is expected to be kept within ±2 mm. The total computation time required to determine the marker position is a few milliseconds. The proposed image processing technique is applicable for imaging dose reduction. PMID:25129556

Kinect based real-time position calibration for nasal endoscopic surgical navigation system

NASA Astrophysics Data System (ADS)

Fan, Jingfan; Yang, Jian; Chu, Yakui; Ma, Shaodong; Wang, Yongtian

2016-03-01

Unanticipated, reactive motion of the patient during skull based tumor resective surgery is the source of the consequence that the nasal endoscopic tracking system is compelled to be recalibrated. To accommodate the calibration process with patient's movement, this paper developed a Kinect based Real-time positional calibration method for nasal endoscopic surgical navigation system. In this method, a Kinect scanner was employed as the acquisition part of the point cloud volumetric reconstruction of the patient's head during surgery. Then, a convex hull based registration algorithm aligned the real-time image of the patient head with a model built upon the CT scans performed in the preoperative preparation to dynamically calibrate the tracking system if a movement was detected. Experimental results confirmed the robustness of the proposed method, presenting a total tracking error within 1 mm under the circumstance of relatively violent motions. These results point out the tracking accuracy can be retained stably and the potential to expedite the calibration of the tracking system against strong interfering conditions, demonstrating high suitability for a wide range of surgical applications.

Calculating observables in inhomogeneous cosmologies. Part I: general framework

NASA Astrophysics Data System (ADS)

Hellaby, Charles; Walters, Anthony

2018-02-01

We lay out a general framework for calculating the variation of a set of cosmological observables, down the past null cone of an arbitrarily placed observer, in a given arbitrary inhomogeneous metric. The observables include redshift, proper motions, area distance and redshift-space density. Of particular interest are observables that are zero in the spherically symmetric case, such as proper motions. The algorithm is based on the null geodesic equation and the geodesic deviation equation, and it is tailored to creating a practical numerical implementation. The algorithm provides a method for tracking which light rays connect moving objects to the observer at successive times. Our algorithm is applied to the particular case of the Szekeres metric. A numerical implementation has been created and some results will be presented in a subsequent paper. Future work will explore the range of possibilities.

Satellite-tracking and earth-dynamics research programs. [NASA Programs on satellite orbits and satellite ground tracks of geodetic satellites

NASA Technical Reports Server (NTRS)

1974-01-01

Observations and research progress of the Smithsonian Astrophysical Observatory are reported. Satellite tracking networks (ground stations) are discussed and equipment (Baker-Nunn cameras) used to observe the satellites is described. The improvement of the accuracy of a laser ranging system of the ground stations is discussed. Also, research efforts in satellite geodesy (tides, gravity anomalies, plate tectonics) is discussed. The use of data processing for geophysical data is examined, and a data base for the Earth and Ocean Physics Applications Program is proposed. Analytical models of the earth's motion (computerized simulation) are described and the computation (numerical integration and algorithms) of satellite orbits affected by the earth's albedo, using computer techniques, is also considered. Research efforts in the study of the atmosphere are examined (the effect of drag on satellite motion), and models of the atmosphere based on satellite data are described.

MagicPlate-512: A 2D silicon detector array for quality assurance of stereotactic motion adaptive radiotherapy.

PubMed

Petasecca, M; Newall, M K; Booth, J T; Duncan, M; Aldosari, A H; Fuduli, I; Espinoza, A A; Porumb, C S; Guatelli, S; Metcalfe, P; Colvill, E; Cammarano, D; Carolan, M; Oborn, B; Lerch, M L F; Perevertaylo, V; Keall, P J; Rosenfeld, A B

2015-06-01

Spatial and temporal resolutions are two of the most important features for quality assurance instrumentation of motion adaptive radiotherapy modalities. The goal of this work is to characterize the performance of the 2D high spatial resolution monolithic silicon diode array named "MagicPlate-512" for quality assurance of stereotactic body radiation therapy (SBRT) and stereotactic radiosurgery (SRS) combined with a dynamic multileaf collimator (MLC) tracking technique for motion compensation. MagicPlate-512 is used in combination with the movable platform HexaMotion and a research version of radiofrequency tracking system Calypso driving MLC tracking software. The authors reconstruct 2D dose distributions of small field square beams in three modalities: in static conditions, mimicking the temporal movement pattern of a lung tumor and tracking the moving target while the MLC compensates almost instantaneously for the tumor displacement. Use of Calypso in combination with MagicPlate-512 requires a proper radiofrequency interference shielding. Impact of the shielding on dosimetry has been simulated by (GEANT)4 and verified experimentally. Temporal and spatial resolutions of the dosimetry system allow also for accurate verification of segments of complex stereotactic radiotherapy plans with identification of the instant and location where a certain dose is delivered. This feature allows for retrospective temporal reconstruction of the delivery process and easy identification of error in the tracking or the multileaf collimator driving systems. A sliding MLC wedge combined with the lung motion pattern has been measured. The ability of the MagicPlate-512 (MP512) in 2D dose mapping in all three modes of operation was benchmarked by EBT3 film. Full width at half maximum and penumbra of the moving and stationary dose profiles measured by EBT3 film and MagicPlate-512 confirm that motion has a significant impact on the dose distribution. Motion, no motion, and motion with MLC tracking profiles agreed within 1 and 0.4 mm, respectively, for all field sizes tested. Use of electromagnetic tracking system generates a fluctuation of the detector baseline up to 10% of the full scale signal requiring a proper shielding strategy. MagicPlate-512 is also able to reconstruct the dose variation pulse-by-pulse in each pixel of the detector. An analysis of the dose transients with motion and motion with tracking shows that the tracking feedback algorithm used for this experiment can compensate effectively only the effect of the slower transient components. The fast changing components of the organ motion can contribute only to discrepancy of the order of 15% in penumbral region while the slower components can change the dose profile up to 75% of the expected dose. MagicPlate-512 is shown to be, potentially, a valid alternative to film or 2D ionizing chambers for quality assurance dosimetry in SRS or SBRT. Its high spatial and temporal resolutions allow for accurate reconstruction of the profile in any conditions with motion and with tracking of the motion. It shows excellent performance to reconstruct the dose deposition in real time or retrospectively as a function of time for detailed analysis of the effect of motion in a specific pixel or area of interest.

Study on robot motion control for intelligent welding processes based on the laser tracking sensor

NASA Astrophysics Data System (ADS)

Zhang, Bin; Wang, Qian; Tang, Chen; Wang, Ju

2017-06-01

A robot motion control method is presented for intelligent welding processes of complex spatial free-form curve seams based on the laser tracking sensor. First, calculate the tip position of the welding torch according to the velocity of the torch and the seam trajectory detected by the sensor. Then, search the optimal pose of the torch under constraints using genetic algorithms. As a result, the intersection point of the weld seam and the laser plane of the sensor is within the detectable range of the sensor. Meanwhile, the angle between the axis of the welding torch and the tangent of the weld seam meets the requirements. The feasibility of the control method is proved by simulation.

A low-cost test-bed for real-time landmark tracking

NASA Astrophysics Data System (ADS)

Csaszar, Ambrus; Hanan, Jay C.; Moreels, Pierre; Assad, Christopher

2007-04-01

A low-cost vehicle test-bed system was developed to iteratively test, refine and demonstrate navigation algorithms before attempting to transfer the algorithms to more advanced rover prototypes. The platform used here was a modified radio controlled (RC) car. A microcontroller board and onboard laptop computer allow for either autonomous or remote operation via a computer workstation. The sensors onboard the vehicle represent the types currently used on NASA-JPL rover prototypes. For dead-reckoning navigation, optical wheel encoders, a single axis gyroscope, and 2-axis accelerometer were used. An ultrasound ranger is available to calculate distance as a substitute for the stereo vision systems presently used on rovers. The prototype also carries a small laptop computer with a USB camera and wireless transmitter to send real time video to an off-board computer. A real-time user interface was implemented that combines an automatic image feature selector, tracking parameter controls, streaming video viewer, and user generated or autonomous driving commands. Using the test-bed, real-time landmark tracking was demonstrated by autonomously driving the vehicle through the JPL Mars yard. The algorithms tracked rocks as waypoints. This generated coordinates calculating relative motion and visually servoing to science targets. A limitation for the current system is serial computing-each additional landmark is tracked in order-but since each landmark is tracked independently, if transferred to appropriate parallel hardware, adding targets would not significantly diminish system speed.

Decentralized digital adaptive control of robot motion

NASA Technical Reports Server (NTRS)

Tarokh, M.

1990-01-01

A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.

SU-E-J-58: Comparison of Conformal Tracking Methods Using Initial, Adaptive and Preceding Image Frames for Image Registration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teo, P; Guo, K; Alayoubi, N

Purpose: Accounting for tumor motion during radiation therapy is important to ensure that the tumor receives the prescribed dose. Increasing the field size to account for this motion exposes the surrounding healthy tissues to unnecessary radiation. In contrast to using motion-encompassing techniques to treat moving tumors, conformal radiation therapy (RT) uses a smaller field to track the tumor and adapts the beam aperture according to the motion detected. This work investigates and compares the performance of three markerless, EPID based, optical flow methods to track tumor motion with conformal RT. Methods: Three techniques were used to track the motions ofmore » a 3D printed lung tumor programmed to move according to the tumor of seven lung cancer patients. These techniques utilized a multi-resolution optical flow algorithm as the core computation for image registration. The first method (DIR) registers the incoming images with an initial reference frame, while the second method (RFSF) uses an adaptive reference frame and the third method (CU) uses preceding image frames for registration. The patient traces and errors were evaluated for the seven patients. Results: The average position errors for all patient traces were 0.12 ± 0.33 mm, −0.05 ± 0.04 mm and −0.28 ± 0.44 mm for CU, DIR and RFSF method respectively. The position errors distributed within 1 standard deviation are 0.74 mm, 0.37 mm and 0.96 mm respectively. The CU and RFSF algorithms are sensitive to the characteristics of the patient trace and produce a wider distribution of errors amongst patients. Although the mean error for the DIR method is negatively biased (−0.05 mm) for all patients, it has the narrowest distribution of position error, which can be corrected using an offset calibration. Conclusion: Three techniques of image registration and position update were studied. Using direct comparison with an initial frame yields the best performance. The authors would like to thank Dr.YeLin Suh for making the Cyberknife dataset available to us. Scholarship funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) and CancerCare Manitoba Foundation is acknowledged.« less

Extracting cardiac shapes and motion of the chick embryo heart outflow tract from four-dimensional optical coherence tomography images

NASA Astrophysics Data System (ADS)

Yin, Xin; Liu, Aiping; Thornburg, Kent L.; Wang, Ruikang K.; Rugonyi, Sandra

2012-09-01

Recent advances in optical coherence tomography (OCT), and the development of image reconstruction algorithms, enabled four-dimensional (4-D) (three-dimensional imaging over time) imaging of the embryonic heart. To further analyze and quantify the dynamics of cardiac beating, segmentation procedures that can extract the shape of the heart and its motion are needed. Most previous studies analyzed cardiac image sequences using manually extracted shapes and measurements. However, this is time consuming and subject to inter-operator variability. Automated or semi-automated analyses of 4-D cardiac OCT images, although very desirable, are also extremely challenging. This work proposes a robust algorithm to semi automatically detect and track cardiac tissue layers from 4-D OCT images of early (tubular) embryonic hearts. Our algorithm uses a two-dimensional (2-D) deformable double-line model (DLM) to detect target cardiac tissues. The detection algorithm uses a maximum-likelihood estimator and was successfully applied to 4-D in vivo OCT images of the heart outflow tract of day three chicken embryos. The extracted shapes captured the dynamics of the chick embryonic heart outflow tract wall, enabling further analysis of cardiac motion.

Tracking of Maneuvering Complex Extended Object with Coupled Motion Kinematics and Extension Dynamics Using Range Extent Measurements

PubMed Central

Sun, Lifan; Ji, Baofeng; Lan, Jian; He, Zishu; Pu, Jiexin

2017-01-01

The key to successful maneuvering complex extended object tracking (MCEOT) using range extent measurements provided by high resolution sensors lies in accurate and effective modeling of both the extension dynamics and the centroid kinematics. During object maneuvers, the extension dynamics of an object with a complex shape is highly coupled with the centroid kinematics. However, this difficult but important problem is rarely considered and solved explicitly. In view of this, this paper proposes a general approach to modeling a maneuvering complex extended object based on Minkowski sum, so that the coupled turn maneuvers in both the centroid states and extensions can be described accurately. The new model has a concise and unified form, in which the complex extension dynamics can be simply and jointly characterized by multiple simple sub-objects’ extension dynamics based on Minkowski sum. The proposed maneuvering model fits range extent measurements very well due to its favorable properties. Based on this model, an MCEOT algorithm dealing with motion and extension maneuvers is also derived. Two different cases of the turn maneuvers with known/unknown turn rates are specifically considered. The proposed algorithm which jointly estimates the kinematic state and the object extension can also be easily implemented. Simulation results demonstrate the effectiveness of the proposed modeling and tracking approaches. PMID:28937629

Position estimation and driving of an autonomous vehicle by monocular vision

NASA Astrophysics Data System (ADS)

Hanan, Jay C.; Kayathi, Pavan; Hughlett, Casey L.

2007-04-01

Automatic adaptive tracking in real-time for target recognition provided autonomous control of a scale model electric truck. The two-wheel drive truck was modified as an autonomous rover test-bed for vision based guidance and navigation. Methods were implemented to monitor tracking error and ensure a safe, accurate arrival at the intended science target. Some methods are situation independent relying only on the confidence error of the target recognition algorithm. Other methods take advantage of the scenario of combined motion and tracking to filter out anomalies. In either case, only a single calibrated camera was needed for position estimation. Results from real-time autonomous driving tests on the JPL simulated Mars yard are presented. Recognition error was often situation dependent. For the rover case, the background was in motion and may be characterized to provide visual cues on rover travel such as rate, pitch, roll, and distance to objects of interest or hazards. Objects in the scene may be used as landmarks, or waypoints, for such estimations. As objects are approached, their scale increases and their orientation may change. In addition, particularly on rough terrain, these orientation and scale changes may be unpredictable. Feature extraction combined with the neural network algorithm was successful in providing visual odometry in the simulated Mars environment.

Interface of Augmented Reality Game Using Face Tracking and Its Application to Advertising

NASA Astrophysics Data System (ADS)

Lee, Young Jae; Lee, Yong Jae

This paper proposes the face interface method which can be used in recognizing gamer's movements in the real world for application in the cyber space so that we could make three-dimensional space recognition motion-based game. The proposed algorithm is the new face recognition technology which incorporates the strengths of two existing algorithms, CBCH and CAMSHIFT and its validity has been proved through a series of experiments. Moreover, for the purpose of the interdisciplinary studies, concepts of advertising have been introduced into the three-dimensional motion-based game to look into the possible new beneficiary models for the game industry. This kind of attempt may be significant in that it tried to see if the advertising brand when placed in the game could play the role of the game item or quest. The proposed method can provide the basic references for developing motion-based game development.

Introductory review on `Flying Triangulation': a motion-robust optical 3D measurement principle

NASA Astrophysics Data System (ADS)

Ettl, Svenja

2015-04-01

'Flying Triangulation' (FlyTri) is a recently developed principle which allows for a motion-robust optical 3D measurement of rough surfaces. It combines a simple sensor with sophisticated algorithms: a single-shot sensor acquires 2D camera images. From each camera image, a 3D profile is generated. The series of 3D profiles generated are aligned to one another by algorithms, without relying on any external tracking device. It delivers real-time feedback of the measurement process which enables an all-around measurement of objects. The principle has great potential for small-space acquisition environments, such as the measurement of the interior of a car, and motion-sensitive measurement tasks, such as the intraoral measurement of teeth. This article gives an overview of the basic ideas and applications of FlyTri. The main challenges and their solutions are discussed. Measurement examples are also given to demonstrate the potential of the measurement principle.

Spatial and rotational quality assurance of 6DOF patient tracking systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belcher, Andrew H.; Liu, Xinmin; Grelewicz, Zachary

Purpose: External tracking systems used for patient positioning and motion monitoring during radiotherapy are now capable of detecting both translations and rotations. In this work, the authors develop a novel technique to evaluate the 6 degree of freedom 6(DOF) (translations and rotations) performance of external motion tracking systems. The authors apply this methodology to an infrared marker tracking system and two 3D optical surface mapping systems in a common tumor 6DOF workspace. Methods: An in-house designed and built 6DOF parallel kinematics robotic motion phantom was used to perform motions with sub-millimeter and subdegree accuracy in a 6DOF workspace. An infraredmore » marker tracking system was first used to validate a calibration algorithm which associates the motion phantom coordinate frame to the camera frame. The 6DOF positions of the mobile robotic system in this space were then tracked and recorded independently by an optical surface tracking system after a cranial phantom was rigidly fixed to the moveable platform of the robotic stage. The calibration methodology was first employed, followed by a comprehensive 6DOF trajectory evaluation, which spanned a full range of positions and orientations in a 20 × 20 × 16 mm and 5° × 5° × 5° workspace. The intended input motions were compared to the calibrated 6DOF measured points. Results: The technique found the accuracy of the infrared (IR) marker tracking system to have maximal root-mean square error (RMSE) values of 0.18, 0.25, 0.07 mm, 0.05°, 0.05°, and 0.09° in left–right (LR), superior–inferior (SI), anterior–posterior (AP), pitch, roll, and yaw, respectively, comparing the intended 6DOF position and the measured position by the IR camera. Similarly, the 6DOF RSME discrepancy for the HD optical surface tracker yielded maximal values of 0.46, 0.60, 0.54 mm, 0.06°, 0.11°, and 0.08° in LR, SI, AP, pitch, roll, and yaw, respectively, over the same 6DOF evaluative workspace. An earlier generation 3D optical surface tracking unit was observed to have worse tracking capabilities than both the IR camera unit and the newer 3D surface tracking system with maximal RMSE of 0.69, 0.74, 0.47 mm, 0.28°, 0.19°, and 0.18°, in LR, SI, AP, pitch, roll, and yaw, respectively, in the same 6DOF evaluation space. Conclusions: The proposed technique was found to be effective at evaluating the performance of 6DOF patient tracking systems. All observed optical tracking systems were found to exhibit tracking capabilities at the sub-millimeter and subdegree level within a 6DOF workspace.« less

Towards designing an optical-flow based colonoscopy tracking algorithm: a comparative study

NASA Astrophysics Data System (ADS)

Liu, Jianfei; Subramanian, Kalpathi R.; Yoo, Terry S.

2013-03-01

Automatic co-alignment of optical and virtual colonoscopy images can supplement traditional endoscopic procedures, by providing more complete information of clinical value to the gastroenterologist. In this work, we present a comparative analysis of our optical flow based technique for colonoscopy tracking, in relation to current state of the art methods, in terms of tracking accuracy, system stability, and computational efficiency. Our optical-flow based colonoscopy tracking algorithm starts with computing multi-scale dense and sparse optical flow fields to measure image displacements. Camera motion parameters are then determined from optical flow fields by employing a Focus of Expansion (FOE) constrained egomotion estimation scheme. We analyze the design choices involved in the three major components of our algorithm: dense optical flow, sparse optical flow, and egomotion estimation. Brox's optical flow method,1 due to its high accuracy, was used to compare and evaluate our multi-scale dense optical flow scheme. SIFT6 and Harris-affine features7 were used to assess the accuracy of the multi-scale sparse optical flow, because of their wide use in tracking applications; the FOE-constrained egomotion estimation was compared with collinear,2 image deformation10 and image derivative4 based egomotion estimation methods, to understand the stability of our tracking system. Two virtual colonoscopy (VC) image sequences were used in the study, since the exact camera parameters(for each frame) were known; dense optical flow results indicated that Brox's method was superior to multi-scale dense optical flow in estimating camera rotational velocities, but the final tracking errors were comparable, viz., 6mm vs. 8mm after the VC camera traveled 110mm. Our approach was computationally more efficient, averaging 7.2 sec. vs. 38 sec. per frame. SIFT and Harris affine features resulted in tracking errors of up to 70mm, while our sparse optical flow error was 6mm. The comparison among egomotion estimation algorithms showed that our FOE-constrained egomotion estimation method achieved the optimal balance between tracking accuracy and robustness. The comparative study demonstrated that our optical-flow based colonoscopy tracking algorithm maintains good accuracy and stability for routine use in clinical practice.

High-precision tracking of brownian boomerang colloidal particles confined in quasi two dimensions.

PubMed

Chakrabarty, Ayan; Wang, Feng; Fan, Chun-Zhen; Sun, Kai; Wei, Qi-Huo

2013-11-26

In this article, we present a high-precision image-processing algorithm for tracking the translational and rotational Brownian motion of boomerang-shaped colloidal particles confined in quasi-two-dimensional geometry. By measuring mean square displacements of an immobilized particle, we demonstrate that the positional and angular precision of our imaging and image-processing system can achieve 13 nm and 0.004 rad, respectively. By analyzing computer-simulated images, we demonstrate that the positional and angular accuracies of our image-processing algorithm can achieve 32 nm and 0.006 rad. Because of zero correlations between the displacements in neighboring time intervals, trajectories of different videos of the same particle can be merged into a very long time trajectory, allowing for long-time averaging of different physical variables. We apply this image-processing algorithm to measure the diffusion coefficients of boomerang particles of three different apex angles and discuss the angle dependence of these diffusion coefficients.

Real-time stylistic prediction for whole-body human motions.

PubMed

Matsubara, Takamitsu; Hyon, Sang-Ho; Morimoto, Jun

2012-01-01

The ability to predict human motion is crucial in several contexts such as human tracking by computer vision and the synthesis of human-like computer graphics. Previous work has focused on off-line processes with well-segmented data; however, many applications such as robotics require real-time control with efficient computation. In this paper, we propose a novel approach called real-time stylistic prediction for whole-body human motions to satisfy these requirements. This approach uses a novel generative model to represent a whole-body human motion including rhythmic motion (e.g., walking) and discrete motion (e.g., jumping). The generative model is composed of a low-dimensional state (phase) dynamics and a two-factor observation model, allowing it to capture the diversity of motion styles in humans. A real-time adaptation algorithm was derived to estimate both state variables and style parameter of the model from non-stationary unlabeled sequential observations. Moreover, with a simple modification, the algorithm allows real-time adaptation even from incomplete (partial) observations. Based on the estimated state and style, a future motion sequence can be accurately predicted. In our implementation, it takes less than 15 ms for both adaptation and prediction at each observation. Our real-time stylistic prediction was evaluated for human walking, running, and jumping behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multiple vehicle tracking in aerial video sequence using driver behavior analysis and improved deterministic data association

NASA Astrophysics Data System (ADS)

Zhang, Xunxun; Xu, Hongke; Fang, Jianwu

2018-01-01

Along with the rapid development of the unmanned aerial vehicle technology, multiple vehicle tracking (MVT) in aerial video sequence has received widespread interest for providing the required traffic information. Due to the camera motion and complex background, MVT in aerial video sequence poses unique challenges. We propose an efficient MVT algorithm via driver behavior-based Kalman filter (DBKF) and an improved deterministic data association (IDDA) method. First, a hierarchical image registration method is put forward to compensate the camera motion. Afterward, to improve the accuracy of the state estimation, we propose the DBKF module by incorporating the driver behavior into the Kalman filter, where artificial potential field is introduced to reflect the driver behavior. Then, to implement the data association, a local optimization method is designed instead of global optimization. By introducing the adaptive operating strategy, the proposed IDDA method can also deal with the situation in which the vehicles suddenly appear or disappear. Finally, comprehensive experiments on the DARPA VIVID data set and KIT AIS data set demonstrate that the proposed algorithm can generate satisfactory and superior results.

Pixel decomposition for tracking in low resolution videos

NASA Astrophysics Data System (ADS)

Govinda, Vivekanand; Ralph, Jason F.; Spencer, Joseph W.; Goulermas, John Y.; Yang, Lihua; Abbas, Alaa M.

2008-04-01

This paper describes a novel set of algorithms that allows indoor activity to be monitored using data from very low resolution imagers and other non-intrusive sensors. The objects are not resolved but activity may still be determined. This allows the use of such technology in sensitive environments where privacy must be maintained. Spectral un-mixing algorithms from remote sensing were adapted for this environment. These algorithms allow the fractional contributions from different colours within each pixel to be estimated and this is used to assist in the detection and monitoring of small objects or sub-pixel motion.

Multiple-camera/motion stereoscopy for range estimation in helicopter flight

NASA Technical Reports Server (NTRS)

Smith, Phillip N.; Sridhar, Banavar; Suorsa, Raymond E.

1993-01-01

Aiding the pilot to improve safety and reduce pilot workload by detecting obstacles and planning obstacle-free flight paths during low-altitude helicopter flight is desirable. Computer vision techniques provide an attractive method of obstacle detection and range estimation for objects within a large field of view ahead of the helicopter. Previous research has had considerable success by using an image sequence from a single moving camera to solving this problem. The major limitations of single camera approaches are that no range information can be obtained near the instantaneous direction of motion or in the absence of motion. These limitations can be overcome through the use of multiple cameras. This paper presents a hybrid motion/stereo algorithm which allows range refinement through recursive range estimation while avoiding loss of range information in the direction of travel. A feature-based approach is used to track objects between image frames. An extended Kalman filter combines knowledge of the camera motion and measurements of a feature's image location to recursively estimate the feature's range and to predict its location in future images. Performance of the algorithm will be illustrated using an image sequence, motion information, and independent range measurements from a low-altitude helicopter flight experiment.

Quantitative assessment of tumor angiogenesis using real-time motion-compensated contrast-enhanced ultrasound imaging

PubMed Central

Pysz, Marybeth A.; Guracar, Ismayil; Foygel, Kira; Tian, Lu; Willmann, Jürgen K.

2015-01-01

Purpose To develop and test a real-time motion compensation algorithm for contrast-enhanced ultrasound imaging of tumor angiogenesis on a clinical ultrasound system. Materials and methods The Administrative Institutional Panel on Laboratory Animal Care approved all experiments. A new motion correction algorithm measuring the sum of absolute differences in pixel displacements within a designated tracking box was implemented in a clinical ultrasound machine. In vivo angiogenesis measurements (expressed as percent contrast area) with and without motion compensated maximum intensity persistence (MIP) ultrasound imaging were analyzed in human colon cancer xenografts (n = 64) in mice. Differences in MIP ultrasound imaging signal with and without motion compensation were compared and correlated with displacements in x- and y-directions. The algorithm was tested in an additional twelve colon cancer xenograft-bearing mice with (n = 6) and without (n = 6) anti-vascular therapy (ASA-404). In vivo MIP percent contrast area measurements were quantitatively correlated with ex vivo microvessel density (MVD) analysis. Results MIP percent contrast area was significantly different (P < 0.001) with and without motion compensation. Differences in percent contrast area correlated significantly (P < 0.001) with x- and y-displacements. MIP percent contrast area measurements were more reproducible with motion compensation (ICC = 0.69) than without (ICC = 0.51) on two consecutive ultrasound scans. Following anti-vascular therapy, motion-compensated MIP percent contrast area significantly (P = 0.03) decreased by 39.4 ± 14.6 % compared to non-treated mice and correlated well with ex vivo MVD analysis (Rho = 0.70; P = 0.05). Conclusion Real-time motion-compensated MIP ultrasound imaging allows reliable and accurate quantification and monitoring of angiogenesis in tumors exposed to breathing-induced motion artifacts. PMID:22535383

Quantitative assessment of tumor angiogenesis using real-time motion-compensated contrast-enhanced ultrasound imaging.

PubMed

Pysz, Marybeth A; Guracar, Ismayil; Foygel, Kira; Tian, Lu; Willmann, Jürgen K

2012-09-01

To develop and test a real-time motion compensation algorithm for contrast-enhanced ultrasound imaging of tumor angiogenesis on a clinical ultrasound system. The Administrative Institutional Panel on Laboratory Animal Care approved all experiments. A new motion correction algorithm measuring the sum of absolute differences in pixel displacements within a designated tracking box was implemented in a clinical ultrasound machine. In vivo angiogenesis measurements (expressed as percent contrast area) with and without motion compensated maximum intensity persistence (MIP) ultrasound imaging were analyzed in human colon cancer xenografts (n = 64) in mice. Differences in MIP ultrasound imaging signal with and without motion compensation were compared and correlated with displacements in x- and y-directions. The algorithm was tested in an additional twelve colon cancer xenograft-bearing mice with (n = 6) and without (n = 6) anti-vascular therapy (ASA-404). In vivo MIP percent contrast area measurements were quantitatively correlated with ex vivo microvessel density (MVD) analysis. MIP percent contrast area was significantly different (P < 0.001) with and without motion compensation. Differences in percent contrast area correlated significantly (P < 0.001) with x- and y-displacements. MIP percent contrast area measurements were more reproducible with motion compensation (ICC = 0.69) than without (ICC = 0.51) on two consecutive ultrasound scans. Following anti-vascular therapy, motion-compensated MIP percent contrast area significantly (P = 0.03) decreased by 39.4 ± 14.6 % compared to non-treated mice and correlated well with ex vivo MVD analysis (Rho = 0.70; P = 0.05). Real-time motion-compensated MIP ultrasound imaging allows reliable and accurate quantification and monitoring of angiogenesis in tumors exposed to breathing-induced motion artifacts.

Three-dimensional liver motion tracking using real-time two-dimensional MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brix, Lau, E-mail: lau.brix@stab.rm.dk; Ringgaard, Steffen; Sørensen, Thomas Sangild

2014-04-15

Purpose: Combined magnetic resonance imaging (MRI) systems and linear accelerators for radiotherapy (MR-Linacs) are currently under development. MRI is noninvasive and nonionizing and can produce images with high soft tissue contrast. However, new tracking methods are required to obtain fast real-time spatial target localization. This study develops and evaluates a method for tracking three-dimensional (3D) respiratory liver motion in two-dimensional (2D) real-time MRI image series with high temporal and spatial resolution. Methods: The proposed method for 3D tracking in 2D real-time MRI series has three steps: (1) Recording of a 3D MRI scan and selection of a blood vessel (ormore » tumor) structure to be tracked in subsequent 2D MRI series. (2) Generation of a library of 2D image templates oriented parallel to the 2D MRI image series by reslicing and resampling the 3D MRI scan. (3) 3D tracking of the selected structure in each real-time 2D image by finding the template and template position that yield the highest normalized cross correlation coefficient with the image. Since the tracked structure has a known 3D position relative to each template, the selection and 2D localization of a specific template translates into quantification of both the through-plane and in-plane position of the structure. As a proof of principle, 3D tracking of liver blood vessel structures was performed in five healthy volunteers in two 5.4 Hz axial, sagittal, and coronal real-time 2D MRI series of 30 s duration. In each 2D MRI series, the 3D localization was carried out twice, using nonoverlapping template libraries, which resulted in a total of 12 estimated 3D trajectories per volunteer. Validation tests carried out to support the tracking algorithm included quantification of the breathing induced 3D liver motion and liver motion directionality for the volunteers, and comparison of 2D MRI estimated positions of a structure in a watermelon with the actual positions. Results: Axial, sagittal, and coronal 2D MRI series yielded 3D respiratory motion curves for all volunteers. The motion directionality and amplitude were very similar when measured directly as in-plane motion or estimated indirectly as through-plane motion. The mean peak-to-peak breathing amplitude was 1.6 mm (left-right), 11.0 mm (craniocaudal), and 2.5 mm (anterior-posterior). The position of the watermelon structure was estimated in 2D MRI images with a root-mean-square error of 0.52 mm (in-plane) and 0.87 mm (through-plane). Conclusions: A method for 3D tracking in 2D MRI series was developed and demonstrated for liver tracking in volunteers. The method would allow real-time 3D localization with integrated MR-Linac systems.« less

Mobile robotic sensors for perimeter detection and tracking.

PubMed

Clark, Justin; Fierro, Rafael

2007-02-01

Mobile robot/sensor networks have emerged as tools for environmental monitoring, search and rescue, exploration and mapping, evaluation of civil infrastructure, and military operations. These networks consist of many sensors each equipped with embedded processors, wireless communication, and motion capabilities. This paper describes a cooperative mobile robot network capable of detecting and tracking a perimeter defined by a certain substance (e.g., a chemical spill) in the environment. Specifically, the contributions of this paper are twofold: (i) a library of simple reactive motion control algorithms and (ii) a coordination mechanism for effectively carrying out perimeter-sensing missions. The decentralized nature of the methodology implemented could potentially allow the network to scale to many sensors and to reconfigure when adding/deleting sensors. Extensive simulation results and experiments verify the validity of the proposed cooperative control scheme.

Myocardial motion estimation of tagged cardiac magnetic resonance images using tag motion constraints and multi-level b-splines interpolation.

PubMed

Liu, Hong; Yan, Meng; Song, Enmin; Wang, Jie; Wang, Qian; Jin, Renchao; Jin, Lianghai; Hung, Chih-Cheng

2016-05-01

Myocardial motion estimation of tagged cardiac magnetic resonance (TCMR) images is of great significance in clinical diagnosis and the treatment of heart disease. Currently, the harmonic phase analysis method (HARP) and the local sine-wave modeling method (SinMod) have been proven as two state-of-the-art motion estimation methods for TCMR images, since they can directly obtain the inter-frame motion displacement vector field (MDVF) with high accuracy and fast speed. By comparison, SinMod has better performance over HARP in terms of displacement detection, noise and artifacts reduction. However, the SinMod method has some drawbacks: 1) it is unable to estimate local displacements larger than half of the tag spacing; 2) it has observable errors in tracking of tag motion; and 3) the estimated MDVF usually has large local errors. To overcome these problems, we present a novel motion estimation method in this study. The proposed method tracks the motion of tags and then estimates the dense MDVF by using the interpolation. In this new method, a parameter estimation procedure for global motion is applied to match tag intersections between different frames, ensuring specific kinds of large displacements being correctly estimated. In addition, a strategy of tag motion constraints is applied to eliminate most of errors produced by inter-frame tracking of tags and the multi-level b-splines approximation algorithm is utilized, so as to enhance the local continuity and accuracy of the final MDVF. In the estimation of the motion displacement, our proposed method can obtain a more accurate MDVF compared with the SinMod method and our method can overcome the drawbacks of the SinMod method. However, the motion estimation accuracy of our method depends on the accuracy of tag lines detection and our method has a higher time complexity. Copyright © 2015 Elsevier Inc. All rights reserved.

Multi-Stage Target Tracking with Drift Correction and Position Prediction

NASA Astrophysics Data System (ADS)

Chen, Xin; Ren, Keyan; Hou, Yibin

2018-04-01

Most existing tracking methods are hard to combine accuracy and performance, and do not consider the shift between clarity and blur that often occurs. In this paper, we propound a multi-stage tracking framework with two particular modules: position prediction and corrective measure. We conduct tracking based on correlation filter with a corrective measure module to increase both performance and accuracy. Specifically, a convolutional network is used for solving the blur problem in realistic scene, training methodology that training dataset with blur images generated by the three blur algorithms. Then, we propose a position prediction module to reduce the computation cost and make tracker more capable of fast motion. Experimental result shows that our tracking method is more robust compared to others and more accurate on the benchmark sequences.

Robust multiple cue fusion-based high-speed and nonrigid object tracking algorithm for short track speed skating

NASA Astrophysics Data System (ADS)

Liu, Chenguang; Cheng, Heng-Da; Zhang, Yingtao; Wang, Yuxuan; Xian, Min

2016-01-01

This paper presents a methodology for tracking multiple skaters in short track speed skating competitions. Nonrigid skaters move at high speed with severe occlusions happening frequently among them. The camera is panned quickly in order to capture the skaters in a large and dynamic scene. To automatically track the skaters and precisely output their trajectories becomes a challenging task in object tracking. We employ the global rink information to compensate camera motion and obtain the global spatial information of skaters, utilize random forest to fuse multiple cues and predict the blob of each skater, and finally apply a silhouette- and edge-based template-matching and blob-evolving method to labelling pixels to a skater. The effectiveness and robustness of the proposed method are verified through thorough experiments.

Real-time marker-free motion capture system using blob feature analysis

NASA Astrophysics Data System (ADS)

Park, Chang-Joon; Kim, Sung-Eun; Kim, Hong-Seok; Lee, In-Ho

2005-02-01

This paper presents a real-time marker-free motion capture system which can reconstruct 3-dimensional human motions. The virtual character of the proposed system mimics the motion of an actor in real-time. The proposed system captures human motions by using three synchronized CCD cameras and detects the root and end-effectors of an actor such as a head, hands, and feet by exploiting the blob feature analysis. And then, the 3-dimensional positions of end-effectors are restored and tracked by using Kalman filter. At last, the positions of the intermediate joint are reconstructed by using anatomically constrained inverse kinematics algorithm. The proposed system was implemented under general lighting conditions and we confirmed that the proposed system could reconstruct motions of a lot of people wearing various clothes in real-time stably.

Visualizing and Quantifying Blob Characteristics on NSTX

NASA Astrophysics Data System (ADS)

Davis, William; Zweben, Stewart; Myra, James; D'Ippolito, Daniel; Ko, Matthew

2012-10-01

Understanding the radial motion of blob-filaments in the tokamak edge plasma is important since this motion can affect the width of the heat and particle scrape-off layer (SOL) [1]. High resolution (64x80), high speed (400,000 frames/sec) edge turbulence movies taken of the NSTX outer midplane separatrix region have recently been analyzed for blob motion. Regions of high light emission from gas puff imaging within a 25x30 cm cross-section were used to track blob-filaments in the plasma edge and into the SOL. Software tools have been developed for visualizing blob movement and automatically generating statistics of blob speed, shape, amplitude, size, and orientation; thousands of blobs have been analyzed for dozens of shots. The blob tracking algorithm and resulting database entries are explained in detail. Visualization tools also show how poloidal and radial motion change as blobs move through the scrape-off-layer (SOL), e.g. suggesting the influence of sheared flow. Relationships between blob size and velocity are shown for various types of plasmas and compared with simplified theories of blob motion. This work was supported by DOE Contract DE-AC02-09-CH11466. [4pt] [1] J.R. Myra et al, Phys. Plasmas 18, 012305 (2011)

SU-E-J-142: Performance Study of Automatic Image-Segmentation Algorithms in Motion Tracking Via MR-IGRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Y; Olsen, J.; Parikh, P.

2014-06-01

Purpose: Evaluate commonly used segmentation algorithms on a commercially available real-time MR image guided radiotherapy (MR-IGRT) system (ViewRay), compare the strengths and weaknesses of each method, with the purpose of improving motion tracking for more accurate radiotherapy. Methods: MR motion images of bladder, kidney, duodenum, and liver tumor were acquired for three patients using a commercial on-board MR imaging system and an imaging protocol used during MR-IGRT. A series of 40 frames were selected for each case to cover at least 3 respiratory cycles. Thresholding, Canny edge detection, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE),more » along with the ViewRay treatment planning and delivery system (TPDS) were included in the comparisons. To evaluate the segmentation results, an expert manual contouring of the organs or tumor from a physician was used as a ground-truth. Metrics value of sensitivity, specificity, Jaccard similarity, and Dice coefficient were computed for comparison. Results: In the segmentation of single image frame, all methods successfully segmented the bladder and kidney, but only FKM, KHM and TPDS were able to segment the liver tumor and the duodenum. For segmenting motion image series, the TPDS method had the highest sensitivity, Jarccard, and Dice coefficients in segmenting bladder and kidney, while FKM and KHM had a slightly higher specificity. A similar pattern was observed when segmenting the liver tumor and the duodenum. The Canny method is not suitable for consistently segmenting motion frames in an automated process, while thresholding and RD-LSE cannot consistently segment a liver tumor and the duodenum. Conclusion: The study compared six different segmentation methods and showed the effectiveness of the ViewRay TPDS algorithm in segmenting motion images during MR-IGRT. Future studies include a selection of conformal segmentation methods based on image/organ-specific information, different filtering methods and their influences on the segmentation results. Parag Parikh receives research grant from ViewRay. Sasa Mutic has consulting and research agreements with ViewRay. Yanle Hu receives travel reimbursement from ViewRay. Iwan Kawrakow and James Dempsey are ViewRay employees.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiu, T; Kearney, V; Liu, H

Purpose: Dynamic tumor tracking or motion compensation techniques have proposed to modify beam delivery following lung tumor motion on the flight. Conventional treatment plan QA could be performed in advance since every delivery may be different. Markerless lung tumor tracking using beams eye view EPID images provides a best treatment evaluation mechanism. The purpose of this study is to improve the accuracy of the online markerless lung tumor motion tracking method. Methods: The lung tumor could be located on every frame of MV images during radiation therapy treatment by comparing with corresponding digitally reconstructed radiograph (DRR). A kV-MV CT correspondingmore » curve is applied on planning kV CT to generate MV CT images for patients in order to enhance the similarity between DRRs and MV treatment images. This kV-MV CT corresponding curve was obtained by scanning a same CT electron density phantom by a kV CT scanner and MV scanner (Tomotherapy) or MV CBCT. Two sets of MV DRRs were then generated for tumor and anatomy without tumor as the references to tracking the tumor on beams eye view EPID images. Results: Phantom studies were performed on a Varian TrueBeam linac. MV treatment images were acquired continuously during each treatment beam delivery at 12 gantry angles by iTools. Markerless tumor tracking was applied with DRRs generated from simulated MVCT. Tumors were tracked on every frame of images and compared with expected positions based on programed phantom motion. It was found that the average tracking error were 2.3 mm. Conclusion: This algorithm is capable of detecting lung tumors at complicated environment without implanting markers. It should be noted that the CT data has a slice thickness of 3 mm. This shows the statistical accuracy is better than the spatial accuracy. This project has been supported by a Varian Research Grant.« less

2-D Myocardial Deformation Imaging Based on RF-Based Nonrigid Image Registration.

PubMed

Chakraborty, Bidisha; Liu, Zhi; Heyde, Brecht; Luo, Jianwen; D'hooge, Jan

2018-06-01

Myocardial deformation imaging is a well-established echocardiographic technique for the assessment of myocardial function. Although some solutions make use of speckle tracking of the reconstructed B-mode images, others apply block matching (BM) on the underlying radio frequency (RF) data in order to increase sensitivity to small interframe motion and deformation. However, for both approaches, lateral motion estimation remains a challenge due to the relatively poor lateral resolution of the ultrasound image in combination with the lack of phase information in this direction. Hereto, nonrigid image registration (NRIR) of B-mode images has previously been proposed as an attractive solution. However, hereby, the advantages of RF-based tracking were lost. The aim of this paper was, therefore, to develop an NRIR motion estimator adapted to RF data sets. The accuracy of this estimator was quantified using synthetic data and was contrasted against a state-of-the-art BM solution. The results show that RF-based NRIR outperforms BM in terms of tracking accuracy, particularly, as hypothesized, in the lateral direction. Finally, this RF-based NRIR algorithm was applied clinically, illustrating its ability to estimate both in-plane velocity components in vivo.

Motion estimation accuracy for visible-light/gamma-ray imaging fusion for portable portal monitoring

NASA Astrophysics Data System (ADS)

Karnowski, Thomas P.; Cunningham, Mark F.; Goddard, James S.; Cheriyadat, Anil M.; Hornback, Donald E.; Fabris, Lorenzo; Kerekes, Ryan A.; Ziock, Klaus-Peter; Gee, Timothy F.

2010-01-01

The use of radiation sensors as portal monitors is increasing due to heightened concerns over the smuggling of fissile material. Portable systems that can detect significant quantities of fissile material that might be present in vehicular traffic are of particular interest. We have constructed a prototype, rapid-deployment portal gamma-ray imaging portal monitor that uses machine vision and gamma-ray imaging to monitor multiple lanes of traffic. Vehicles are detected and tracked by using point detection and optical flow methods as implemented in the OpenCV software library. Points are clustered together but imperfections in the detected points and tracks cause errors in the accuracy of the vehicle position estimates. The resulting errors cause a "blurring" effect in the gamma image of the vehicle. To minimize these errors, we have compared a variety of motion estimation techniques including an estimate using the median of the clustered points, a "best-track" filtering algorithm, and a constant velocity motion estimation model. The accuracy of these methods are contrasted and compared to a manually verified ground-truth measurement by quantifying the rootmean- square differences in the times the vehicles cross the gamma-ray image pixel boundaries compared with a groundtruth manual measurement.

Motion compensation for fully 4D PET reconstruction using PET superset data

NASA Astrophysics Data System (ADS)

Verhaeghe, J.; Gravel, P.; Mio, R.; Fukasawa, R.; Rosa-Neto, P.; Soucy, J.-P.; Thompson, C. J.; Reader, A. J.

2010-07-01

Fully 4D PET image reconstruction is receiving increasing research interest due to its ability to significantly reduce spatiotemporal noise in dynamic PET imaging. However, thus far in the literature, the important issue of correcting for subject head motion has not been considered. Specifically, as a direct consequence of using temporally extensive basis functions, a single instance of movement propagates to impair the reconstruction of multiple time frames, even if no further movement occurs in those frames. Existing 3D motion compensation strategies have not yet been adapted to 4D reconstruction, and as such the benefits of 4D algorithms have not yet been reaped in a clinical setting where head movement undoubtedly occurs. This work addresses this need, developing a motion compensation method suitable for fully 4D reconstruction methods which exploits an optical tracking system to measure the head motion along with PET superset data to store the motion compensated data. List-mode events are histogrammed as PET superset data according to the measured motion, and a specially devised normalization scheme for motion compensated reconstruction from the superset data is required. This work proceeds to propose the corresponding time-dependent normalization modifications which are required for a major class of fully 4D image reconstruction algorithms (those which use linear combinations of temporal basis functions). Using realistically simulated as well as real high-resolution PET data from the HRRT, we demonstrate both the detrimental impact of subject head motion in fully 4D PET reconstruction and the efficacy of our proposed modifications to 4D algorithms. Benefits are shown both for the individual PET image frames as well as for parametric images of tracer uptake and volume of distribution for 18F-FDG obtained from Patlak analysis.

Determining the 3-D structure and motion of objects using a scanning laser range sensor

NASA Technical Reports Server (NTRS)

Nandhakumar, N.; Smith, Philip W.

1993-01-01

In order for the EVAHR robot to autonomously track and grasp objects, its vision system must be able to determine the 3-D structure and motion of an object from a sequence of sensory images. This task is accomplished by the use of a laser radar range sensor which provides dense range maps of the scene. Unfortunately, the currently available laser radar range cameras use a sequential scanning approach which complicates image analysis. Although many algorithms have been developed for recognizing objects from range images, none are suited for use with single beam, scanning, time-of-flight sensors because all previous algorithms assume instantaneous acquisition of the entire image. This assumption is invalid since the EVAHR robot is equipped with a sequential scanning laser range sensor. If an object is moving while being imaged by the device, the apparent structure of the object can be significantly distorted due to the significant non-zero delay time between sampling each image pixel. If an estimate of the motion of the object can be determined, this distortion can be eliminated; but, this leads to the motion-structure paradox - most existing algorithms for 3-D motion estimation use the structure of objects to parameterize their motions. The goal of this research is to design a rigid-body motion recovery technique which overcomes this limitation. The method being developed is an iterative, linear, feature-based approach which uses the non-zero image acquisition time constraint to accurately recover the motion parameters from the distorted structure of the 3-D range maps. Once the motion parameters are determined, the structural distortion in the range images is corrected.

Motion compensation for fully 4D PET reconstruction using PET superset data.

PubMed

Verhaeghe, J; Gravel, P; Mio, R; Fukasawa, R; Rosa-Neto, P; Soucy, J-P; Thompson, C J; Reader, A J

2010-07-21

Fully 4D PET image reconstruction is receiving increasing research interest due to its ability to significantly reduce spatiotemporal noise in dynamic PET imaging. However, thus far in the literature, the important issue of correcting for subject head motion has not been considered. Specifically, as a direct consequence of using temporally extensive basis functions, a single instance of movement propagates to impair the reconstruction of multiple time frames, even if no further movement occurs in those frames. Existing 3D motion compensation strategies have not yet been adapted to 4D reconstruction, and as such the benefits of 4D algorithms have not yet been reaped in a clinical setting where head movement undoubtedly occurs. This work addresses this need, developing a motion compensation method suitable for fully 4D reconstruction methods which exploits an optical tracking system to measure the head motion along with PET superset data to store the motion compensated data. List-mode events are histogrammed as PET superset data according to the measured motion, and a specially devised normalization scheme for motion compensated reconstruction from the superset data is required. This work proceeds to propose the corresponding time-dependent normalization modifications which are required for a major class of fully 4D image reconstruction algorithms (those which use linear combinations of temporal basis functions). Using realistically simulated as well as real high-resolution PET data from the HRRT, we demonstrate both the detrimental impact of subject head motion in fully 4D PET reconstruction and the efficacy of our proposed modifications to 4D algorithms. Benefits are shown both for the individual PET image frames as well as for parametric images of tracer uptake and volume of distribution for (18)F-FDG obtained from Patlak analysis.

TH-CD-207A-03: A Surface Deformation Driven Respiratory Model for Organ Motion Tracking in Lung Cancer Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, H; Zhen, X; Zhou, L

Purpose: To propose and validate a novel real-time surface-mesh-based internal organ-external surface motion and deformation tracking method for lung cancer radiotherapy. Methods: Deformation vector fields (DVFs) which characterizes the internal and external motion are obtained by registering the internal organ and tumor contours and external surface meshes to a reference phase in the 4D CT images using a recent developed local topology preserved non-rigid point matching algorithm (TOP). A composite matrix is constructed by combing the estimated internal and external DVFs. Principle component analysis (PCA) is then applied on the composite matrix to extract principal motion characteristics and finally yieldmore » the respiratory motion model parameters which correlates the internal and external motion and deformation. The accuracy of the respiratory motion model is evaluated using a 4D NURBS-based cardiac-torso (NCAT) synthetic phantom and three lung cancer cases. The center of mass (COM) difference is used to measure the tumor motion tracking accuracy, and the Dice’s coefficient (DC), percent error (PE) and Housdourf’s distance (HD) are used to measure the agreement between the predicted and ground truth tumor shape. Results: The mean COM is 0.84±0.49mm and 0.50±0.47mm for the phantom and patient data respectively. The mean DC, PE and HD are 0.93±0.01, 0.13±0.03 and 1.24±0.34 voxels for the phantom, and 0.91±0.04, 0.17±0.07 and 3.93±2.12 voxels for the three lung cancer patients, respectively. Conclusions: We have proposed and validate a real-time surface-mesh-based organ motion and deformation tracking method with an internal-external motion modeling. The preliminary results conducted on a synthetic 4D NCAT phantom and 4D CT images from three lung cancer cases show that the proposed method is reliable and accurate in tracking both the tumor motion trajectory and deformation, which can serve as a potential tool for real-time organ motion and deformation monitoring in lung cancer radiotherapy. This work is supported in part by grant from VARIAN MEDICAL SYSTEMS INC, the National Natural Science Foundation of China (no 81428019 and no 81301940), the Guangdong Natural Science Foundation (2015A030313302)and the 2015 Pearl River S&T Nova Program of Guangzhou (201506010096).« less

Optimum Value of Original Events on the Pept Technique

NASA Astrophysics Data System (ADS)

Sadremomtaz, Alireza; Taherparvar, Payvand

2011-12-01

Do Positron emission particle tracking (PEPT) has been used to track the motion of a single radioactively labeled tracer particle within a bed of similar particles. In this paper, the effect of the original event fraction on the results precise in two experiments has been reviewed. Results showed that the algorithm can no longer distinguish some corrupt trajectories, in addition to; further iteration reduces the statistical significance of the sample without improving its quality. Results show that the optimum value of trajectories depends on the type of experiment.

Development of collision avoidance system for useful UAV applications using image sensors with laser transmitter

NASA Astrophysics Data System (ADS)

Cheong, M. K.; Bahiki, M. R.; Azrad, S.

2016-10-01

The main goal of this study is to demonstrate the approach of achieving collision avoidance on Quadrotor Unmanned Aerial Vehicle (QUAV) using image sensors with colour- based tracking method. A pair of high definition (HD) stereo cameras were chosen as the stereo vision sensor to obtain depth data from flat object surfaces. Laser transmitter was utilized to project high contrast tracking spot for depth calculation using common triangulation. Stereo vision algorithm was developed to acquire the distance from tracked point to QUAV and the control algorithm was designed to manipulate QUAV's response based on depth calculated. Attitude and position controller were designed using the non-linear model with the help of Optitrack motion tracking system. A number of collision avoidance flight tests were carried out to validate the performance of the stereo vision and control algorithm based on image sensors. In the results, the UAV was able to hover with fairly good accuracy in both static and dynamic collision avoidance for short range collision avoidance. Collision avoidance performance of the UAV was better with obstacle of dull surfaces in comparison to shiny surfaces. The minimum collision avoidance distance achievable was 0.4 m. The approach was suitable to be applied in short range collision avoidance.

An efficient fully unsupervised video object segmentation scheme using an adaptive neural-network classifier architecture.

PubMed

Doulamis, A; Doulamis, N; Ntalianis, K; Kollias, S

2003-01-01

In this paper, an unsupervised video object (VO) segmentation and tracking algorithm is proposed based on an adaptable neural-network architecture. The proposed scheme comprises: 1) a VO tracking module and 2) an initial VO estimation module. Object tracking is handled as a classification problem and implemented through an adaptive network classifier, which provides better results compared to conventional motion-based tracking algorithms. Network adaptation is accomplished through an efficient and cost effective weight updating algorithm, providing a minimum degradation of the previous network knowledge and taking into account the current content conditions. A retraining set is constructed and used for this purpose based on initial VO estimation results. Two different scenarios are investigated. The first concerns extraction of human entities in video conferencing applications, while the second exploits depth information to identify generic VOs in stereoscopic video sequences. Human face/ body detection based on Gaussian distributions is accomplished in the first scenario, while segmentation fusion is obtained using color and depth information in the second scenario. A decision mechanism is also incorporated to detect time instances for weight updating. Experimental results and comparisons indicate the good performance of the proposed scheme even in sequences with complicated content (object bending, occlusion).

A linear complementarity method for the solution of vertical vehicle-track interaction

NASA Astrophysics Data System (ADS)

Zhang, Jian; Gao, Qiang; Wu, Feng; Zhong, Wan-Xie

2018-02-01

A new method is proposed for the solution of the vertical vehicle-track interaction including a separation between wheel and rail. The vehicle is modelled as a multi-body system using rigid bodies, and the track is treated as a three-layer beam model in which the rail is considered as an Euler-Bernoulli beam and both the sleepers and the ballast are represented by lumped masses. A linear complementarity formulation is directly established using a combination of the wheel-rail normal contact condition and the generalised-α method. This linear complementarity problem is solved using the Lemke algorithm, and the wheel-rail contact force can be obtained. Then the dynamic responses of the vehicle and the track are solved without iteration based on the generalised-α method. The same equations of motion for the vehicle and track are adopted at the different wheel-rail contact situations. This method can remove some restrictions, that is, time-dependent mass, damping and stiffness matrices of the coupled system, multiple equations of motion for the different contact situations and the effect of the contact stiffness. Numerical results demonstrate that the proposed method is effective for simulating the vehicle-track interaction including a separation between wheel and rail.

Patient motion tracking in the presence of measurement errors.

PubMed

Haidegger, Tamás; Benyó, Zoltán; Kazanzides, Peter

2009-01-01

The primary aim of computer-integrated surgical systems is to provide physicians with superior surgical tools for better patient outcome. Robotic technology is capable of both minimally invasive surgery and microsurgery, offering remarkable advantages for the surgeon and the patient. Current systems allow for sub-millimeter intraoperative spatial positioning, however certain limitations still remain. Measurement noise and unintended changes in the operating room environment can result in major errors. Positioning errors are a significant danger to patients in procedures involving robots and other automated devices. We have developed a new robotic system at the Johns Hopkins University to support cranial drilling in neurosurgery procedures. The robot provides advanced visualization and safety features. The generic algorithm described in this paper allows for automated compensation of patient motion through optical tracking and Kalman filtering. When applied to the neurosurgery setup, preliminary results show that it is possible to identify patient motion within 700 ms, and apply the appropriate compensation with an average of 1.24 mm positioning error after 2 s of setup time.

Adaptive independent joint control of manipulators - Theory and experiment

NASA Technical Reports Server (NTRS)

Seraji, H.

1988-01-01

The author presents a simple decentralized adaptive control scheme for multijoint robot manipulators based on the independent joint control concept. The proposed control scheme for each joint consists of a PID (proportional integral and differential) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. The static and dynamic couplings that exist between the joint motions are compensated by the adaptive independent joint controllers while ensuring trajectory tracking. The proposed scheme is implemented on a MicroVAX II computer for motion control of the first three joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite strongly coupled, highly nonlinear joint dynamics. The results confirm that the proposed decentralized adaptive control of manipulators is feasible, in spite of strong interactions between joint motions. The control scheme presented is computationally very fast and is amenable to parallel processing implementation within a distributed computing architecture, where each joint is controlled independently by a simple algorithm on a dedicated microprocessor.

Jerk-level synchronous repetitive motion scheme with gradient-type and zeroing-type dynamics algorithms applied to dual-arm redundant robot system control

NASA Astrophysics Data System (ADS)

Chen, Dechao; Zhang, Yunong

2017-10-01

Dual-arm redundant robot systems are usually required to handle primary tasks, repetitively and synchronously in practical applications. In this paper, a jerk-level synchronous repetitive motion scheme is proposed to remedy the joint-angle drift phenomenon and achieve the synchronous control of a dual-arm redundant robot system. The proposed scheme is novelly resolved at jerk level, which makes the joint variables, i.e. joint angles, joint velocities and joint accelerations, smooth and bounded. In addition, two types of dynamics algorithms, i.e. gradient-type (G-type) and zeroing-type (Z-type) dynamics algorithms, for the design of repetitive motion variable vectors, are presented in detail with the corresponding circuit schematics. Subsequently, the proposed scheme is reformulated as two dynamical quadratic programs (DQPs) and further integrated into a unified DQP (UDQP) for the synchronous control of a dual-arm robot system. The optimal solution of the UDQP is found by the piecewise-linear projection equation neural network. Moreover, simulations and comparisons based on a six-degrees-of-freedom planar dual-arm redundant robot system substantiate the operation effectiveness and tracking accuracy of the robot system with the proposed scheme for repetitive motion and synchronous control.

Robust human detection, tracking, and recognition in crowded urban areas

NASA Astrophysics Data System (ADS)

Chen, Hai-Wen; McGurr, Mike

2014-06-01

In this paper, we present algorithms we recently developed to support an automated security surveillance system for very crowded urban areas. In our approach for human detection, the color features are obtained by taking the difference of R, G, B spectrum and converting R, G, B to HSV (Hue, Saturation, Value) space. Morphological patch filtering and regional minimum and maximum segmentation on the extracted features are applied for target detection. The human tracking process approach includes: 1) Color and intensity feature matching track candidate selection; 2) Separate three parallel trackers for color, bright (above mean intensity), and dim (below mean intensity) detections, respectively; 3) Adaptive track gate size selection for reducing false tracking probability; and 4) Forward position prediction based on previous moving speed and direction for continuing tracking even when detections are missed from frame to frame. The Human target recognition is improved with a Super-Resolution Image Enhancement (SRIE) process. This process can improve target resolution by 3-5 times and can simultaneously process many targets that are tracked. Our approach can project tracks from one camera to another camera with a different perspective viewing angle to obtain additional biometric features from different perspective angles, and to continue tracking the same person from the 2nd camera even though the person moved out of the Field of View (FOV) of the 1st camera with `Tracking Relay'. Finally, the multiple cameras at different view poses have been geo-rectified to nadir view plane and geo-registered with Google- Earth (or other GIS) to obtain accurate positions (latitude, longitude, and altitude) of the tracked human for pin-point targeting and for a large area total human motion activity top-view. Preliminary tests of our algorithms indicate than high probability of detection can be achieved for both moving and stationary humans. Our algorithms can simultaneously track more than 100 human targets with averaged tracking period (time length) longer than the performance of the current state-of-the-art.

Dynamic dual-energy chest radiography: a potential tool for lung tissue motion monitoring and kinetic study

PubMed Central

Xu, Tong; Ducote, Justin L.; Wong, Jerry T.; Molloi, Sabee

2011-01-01

Dual-energy chest radiography has the potential to provide better diagnosis of lung disease by removing the bone signal from the image. Dynamic dual-energy radiography is now possible with the introduction of digital flat panel detectors. The purpose of this study is to evaluate the feasibility of using dynamic dual-energy chest radiography for functional lung imaging and tumor motion assessment. The dual energy system used in this study can acquire up to 15 frame of dual-energy images per second. A swine animal model was mechanically ventilated and imaged using the dual-energy system. Sequences of soft-tissue images were obtained using dual-energy subtraction. Time subtracted soft-tissue images were shown to be able to provide information on regional ventilation. Motion tracking of a lung anatomic feature (a branch of pulmonary artery) was performed based on an image cross-correlation algorithm. The tracking precision was found to be better than 1 mm. An adaptive correlation model was established between the above tracked motion and an external surrogate signal (temperature within the tracheal tube). This model is used to predict lung feature motion using the continuous surrogate signal and low frame rate dual-energy images (0.1 to 3.0 frames /sec). The average RMS error of the prediction was (1.1 ± 0.3) mm. The dynamic dual-energy was shown to be potentially useful for lung functional imaging such as regional ventilation and kinetic studies. It can also be used for lung tumor motion assessment and prediction during radiation therapy. PMID:21285477

Dynamic dual-energy chest radiography: a potential tool for lung tissue motion monitoring and kinetic study.

PubMed

Xu, Tong; Ducote, Justin L; Wong, Jerry T; Molloi, Sabee

2011-02-21

Dual-energy chest radiography has the potential to provide better diagnosis of lung disease by removing the bone signal from the image. Dynamic dual-energy radiography is now possible with the introduction of digital flat-panel detectors. The purpose of this study is to evaluate the feasibility of using dynamic dual-energy chest radiography for functional lung imaging and tumor motion assessment. The dual-energy system used in this study can acquire up to 15 frames of dual-energy images per second. A swine animal model was mechanically ventilated and imaged using the dual-energy system. Sequences of soft-tissue images were obtained using dual-energy subtraction. Time subtracted soft-tissue images were shown to be able to provide information on regional ventilation. Motion tracking of a lung anatomic feature (a branch of pulmonary artery) was performed based on an image cross-correlation algorithm. The tracking precision was found to be better than 1 mm. An adaptive correlation model was established between the above tracked motion and an external surrogate signal (temperature within the tracheal tube). This model is used to predict lung feature motion using the continuous surrogate signal and low frame rate dual-energy images (0.1-3.0 frames per second). The average RMS error of the prediction was (1.1 ± 0.3) mm. The dynamic dual energy was shown to be potentially useful for lung functional imaging such as regional ventilation and kinetic studies. It can also be used for lung tumor motion assessment and prediction during radiation therapy.

CAT & MAUS: A novel system for true dynamic motion measurement of underlying bony structures with compensation for soft tissue movement.

PubMed

Jia, Rui; Monk, Paul; Murray, David; Noble, J Alison; Mellon, Stephen

2017-09-06

Optoelectronic motion capture systems are widely employed to measure the movement of human joints. However, there can be a significant discrepancy between the data obtained by a motion capture system (MCS) and the actual movement of underlying bony structures, which is attributed to soft tissue artefact. In this paper, a computer-aided tracking and motion analysis with ultrasound (CAT & MAUS) system with an augmented globally optimal registration algorithm is presented to dynamically track the underlying bony structure during movement. The augmented registration part of CAT & MAUS was validated with a high system accuracy of 80%. The Euclidean distance between the marker-based bony landmark and the bony landmark tracked by CAT & MAUS was calculated to quantify the measurement error of an MCS caused by soft tissue artefact during movement. The average Euclidean distance between the target bony landmark measured by each of the CAT & MAUS system and the MCS alone varied from 8.32mm to 16.87mm in gait. This indicates the discrepancy between the MCS measured bony landmark and the actual underlying bony landmark. Moreover, Procrustes analysis was applied to demonstrate that CAT & MAUS reduces the deformation of the body segment shape modeled by markers during motion. The augmented CAT & MAUS system shows its potential to dynamically detect and locate actual underlying bony landmarks, which reduces the MCS measurement error caused by soft tissue artefact during movement. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real-time circumferential mapping catheter tracking for motion compensation in atrial fibrillation ablation procedures

NASA Astrophysics Data System (ADS)

Brost, Alexander; Bourier, Felix; Wimmer, Andreas; Koch, Martin; Kiraly, Atilla; Liao, Rui; Kurzidim, Klaus; Hornegger, Joachim; Strobel, Norbert

2012-02-01

Atrial fibrillation (AFib) has been identified as a major cause of stroke. Radiofrequency catheter ablation has become an increasingly important treatment option, especially when drug therapy fails. Navigation under X-ray can be enhanced by using augmented fluoroscopy. It renders overlay images from pre-operative 3-D data sets which are then fused with X-ray images to provide more details about the underlying soft-tissue anatomy. Unfortunately, these fluoroscopic overlay images are compromised by respiratory and cardiac motion. Various methods to deal with motion have been proposed. To meet clinical demands, they have to be fast. Methods providing a processing frame rate of 3 frames-per-second (fps) are considered suitable for interventional electrophysiology catheter procedures if an acquisition frame rate of 2 fps is used. Unfortunately, when working at a processing rate of 3 fps, the delay until the actual motion compensated image can be displayed is about 300 ms. More recent algorithms can achieve frame rates of up to 20 fps, which reduces the lag to 50 ms. By using a novel approach involving a 3-D catheter model, catheter segmentation and a distance transform, we can speed up motion compensation to 25 fps which results in a display delay of only 40 ms on a standard workstation for medical applications. Our method uses a constrained 2-D/3-D registration to perform catheter tracking, and it obtained a 2-D tracking error of 0.61 mm.

Guided filter and convolutional network based tracking for infrared dim moving target

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Qin, Hanlin; Rong, Shenghui; Zhao, Dong; Du, Juan

2017-09-01

The dim moving target usually submerges in strong noise, and its motion observability is debased by numerous false alarms for low signal-to-noise ratio. A tracking algorithm that integrates the Guided Image Filter (GIF) and the Convolutional neural network (CNN) into the particle filter framework is presented to cope with the uncertainty of dim targets. First, the initial target template is treated as a guidance to filter incoming templates depending on similarities between the guidance and candidate templates. The GIF algorithm utilizes the structure in the guidance and performs as an edge-preserving smoothing operator. Therefore, the guidance helps to preserve the detail of valuable templates and makes inaccurate ones blurry, alleviating the tracking deviation effectively. Besides, the two-layer CNN method is adopted to obtain a powerful appearance representation. Subsequently, a Bayesian classifier is trained with these discriminative yet strong features. Moreover, an adaptive learning factor is introduced to prevent the update of classifier's parameters when a target undergoes sever background. At last, classifier responses of particles are utilized to generate particle importance weights and a re-sample procedure preserves samples according to the weight. In the predication stage, a 2-order transition model considers the target velocity to estimate current position. Experimental results demonstrate that the presented algorithm outperforms several relative algorithms in the accuracy.

Use of a genetic algorithm for the analysis of eye movements from the linear vestibulo-ocular reflex

NASA Technical Reports Server (NTRS)

Shelhamer, M.

2001-01-01

It is common in vestibular and oculomotor testing to use a single-frequency (sine) or combination of frequencies [sum-of-sines (SOS)] stimulus for head or target motion. The resulting eye movements typically contain a smooth tracking component, which follows the stimulus, in which are interspersed rapid eye movements (saccades or fast phases). The parameters of the smooth tracking--the amplitude and phase of each component frequency--are of interest; many methods have been devised that attempt to identify and remove the fast eye movements from the smooth. We describe a new approach to this problem, tailored to both single-frequency and sum-of-sines stimulation of the human linear vestibulo-ocular reflex. An approximate derivative is used to identify fast movements, which are then omitted from further analysis. The remaining points form a series of smooth tracking segments. A genetic algorithm is used to fit these segments together to form a smooth (but disconnected) wave form, by iteratively removing biases due to the missing fast phases. A genetic algorithm is an iterative optimization procedure; it provides a basis for extending this approach to more complex stimulus-response situations. In the SOS case, the genetic algorithm estimates the amplitude and phase values of the component frequencies as well as removing biases.

Tri-track: free software for large-scale particle tracking.

PubMed

Vallotton, Pascal; Olivier, Sandra

2013-04-01

The ability to correctly track objects in time-lapse sequences is important in many applications of microscopy. Individual object motions typically display a level of dynamic regularity reflecting the existence of an underlying physics or biology. Best results are obtained when this local information is exploited. Additionally, if the particle number is known to be approximately constant, a large number of tracking scenarios may be rejected on the basis that they are not compatible with a known maximum particle velocity. This represents information of a global nature, which should ideally be exploited too. Some time ago, we devised an efficient algorithm that exploited both types of information. The tracking task was reduced to a max-flow min-cost problem instance through a novel graph structure that comprised vertices representing objects from three consecutive image frames. The algorithm is explained here for the first time. A user-friendly implementation is provided, and the specific relaxation mechanism responsible for the method's effectiveness is uncovered. The software is particularly competitive for complex dynamics such as dense antiparallel flows, or in situations where object displacements are considerable. As an application, we characterize a remarkable vortex structure formed by bacteria engaged in interstitial motility.

Detecting and Analyzing Multiple Moving Objects in Crowded Environments with Coherent Motion Regions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheriyadat, Anil M.

Understanding the world around us from large-scale video data requires vision systems that can perform automatic interpretation. While human eyes can unconsciously perceive independent objects in crowded scenes and other challenging operating environments, automated systems have difficulty detecting, counting, and understanding their behavior in similar scenes. Computer scientists at ORNL have a developed a technology termed as "Coherent Motion Region Detection" that invloves identifying multiple indepedent moving objects in crowded scenes by aggregating low-level motion cues extracted from moving objects. Humans and other species exploit such low-level motion cues seamlessely to perform perceptual grouping for visual understanding. The algorithm detectsmore » and tracks feature points on moving objects resulting in partial trajectories that span coherent 3D region in the space-time volume defined by the video. In the case of multi-object motion, many possible coherent motion regions can be constructed around the set of trajectories. The unique approach in the algorithm is to identify all possible coherent motion regions, then extract a subset of motion regions based on an innovative measure to automatically locate moving objects in crowded environments.The software reports snapshot of the object, count, and derived statistics ( count over time) from input video streams. The software can directly process videos streamed over the internet or directly from a hardware device (camera).« less

Design and Implementation of a Compact Master-Slave Robotic System with Force Feedback and Energy Recycling

NASA Astrophysics Data System (ADS)

Li, Chunguang; Inoue, Yoshio; Liu, Tao; Shibata, Kyoko; Oka, Koichi

Master-slave control is becoming increasingly popular in the development of robotic systems which can provide rehabilitation training for hemiplegic patients with a unilaterally disabled limb. However, the system structures and control strategies of existent master-slave systems are always complex. An innovative master-slave system implementing force feedback and motion tracking for a rehabilitation robot is presented in this paper. The system consists of two identical motors with a wired connection, and the two motors are located at the master and slave manipulator sites respectively. The slave motor tracks the motion of the master motor directly driven by a patient. As well, the interaction force produced at the slave site is fed back to the patient. Therefore, the impaired limb driven by the slave motor can imitate the motion of the healthy limb controlling the master motor, and the patient can regulate the control force of the healthy limb properly according to the force sensation. The force sensing and motion tracking are achieved simultaneously with neither force sensors nor sophisticated control algorithms. The system is characterized by simple structure, bidirectional controllability, energy recycling, and force feedback without a force sensor. Test experiments on a prototype were conducted, and the results appraise the advantages of the system and demonstrate the feasibility of the proposed control scheme for a rehabilitation robot.

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

2013-09-01

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

Fluoroscopic tumor tracking for image-guided lung cancer radiotherapy

NASA Astrophysics Data System (ADS)

Lin, Tong; Cerviño, Laura I.; Tang, Xiaoli; Vasconcelos, Nuno; Jiang, Steve B.

2009-02-01

Accurate lung tumor tracking in real time is a keystone to image-guided radiotherapy of lung cancers. Existing lung tumor tracking approaches can be roughly grouped into three categories: (1) deriving tumor position from external surrogates; (2) tracking implanted fiducial markers fluoroscopically or electromagnetically; (3) fluoroscopically tracking lung tumor without implanted fiducial markers. The first approach suffers from insufficient accuracy, while the second may not be widely accepted due to the risk of pneumothorax. Previous studies in fluoroscopic markerless tracking are mainly based on template matching methods, which may fail when the tumor boundary is unclear in fluoroscopic images. In this paper we propose a novel markerless tumor tracking algorithm, which employs the correlation between the tumor position and surrogate anatomic features in the image. The positions of the surrogate features are not directly tracked; instead, we use principal component analysis of regions of interest containing them to obtain parametric representations of their motion patterns. Then, the tumor position can be predicted from the parametric representations of surrogates through regression. Four regression methods were tested in this study: linear and two-degree polynomial regression, artificial neural network (ANN) and support vector machine (SVM). The experimental results based on fluoroscopic sequences of ten lung cancer patients demonstrate a mean tracking error of 2.1 pixels and a maximum error at a 95% confidence level of 4.6 pixels (pixel size is about 0.5 mm) for the proposed tracking algorithm.

Application of Satellite-Derived Atmospheric Motion Vectors for Estimating Mesoscale Flows.

NASA Astrophysics Data System (ADS)

Bedka, Kristopher M.; Mecikalski, John R.

2005-11-01

This study demonstrates methods to obtain high-density, satellite-derived atmospheric motion vectors (AMV) that contain both synoptic-scale and mesoscale flow components associated with and induced by cumuliform clouds through adjustments made to the University of Wisconsin—Madison Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS) AMV processing algorithm. Operational AMV processing is geared toward the identification of synoptic-scale motions in geostrophic balance, which are useful in data assimilation applications. AMVs identified in the vicinity of deep convection are often rejected by quality-control checks used in the production of operational AMV datasets. Few users of these data have considered the use of AMVs with ageostrophic flow components, which often fail checks that assure both spatial coherence between neighboring AMVs and a strong correlation to an NWP-model first-guess wind field. The UW-CIMSS algorithm identifies coherent cloud and water vapor features (i.e., targets) that can be tracked within a sequence of geostationary visible (VIS) and infrared (IR) imagery. AMVs are derived through the combined use of satellite feature tracking and an NWP-model first guess. Reducing the impact of the NWP-model first guess on the final AMV field, in addition to adjusting the target selection and vector-editing schemes, is found to result in greater than a 20-fold increase in the number of AMVs obtained from the UW-CIMSS algorithm for one convective storm case examined here. Over a three-image sequence of Geostationary Operational Environmental Satellite (GOES)-12 VIS and IR data, 3516 AMVs are obtained, most of which contain flow components that deviate considerably from geostrophy. In comparison, 152 AMVs are derived when a tighter NWP-model constraint and no targeting adjustments were imposed, similar to settings used with operational AMV production algorithms. A detailed analysis reveals that many of these 3516 vectors contain low-level (100 70 kPa) convergent and midlevel (70 40 kPa) to upper-level (40 10 kPa) divergent motion components consistent with localized mesoscale flow patterns. The applicability of AMVs for estimating cloud-top cooling rates at the 1-km pixel scale is demonstrated with excellent correspondence to rates identified by a human expert.

Resource Balancing Control Allocation

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Bodson, Marc

2010-01-01

Next generation aircraft with a large number of actuators will require advanced control allocation methods to compute the actuator commands needed to follow desired trajectories while respecting system constraints. Previously, algorithms were proposed to minimize the l1 or l2 norms of the tracking error and of the control effort. The paper discusses the alternative choice of using the l1 norm for minimization of the tracking error and a normalized l(infinity) norm, or sup norm, for minimization of the control effort. The algorithm computes the norm of the actuator deflections scaled by the actuator limits. Minimization of the control effort then translates into the minimization of the maximum actuator deflection as a percentage of its range of motion. The paper shows how the problem can be solved effectively by converting it into a linear program and solving it using a simplex algorithm. Properties of the algorithm are investigated through examples. In particular, the min-max criterion results in a type of resource balancing, where the resources are the control surfaces and the algorithm balances these resources to achieve the desired command. A study of the sensitivity of the algorithms to the data is presented, which shows that the normalized l(infinity) algorithm has the lowest sensitivity, although high sensitivities are observed whenever the limits of performance are reached.

Automatic respiration tracking for radiotherapy using optical 3D camera

NASA Astrophysics Data System (ADS)

Li, Tuotuo; Geng, Jason; Li, Shidong

2013-03-01

Rapid optical three-dimensional (O3D) imaging systems provide accurate digitized 3D surface data in real-time, with no patient contact nor radiation. The accurate 3D surface images offer crucial information in image-guided radiation therapy (IGRT) treatments for accurate patient repositioning and respiration management. However, applications of O3D imaging techniques to image-guided radiotherapy have been clinically challenged by body deformation, pathological and anatomical variations among individual patients, extremely high dimensionality of the 3D surface data, and irregular respiration motion. In existing clinical radiation therapy (RT) procedures target displacements are caused by (1) inter-fractional anatomy changes due to weight, swell, food/water intake; (2) intra-fractional variations from anatomy changes within any treatment session due to voluntary/involuntary physiologic processes (e.g. respiration, muscle relaxation); (3) patient setup misalignment in daily reposition due to user errors; and (4) changes of marker or positioning device, etc. Presently, viable solution is lacking for in-vivo tracking of target motion and anatomy changes during the beam-on time without exposing patient with additional ionized radiation or high magnet field. Current O3D-guided radiotherapy systems relay on selected points or areas in the 3D surface to track surface motion. The configuration of the marks or areas may change with time that makes it inconsistent in quantifying and interpreting the respiration patterns. To meet the challenge of performing real-time respiration tracking using O3D imaging technology in IGRT, we propose a new approach to automatic respiration motion analysis based on linear dimensionality reduction technique based on PCA (principle component analysis). Optical 3D image sequence is decomposed with principle component analysis into a limited number of independent (orthogonal) motion patterns (a low dimension eigen-space span by eigen-vectors). New images can be accurately represented as weighted summation of those eigen-vectors, which can be easily discriminated with a trained classifier. We developed algorithms, software and integrated with an O3D imaging system to perform the respiration tracking automatically. The resulting respiration tracking system requires no human intervene during it tracking operation. Experimental results show that our approach to respiration tracking is more accurate and robust than the methods using manual selected markers, even in the presence of incomplete imaging data.

Egomotion estimation with optic flow and air velocity sensors.

PubMed

Rutkowski, Adam J; Miller, Mikel M; Quinn, Roger D; Willis, Mark A

2011-06-01

We develop a method that allows a flyer to estimate its own motion (egomotion), the wind velocity, ground slope, and flight height using only inputs from onboard optic flow and air velocity sensors. Our artificial algorithm demonstrates how it could be possible for flying insects to determine their absolute egomotion using their available sensors, namely their eyes and wind sensitive hairs and antennae. Although many behaviors can be performed by only knowing the direction of travel, behavioral experiments indicate that odor tracking insects are able to estimate the wind direction and control their absolute egomotion (i.e., groundspeed). The egomotion estimation method that we have developed, which we call the opto-aeronautic algorithm, is tested in a variety of wind and ground slope conditions using a video recorded flight of a moth tracking a pheromone plume. Over all test cases that we examined, the algorithm achieved a mean absolute error in height of 7% or less. Furthermore, our algorithm is suitable for the navigation of aerial vehicles in environments where signals from the Global Positioning System are unavailable.

Four-dimensional dose distributions of step-and-shoot IMRT delivered with real-time tumor tracking for patients with irregular breathing: Constant dose rate vs dose rate regulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang Xiaocheng; Han-Oh, Sarah; Gui Minzhi

2012-09-15

Purpose: Dose-rate-regulated tracking (DRRT) is a tumor tracking strategy that programs the MLC to track the tumor under regular breathing and adapts to breathing irregularities during delivery using dose rate regulation. Constant-dose-rate tracking (CDRT) is a strategy that dynamically repositions the beam to account for intrafractional 3D target motion according to real-time information of target location obtained from an independent position monitoring system. The purpose of this study is to illustrate the differences in the effectiveness and delivery accuracy between these two tracking methods in the presence of breathing irregularities. Methods: Step-and-shoot IMRT plans optimized at a reference phase weremore » extended to remaining phases to generate 10-phased 4D-IMRT plans using segment aperture morphing (SAM) algorithm, where both tumor displacement and deformation were considered. A SAM-based 4D plan has been demonstrated to provide better plan quality than plans not considering target deformation. However, delivering such a plan requires preprogramming of the MLC aperture sequence. Deliveries of the 4D plans using DRRT and CDRT tracking approaches were simulated assuming the breathing period is either shorter or longer than the planning day, for 4 IMRT cases: two lung and two pancreatic cases with maximum GTV centroid motion greater than 1 cm were selected. In DRRT, dose rate was regulated to speed up or slow down delivery as needed such that each planned segment is delivered at the planned breathing phase. In CDRT, MLC is separately controlled to follow the tumor motion, but dose rate was kept constant. In addition to breathing period change, effect of breathing amplitude variation on target and critical tissue dose distribution is also evaluated. Results: Delivery of preprogrammed 4D plans by the CDRT method resulted in an average of 5% increase in target dose and noticeable increase in organs at risk (OAR) dose when patient breathing is either 10% faster or slower than the planning day. In contrast, DRRT method showed less than 1% reduction in target dose and no noticeable change in OAR dose under the same breathing period irregularities. When {+-}20% variation of target motion amplitude was present as breathing irregularity, the two delivery methods show compatible plan quality if the dose distribution of CDRT delivery is renormalized. Conclusions: Delivery of 4D-IMRT treatment plans, stemmed from 3D step-and-shoot IMRT and preprogrammed using SAM algorithm, is simulated for two dynamic MLC-based real-time tumor tracking strategies: with and without dose-rate regulation. Comparison of cumulative dose distribution indicates that the preprogrammed 4D plan is more accurately and efficiently conformed using the DRRT strategy, as it compensates the interplay between patient breathing irregularity and tracking delivery without compromising the segment-weight modulation.« less

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

PubMed Central

Filippeschi, Alessandro; Schmitz, Norbert; Miezal, Markus; Bleser, Gabriele; Ruffaldi, Emanuele; Stricker, Didier

2017-01-01

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error). PMID:28587178

Minimal time change detection algorithm for reconfigurable control system and application to aerospace

NASA Technical Reports Server (NTRS)

Kim, Sungwan

1994-01-01

System parameters should be tracked on-line to build a reconfigurable control system even though there exists an abrupt change. For this purpose, a new performance index that we are studying is the speed of adaptation- how quickly does the system determine that a change has occurred? In this paper, a new, robust algorithm that is optimized to minimize the time delay in detecting a change for fixed false alarm probability is proposed. Simulation results for the aircraft lateral motion with a known or unknown change in control gain matrices, in the presence of doublet input, indicate that the algorithm works fairly well. One of its distinguishing properties is that detection delay of this algorithm is superior to that of Whiteness Test.

Simulation evaluation of a low-altitude helicopter flight guidance system adapted for a helmet-mounted display

NASA Technical Reports Server (NTRS)

Swenson, Harry N.; Zelenka, Richard E.; Hardy, Gordon H.; Dearing, Munro G.

1992-01-01

A computer aiding concept for low-altitude helicopter flight was developed and evaluated in a real-time piloted simulation. The concept included an optimal control trajectory-generation algorithm based upon dynamic programming and a helmet-mounted display (HMD) presentation of a pathway-in-the-sky, a phantom aircraft, and flight-path vector/predictor guidance symbology. The trajectory-generation algorithm uses knowledge of the global mission requirements, a digital terrain map, aircraft performance capabilities, and advanced navigation information to determine a trajectory between mission way points that seeks valleys to minimize threat exposure. The pilot evaluation was conducted at NASA ARC moving base Vertical Motion Simulator (VMS) by pilots representing NASA, the U.S. Army, the Air Force, and the helicopter industry. The pilots manually tracked the trajectory generated by the algorithm utilizing the HMD symbology. The pilots were able to satisfactorily perform the tracking tasks while maintaining a high degree of awareness of the outside world.

Computer aiding for low-altitude helicopter flight

NASA Technical Reports Server (NTRS)

Swenson, Harry N.

1991-01-01

A computer-aiding concept for low-altitude helicopter flight was developed and evaluated in a real-time piloted simulation. The concept included an optimal control trajectory-generated algorithm based on dynamic programming, and a head-up display (HUD) presentation of a pathway-in-the-sky, a phantom aircraft, and flight-path vector/predictor symbol. The trajectory-generation algorithm uses knowledge of the global mission requirements, a digital terrain map, aircraft performance capabilities, and advanced navigation information to determine a trajectory between mission waypoints that minimizes threat exposure by seeking valleys. The pilot evaluation was conducted at NASA Ames Research Center's Sim Lab facility in both the fixed-base Interchangeable Cab (ICAB) simulator and the moving-base Vertical Motion Simulator (VMS) by pilots representing NASA, the U.S. Army, and the U.S. Air Force. The pilots manually tracked the trajectory generated by the algorithm utilizing the HUD symbology. They were able to satisfactorily perform the tracking tasks while maintaining a high degree of awareness of the outside world.

Tracking scanning laser ophthalmoscope (TSLO)

NASA Astrophysics Data System (ADS)

Hammer, Daniel X.; Ferguson, R. Daniel; Magill, John C.; White, Michael A.; Elsner, Ann E.; Webb, Robert H.

2003-07-01

The effectiveness of image stabilization with a retinal tracker in a multi-function, compact scanning laser ophthalmoscope (TSLO) was demonstrated in initial human subject tests. The retinal tracking system uses a confocal reflectometer with a closed loop optical servo system to lock onto features in the fundus. The system is modular to allow configuration for many research and clinical applications, including hyperspectral imaging, multifocal electroretinography (MFERG), perimetry, quantification of macular and photo-pigmentation, imaging of neovascularization and other subretinal structures (drusen, hyper-, and hypo-pigmentation), and endogenous fluorescence imaging. Optical hardware features include dual wavelength imaging and detection, integrated monochromator, higher-order motion control, and a stimulus source. The system software consists of a real-time feedback control algorithm and a user interface. Software enhancements include automatic bias correction, asymmetric feature tracking, image averaging, automatic track re-lock, and acquisition and logging of uncompressed images and video files. Normal adult subjects were tested without mydriasis to optimize the tracking instrumentation and to characterize imaging performance. The retinal tracking system achieves a bandwidth of greater than 1 kHz, which permits tracking at rates that greatly exceed the maximum rate of motion of the human eye. The TSLO stabilized images in all test subjects during ordinary saccades up to 500 deg/sec with an inter-frame accuracy better than 0.05 deg. Feature lock was maintained for minutes despite subject eye blinking. Successful frame averaging allowed image acquisition with decreased noise in low-light applications. The retinal tracking system significantly enhances the imaging capabilities of the scanning laser ophthalmoscope.

Biologically inspired computation and learning in Sensorimotor Systems

NASA Astrophysics Data System (ADS)

Lee, Daniel D.; Seung, H. S.

2001-11-01

Networking systems presently lack the ability to intelligently process the rich multimedia content of the data traffic they carry. Endowing artificial systems with the ability to adapt to changing conditions requires algorithms that can rapidly learn from examples. We demonstrate the application of such learning algorithms on an inexpensive quadruped robot constructed to perform simple sensorimotor tasks. The robot learns to track a particular object by discovering the salient visual and auditory cues unique to that object. The system uses a convolutional neural network that automatically combines color, luminance, motion, and auditory information. The weights of the networks are adjusted using feedback from a teacher to reflect the reliability of the various input channels in the surrounding environment. Additionally, the robot is able to compensate for its own motion by adapting the parameters of a vestibular ocular reflex system.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments.

PubMed

Wu, Paul P-Y; Campbell, Duncan; Merz, Torsten

2011-06-01

This paper presents Multi-Step A∗ (MSA∗), a search algorithm based on A∗ for multi-objective 4-D vehicle motion planning (three spatial and one time dimensions). The research is principally motivated by the need for offline and online motion planning for autonomous unmanned aerial vehicles (UAVs). For UAVs operating in large dynamic uncertain 4-D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and a grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles, and the rules of the air. It is shown that MSA∗ finds a cost optimal solution using variable length, angle, and velocity trajectory segments. These segments are approximated with a grid-based cell sequence that provides an inherent tolerance to uncertainty. The computational efficiency is achieved by using variable successor operators to create a multiresolution memory-efficient lattice sampling structure. The simulation studies on the UAV flight planning problem show that MSA∗ meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of a vector neighborhood-based A∗.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions

NASA Astrophysics Data System (ADS)

Zachiu, C.; Ries, M.; Ramaekers, P.; Guey, J.-L.; Moonen, C. T. W.; de Senneville, B. Denis

2017-10-01

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of  ˜1.5 mm and submillimeter precision. This, together with a computational performance of 20 images per second make the proposed method an attractive solution for real-time target tracking during US-guided clinical interventions.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions.

PubMed

Zachiu, C; Ries, M; Ramaekers, P; Guey, J-L; Moonen, C T W; de Senneville, B Denis

2017-10-04

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of  ∼1.5 mm and submillimeter precision. This, together with a computational performance of 20 images per second make the proposed method an attractive solution for real-time target tracking during US-guided clinical interventions.

A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors

PubMed Central

Mishra, Abhishek; Ghosh, Rohan; Principe, Jose C.; Thakor, Nitish V.; Kukreja, Sunil L.

2017-01-01

Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available. To address these limitations, in this paper we develop a technique for generalized motion segmentation based on spatial statistics across time frames. First, we create micromotion on the platform to facilitate the separation of static and dynamic elements of a scene, inspired by human saccadic eye movements. Second, we introduce the concept of spike-groups as a methodology to partition spatio-temporal event groups, which facilitates computation of scene statistics and characterize objects in it. Experimental results show that our algorithm is able to classify dynamic objects with a moving camera with maximum accuracy of 92%. PMID:28316563

Hand motion segmentation against skin colour background in breast awareness applications.

PubMed

Hu, Yuqin; Naguib, Raouf N G; Todman, Alison G; Amin, Saad A; Al-Omishy, Hassanein; Oikonomou, Andreas; Tucker, Nick

2004-01-01

Skin colour modelling and classification play significant roles in face and hand detection, recognition and tracking. A hand is an essential tool used in breast self-examination, which needs to be detected and analysed during the process of breast palpation. However, the background of a woman's moving hand is her breast that has the same or similar colour as the hand. Additionally, colour images recorded by a web camera are strongly affected by the lighting or brightness conditions. Hence, it is a challenging task to segment and track the hand against the breast without utilising any artificial markers, such as coloured nail polish. In this paper, a two-dimensional Gaussian skin colour model is employed in a particular way to identify a breast but not a hand. First, an input image is transformed to YCbCr colour space, which is less sensitive to the lighting conditions and more tolerant of skin tone. The breast, thus detected by the Gaussian skin model, is used as the baseline or framework for the hand motion. Secondly, motion cues are used to segment the hand motion against the detected baseline. Desired segmentation results have been achieved and the robustness of this algorithm is demonstrated in this paper.

Blind retrospective motion correction of MR images.

PubMed

Loktyushin, Alexander; Nickisch, Hannes; Pohmann, Rolf; Schölkopf, Bernhard

2013-12-01

Subject motion can severely degrade MR images. A retrospective motion correction algorithm, Gradient-based motion correction, which significantly reduces ghosting and blurring artifacts due to subject motion was proposed. The technique uses the raw data of standard imaging sequences; no sequence modifications or additional equipment such as tracking devices are required. Rigid motion is assumed. The approach iteratively searches for the motion trajectory yielding the sharpest image as measured by the entropy of spatial gradients. The vast space of motion parameters is efficiently explored by gradient-based optimization with a convergence guarantee. The method has been evaluated on both synthetic and real data in two and three dimensions using standard imaging techniques. MR images are consistently improved over different kinds of motion trajectories. Using a graphics processing unit implementation, computation times are in the order of a few minutes for a full three-dimensional volume. The presented technique can be an alternative or a complement to prospective motion correction methods and is able to improve images with strong motion artifacts from standard imaging sequences without requiring additional data. Copyright © 2013 Wiley Periodicals, Inc., a Wiley company.

SU-G-BRA-02: Development of a Learning Based Block Matching Algorithm for Ultrasound Tracking in Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shepard, A; Bednarz, B

Purpose: To develop an ultrasound learning-based tracking algorithm with the potential to provide real-time motion traces of anatomy-based fiducials that may aid in the effective delivery of external beam radiation. Methods: The algorithm was developed in Matlab R2015a and consists of two main stages: reference frame selection, and localized block matching. Immediately following frame acquisition, a normalized cross-correlation (NCC) similarity metric is used to determine a reference frame most similar to the current frame from a series of training set images that were acquired during a pretreatment scan. Segmented features in the reference frame provide the basis for the localizedmore » block matching to determine the feature locations in the current frame. The boundary points of the reference frame segmentation are used as the initial locations for the block matching and NCC is used to find the most similar block in the current frame. The best matched block locations in the current frame comprise the updated feature boundary. The algorithm was tested using five features from two sets of ultrasound patient data obtained from MICCAI 2014 CLUST. Due to the lack of a training set associated with the image sequences, the first 200 frames of the image sets were considered a valid training set for preliminary testing, and tracking was performed over the remaining frames. Results: Tracking of the five vessel features resulted in an average tracking error of 1.21 mm relative to predefined annotations. The average analysis rate was 15.7 FPS with analysis for one of the two patients reaching real-time speeds. Computations were performed on an i5-3230M at 2.60 GHz. Conclusion: Preliminary tests show tracking errors comparable with similar algorithms at close to real-time speeds. Extension of the work onto a GPU platform has the potential to achieve real-time performance, making tracking for therapy applications a feasible option. This work is partially funded by NIH grant R01CA190298.« less

Development of a robust and cost-effective 3D respiratory motion monitoring system using the kinect device: Accuracy comparison with the conventional stereovision navigation system.

PubMed

Bae, Myungsoo; Lee, Sangmin; Kim, Namkug

2018-07-01

To develop and validate a robust and cost-effective 3D respiratory monitoring system based on a Kinect device with a custom-made simple marker. A 3D respiratory monitoring system comprising the simple marker and the Microsoft Kinect v2 device was developed. The marker was designed for simple and robust detection, and the tracking algorithm was developed using the depth, RGB, and infra-red images acquired from the Kinect sensor. A Kalman filter was used to suppress movement noises. The major movements of the marker attached to the four different locations of body surface were determined from the initially collected tracking points of the marker while breathing. The signal level of respiratory motion with the tracking point was estimated along the major direction vector. The accuracy of the results was evaluated through a comparison with those of the conventional stereovision navigation system (NDI Polaris Spectra). Sixteen normal volunteers were enrolled to evaluate the accuracy of this system. The correlation coefficients between the respiratory motion signal from the Kinect device and conventional navigation system ranged from 0.970 to 0.999 and from 0.837 to 0.995 at the abdominal and thoracic surfaces, respectively. The respiratory motion signal from this system was obtained at 27-30 frames/s. This system with the Kinect v2 device and simple marker could be used for cost-effective, robust and accurate 3D respiratory motion monitoring. In addition, this system is as reliable for respiratory motion signal generation and as practically useful as the conventional stereovision navigation system and is less sensitive to patient posture. Copyright © 2018 Elsevier B.V. All rights reserved.

Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies.

PubMed

Peikon, Ian D; Fitzsimmons, Nathan A; Lebedev, Mikhail A; Nicolelis, Miguel A L

2009-06-15

Collection and analysis of limb kinematic data are essential components of the study of biological motion, including research into biomechanics, kinesiology, neurophysiology and brain-machine interfaces (BMIs). In particular, BMI research requires advanced, real-time systems capable of sampling limb kinematics with minimal contact to the subject's body. To answer this demand, we have developed an automated video tracking system for real-time tracking of multiple body parts in freely behaving primates. The system employs high-contrast markers painted on the animal's joints to continuously track the three-dimensional positions of their limbs during activity. Two-dimensional coordinates captured by each video camera are combined and converted to three-dimensional coordinates using a quadratic fitting algorithm. Real-time operation of the system is accomplished using direct memory access (DMA). The system tracks the markers at a rate of 52 frames per second (fps) in real-time and up to 100fps if video recordings are captured to be later analyzed off-line. The system has been tested in several BMI primate experiments, in which limb position was sampled simultaneously with chronic recordings of the extracellular activity of hundreds of cortical cells. During these recordings, multiple computational models were employed to extract a series of kinematic parameters from neuronal ensemble activity in real-time. The system operated reliably under these experimental conditions and was able to compensate for marker occlusions that occurred during natural movements. We propose that this system could also be extended to applications that include other classes of biological motion.

Using an external surrogate for predictor model training in real-time motion management of lung tumors.

PubMed

Rottmann, Joerg; Berbeco, Ross

2014-12-01

Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal-external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of 8 s and history vector length of 3 s achieve maximal performance. Sampling frequency appears to have little impact on performance confirming previously published work. By using the linear predictor, a relative geometric 3D error reduction of about 50% was achieved (using adaptive retraining, a history vector length of 3 s and with results averaged over all investigated lookahead times and signal sampling frequencies). The absolute mean error could be reduced from (2.0 ± 1.6) mm when using no prediction at all to (0.9 ± 0.8) mm and (1.0 ± 0.9) mm when using the predictor trained with internal tumor motion training data and external surrogate motion training data, respectively (for a typical lookahead time of 250 ms and sampling frequency of 15 Hz). A linear prediction model can reduce latency induced tracking errors by an average of about 50% in real-time image guided radiotherapy systems with system latencies of up to 300 ms. Training a linear model for lung tumor motion prediction with an external surrogate signal alone is feasible and results in similar performance as training with (internal) tumor motion. Particularly for scenarios where motion data are extracted from fluoroscopic imaging with ionizing radiation, this may alleviate the need for additional imaging dose during the collection of model training data.

A rigid motion correction method for helical computed tomography (CT)

NASA Astrophysics Data System (ADS)

Kim, J.-H.; Nuyts, J.; Kyme, A.; Kuncic, Z.; Fulton, R.

2015-03-01

We propose a method to compensate for six degree-of-freedom rigid motion in helical CT of the head. The method is demonstrated in simulations and in helical scans performed on a 16-slice CT scanner. Scans of a Hoffman brain phantom were acquired while an optical motion tracking system recorded the motion of the bed and the phantom. Motion correction was performed by restoring projection consistency using data from the motion tracking system, and reconstructing with an iterative fully 3D algorithm. Motion correction accuracy was evaluated by comparing reconstructed images with a stationary reference scan. We also investigated the effects on accuracy of tracker sampling rate, measurement jitter, interpolation of tracker measurements, and the synchronization of motion data and CT projections. After optimization of these aspects, motion corrected images corresponded remarkably closely to images of the stationary phantom with correlation and similarity coefficients both above 0.9. We performed a simulation study using volunteer head motion and found similarly that our method is capable of compensating effectively for realistic human head movements. To the best of our knowledge, this is the first practical demonstration of generalized rigid motion correction in helical CT. Its clinical value, which we have yet to explore, may be significant. For example it could reduce the necessity for repeat scans and resource-intensive anesthetic and sedation procedures in patient groups prone to motion, such as young children. It is not only applicable to dedicated CT imaging, but also to hybrid PET/CT and SPECT/CT, where it could also ensure an accurate CT image for lesion localization and attenuation correction of the functional image data.

Derivation of cloud-free-region atmospheric motion vectors from FY-2E thermal infrared imagery

NASA Astrophysics Data System (ADS)

Wang, Zhenhui; Sui, Xinxiu; Zhang, Qing; Yang, Lu; Zhao, Hang; Tang, Min; Zhan, Yizhe; Zhang, Zhiguo

2017-02-01

The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors (AMVs) in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference (NEdT) performance of FY-2E split window (10.3-11.5 μm, 11.6-12.8 μm) channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference (SD) methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the "truth". The results show that all three algorithms, though not perfect in some cases, generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 hPa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.

Dynamic displacement measurement of large-scale structures based on the Lucas-Kanade template tracking algorithm

NASA Astrophysics Data System (ADS)

Guo, Jie; Zhu, Chang`an

2016-01-01

The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas-Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.

A neural-based remote eye gaze tracker under natural head motion.

PubMed

Torricelli, Diego; Conforto, Silvia; Schmid, Maurizio; D'Alessio, Tommaso

2008-10-01

A novel approach to view-based eye gaze tracking for human computer interface (HCI) is presented. The proposed method combines different techniques to address the problems of head motion, illumination and usability in the framework of low cost applications. Feature detection and tracking algorithms have been designed to obtain an automatic setup and strengthen the robustness to light conditions. An extensive analysis of neural solutions has been performed to deal with the non-linearity associated with gaze mapping under free-head conditions. No specific hardware, such as infrared illumination or high-resolution cameras, is needed, rather a simple commercial webcam working in visible light spectrum suffices. The system is able to classify the gaze direction of the user over a 15-zone graphical interface, with a success rate of 95% and a global accuracy of around 2 degrees , comparable with the vast majority of existing remote gaze trackers.

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Liu, Hao; Zhu, Xiaocong

2014-07-01

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller which can compensate the friction force in the cylinder.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rottmann, Joerg; Berbeco, Ross

Purpose: Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. Methods: The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable tomore » overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal–external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Results: Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of 8 s and history vector length of 3 s achieve maximal performance. Sampling frequency appears to have little impact on performance confirming previously published work. By using the linear predictor, a relative geometric 3D error reduction of about 50% was achieved (using adaptive retraining, a history vector length of 3 s and with results averaged over all investigated lookahead times and signal sampling frequencies). The absolute mean error could be reduced from (2.0 ± 1.6) mm when using no prediction at all to (0.9 ± 0.8) mm and (1.0 ± 0.9) mm when using the predictor trained with internal tumor motion training data and external surrogate motion training data, respectively (for a typical lookahead time of 250 ms and sampling frequency of 15 Hz). Conclusions: A linear prediction model can reduce latency induced tracking errors by an average of about 50% in real-time image guided radiotherapy systems with system latencies of up to 300 ms. Training a linear model for lung tumor motion prediction with an external surrogate signal alone is feasible and results in similar performance as training with (internal) tumor motion. Particularly for scenarios where motion data are extracted from fluoroscopic imaging with ionizing radiation, this may alleviate the need for additional imaging dose during the collection of model training data.« less

Infrared Submillimeter and Radio Astronomy Research and Analysis Program

NASA Technical Reports Server (NTRS)

Traub, Wesley A.

2000-01-01

This program entitled "Infrared Submillimeter and Radio Astronomy Research and Analysis Program" with NASA-Ames Research Center (ARC) was proposed by the Smithsonian Astrophysical Observatory (SAO) to cover three years. Due to funding constraints only the first year installment of $18,436 was funded, but this funding was spread out over two years to try to maximize the benefit to the program. During the tenure of this contact, the investigators at the SAO, Drs. Wesley A. Traub and Nathaniel P. Carleton, worked with the investigators at ARC, Drs. Jesse Bregman and Fred Wittebom, on the following three main areas: 1. Rapid scanning SAO and ARC collaborated on purchasing and constructing a Rapid Scan Platform for the delay arm of the Infrared-Optical Telescope Array (IOTA) interferometer on Mt. Hopkins, Arizona. The Rapid Scan Platform was tested and improved by the addition of stiffening plates which eliminated a very small but noticeable bending of the metal platform at the micro-meter level. 2. Star tracking Bregman and Wittebom conducted a study of the IOTA CCD-based star tracker system, by constructing a device to simulate star motion having a specified frequency and amplitude of motion, and by examining the response of the tracker to this simulated star input. 3. Fringe tracking. ARC, and in particular Dr. Robert Mah, developed a fringe-packet tracking algorithm, based on data that Bregman and Witteborn obtained on IOTA. The algorithm was tested in the laboratory at ARC, and found to work well for both strong and weak fringes.

Evaluation of Rigid-Body Motion Compensation in Cardiac Perfusion SPECT Employing Polar-Map Quantification

PubMed Central

Pretorius, P. Hendrik; Johnson, Karen L.; King, Michael A.

2016-01-01

We have recently been successful in the development and testing of rigid-body motion tracking, estimation and compensation for cardiac perfusion SPECT based on a visual tracking system (VTS). The goal of this study was to evaluate in patients the effectiveness of our rigid-body motion compensation strategy. Sixty-four patient volunteers were asked to remain motionless or execute some predefined body motion during an additional second stress perfusion acquisition. Acquisitions were performed using the standard clinical protocol with 64 projections acquired through 180 degrees. All data were reconstructed with an ordered-subsets expectation-maximization (OSEM) algorithm using 4 projections per subset and 5 iterations. All physical degradation factors were addressed (attenuation, scatter, and distance dependent resolution), while a 3-dimensional Gaussian rotator was used during reconstruction to correct for six-degree-of-freedom (6-DOF) rigid-body motion estimated by the VTS. Polar map quantification was employed to evaluate compensation techniques. In 54.7% of the uncorrected second stress studies there was a statistically significant difference in the polar maps, and in 45.3% this made a difference in the interpretation of segmental perfusion. Motion correction reduced the impact of motion such that with it 32.8 % of the polar maps were statistically significantly different, and in 14.1% this difference changed the interpretation of segmental perfusion. The improvement shown in polar map quantitation translated to visually improved uniformity of the SPECT slices. PMID:28042170

Initial assessment of facial nerve paralysis based on motion analysis using an optical flow method.

PubMed

Samsudin, Wan Syahirah W; Sundaraj, Kenneth; Ahmad, Amirozi; Salleh, Hasriah

2016-01-01

An initial assessment method that can classify as well as categorize the severity of paralysis into one of six levels according to the House-Brackmann (HB) system based on facial landmarks motion using an Optical Flow (OF) algorithm is proposed. The desired landmarks were obtained from the video recordings of 5 normal and 3 Bell's Palsy subjects and tracked using the Kanade-Lucas-Tomasi (KLT) method. A new scoring system based on the motion analysis using area measurement is proposed. This scoring system uses the individual scores from the facial exercises and grades the paralysis based on the HB system. The proposed method has obtained promising results and may play a pivotal role towards improved rehabilitation programs for patients.

Efficient integration of spectral features for vehicle tracking utilizing an adaptive sensor

NASA Astrophysics Data System (ADS)

Uzkent, Burak; Hoffman, Matthew J.; Vodacek, Anthony

2015-03-01

Object tracking in urban environments is an important and challenging problem that is traditionally tackled using visible and near infrared wavelengths. By inserting extended data such as spectral features of the objects one can improve the reliability of the identification process. However, huge increase in data created by hyperspectral imaging is usually prohibitive. To overcome the complexity problem, we propose a persistent air-to-ground target tracking system inspired by a state-of-the-art, adaptive, multi-modal sensor. The adaptive sensor is capable of providing panchromatic images as well as the spectra of desired pixels. This addresses the data challenge of hyperspectral tracking by only recording spectral data as needed. Spectral likelihoods are integrated into a data association algorithm in a Bayesian fashion to minimize the likelihood of misidentification. A framework for controlling spectral data collection is developed by incorporating motion segmentation information and prior information from a Gaussian Sum filter (GSF) movement predictions from a multi-model forecasting set. An intersection mask of the surveillance area is extracted from OpenStreetMap source and incorporated into the tracking algorithm to perform online refinement of multiple model set. The proposed system is tested using challenging and realistic scenarios generated in an adverse environment.

Deterministic object tracking using Gaussian ringlet and directional edge features

NASA Astrophysics Data System (ADS)

Krieger, Evan W.; Sidike, Paheding; Aspiras, Theus; Asari, Vijayan K.

2017-10-01

Challenges currently existing for intensity-based histogram feature tracking methods in wide area motion imagery (WAMI) data include object structural information distortions, background variations, and object scale change. These issues are caused by different pavement or ground types and from changing the sensor or altitude. All of these challenges need to be overcome in order to have a robust object tracker, while attaining a computation time appropriate for real-time processing. To achieve this, we present a novel method, Directional Ringlet Intensity Feature Transform (DRIFT), which employs Kirsch kernel filtering for edge features and a ringlet feature mapping for rotational invariance. The method also includes an automatic scale change component to obtain accurate object boundaries and improvements for lowering computation times. We evaluated the DRIFT algorithm on two challenging WAMI datasets, namely Columbus Large Image Format (CLIF) and Large Area Image Recorder (LAIR), to evaluate its robustness and efficiency. Additional evaluations on general tracking video sequences are performed using the Visual Tracker Benchmark and Visual Object Tracking 2014 databases to demonstrate the algorithms ability with additional challenges in long complex sequences including scale change. Experimental results show that the proposed approach yields competitive results compared to state-of-the-art object tracking methods on the testing datasets.

Scene-Aware Adaptive Updating for Visual Tracking via Correlation Filters

PubMed Central

Zhang, Sirou; Qiao, Xiaoya

2017-01-01

In recent years, visual object tracking has been widely used in military guidance, human-computer interaction, road traffic, scene monitoring and many other fields. The tracking algorithms based on correlation filters have shown good performance in terms of accuracy and tracking speed. However, their performance is not satisfactory in scenes with scale variation, deformation, and occlusion. In this paper, we propose a scene-aware adaptive updating mechanism for visual tracking via a kernel correlation filter (KCF). First, a low complexity scale estimation method is presented, in which the corresponding weight in five scales is employed to determine the final target scale. Then, the adaptive updating mechanism is presented based on the scene-classification. We classify the video scenes as four categories by video content analysis. According to the target scene, we exploit the adaptive updating mechanism to update the kernel correlation filter to improve the robustness of the tracker, especially in scenes with scale variation, deformation, and occlusion. We evaluate our tracker on the CVPR2013 benchmark. The experimental results obtained with the proposed algorithm are improved by 33.3%, 15%, 6%, 21.9% and 19.8% compared to those of the KCF tracker on the scene with scale variation, partial or long-time large-area occlusion, deformation, fast motion and out-of-view. PMID:29140311

Real-time WAMI streaming target tracking in fog

NASA Astrophysics Data System (ADS)

Chen, Yu; Blasch, Erik; Chen, Ning; Deng, Anna; Ling, Haibin; Chen, Genshe

2016-05-01

Real-time information fusion based on WAMI (Wide-Area Motion Imagery), FMV (Full Motion Video), and Text data is highly desired for many mission critical emergency or security applications. Cloud Computing has been considered promising to achieve big data integration from multi-modal sources. In many mission critical tasks, however, powerful Cloud technology cannot satisfy the tight latency tolerance as the servers are allocated far from the sensing platform, actually there is no guaranteed connection in the emergency situations. Therefore, data processing, information fusion, and decision making are required to be executed on-site (i.e., near the data collection). Fog Computing, a recently proposed extension and complement for Cloud Computing, enables computing on-site without outsourcing jobs to a remote Cloud. In this work, we have investigated the feasibility of processing streaming WAMI in the Fog for real-time, online, uninterrupted target tracking. Using a single target tracking algorithm, we studied the performance of a Fog Computing prototype. The experimental results are very encouraging that validated the effectiveness of our Fog approach to achieve real-time frame rates.

TH-AB-202-03: A Novel Tool for Computing Deliverable Doses in Dynamic MLC Tracking Treatments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fast, M; Kamerling, C; Menten, M

2016-06-15

Purpose: In tracked dynamic multi-leaf collimator (MLC) treatments, segments are continuously adapted to the target centroid motion in beams-eye-view. On-the-fly segment adaptation, however, potentially induces dosimetric errors due to the finite MLC leaf width and non-rigid target motion. In this study, we outline a novel tool for computing the 4d dose of lung SBRT plans delivered with MLC tracking. Methods: The following automated workflow was developed: A) centroid tracking, where the initial segments are morphed to each 4dCT phase based on the beams-eye-view GTV shift (followed by a dose calculation on each phase); B) re-optimized tracking, in which all morphedmore » initial plans from (A) are further optimised (“warm-started”) in each 4dCT phase using the initial optimisation parameters but phase-specific volume definitions. Finally, both dose sets are accumulated to the reference phase using deformable image registration. Initial plans were generated according to the RTOG-1021 guideline (54Gy, 3-Fx, equidistant 9-beam IMRT) on the peak-exhale (reference) phase of a phase-binned 4dCT. Treatment planning and delivery simulations were performed in RayStation (research v4.6) using our in-house segment-morphing algorithm, which directly links to RayStation through a native C++ interface. Results: Computing the tracking plans and 4d dose distributions via the in-house interface takes 5 and 8 minutes respectively for centroid and re-optimized tracking. For a sample lung SBRT patient with 14mm peak-to-peak motion in sup-inf direction, mainly perpendicular leaf motion (0-collimator) resulted in small dose changes for PTV-D95 (−13cGy) and GTV-D98 (+18cGy) for the centroid tracking case compared to the initial plan. Modest reductions of OAR doses (e.g. spinal cord D2: −11cGy) were achieved in the idealized tracking case. Conclusion: This study presents an automated “1-click” workflow for computing deliverable MLC tracking doses in RayStation. Adding a non-deliverable re-optimized tracking scenario is expected to help quantify plan robustness for more challenging patients with anatomy deformations. We acknowledge support of the MLC tracking research from Elekta AB. MFF is supported by Cancer Research UK under Programme C33589/A19908. Research at ICR is also supported by Cancer Research UK under Programme C33589/A19727 and NHS funding to the NIHR Biomedical Research Centre at RMH and ICR.« less

Virtual remote center of motion control for needle placement robots.

PubMed

Boctor, Emad M; Webster, Robert J; Mathieu, Herve; Okamura, Allison M; Fichtinger, Gabor

2004-01-01

We present an algorithm that enables percutaneous needle-placement procedures to be performed with unencoded, unregistered, minimally calibrated robots while removing the constraint of placing the needle tip on a mechanically enforced Remote Center of Motion (RCM). The algorithm requires only online tracking of the surgical tool and a five-degree-of-freedom (5-DOF) robot comprising three prismatic DOF and two rotational DOF. An incremental adaptive motion control cycle guides the needle to the insertion point and also orients it to align with the target-entry-point line. The robot executes RCM motion without having a physically constrained fulcrum point. The proof-of-concept prototype system achieved 0.78 mm translation accuracy and 1.4 degrees rotational accuracy (this is within the tracker accuracy) within 17 iterative steps (0.5-1 s). This research enables robotic assistant systems for image-guided percutaneous procedures to be prototyped/constructed more quickly and less expensively than has been previously possible. Since the clinical utility of such systems is clear and has been demonstrated in the literature, our work may help promote widespread clinical adoption of this technology by lowering system cost and complexity.

Complex differential variance angiography with noise-bias correction for optical coherence tomography of the retina

PubMed Central

Braaf, Boy; Donner, Sabine; Nam, Ahhyun S.; Bouma, Brett E.; Vakoc, Benjamin J.

2018-01-01

Complex differential variance (CDV) provides phase-sensitive angiographic imaging for optical coherence tomography (OCT) with immunity to phase-instabilities of the imaging system and small-scale axial bulk motion. However, like all angiographic methods, measurement noise can result in erroneous indications of blood flow that confuse the interpretation of angiographic images. In this paper, a modified CDV algorithm that corrects for this noise-bias is presented. This is achieved by normalizing the CDV signal by analytically derived upper and lower limits. The noise-bias corrected CDV algorithm was implemented into an experimental 1 μm wavelength OCT system for retinal imaging that used an eye tracking scanner laser ophthalmoscope at 815 nm for compensation of lateral eye motions. The noise-bias correction improved the CDV imaging of the blood flow in tissue layers with a low signal-to-noise ratio and suppressed false indications of blood flow outside the tissue. In addition, the CDV signal normalization suppressed noise induced by galvanometer scanning errors and small-scale lateral motion. High quality cross-section and motion-corrected en face angiograms of the retina and choroid are presented. PMID:29552388

Complex differential variance angiography with noise-bias correction for optical coherence tomography of the retina.

PubMed

Braaf, Boy; Donner, Sabine; Nam, Ahhyun S; Bouma, Brett E; Vakoc, Benjamin J

2018-02-01

Complex differential variance (CDV) provides phase-sensitive angiographic imaging for optical coherence tomography (OCT) with immunity to phase-instabilities of the imaging system and small-scale axial bulk motion. However, like all angiographic methods, measurement noise can result in erroneous indications of blood flow that confuse the interpretation of angiographic images. In this paper, a modified CDV algorithm that corrects for this noise-bias is presented. This is achieved by normalizing the CDV signal by analytically derived upper and lower limits. The noise-bias corrected CDV algorithm was implemented into an experimental 1 μm wavelength OCT system for retinal imaging that used an eye tracking scanner laser ophthalmoscope at 815 nm for compensation of lateral eye motions. The noise-bias correction improved the CDV imaging of the blood flow in tissue layers with a low signal-to-noise ratio and suppressed false indications of blood flow outside the tissue. In addition, the CDV signal normalization suppressed noise induced by galvanometer scanning errors and small-scale lateral motion. High quality cross-section and motion-corrected en face angiograms of the retina and choroid are presented.

An orbital emulator for pursuit-evasion game theoretic sensor management

NASA Astrophysics Data System (ADS)

Shen, Dan; Wang, Tao; Wang, Gang; Jia, Bin; Wang, Zhonghai; Chen, Genshe; Blasch, Erik; Pham, Khanh

2017-05-01

This paper develops and evaluates an orbital emulator (OE) for space situational awareness (SSA). The OE can produce 3D satellite movements using capabilities generated from omni-wheeled robot and robotic arm motion methods. The 3D motion of a satellite is partitioned into the movements in the equatorial plane and the up-down motions in the vertical plane. The 3D actions are emulated by omni-wheeled robot models while the up-down motions are performed by a stepped-motor-controlled-ball along a rod (robotic arm), which is attached to the robot. For multiple satellites, a fast map-merging algorithm is integrated into the robot operating system (ROS) and simultaneous localization and mapping (SLAM) routines to locate the multiple robots in the scene. The OE is used to demonstrate a pursuit-evasion (PE) game theoretic sensor management algorithm, which models conflicts between a space-based-visible (SBV) satellite (as pursuer) and a geosynchronous (GEO) satellite (as evader). The cost function of the PE game is based on the informational entropy of the SBV-tracking-GEO scenario. GEO can maneuver using a continuous and low thruster. The hard-in-loop space emulator visually illustrates the SSA problem solution based PE game.

Performance evaluations of demons and free form deformation algorithms for the liver region.

PubMed

Wang, Hui; Gong, Guanzhong; Wang, Hongjun; Li, Dengwang; Yin, Yong; Lu, Jie

2014-04-01

We investigated the influence of breathing motion on radiation therapy according to four- dimensional computed tomography (4D-CT) technology and indicated the registration of 4D-CT images was significant. The demons algorithm in two interpolation modes was compared to the FFD model algorithm to register the different phase images of 4D-CT in tumor tracking, using iodipin as verification. Linear interpolation was used in both mode 1 and mode 2. Mode 1 set outside pixels to nearest pixel, while mode 2 set outside pixels to zero. We used normalized mutual information (NMI), sum of squared differences, modified Hausdorff-distance, and registration speed to evaluate the performance of each algorithm. The average NMI after demons registration method in mode 1 improved 1.76% and 4.75% when compared to mode 2 and FFD model algorithm, respectively. Further, the modified Hausdorff-distance was no different between demons modes 1 and 2, but mode 1 was 15.2% lower than FFD. Finally, demons algorithm has the absolute advantage in registration speed. The demons algorithm in mode 1 was therefore found to be much more suitable for the registration of 4D-CT images. The subtractions of floating images and reference image before and after registration by demons further verified that influence of breathing motion cannot be ignored and the demons registration method is feasible.

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging

PubMed Central

Cho, Youngjun; Julier, Simon J.; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-01-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area. PMID:29082079

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging.

PubMed

Cho, Youngjun; Julier, Simon J; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-10-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area.

KOLAM: a cross-platform architecture for scalable visualization and tracking in wide-area imagery

NASA Astrophysics Data System (ADS)

Fraser, Joshua; Haridas, Anoop; Seetharaman, Guna; Rao, Raghuveer M.; Palaniappan, Kannappan

2013-05-01

KOLAM is an open, cross-platform, interoperable, scalable and extensible framework supporting a novel multi- scale spatiotemporal dual-cache data structure for big data visualization and visual analytics. This paper focuses on the use of KOLAM for target tracking in high-resolution, high throughput wide format video also known as wide-area motion imagery (WAMI). It was originally developed for the interactive visualization of extremely large geospatial imagery of high spatial and spectral resolution. KOLAM is platform, operating system and (graphics) hardware independent, and supports embedded datasets scalable from hundreds of gigabytes to feasibly petabytes in size on clusters, workstations, desktops and mobile computers. In addition to rapid roam, zoom and hyper- jump spatial operations, a large number of simultaneously viewable embedded pyramid layers (also referred to as multiscale or sparse imagery), interactive colormap and histogram enhancement, spherical projection and terrain maps are supported. The KOLAM software architecture was extended to support airborne wide-area motion imagery by organizing spatiotemporal tiles in very large format video frames using a temporal cache of tiled pyramid cached data structures. The current version supports WAMI animation, fast intelligent inspection, trajectory visualization and target tracking (digital tagging); the latter by interfacing with external automatic tracking software. One of the critical needs for working with WAMI is a supervised tracking and visualization tool that allows analysts to digitally tag multiple targets, quickly review and correct tracking results and apply geospatial visual analytic tools on the generated trajectories. One-click manual tracking combined with multiple automated tracking algorithms are available to assist the analyst and increase human effectiveness.

Track-Before-Detect Algorithm for Faint Moving Objects based on Random Sampling and Consensus

NASA Astrophysics Data System (ADS)

Dao, P.; Rast, R.; Schlaegel, W.; Schmidt, V.; Dentamaro, A.

2014-09-01

There are many algorithms developed for tracking and detecting faint moving objects in congested backgrounds. One obvious application is detection of targets in images where each pixel corresponds to the received power in a particular location. In our application, a visible imager operated in stare mode observes geostationary objects as fixed, stars as moving and non-geostationary objects as drifting in the field of view. We would like to achieve high sensitivity detection of the drifters. The ability to improve SNR with track-before-detect (TBD) processing, where target information is collected and collated before the detection decision is made, allows respectable performance against dim moving objects. Generally, a TBD algorithm consists of a pre-processing stage that highlights potential targets and a temporal filtering stage. However, the algorithms that have been successfully demonstrated, e.g. Viterbi-based and Bayesian-based, demand formidable processing power and memory. We propose an algorithm that exploits the quasi constant velocity of objects, the predictability of the stellar clutter and the intrinsically low false alarm rate of detecting signature candidates in 3-D, based on an iterative method called "RANdom SAmple Consensus” and one that can run real-time on a typical PC. The technique is tailored for searching objects with small telescopes in stare mode. Our RANSAC-MT (Moving Target) algorithm estimates parameters of a mathematical model (e.g., linear motion) from a set of observed data which contains a significant number of outliers while identifying inliers. In the pre-processing phase, candidate blobs were selected based on morphology and an intensity threshold that would normally generate unacceptable level of false alarms. The RANSAC sampling rejects candidates that conform to the predictable motion of the stars. Data collected with a 17 inch telescope by AFRL/RH and a COTS lens/EM-CCD sensor by the AFRL/RD Satellite Assessment Center is used to assess the performance of the algorithm. In the second application, a visible imager operated in sidereal mode observes geostationary objects as moving, stars as fixed except for field rotation, and non-geostationary objects as drifting. RANSAC-MT is used to detect the drifter. In this set of data, the drifting space object was detected at a distance of 13800 km. The AFRL/RH set of data, collected in the stare mode, contained the signature of two geostationary satellites. The signature of a moving object was simulated and added to the sequence of frames to determine the sensitivity in magnitude. The performance compares well with the more intensive TBD algorithms reported in the literature.

Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis

PubMed Central

Dehghan, Ehsan; Moradi, Mehdi; Wen, Xu; French, Danny; Lobo, Julio; Morris, W. James; Salcudean, Septimiu E.; Fichtinger, Gabor

2011-01-01

Purpose: Accurate localization of prostate implants from several C-arm images is necessary for ultrasound-fluoroscopy fusion and intraoperative dosimetry. The authors propose a computational motion compensation method for tomosynthesis-based reconstruction that enables 3D localization of prostate implants from C-arm images despite C-arm oscillation and sagging. Methods: Five C-arm images are captured by rotating the C-arm around its primary axis, while measuring its rotation angle using a protractor or the C-arm joint encoder. The C-arm images are processed to obtain binary seed-only images from which a volume of interest is reconstructed. The motion compensation algorithm, iteratively, compensates for 2D translational motion of the C-arm by maximizing the number of voxels that project on a seed projection in all of the images. This obviates the need for C-arm full pose tracking traditionally implemented using radio-opaque fiducials or external trackers. The proposed reconstruction method is tested in simulations, in a phantom study and on ten patient data sets. Results: In a phantom implanted with 136 dummy seeds, the seed detection rate was 100% with a localization error of 0.86 ± 0.44 mm (Mean ± STD) compared to CT. For patient data sets, a detection rate of 99.5% was achieved in approximately 1 min per patient. The reconstruction results for patient data sets were compared against an available matching-based reconstruction method and showed relative localization difference of 0.5 ± 0.4 mm. Conclusions: The motion compensation method can successfully compensate for large C-arm motion without using radio-opaque fiducial or external trackers. Considering the efficacy of the algorithm, its successful reconstruction rate and low computational burden, the algorithm is feasible for clinical use. PMID:21992346

A hybrid smartphone indoor positioning solution for mobile LBS.

PubMed

Liu, Jingbin; Chen, Ruizhi; Pei, Ling; Guinness, Robert; Kuusniemi, Heidi

2012-12-12

Smartphone positioning is an enabling technology used to create new business in the navigation and mobile location-based services (LBS) industries. This paper presents a smartphone indoor positioning engine named HIPE that can be easily integrated with mobile LBS. HIPE is a hybrid solution that fuses measurements of smartphone sensors with wireless signals. The smartphone sensors are used to measure the user's motion dynamics information (MDI), which represent the spatial correlation of various locations. Two algorithms based on hidden Markov model (HMM) problems, the grid-based filter and the Viterbi algorithm, are used in this paper as the central processor for data fusion to resolve the position estimates, and these algorithms are applicable for different applications, e.g., real-time navigation and location tracking, respectively. HIPE is more widely applicable for various motion scenarios than solutions proposed in previous studies because it uses no deterministic motion models, which have been commonly used in previous works. The experimental results showed that HIPE can provide adequate positioning accuracy and robustness for different scenarios of MDI combinations. HIPE is a cost-efficient solution, and it can work flexibly with different smartphone platforms, which may have different types of sensors available for the measurement of MDI data. The reliability of the positioning solution was found to increase with increasing precision of the MDI data.

Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions

PubMed Central

Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Mª; de la Escalera, Arturo

2010-01-01

The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle. PMID:22163639

Identifying and tracking pedestrians based on sensor fusion and motion stability predictions.

PubMed

Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Maria; de la Escalera, Arturo

2010-01-01

The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.

Particle tracking in drug and gene delivery research: State-of-the-art applications and methods.

PubMed

Schuster, Benjamin S; Ensign, Laura M; Allan, Daniel B; Suk, Jung Soo; Hanes, Justin

2015-08-30

Particle tracking is a powerful microscopy technique to quantify the motion of individual particles at high spatial and temporal resolution in complex fluids and biological specimens. Particle tracking's applications and impact in drug and gene delivery research have greatly increased during the last decade. Thanks to advances in hardware and software, this technique is now more accessible than ever, and can be reliably automated to enable rapid processing of large data sets, thereby further enhancing the role that particle tracking will play in drug and gene delivery studies in the future. We begin this review by discussing particle tracking-based advances in characterizing extracellular and cellular barriers to therapeutic nanoparticles and in characterizing nanoparticle size and stability. To facilitate wider adoption of the technique, we then present a user-friendly review of state-of-the-art automated particle tracking algorithms and methods of analysis. We conclude by reviewing technological developments for next-generation particle tracking methods, and we survey future research directions in drug and gene delivery where particle tracking may be useful. Copyright © 2015 Elsevier B.V. All rights reserved.

Visual Persons Behavior Diary Generation Model based on Trajectories and Pose Estimation

NASA Astrophysics Data System (ADS)

Gang, Chen; Bin, Chen; Yuming, Liu; Hui, Li

2018-03-01

The behavior pattern of persons was the important output of the surveillance analysis. This paper focus on the generation model of visual person behavior diary. The pipeline includes the person detection, tracking, and the person behavior classify. This paper adopts the deep convolutional neural model YOLO (You Only Look Once)V2 for person detection module. Multi person tracking was based on the detection framework. The Hungarian assignment algorithm was used to the matching. The person appearance model was integrated by HSV color model and Hash code model. The person object motion was estimated by the Kalman Filter. The multi objects were matching with exist tracklets through the appearance and motion location distance by the Hungarian assignment method. A long continuous trajectory for one person was get by the spatial-temporal continual linking algorithm. And the face recognition information was used to identify the trajectory. The trajectories with identification information can be used to generate the visual diary of person behavior based on the scene context information and person action estimation. The relevant modules are tested in public data sets and our own capture video sets. The test results show that the method can be used to generate the visual person behavior pattern diary with certain accuracy.

Modeling and optimization of a time-resolved proton radiographic imaging system for proton cancer treatment

NASA Astrophysics Data System (ADS)

Han, Bin

This dissertation describes a research project to test the clinical utility of a time-resolved proton radiographic (TRPR) imaging system by performing comprehensive Monte Carlo simulations of a physical device coupled with realistic lung cancer patient anatomy defined by 4DCT for proton therapy. A time-resolved proton radiographic imaging system was modeled through Monte Carlo simulations. A particle-tracking feature was employed to evaluate the performance of the proton imaging system, especially in its ability to visualize and quantify proton range variations during respiration. The Most Likely Path (MLP) algorithm was developed to approximate the multiple Coulomb scattering paths of protons for the purpose of image reconstruction. Spatial resolution of ˜ 1 mm and range resolution of 1.3% of the total range were achieved using the MLP algorithm. Time-resolved proton radiographs of five patient cases were reconstructed to track tumor motion and to calculate water equivalent length variations. By comparing with direct 4DCT measurement, the accuracy of tumor tracking was found to be better than 2 mm in five patient cases. Utilizing tumor tracking information to reduce margins to the planning target volume, a gated treatment plan was compared with un-gated treatment plan. The equivalent uniform dose (EUD) and the normal tissue complication probability (NTCP) were used to quantify the gain in the quality of treatments. The EUD of the OARs was found to be reduced up to 11% and the corresponding NTCP of organs at risk (OARs) was found to be reduced up to 16.5%. These results suggest that, with image guidance by proton radiography, dose to OARs can be reduced and the corresponding NTCPs can be significantly reduced. The study concludes that the proton imaging system can accurately track the motion of the tumor and detect the WEL variations, leading to potential gains in using image-guided proton radiography for lung cancer treatments.

Lightweight biometric detection system for human classification using pyroelectric infrared detectors.

PubMed

Burchett, John; Shankar, Mohan; Hamza, A Ben; Guenther, Bob D; Pitsianis, Nikos; Brady, David J

2006-05-01

We use pyroelectric detectors that are differential in nature to detect motion in humans by their heat emissions. Coded Fresnel lens arrays create boundaries that help to localize humans in space as well as to classify the nature of their motion. We design and implement a low-cost biometric tracking system by using off-the-shelf components. We demonstrate two classification methods by using data gathered from sensor clusters of dual-element pyroelectric detectors with coded Fresnel lens arrays. We propose two algorithms for person identification, a more generalized spectral clustering method and a more rigorous example that uses principal component regression to perform a blind classification.

Optimal Predictive Control for Path Following of a Full Drive-by-Wire Vehicle at Varying Speeds

NASA Astrophysics Data System (ADS)

SONG, Pan; GAO, Bolin; XIE, Shugang; FANG, Rui

2017-05-01

The current research of the global chassis control problem for the full drive-by-wire vehicle focuses on the control allocation (CA) of the four-wheel-distributed traction/braking/steering systems. However, the path following performance and the handling stability of the vehicle can be enhanced a step further by automatically adjusting the vehicle speed to the optimal value. The optimal solution for the combined longitudinal and lateral motion control (MC) problem is given. First, a new variable step-size spatial transformation method is proposed and utilized in the prediction model to derive the dynamics of the vehicle with respect to the road, such that the tracking errors can be explicitly obtained over the prediction horizon at varying speeds. Second, a nonlinear model predictive control (NMPC) algorithm is introduced to handle the nonlinear coupling between any two directions of the vehicular planar motion and computes the sequence of the optimal motion states for following the desired path. Third, a hierarchical control structure is proposed to separate the motion controller into a NMPC based path planner and a terminal sliding mode control (TSMC) based path follower. As revealed through off-line simulations, the hierarchical methodology brings nearly 1700% improvement in computational efficiency without loss of control performance. Finally, the control algorithm is verified through a hardware in-the-loop simulation system. Double-lane-change (DLC) test results show that by using the optimal predictive controller, the root-mean-square (RMS) values of the lateral deviations and the orientation errors can be reduced by 41% and 30%, respectively, comparing to those by the optimal preview acceleration (OPA) driver model with the non-preview speed-tracking method. Additionally, the average vehicle speed is increased by 0.26 km/h with the peak sideslip angle suppressed to 1.9°. This research proposes a novel motion controller, which provides the full drive-by-wire vehicle with better lane-keeping and collision-avoidance capabilities during autonomous driving.

Cone-Beam Computed Tomography Internal Motion Tracking Should Be Used to Validate 4-Dimensional Computed Tomography for Abdominal Radiation Therapy Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rankine, Leith; Wan, Hanlin; Parikh, Parag

Purpose: To demonstrate that fiducial tracking during pretreatment Cone-Beam CT (CBCT) can accurately measure tumor motion and that this method should be used to validate 4-dimensional CT (4DCT) margins before each treatment fraction. Methods and Materials: For 31 patients with abdominal tumors and implanted fiducial markers, tumor motion was measured daily with CBCT and fluoroscopy for 202 treatment fractions. Fiducial tracking and maximum-likelihood algorithms extracted 3-dimensional fiducial trajectories from CBCT projections. The daily internal margin (IM) (ie, range of fiducial motion) was calculated for CBCT and fluoroscopy as the 5th-95th percentiles of displacement in each cardinal direction. The planning IMmore » from simulation 4DCT (IM{sub 4DCT}) was considered adequate when within ±1.2 mm (anterior–posterior, left–right) and ±3 mm (superior–inferior) of the daily measured IM. We validated CBCT fiducial tracking as an accurate predictive measure of intrafraction motion by comparing the daily measured IM{sub CBCT} with the daily IM measured by pretreatment fluoroscopy (IM{sub pre-fluoro}); these were compared with pre- and posttreatment fluoroscopy (IM{sub fluoro}) to identify those patients who could benefit from imaging during treatment. Results: Four-dimensional CT could not accurately predict intrafractional tumor motion for ≥80% of fractions in 94% (IM{sub CBCT}), 97% (IM{sub pre-fluoro}), and 100% (IM{sub fluoro}) of patients. The IM{sub CBCT} was significantly closer to IM{sub pre-fluoro} than IM{sub 4DCT} (P<.01). For patients with median treatment time t < 7.5 minutes, IM{sub CBCT} was in agreement with IM{sub fluoro} for 93% of fractions (superior–inferior), compared with 63% for the t > 7.5 minutes group, demonstrating the need for patient-specific intratreatment imaging. Conclusions: Tumor motion determined from 4DCT simulation does not accurately predict the daily motion observed on CBCT or fluoroscopy. Cone-beam CT could replace fluoroscopy for pretreatment verification of simulation IM{sub 4DCT}, reducing patient setup time and imaging dose. Patients with treatment time t > 7.5 minutes could benefit from the addition of intratreatment imaging.« less

WE-G-BRD-04: BEST IN PHYSICS (JOINT IMAGING-THERAPY): An Integrated Model-Based Intrafractional Organ Motion Tracking Approach with Dynamic MRI in Head and Neck Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, H; Dolly, S; Anastasio, M

Purpose: In-treatment dynamic cine images, provided by the first commercially available MRI-guided radiotherapy system, allow physicians to observe intrafractional motion of head and neck (H&N) internal structures. Nevertheless, high anatomical complexity and relatively poor cine image contrast/resolution have complicated automatic intrafractional motion evaluation. We proposed an integrated model-based approach to automatically delineate and analyze moving structures from on-board cine images. Methods: The H&N upper airway, a complex and highly deformable region wherein severe internal motion often occurs, was selected as the target-to-be-tracked. To reliably capture its motion, a hierarchical structure model containing three statistical shapes (face, face-jaw, and face-jaw-palate) wasmore » first built from a set of manually delineated shapes using principal component analysis. An integrated model-fitting algorithm was then employed to align the statistical shapes to the first to-be-detected cine frame, and multi-feature level-set contour propagation was performed to identify the airway shape change in the remaining frames. Ninety sagittal cine MR image sets, acquired from three H&N cancer patients, were utilized to demonstrate this approach. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 20 randomly selected images from each patient. The resulting dice similarity coefficient (93.28+/−1.46 %) and margin error (0.49+/−0.12 mm) showed good agreement with the manual results. Intrafractional displacements of anterior, posterior, inferior, and superior airway boundaries were observed, with values of 2.62+/−2.92, 1.78+/−1.43, 3.51+/−3.99, and 0.68+/−0.89 mm, respectively. The H&N airway motion was found to vary across directions, fractions, and patients, and highly correlated with patients’ respiratory frequency. Conclusion: We proposed the integrated computational approach, which for the first time allows to automatically identify the H&N upper airway and quantify in-treatment H&N internal motion in real-time. This approach can be applied to track other structures’ motion, and provide guidance on patient-specific prediction of intra-/inter-fractional structure displacements.« less

Detecting periods of eating during free-living by tracking wrist motion.

PubMed

Dong, Yujie; Scisco, Jenna; Wilson, Mike; Muth, Eric; Hoover, Adam

2014-07-01

This paper is motivated by the growing prevalence of obesity, a health problem affecting over 500 million people. Measurements of energy intake are commonly used for the study and treatment of obesity. However, the most widely used tools rely upon self-report and require a considerable manual effort, leading to underreporting of consumption, noncompliance, and discontinued use over the long term. The purpose of this paper is to describe a new method that uses a watch-like configuration of sensors to continuously track wrist motion throughout the day and automatically detect periods of eating. Our method uses the novel idea that meals tend to be preceded and succeeded by the periods of vigorous wrist motion. We describe an algorithm that segments and classifies such periods as eating or noneating activities. We also evaluate our method on a large dataset (43 subjects, 449 total h of data, containing 116 periods of eating) collected during free-living. Our results show an accuracy of 81% for detecting eating at 1-s resolution in comparison to manually marked event logs of periods eating. These results indicate that vigorous wrist motion is a useful indicator for identifying the boundaries of eating activities, and that our method should prove useful in the continued development of body-worn sensor tools for monitoring energy intake.

A fiducial detection algorithm for real-time image guided IMRT based on simultaneous MV and kV imaging

PubMed Central

Mao, Weihua; Riaz, Nadeem; Lee, Louis; Wiersma, Rodney; Xing, Lei

2008-01-01

The advantage of highly conformal dose techniques such as 3DCRT and IMRT is limited by intrafraction organ motion. A new approach to gain near real-time 3D positions of internally implanted fiducial markers is to analyze simultaneous onboard kV beam and treatment MV beam images (from fluoroscopic or electronic portal image devices). Before we can use this real-time image guidance for clinical 3DCRT and IMRT treatments, four outstanding issues need to be addressed. (1) How will fiducial motion blur the image and hinder tracking fiducials? kV and MV images are acquired while the tumor is moving at various speeds. We find that a fiducial can be successfully detected at a maximum linear speed of 1.6 cm∕s. (2) How does MV beam scattering affect kV imaging? We investigate this by varying MV field size and kV source to imager distance, and find that common treatment MV beams do not hinder fiducial detection in simultaneous kV images. (3) How can one detect fiducials on images from 3DCRT and IMRT treatment beams when the MV fields are modified by a multileaf collimator (MLC)? The presented analysis is capable of segmenting a MV field from the blocking MLC and detecting visible fiducials. This enables the calculation of nearly real-time 3D positions of markers during a real treatment. (4) Is the analysis fast enough to track fiducials in nearly real time? Multiple methods are adopted to predict marker positions and reduce search regions. The average detection time per frame for three markers in a 1024×768 image was reduced to 0.1 s or less. Solving these four issues paves the way to tracking moving fiducial markers throughout a 3DCRT or IMRT treatment. Altogether, these four studies demonstrate that our algorithm can track fiducials in real time, on degraded kV images (MV scatter), in rapidly moving tumors (fiducial blurring), and even provide useful information in the case when some fiducials are blocked from view by the MLC. This technique can provide a gating signal or be used for intra-fractional tumor tracking on a Linac equipped with a kV imaging system. Any motion exceeding a preset threshold can warn the therapist to suspend a treatment session and reposition the patient. PMID:18777916

Accurate and efficient spin integration for particle accelerators

DOE PAGES

Abell, Dan T.; Meiser, Dominic; Ranjbar, Vahid H.; ...

2015-02-01

Accurate spin tracking is a valuable tool for understanding spin dynamics in particle accelerators and can help improve the performance of an accelerator. In this paper, we present a detailed discussion of the integrators in the spin tracking code GPUSPINTRACK. We have implemented orbital integrators based on drift-kick, bend-kick, and matrix-kick splits. On top of the orbital integrators, we have implemented various integrators for the spin motion. These integrators use quaternions and Romberg quadratures to accelerate both the computation and the convergence of spin rotations.We evaluate their performance and accuracy in quantitative detail for individual elements as well as formore » the entire RHIC lattice. We exploit the inherently data-parallel nature of spin tracking to accelerate our algorithms on graphics processing units.« less

Pyroclast Tracking Velocimetry: A particle tracking velocimetry-based tool for the study of Strombolian explosive eruptions

NASA Astrophysics Data System (ADS)

Gaudin, Damien; Moroni, Monica; Taddeucci, Jacopo; Scarlato, Piergiorgio; Shindler, Luca

2014-07-01

Image-based techniques enable high-resolution observation of the pyroclasts ejected during Strombolian explosions and drawing inferences on the dynamics of volcanic activity. However, data extraction from high-resolution videos is time consuming and operator dependent, while automatic analysis is often challenging due to the highly variable quality of images collected in the field. Here we present a new set of algorithms to automatically analyze image sequences of explosive eruptions: the pyroclast tracking velocimetry (PyTV) toolbox. First, a significant preprocessing is used to remove the image background and to detect the pyroclasts. Then, pyroclast tracking is achieved with a new particle tracking velocimetry algorithm, featuring an original predictor of velocity based on the optical flow equation. Finally, postprocessing corrects the systematic errors of measurements. Four high-speed videos of Strombolian explosions from Yasur and Stromboli volcanoes, representing various observation conditions, have been used to test the efficiency of the PyTV against manual analysis. In all cases, >106 pyroclasts have been successfully detected and tracked by PyTV, with a precision of 1 m/s for the velocity and 20% for the size of the pyroclast. On each video, more than 1000 tracks are several meters long, enabling us to study pyroclast properties and trajectories. Compared to manual tracking, 3 to 100 times more pyroclasts are analyzed. PyTV, by providing time-constrained information, links physical properties and motion of individual pyroclasts. It is a powerful tool for the study of explosive volcanic activity, as well as an ideal complement for other geological and geophysical volcano observation systems.

Measuring molecular motions inside single cells with improved analysis of single-particle trajectories

NASA Astrophysics Data System (ADS)

Rowland, David J.; Biteen, Julie S.

2017-04-01

Single-molecule super-resolution imaging and tracking can measure molecular motions inside living cells on the scale of the molecules themselves. Diffusion in biological systems commonly exhibits multiple modes of motion, which can be effectively quantified by fitting the cumulative probability distribution of the squared step sizes in a two-step fitting process. Here we combine this two-step fit into a single least-squares minimization; this new method vastly reduces the total number of fitting parameters and increases the precision with which diffusion may be measured. We demonstrate this Global Fit approach on a simulated two-component system as well as on a mixture of diffusing 80 nm and 200 nm gold spheres to show improvements in fitting robustness and localization precision compared to the traditional Local Fit algorithm.

Observation and analysis of high-speed human motion with frequent occlusion in a large area

NASA Astrophysics Data System (ADS)

Wang, Yuru; Liu, Jiafeng; Liu, Guojun; Tang, Xianglong; Liu, Peng

2009-12-01

The use of computer vision technology in collecting and analyzing statistics during sports matches or training sessions is expected to provide valuable information for tactics improvement. However, the measurements published in the literature so far are either unreliably documented to be used in training planning due to their limitations or unsuitable for studying high-speed motion in large area with frequent occlusions. A sports annotation system is introduced in this paper for tracking high-speed non-rigid human motion over a large playing area with the aid of motion camera, taking short track speed skating competitions as an example. The proposed system is composed of two sub-systems: precise camera motion compensation and accurate motion acquisition. In the video registration step, a distinctive invariant point feature detector (probability density grads detector) and a global parallax based matching points filter are used, to provide reliable and robust matching across a large range of affine distortion and illumination change. In the motion acquisition step, a two regions' relationship constrained joint color model and Markov chain Monte Carlo based joint particle filter are emphasized, by dividing the human body into two relative key regions. Several field tests are performed to assess measurement errors, including comparison to popular algorithms. With the help of the system presented, the system obtains position data on a 30 m × 60 m large rink with root-mean-square error better than 0.3975 m, velocity and acceleration data with absolute error better than 1.2579 m s-1 and 0.1494 m s-2, respectively.

Segmentation and tracking of lung nodules via graph-cuts incorporating shape prior and motion from 4D CT.

PubMed

Cha, Jungwon; Farhangi, Mohammad Mehdi; Dunlap, Neal; Amini, Amir A

2018-01-01

We have developed a robust tool for performing volumetric and temporal analysis of nodules from respiratory gated four-dimensional (4D) CT. The method could prove useful in IMRT of lung cancer. We modified the conventional graph-cuts method by adding an adaptive shape prior as well as motion information within a signed distance function representation to permit more accurate and automated segmentation and tracking of lung nodules in 4D CT data. Active shape models (ASM) with signed distance function were used to capture the shape prior information, preventing unwanted surrounding tissues from becoming part of the segmented object. The optical flow method was used to estimate the local motion and to extend three-dimensional (3D) segmentation to 4D by warping a prior shape model through time. The algorithm has been applied to segmentation of well-circumscribed, vascularized, and juxtapleural lung nodules from respiratory gated CT data. In all cases, 4D segmentation and tracking for five phases of high-resolution CT data took approximately 10 min on a PC workstation with AMD Phenom II and 32 GB of memory. The method was trained based on 500 breath-held 3D CT data from the LIDC data base and was tested on 17 4D lung nodule CT datasets consisting of 85 volumetric frames. The validation tests resulted in an average Dice Similarity Coefficient (DSC) = 0.68 for all test data. An important by-product of the method is quantitative volume measurement from 4D CT from end-inspiration to end-expiration which will also have important diagnostic value. The algorithm performs robust segmentation of lung nodules from 4D CT data. Signed distance ASM provides the shape prior information which based on the iterative graph-cuts framework is adaptively refined to best fit the input data, preventing unwanted surrounding tissue from merging with the segmented object. © 2017 American Association of Physicists in Medicine.

Trace-transform invariants of tracks of high-velocity jets from the surface of tungsten droplets in the plasma flow

NASA Astrophysics Data System (ADS)

Gulyaev, P.; Jordan, V.; Gulyaev, I.; Dolmatov, A.

2017-05-01

The paper presents the analysis of the recorded tracks of high-velocity emission in the air-argon plasma flow during breaking up of tungsten microdroplets. This new physical effect of optical emission involves two stages. The first one includes thermionic emission of electrons from the surface of the melted tungsten droplet of 100-200 μm size and formation of the charged sphere of 3-5 mm diameter. After it reaches the breakdown electric potential, it collapses and produces a spherical shock wave and luminous radiation. The second stage includes previously unknown physical phenomenon of narrowly directed energy jet with velocity exceeding 4000 m/s from the surface of the tungsten droplet. The luminous spherical collapse and high-velocity jets were recorded using CMOS photo-array operating in a global shutter charge storage mode. Special features of the CMOS array scanning algorithm affect formation of distinctive signs of the recorded tracks, which stay invariant to trace transform (TT) with specific functional. The series of concentric circles were adopted as primitive object models (patterns) used in TT at the spherical collapse stage and linear segment of fixed thickness - at the high-velocity emission stage. The two invariants of the physical object, motion velocity and optical brightness distribution in the motion front, were adopted as desired identification features of tracks. The analytical expressions of the relation of 2D TT parameters and physical object motion invariants were obtained. The equations for spherical collapse stage correspond to Radon-Nikodym transform.

Real-time visual target tracking: two implementations of velocity-based smooth pursuit

NASA Astrophysics Data System (ADS)

Etienne-Cummings, Ralph; Longo, Paul; Van der Spiegel, Jan; Mueller, Paul

1995-06-01

Two systems for velocity-based visual target tracking are presented. The first two computational layers of both implementations are composed of VLSI photoreceptors (logarithmic compression) and edge detection (difference-of-Gaussians) arrays that mimic the outer-plexiform layer of mammalian retinas. The subsequent processing layers for measuring the target velocity and to realize smooth pursuit tracking are implemented in software and at the focal plane in the two versions, respectively. One implentation uses a hybrid of a PC and a silicon retina (39 X 38 pixels) operating at 333 frames/second. The software implementation of a real-time optical flow measurement algorithm is used to determine the target velocity, and a closed-loop control system zeroes the relative velocity of the target and retina. The second implementation is a single VLSI chip, which contains a linear array of photoreceptors, edge detectors and motion detectors at the focal plane. The closed-loop control system is also included on chip. This chip realizes all the computational properties of the hybrid system. The effects of background motion, target occlusion, and disappearance are studied as a function of retinal size and spatial distribution of the measured motion vectors (i.e. foveal/peripheral and diverging/converging measurement schemes). The hybrid system, which tested successfully, tracks targets moving as fast as 3 m/s at 1.3 meters from the camera and it can compensate for external arbitrary movements in its mounting platform. The single chip version, whose circuits tested successfully, can handle targets moving at 10 m/s.

Development of an in vitro diaphragm motion reproduction system.

PubMed

Liao, Ai-Ho; Chuang, Ho-Chiao; Shih, Ming-Chih; Hsu, Hsiao-Yu; Tien, Der-Chi; Kuo, Chia-Chun; Jeng, Shiu-Chen; Chiou, Jeng-Fong

2017-07-01

This study developed an in vitro diaphragm motion reproduction system (IVDMRS) based on noninvasive and real-time ultrasound imaging to track the internal displacement of the human diaphragm and diaphragm phantoms with a respiration simulation system (RSS). An ultrasound image tracking algorithm (UITA) was used to retrieve the displacement data of the tracking target and reproduce the diaphragm motion in real time using a red laser to irradiate the diaphragm phantom in vitro. This study also recorded the respiration patterns in 10 volunteers. Both simulated and the respiration patterns in 10 human volunteers signals were input to the RSS for conducting experiments involving the reproduction of diaphragm motion in vitro using the IVDMRS. The reproduction accuracy of the IVDMRS was calculated and analyzed. The results indicate that the respiration frequency substantially affects the correlation between ultrasound and kV images, as well as the reproduction accuracy of the IVDMRS due to the system delay time (0.35s) of ultrasound imaging and signal transmission. The utilization of a phase lead compensator (PLC) reduced the error caused by this delay, thereby improving the reproduction accuracy of the IVDMRS by 14.09-46.98%. Applying the IVDMRS in clinical treatments will allow medical staff to monitor the target displacements in real time by observing the movement of the laser beam. If the target displacement moves outside the planning target volume (PTV), the treatment can be immediately stopped to ensure that healthy tissues do not receive high doses of radiation. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, J; Nguyen, D; O’Brien, R

Purpose: Kilovoltage intrafraction monitoring (KIM) scheme has been successfully used to simultaneously monitor 3D tumor motion during radiotherapy. Recently, an iterative closest point (ICP) algorithm was implemented in KIM to also measure rotations about three axes, enabling real-time tracking of tumor motion in six degrees-of-freedom (DoF). This study aims to evaluate the accuracy of the six DoF motion estimates of KIM by comparing it with the corresponding motion (i) measured by the Calypso; and (ii) derived from kV/MV triangulation. Methods: (i) Various motions (static and dynamic) were applied to a CIRS phantom with three embedded electromagnetic transponders (Calypso Medical) usingmore » a 5D motion platform (HexaMotion) and a rotating treatment couch while both KIM and Calypso were used to concurrently track the phantom motion in six DoF. (ii) KIM was also used to retrospectively estimate six DoF motion from continuous sets of kV projections of a prostate, implanted with three gold fiducial markers (2 patients with 80 fractions in total), acquired during the treatment. Corresponding motion was obtained from kV/MV triangulation using a closed form least squares method based on three markers’ positions. Only the frames where all three markers were present were used in the analysis. The mean differences between the corresponding motion estimates were calculated for each DoF. Results: Experimental results showed that the mean of absolute differences in six DoF phantom motion measured by Calypso and KIM were within 1.1° and 0.7 mm. kV/MV triangulation derived six DoF prostate tumor better agreed with KIM estimated motion with the mean (s.d.) difference of up to 0.2° (1.36°) and 0.2 (0.25) mm for rotation and translation, respectively. Conclusion: These results suggest that KIM can provide an accurate six DoF intrafraction tumor during radiotherapy.« less

Simultaneous localization and calibration for electromagnetic tracking systems.

PubMed

Sadjadi, Hossein; Hashtrudi-Zaad, Keyvan; Fichtinger, Gabor

2016-06-01

In clinical environments, field distortion can cause significant electromagnetic tracking errors. Therefore, dynamic calibration of electromagnetic tracking systems is essential to compensate for measurement errors. It is proposed to integrate the motion model of the tracked instrument with redundant EM sensor observations and to apply a simultaneous localization and mapping algorithm in order to accurately estimate the pose of the instrument and create a map of the field distortion in real-time. Experiments were conducted in the presence of ferromagnetic and electrically-conductive field distorting objects and results compared with those of a conventional sensor fusion approach. The proposed method reduced the tracking error from 3.94±1.61 mm to 1.82±0.62 mm in the presence of steel, and from 0.31±0.22 mm to 0.11±0.14 mm in the presence of aluminum. With reduced tracking error and independence from external tracking devices or pre-operative calibrations, the approach is promising for reliable EM navigation in various clinical procedures. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Electromagnetic guided couch and multileaf collimator tracking on a TrueBeam accelerator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hansen, Rune; Ravkilde, Thomas; Worm, Esben Schjødt

2016-05-15

Purpose: Couch and MLC tracking are two promising methods for real-time motion compensation during radiation therapy. So far, couch and MLC tracking experiments have mainly been performed by different research groups, and no direct comparison of couch and MLC tracking of volumetric modulated arc therapy (VMAT) plans has been published. The Varian TrueBeam 2.0 accelerator includes a prototype tracking system with selectable couch or MLC compensation. This study provides a direct comparison of the two tracking types with an otherwise identical setup. Methods: Several experiments were performed to characterize the geometric and dosimetric performance of electromagnetic guided couch and MLCmore » tracking on a TrueBeam accelerator equipped with a Millennium MLC. The tracking system latency was determined without motion prediction as the time lag between sinusoidal target motion and the compensating motion of the couch or MLC as recorded by continuous MV portal imaging. The geometric and dosimetric tracking accuracies were measured in tracking experiments with motion phantoms that reproduced four prostate and four lung tumor trajectories. The geometric tracking error in beam’s eye view was determined as the distance between an embedded gold marker and a circular MLC aperture in continuous MV images. The dosimetric tracking error was quantified as the measured 2%/2 mm gamma failure rate of a low and a high modulation VMAT plan delivered with the eight motion trajectories using a static dose distribution as reference. Results: The MLC tracking latency was approximately 146 ms for all sinusoidal period lengths while the couch tracking latency increased from 187 to 246 ms with decreasing period length due to limitations in the couch acceleration. The mean root-mean-square geometric error was 0.80 mm (couch tracking), 0.52 mm (MLC tracking), and 2.75 mm (no tracking) parallel to the MLC leaves and 0.66 mm (couch), 1.14 mm (MLC), and 2.41 mm (no tracking) perpendicular to the leaves. The motion-induced gamma failure rate was in mean 0.1% (couch tracking), 8.1% (MLC tracking), and 30.4% (no tracking) for prostate motion and 2.9% (couch), 2.4% (MLC), and 41.2% (no tracking) for lung tumor motion. The residual tracking errors were mainly caused by inadequate adaptation to fast lung tumor motion for couch tracking and to prostate motion perpendicular to the MLC leaves for MLC tracking. Conclusions: Couch and MLC tracking markedly improved the geometric and dosimetric accuracies of VMAT delivery. However, the two tracking types have different strengths and weaknesses. While couch tracking can correct perfectly for slowly moving targets such as the prostate, MLC tracking may have considerably larger dose errors for persistent target shift perpendicular to the MLC leaves. Advantages of MLC tracking include faster dynamics with better adaptation to fast moving targets, the avoidance of moving the patient, and the potential to track target rotations and deformations.« less

The effect of concurrent hand movement on estimated time to contact in a prediction motion task.

PubMed

Zheng, Ran; Maraj, Brian K V

2018-04-27

In many activities, we need to predict the arrival of an occluded object. This action is called prediction motion or motion extrapolation. Previous researchers have found that both eye tracking and the internal clocking model are involved in the prediction motion task. Additionally, it is reported that concurrent hand movement facilitates the eye tracking of an externally generated target in a tracking task, even if the target is occluded. The present study examined the effect of concurrent hand movement on the estimated time to contact in a prediction motion task. We found different (accurate/inaccurate) concurrent hand movements had the opposite effect on the eye tracking accuracy and estimated TTC in the prediction motion task. That is, the accurate concurrent hand tracking enhanced eye tracking accuracy and had the trend to increase the precision of estimated TTC, but the inaccurate concurrent hand tracking decreased eye tracking accuracy and disrupted estimated TTC. However, eye tracking accuracy does not determine the precision of estimated TTC.

Optimised collision avoidance for an ultra-close rendezvous with a failed satellite based on the Gauss pseudospectral method

NASA Astrophysics Data System (ADS)

Chu, Xiaoyu; Zhang, Jingrui; Lu, Shan; Zhang, Yao; Sun, Yue

2016-11-01

This paper presents a trajectory planning algorithm to optimise the collision avoidance of a chasing spacecraft operating in an ultra-close proximity to a failed satellite. The complex configuration and the tumbling motion of the failed satellite are considered. The two-spacecraft rendezvous dynamics are formulated based on the target body frame, and the collision avoidance constraints are detailed, particularly concerning the uncertainties. An optimisation solution of the approaching problem is generated using the Gauss pseudospectral method. A closed-loop control is used to track the optimised trajectory. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms.

Exploring dynamics in living cells by tracking single particles.

PubMed

Levi, Valeria; Gratton, Enrico

2007-01-01

In the last years, significant advances in microscopy techniques and the introduction of a novel technology to label living cells with genetically encoded fluorescent proteins revolutionized the field of Cell Biology. Our understanding on cell dynamics built from snapshots on fixed specimens has evolved thanks to our actual capability to monitor in real time the evolution of processes in living cells. Among these new tools, single particle tracking techniques were developed to observe and follow individual particles. Hence, we are starting to unravel the mechanisms driving the motion of a wide variety of cellular components ranging from organelles to protein molecules by following their way through the cell. In this review, we introduce the single particle tracking technology to new users. We briefly describe the instrumentation and explain some of the algorithms commonly used to locate and track particles. Also, we present some common tools used to analyze trajectories and illustrate with some examples the applications of single particle tracking to study dynamics in living cells.

Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods.

PubMed

Abella, Jayvee R; Moll, Mark; Kavraki, Lydia E

2018-01-01

The ability to efficiently sample structurally diverse protein conformations allows one to gain a high-level view of a protein's energy landscape. Algorithms from robot motion planning have been used for conformational sampling, and several of these algorithms promote diversity by keeping track of "coverage" in conformational space based on the local sampling density. However, large proteins present special challenges. In particular, larger systems require running many concurrent instances of these algorithms, but these algorithms can quickly become memory intensive because they typically keep previously sampled conformations in memory to maintain coverage estimates. In addition, robotics-inspired algorithms depend on defining useful perturbation strategies for exploring the conformational space, which is a difficult task for large proteins because such systems are typically more constrained and exhibit complex motions. In this article, we introduce two methodologies for maintaining and enhancing diversity in robotics-inspired conformational sampling. The first method addresses algorithms based on coverage estimates and leverages the use of a low-dimensional projection to define a global coverage grid that maintains coverage across concurrent runs of sampling. The second method is an automatic definition of a perturbation strategy through readily available flexibility information derived from B-factors, secondary structure, and rigidity analysis. Our results show a significant increase in the diversity of the conformations sampled for proteins consisting of up to 500 residues when applied to a specific robotics-inspired algorithm for conformational sampling. The methodologies presented in this article may be vital components for the scalability of robotics-inspired approaches.

How Many Objects are You Worth? Quantification of the Self-Motion Load on Multiple Object Tracking

PubMed Central

Thomas, Laura E.; Seiffert, Adriane E.

2011-01-01

Perhaps walking and chewing gum is effortless, but walking and tracking moving objects is not. Multiple object tracking is impaired by walking from one location to another, suggesting that updating location of the self puts demands on object tracking processes. Here, we quantified the cost of self-motion in terms of the tracking load. Participants in a virtual environment tracked a variable number of targets (1–5) among distractors while either staying in one place or moving along a path that was similar to the objects’ motion. At the end of each trial, participants decided whether a probed dot was a target or distractor. As in our previous work, self-motion significantly impaired performance in tracking multiple targets. Quantifying tracking capacity for each individual under move versus stay conditions further revealed that self-motion during tracking produced a cost to capacity of about 0.8 (±0.2) objects. Tracking your own motion is worth about one object, suggesting that updating the location of the self is similar, but perhaps slightly easier, than updating locations of objects. PMID:21991259

Eye-Tracking Technology and the Dynamics of Natural Gaze Behavior in Sports: A Systematic Review of 40 Years of Research.

PubMed

Kredel, Ralf; Vater, Christian; Klostermann, André; Hossner, Ernst-Joachim

2017-01-01

Reviewing 60 studies on natural gaze behavior in sports, it becomes clear that, over the last 40 years, the use of eye-tracking devices has considerably increased. Specifically, this review reveals the large variance of methods applied, analyses performed, and measures derived within the field. The results of sub-sample analyses suggest that sports-related eye-tracking research strives, on the one hand, for ecologically valid test settings (i.e., viewing conditions and response modes), while on the other, for experimental control along with high measurement accuracy (i.e., controlled test conditions with high-frequency eye-trackers linked to algorithmic analyses). To meet both demands, some promising compromises of methodological solutions have been proposed-in particular, the integration of robust mobile eye-trackers in motion-capture systems. However, as the fundamental trade-off between laboratory and field research cannot be solved by technological means, researchers need to carefully weigh the arguments for one or the other approach by accounting for the respective consequences. Nevertheless, for future research on dynamic gaze behavior in sports, further development of the current mobile eye-tracking methodology seems highly advisable to allow for the acquisition and algorithmic analyses of larger amounts of gaze-data and further, to increase the explanatory power of the derived results.

Model-based control strategies for systems with constraints of the program type

NASA Astrophysics Data System (ADS)

Jarzębowska, Elżbieta

2006-08-01

The paper presents a model-based tracking control strategy for constrained mechanical systems. Constraints we consider can be material and non-material ones referred to as program constraints. The program constraint equations represent tasks put upon system motions and they can be differential equations of orders higher than one or two, and be non-integrable. The tracking control strategy relies upon two dynamic models: a reference model, which is a dynamic model of a system with arbitrary order differential constraints and a dynamic control model. The reference model serves as a motion planner, which generates inputs to the dynamic control model. It is based upon a generalized program motion equations (GPME) method. The method enables to combine material and program constraints and merge them both into the motion equations. Lagrange's equations with multipliers are the peculiar case of the GPME, since they can be applied to systems with constraints of first orders. Our tracking strategy referred to as a model reference program motion tracking control strategy enables tracking of any program motion predefined by the program constraints. It extends the "trajectory tracking" to the "program motion tracking". We also demonstrate that our tracking strategy can be extended to a hybrid program motion/force tracking.

Array-based infra-red detection: an enabling technology for people counting, sensing, tracking, and intelligent detection

NASA Astrophysics Data System (ADS)

Stogdale, Nick; Hollock, Steve; Johnson, Neil; Sumpter, Neil

2003-09-01

A 16x16 element un-cooled pyroelectric detector array has been developed which, when allied with advanced tracking and detection algorithms, has created a universal detector with multiple applications. Low-cost manufacturing techniques are used to fabricate a hybrid detector, intended for economic use in commercial markets. The detector has found extensive application in accurate people counting, detection, tracking, secure area protection, directional sensing and area violation; topics which are all pertinent to the provision of Homeland Security. The detection and tracking algorithms have, when allied with interpolation techniques, allowed a performance much higher than might be expected from a 16x16 array. This paper reviews the technology, with particular attention to the array structure, algorithms and interpolation techniques and outlines its application in a number of challenging market areas. Viewed from above, moving people are seen as 'hot blobs' moving through the field of view of the detector; background clutter or stationary objects are not seen and the detector works irrespective of lighting or environmental conditions. Advanced algorithms detect the people and extract size, shape, direction and velocity vectors allowing the number of people to be detected and their trajectories of motion to be tracked. Provision of virtual lines in the scene allows bi-directional counting of people flowing in and out of an entrance or area. Definition of a virtual closed area in the scene allows counting of the presence of stationary people within a defined area. Definition of 'counting lines' allows the counting of people, the ability to augment access control devices by confirming a 'one swipe one entry' judgement and analysis of the flow and destination of moving people. For example, passing the 'wrong way' up a denied passageway can be detected. Counting stationary people within a 'defined area' allows the behaviour and size of groups of stationary people to be analysed and counted, an alarm condition can also be generated when people stray into such areas.

Visual Target Tracking in the Presence of Unknown Observer Motion

NASA Technical Reports Server (NTRS)

Williams, Stephen; Lu, Thomas

2009-01-01

Much attention has been given to the visual tracking problem due to its obvious uses in military surveillance. However, visual tracking is complicated by the presence of motion of the observer in addition to the target motion, especially when the image changes caused by the observer motion are large compared to those caused by the target motion. Techniques for estimating the motion of the observer based on image registration techniques and Kalman filtering are presented and simulated. With the effects of the observer motion removed, an additional phase is implemented to track individual targets. This tracking method is demonstrated on an image stream from a buoy-mounted or periscope-mounted camera, where large inter-frame displacements are present due to the wave action on the camera. This system has been shown to be effective at tracking and predicting the global position of a planar vehicle (boat) being observed from a single, out-of-plane camera. Finally, the tracking system has been extended to a multi-target scenario.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

PubMed

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

PubMed Central

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Measurement of joint kinematics using a conventional clinical single-perspective flat-panel radiography system.

PubMed

Seslija, Petar; Teeter, Matthew G; Yuan, Xunhua; Naudie, Douglas D R; Bourne, Robert B; Macdonald, Steven J; Peters, Terry M; Holdsworth, David W

2012-10-01

The ability to accurately measure joint kinematics is an important tool in studying both normal joint function and pathologies associated with injury and disease. The purpose of this study is to evaluate the efficacy, accuracy, precision, and clinical safety of measuring 3D joint motion using a conventional flat-panel radiography system prior to its application in an in vivo study. An automated, image-based tracking algorithm was implemented to measure the three-dimensional pose of a sparse object from a two-dimensional radiographic projection. The algorithm was tested to determine its efficiency and failure rate, defined as the number of image frames where automated tracking failed, or required user intervention. The accuracy and precision of measuring three-dimensional motion were assessed using a robotic controlled, tibiofemoral knee phantom programmed to mimic a subject with a total knee replacement performing a stair ascent activity. Accuracy was assessed by comparing the measurements of the single-plane radiographic tracking technique to those of an optical tracking system, and quantified by the measurement discrepancy between the two systems using the Bland-Altman technique. Precision was assessed through a series of repeated measurements of the tibiofemoral kinematics, and was quantified using the across-trial deviations of the repeated kinematic measurements. The safety of the imaging procedure was assessed by measuring the effective dose of ionizing radiation associated with the x-ray exposures, and analyzing its relative risk to a human subject. The automated tracking algorithm displayed a failure rate of 2% and achieved an average computational throughput of 8 image frames/s. Mean differences between the radiographic and optical measurements for translations and rotations were less than 0.08 mm and 0.07° in-plane, and 0.24 mm and 0.6° out-of-plane. The repeatability of kinematics measurements performed using the radiographic tracking technique was better than ±0.09 mm and 0.12° in-plane, and ±0.70 mm and ±0.07° out-of-plane. The effective dose associated with the imaging protocol used was 15 μSv for 10 s of radiographic cine acquisition. This study demonstrates the ability to accurately measure knee-joint kinematics using a single-plane radiographic measurement technique. The measurement technique can be easily implemented at most clinical centers equipped with a modern-day radiographic x-ray system. The dose of ionizing radiation associated with the image acquisition represents a minimal risk to any subjects undergoing the examination.

Flower tracking in hawkmoths: behavior and energetics.

PubMed

Sprayberry, Jordanna D H; Daniel, Thomas L

2007-01-01

As hovering feeders, hawkmoths cope with flower motions by tracking those motions to maintain contact with the nectary. This study examined the tracking, feeding and energetic performance of Manduca sexta feeding from flowers moving at varied frequencies and in different directions. In general we found that tracking performance decreased as frequency increased; M. sexta tracked flowers moving at 1 Hz best. While feeding rates were highest for stationary flowers, they remained relatively constant for all tested frequencies of flower motion. Calculations of net energy gain showed that energy expenditure to track flowers is minimal compared to energy intake; therefore, patterns of net energy gain mimicked patterns of feeding rate. The direction effects of flower motion were greater than the frequency effects. While M. sexta appeared equally capable of tracking flowers moving in the horizontal and vertical motion axes, they demonstrated poor ability to track flowers moving in the looming axis. Additionally, both feeding rates and net energy gain were lower for looming axis flower motions.

A hierarchical framework for air traffic control

NASA Astrophysics Data System (ADS)

Roy, Kaushik

Air travel in recent years has been plagued by record delays, with over $8 billion in direct operating costs being attributed to 100 million flight delay minutes in 2007. Major contributing factors to delay include weather, congestion, and aging infrastructure; the Next Generation Air Transportation System (NextGen) aims to alleviate these delays through an upgrade of the air traffic control system. Changes to large-scale networked systems such as air traffic control are complicated by the need for coordinated solutions over disparate temporal and spatial scales. Individual air traffic controllers must ensure aircraft maintain safe separation locally with a time horizon of seconds to minutes, whereas regional plans are formulated to efficiently route flows of aircraft around weather and congestion on the order of every hour. More efficient control algorithms that provide a coordinated solution are required to safely handle a larger number of aircraft in a fixed amount of airspace. Improved estimation algorithms are also needed to provide accurate aircraft state information and situational awareness for human controllers. A hierarchical framework is developed to simultaneously solve the sometimes conflicting goals of regional efficiency and local safety. Careful attention is given in defining the interactions between the layers of this hierarchy. In this way, solutions to individual air traffic problems can be targeted and implemented as needed. First, the regional traffic flow management problem is posed as an optimization problem and shown to be NP-Hard. Approximation methods based on aggregate flow models are developed to enable real-time implementation of algorithms that reduce the impact of congestion and adverse weather. Second, the local trajectory design problem is solved using a novel slot-based sector model. This model is used to analyze sector capacity under varying traffic patterns, providing a more comprehensive understanding of how increased automation in NextGen will affect the overall performance of air traffic control. The dissertation also provides solutions to several key estimation problems that support corresponding control tasks. Throughout the development of these estimation algorithms, aircraft motion is modeled using hybrid systems, which encapsulate both the discrete flight mode of an aircraft and the evolution of continuous states such as position and velocity. The target-tracking problem is posed as one of hybrid state estimation, and two new algorithms are developed to exploit structure specific to aircraft motion, especially near airports. First, discrete mode evolution is modeled using state-dependent transitions, in which the likelihood of changing flight modes is dependent on aircraft state. Second, an estimator is designed for systems with limited mode changes, including arrival aircraft. Improved target tracking facilitates increased safety in collision avoidance and trajectory design problems. A multiple-target tracking and identity management algorithm is developed to improve situational awareness for controllers about multiple maneuvering targets in a congested region. Finally, tracking algorithms are extended to predict aircraft landing times; estimated time of arrival prediction is one example of important decision support information for air traffic control.

Suitability of markerless EPID tracking for tumor position verification in gated radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Serpa, Marco; University Clinic for Radiotherapy and Radio-Oncology, Landeskrankenhaus Salzburg, Paracelsus Medical University Clinics, 5020 Salzburg; Department of Physics and Astronomy, University of Canterbury, Christchurch 8140

2014-03-15

Purpose: To maximize the benefits of respiratory gated radiotherapy (RGRT) of lung tumors real-time verification of the tumor position is required. This work investigates the feasibility of markerless tracking of lung tumors during beam-on time in electronic portal imaging device (EPID) images of the MV therapeutic beam. Methods: EPID movies were acquired at ∼2 fps for seven lung cancer patients with tumor peak-to-peak motion ranges between 7.8 and 17.9 mm (mean: 13.7 mm) undergoing stereotactic body radiotherapy. The external breathing motion of the abdomen was synchronously measured. Both datasets were retrospectively analyzed inPortalTrack, an in-house developed tracking software. The authorsmore » define a three-step procedure to run the simulations: (1) gating window definition, (2) gated-beam delivery simulation, and (3) tumor tracking. First, an amplitude threshold level was set on the external signal, defining the onset of beam-on/-off signals. This information was then mapped onto a sequence of EPID images to generate stamps of beam-on/-hold periods throughout the EPID movies in PortalTrack, by obscuring the frames corresponding to beam-off times. Last, tumor motion in the superior-inferior direction was determined on portal images by the tracking algorithm during beam-on time. The residual motion inside the gating window as well as target coverage (TC) and the marginal target displacement (MTD) were used as measures to quantify tumor position variability. Results: Tumor position monitoring and estimation from beam's-eye-view images during RGRT was possible in 67% of the analyzed beams. For a reference gating window of 5 mm, deviations ranging from 2% to 86% (35% on average) were recorded between the reference and measured residual motion. TC (range: 62%–93%; mean: 77%) losses were correlated with false positives incidence rates resulting mostly from intra-/inter-beam baseline drifts, as well as sudden cycle-to-cycle fluctuations in exhale positions. Both phenomena can lead to considerable deviations (with MTD values up to a maximum of 7.8 mm) from the intended tumor position, and in turn may result in a marginal miss. The difference between tumor traces determined within the gating window against ground truth trajectory maps was 1.1 ± 0.7 mm on average (range: 0.4–2.3 mm). Conclusions: In this retrospective analysis of motion data, it is demonstrated that the system is capable of determining tumor positions in the plane perpendicular to the beam direction without the aid of fiducial markers, and may hence be suitable as an online verification tool in RGRT. It may be possible to use the tracking information to enable on-the-fly corrections to intra-/inter-beam variations by adapting the gating window by means of a robotic couch.« less

Enhanced Algorithms for EO/IR Electronic Stabilization, Clutter Suppression, and Track-Before-Detect for Multiple Low Observable Targets

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Brown, A.; Brown, J.

The paper describes the development and evaluation of a suite of advanced algorithms which provide significantly-improved capabilities for finding, fixing, and tracking multiple ballistic and flying low observable objects in highly stressing cluttered environments. The algorithms have been developed for use in satellite-based staring and scanning optical surveillance suites for applications including theatre and intercontinental ballistic missile early warning, trajectory prediction, and multi-sensor track handoff for midcourse discrimination and intercept. The functions performed by the algorithms include electronic sensor motion compensation providing sub-pixel stabilization (to 1/100 of a pixel), as well as advanced temporal-spatial clutter estimation and suppression to below sensor noise levels, followed by statistical background modeling and Bayesian multiple-target track-before-detect filtering. The multiple-target tracking is performed in physical world coordinates to allow for multi-sensor fusion, trajectory prediction, and intercept. Output of detected object cues and data visualization are also provided. The algorithms are designed to handle a wide variety of real-world challenges. Imaged scenes may be highly complex and infinitely varied -- the scene background may contain significant celestial, earth limb, or terrestrial clutter. For example, when viewing combined earth limb and terrestrial scenes, a combination of stationary and non-stationary clutter may be present, including cloud formations, varying atmospheric transmittance and reflectance of sunlight and other celestial light sources, aurora, glint off sea surfaces, and varied natural and man-made terrain features. The targets of interest may also appear to be dim, relative to the scene background, rendering much of the existing deployed software useless for optical target detection and tracking. Additionally, it may be necessary to detect and track a large number of objects in the threat cloud, and these objects may not always be resolvable in individual data frames. In the present paper, the performance of the developed algorithms is demonstrated using real-world data containing resident space objects observed from the MSX platform, with backgrounds varying from celestial to combined celestial and earth limb, with instances of extremely bright aurora clutter. Simulation results are also presented for parameterized variations in signal-to-clutter levels (down to 1/1000) and signal-to-noise levels (down to 1/6) for simulated targets against real-world terrestrial clutter backgrounds. We also discuss algorithm processing requirements and C++ software processing capabilities from our on-going MDA- and AFRL-sponsored development of an image processing toolkit (iPTK). In the current effort, the iPTK is being developed to a Technology Readiness Level (TRL) of 6 by mid-2010, in preparation for possible integration with STSS-like, SBIRS high-like and SBSS-like surveillance suites.

Design and Performance Evaluation of a UWB Communication and Tracking System for Mini-AERCam

NASA Technical Reports Server (NTRS)

Barton, Richard J.

2005-01-01

NASA Johnson Space Center (JSC) is developing a low-volume, low-mass, robotic free-flying camera known as Mini-AERCam (Autonomous Extra-vehicular Robotic Camera) to assist the International Space Station (ISS) operations. Mini-AERCam is designed to provide astronauts and ground control real-time video for camera views of ISS. The system will assist ISS crewmembers and ground personnel to monitor ongoing operations and perform visual inspections of exterior ISS components without requiring extravehicular activity (EAV). Mini-AERCam consists of a great number of subsystems. Many institutions and companies have been involved in the R&D for this project. A Mini-AERCam ground control system has been studied at Texas A&M University [3]. The path planning and control algorithms that direct the motions of Mini-AERCam have been developed through the joint effort of Carnegie Mellon University and the Texas Robotics and Automation Center [5]. NASA JSC has designed a layered control architecture that integrates all functions of Mini-AERCam [8]. The research described in this report is part of a larger effort focused on the communication and tracking subsystem that is designed to perform three major tasks: 1. To transmit commands from ISS to Mini-AERCam for control of robotic camera motions (downlink); 2. To transmit real-time video from Mini-AERCam to ISS for inspections (uplink); 3. To track the position of Mini-AERCam for precise motion control. The ISS propagation environment is unique due to the nature of the ISS structure and multiple RF interference sources [9]. The ISS is composed of various truss segments, solar panels, thermal radiator panels, and modules for laboratories and crew accommodations. A tracking system supplemental to GPS is desirable both to improve accuracy and to eliminate the structural blockage due to the close proximity of the ISS which could at times limit the number of GPS satellites accessible to the Mini-AERCam. Ideally, the tracking system will be a passive component of the communication system which will need to operate in a time-varying multipath environment created as the robot camera moves over the ISS structure. In addition, due to many interference sources located on the ISS, SSO, LEO satellites and ground-based transmitters, selecting a frequency for the ISS and Mini-AERCam link which will coexist with all interferers poses a major design challenge. To meet all of these challenges, ultrawideband (UWB) radio technology is being studied for use in the Mini-AERCam communication and tracking subsystem. The research described in this report is focused on design and evaluation of passive tracking system algorithms based on UWB radio transmissions from mini-AERCam.

Radar for tracer particles

NASA Astrophysics Data System (ADS)

Ott, Felix; Herminghaus, Stephan; Huang, Kai

2017-05-01

We introduce a radar system capable of tracking a 5 mm spherical target continuously in three dimensions. The 10 GHz (X-band) radar system has a transmission power of 1 W and operates in the near field of the horn antennae. By comparing the phase shift of the electromagnetic wave traveling through the free space with an IQ-mixer, we obtain the relative movement of the target with respect to the antennae. From the azimuth and inclination angles of the receiving antennae obtained in the calibration, we reconstruct the target trajectory in a three-dimensional Cartesian system. Finally, we test the tracking algorithm with target moving in circular as well as in pendulum motions and discuss the capability of the radar system.

A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS

PubMed Central

Liu, Jingbin; Chen, Ruizhi; Pei, Ling; Guinness, Robert; Kuusniemi, Heidi

2012-01-01

Smartphone positioning is an enabling technology used to create new business in the navigation and mobile location-based services (LBS) industries. This paper presents a smartphone indoor positioning engine named HIPE that can be easily integrated with mobile LBS. HIPE is a hybrid solution that fuses measurements of smartphone sensors with wireless signals. The smartphone sensors are used to measure the user’s motion dynamics information (MDI), which represent the spatial correlation of various locations. Two algorithms based on hidden Markov model (HMM) problems, the grid-based filter and the Viterbi algorithm, are used in this paper as the central processor for data fusion to resolve the position estimates, and these algorithms are applicable for different applications, e.g., real-time navigation and location tracking, respectively. HIPE is more widely applicable for various motion scenarios than solutions proposed in previous studies because it uses no deterministic motion models, which have been commonly used in previous works. The experimental results showed that HIPE can provide adequate positioning accuracy and robustness for different scenarios of MDI combinations. HIPE is a cost-efficient solution, and it can work flexibly with different smartphone platforms, which may have different types of sensors available for the measurement of MDI data. The reliability of the positioning solution was found to increase with increasing precision of the MDI data. PMID:23235455

Optical tweezers with 2.5 kHz bandwidth video detection for single-colloid electrophoresis

NASA Astrophysics Data System (ADS)

Otto, Oliver; Gutsche, Christof; Kremer, Friedrich; Keyser, Ulrich F.

2008-02-01

We developed an optical tweezers setup to study the electrophoretic motion of colloids in an external electric field. The setup is based on standard components for illumination and video detection. Our video based optical tracking of the colloid motion has a time resolution of 0.2ms, resulting in a bandwidth of 2.5kHz. This enables calibration of the optical tweezers by Brownian motion without applying a quadrant photodetector. We demonstrate that our system has a spatial resolution of 0.5nm and a force sensitivity of 20fN using a Fourier algorithm to detect periodic oscillations of the trapped colloid caused by an external ac field. The electrophoretic mobility and zeta potential of a single colloid can be extracted in aqueous solution avoiding screening effects common for usual bulk measurements.

Object tracking using multiple camera video streams

NASA Astrophysics Data System (ADS)

Mehrubeoglu, Mehrube; Rojas, Diego; McLauchlan, Lifford

2010-05-01

Two synchronized cameras are utilized to obtain independent video streams to detect moving objects from two different viewing angles. The video frames are directly correlated in time. Moving objects in image frames from the two cameras are identified and tagged for tracking. One advantage of such a system involves overcoming effects of occlusions that could result in an object in partial or full view in one camera, when the same object is fully visible in another camera. Object registration is achieved by determining the location of common features in the moving object across simultaneous frames. Perspective differences are adjusted. Combining information from images from multiple cameras increases robustness of the tracking process. Motion tracking is achieved by determining anomalies caused by the objects' movement across frames in time in each and the combined video information. The path of each object is determined heuristically. Accuracy of detection is dependent on the speed of the object as well as variations in direction of motion. Fast cameras increase accuracy but limit the speed and complexity of the algorithm. Such an imaging system has applications in traffic analysis, surveillance and security, as well as object modeling from multi-view images. The system can easily be expanded by increasing the number of cameras such that there is an overlap between the scenes from at least two cameras in proximity. An object can then be tracked long distances or across multiple cameras continuously, applicable, for example, in wireless sensor networks for surveillance or navigation.

SU-G-JeP4-03: Anomaly Detection of Respiratory Motion by Use of Singular Spectrum Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kotoku, J; Kumagai, S; Nakabayashi, S

Purpose: The implementation and realization of automatic anomaly detection of respiratory motion is a very important technique to prevent accidental damage during radiation therapy. Here, we propose an automatic anomaly detection method using singular value decomposition analysis. Methods: The anomaly detection procedure consists of four parts:1) measurement of normal respiratory motion data of a patient2) calculation of a trajectory matrix representing normal time-series feature3) real-time monitoring and calculation of a trajectory matrix of real-time data.4) calculation of an anomaly score from the similarity of the two feature matrices. Patient motion was observed by a marker-less tracking system using a depthmore » camera. Results: Two types of motion e.g. cough and sudden stop of breathing were successfully detected in our real-time application. Conclusion: Automatic anomaly detection of respiratory motion using singular spectrum analysis was successful in the cough and sudden stop of breathing. The clinical use of this algorithm will be very hopeful. This work was supported by JSPS KAKENHI Grant Number 15K08703.« less

Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization

NASA Astrophysics Data System (ADS)

Raghunath, N.; Faber, T. L.; Suryanarayanan, S.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.

Knowledge-based vision for space station object motion detection, recognition, and tracking

NASA Technical Reports Server (NTRS)

Symosek, P.; Panda, D.; Yalamanchili, S.; Wehner, W., III

1987-01-01

Computer vision, especially color image analysis and understanding, has much to offer in the area of the automation of Space Station tasks such as construction, satellite servicing, rendezvous and proximity operations, inspection, experiment monitoring, data management and training. Knowledge-based techniques improve the performance of vision algorithms for unstructured environments because of their ability to deal with imprecise a priori information or inaccurately estimated feature data and still produce useful results. Conventional techniques using statistical and purely model-based approaches lack flexibility in dealing with the variabilities anticipated in the unstructured viewing environment of space. Algorithms developed under NASA sponsorship for Space Station applications to demonstrate the value of a hypothesized architecture for a Video Image Processor (VIP) are presented. Approaches to the enhancement of the performance of these algorithms with knowledge-based techniques and the potential for deployment of highly-parallel multi-processor systems for these algorithms are discussed.

A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

PubMed

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa; Hu, Yanle

2016-03-08

On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image-guided radiotherapy (MR-IGRT) system. Manual con-tours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR-TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR-TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD-LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP-TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high-contrast images (i.e., kidney), the thresholding method provided the best speed (< 1 ms) with a satisfying accuracy (Dice = 0.95). When the image contrast was low, the VR-TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of different methods for optimal segmentation with the on-board MR-IGRT system.

Three-Dimensional Eye Tracking in a Surgical Scenario.

PubMed

Bogdanova, Rositsa; Boulanger, Pierre; Zheng, Bin

2015-10-01

Eye tracking has been widely used in studying the eye behavior of surgeons in the past decade. Most eye-tracking data are reported in a 2-dimensional (2D) fashion, and data for describing surgeons' behaviors on stereoperception are often missed. With the introduction of stereoscopes in laparoscopic procedures, there is an increasing need for studying the depth perception of surgeons under 3D image-guided surgery. We developed a new algorithm for the computation of convergence points in stereovision by measuring surgeons' interpupillary distance, the distance to the view target, and the difference between gaze locations of the 2 eyes. To test the feasibility of our new algorithm, we recruited 10 individuals to watch stereograms using binocular disparity and asked them to develop stereoperception using a cross-eyed viewing technique. Participants' eye motions were recorded by the Tobii eye tracker while they performed the trials. Convergence points between normal and stereo-viewing conditions were computed using the developed algorithm. All 10 participants were able to develop stereovision after a short period of training. During stereovision, participants' eye convergence points were 14 ± 1 cm in front of their eyes, which was significantly closer than the convergence points under the normal viewing condition (77 ± 20 cm). By applying our method of calculating convergence points using eye tracking, we were able to elicit the eye movement patterns of human operators between the normal and stereovision conditions. Knowledge from this study can be applied to the design of surgical visual systems, with the goal of improving surgical performance and patient safety. © The Author(s) 2015.

Decentralized Adaptive Control For Robots

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1989-01-01

Precise knowledge of dynamics not required. Proposed scheme for control of multijointed robotic manipulator calls for independent control subsystem for each joint, consisting of proportional/integral/derivative feedback controller and position/velocity/acceleration feedforward controller, both with adjustable gains. Independent joint controller compensates for unpredictable effects, gravitation, and dynamic coupling between motions of joints, while forcing joints to track reference trajectories. Scheme amenable to parallel processing in distributed computing system wherein each joint controlled by relatively simple algorithm on dedicated microprocessor.

Digital stereophotogrammetry based on circular markers and zooming cameras: evaluation of a method for 3D analysis of small motions in orthopaedic research

PubMed Central

2011-01-01

Background Orthopaedic research projects focusing on small displacements in a small measurement volume require a radiation free, three dimensional motion analysis system. A stereophotogrammetrical motion analysis system can track wireless, small, light-weight markers attached to the objects. Thereby the disturbance of the measured objects through the marker tracking can be kept at minimum. The purpose of this study was to develop and evaluate a non-position fixed compact motion analysis system configured for a small measurement volume and able to zoom while tracking small round flat markers in respect to a fiducial marker which was used for the camera pose estimation. Methods The system consisted of two web cameras and the fiducial marker placed in front of them. The markers to track were black circles on a white background. The algorithm to detect a centre of the projected circle on the image plane was described and applied. In order to evaluate the accuracy (mean measurement error) and precision (standard deviation of the measurement error) of the optical measurement system, two experiments were performed: 1) inter-marker distance measurement and 2) marker displacement measurement. Results The first experiment of the 10 mm distances measurement showed a total accuracy of 0.0086 mm and precision of ± 0.1002 mm. In the second experiment, translations from 0.5 mm to 5 mm were measured with total accuracy of 0.0038 mm and precision of ± 0.0461 mm. The rotations of 2.25° amount were measured with the entire accuracy of 0.058° and the precision was of ± 0.172°. Conclusions The description of the non-proprietary measurement device with very good levels of accuracy and precision may provide opportunities for new, cost effective applications of stereophotogrammetrical analysis in musculoskeletal research projects, focusing on kinematics of small displacements in a small measurement volume. PMID:21284867

Tracking and characterizing the head motion of unanaesthetized rats in positron emission tomography

PubMed Central

Kyme, Andre; Meikle, Steven; Baldock, Clive; Fulton, Roger

2012-01-01

Positron emission tomography (PET) is an important in vivo molecular imaging technique for translational research. Imaging unanaesthetized rats using motion-compensated PET avoids the confounding impact of anaesthetic drugs and enables animals to be imaged during normal or evoked behaviour. However, there is little published data on the nature of rat head motion to inform the design of suitable marker-based motion-tracking set-ups for brain imaging—specifically, set-ups that afford close to uninterrupted tracking. We performed a systematic study of rat head motion parameters for unanaesthetized tube-bound and freely moving rats with a view to designing suitable motion-tracking set-ups in each case. For tube-bound rats, using a single appropriately placed binocular tracker, uninterrupted tracking was possible greater than 95 per cent of the time. For freely moving rats, simulations and measurements of a live subject indicated that two opposed binocular trackers are sufficient (less than 10% interruption to tracking) for a wide variety of behaviour types. We conclude that reliable tracking of head pose can be achieved with marker-based optical-motion-tracking systems for both tube-bound and freely moving rats undergoing PET studies without sedation. PMID:22718992

Ocular tracking responses to background motion gated by feature-based attention.

PubMed

Souto, David; Kerzel, Dirk

2014-09-01

Involuntary ocular tracking responses to background motion offer a window on the dynamics of motion computations. In contrast to spatial attention, we know little about the role of feature-based attention in determining this ocular response. To probe feature-based effects of background motion on involuntary eye movements, we presented human observers with a balanced background perturbation. Two clouds of dots moved in opposite vertical directions while observers tracked a target moving in horizontal direction. Additionally, they had to discriminate a change in the direction of motion (±10° from vertical) of one of the clouds. A vertical ocular following response occurred in response to the motion of the attended cloud. When motion selection was based on motion direction and color of the dots, the peak velocity of the tracking response was 30% of the tracking response elicited in a single task with only one direction of background motion. In two other experiments, we tested the effect of the perturbation when motion selection was based on color, by having motion direction vary unpredictably, or on motion direction alone. Although the gain of pursuit in the horizontal direction was significantly reduced in all experiments, indicating a trade-off between perceptual and oculomotor tasks, ocular responses to perturbations were only observed when selection was based on both motion direction and color. It appears that selection by motion direction can only be effective for driving ocular tracking when the relevant elements can be segregated before motion onset. Copyright © 2014 the American Physiological Society.

Evaluation of the clinical efficacy of the PeTrack motion tracking system for respiratory gating in cardiac PET imaging

NASA Astrophysics Data System (ADS)

Manwell, Spencer; Chamberland, Marc J. P.; Klein, Ran; Xu, Tong; deKemp, Robert

2017-03-01

Respiratory gating is a common technique used to compensate for patient breathing motion and decrease the prevalence of image artifacts that can impact diagnoses. In this study a new data-driven respiratory gating method (PeTrack) was compared with a conventional optical tracking system. The performance of respiratory gating of the two systems was evaluated by comparing the number of respiratory triggers, patient breathing intervals and gross heart motion as measured in the respiratory-gated image reconstructions of rubidium-82 cardiac PET scans in test and control groups consisting of 15 and 8 scans, respectively. We found evidence suggesting that PeTrack is a robust patient motion tracking system that can be used to retrospectively assess patient motion in the event of failure of the conventional optical tracking system.

Research on target tracking algorithm based on spatio-temporal context

NASA Astrophysics Data System (ADS)

Li, Baiping; Xu, Sanmei; Kang, Hongjuan

2017-07-01

In this paper, a novel target tracking algorithm based on spatio-temporal context is proposed. During the tracking process, the camera shaking or occlusion may lead to the failure of tracking. The proposed algorithm can solve this problem effectively. The method use the spatio-temporal context algorithm as the main research object. We get the first frame's target region via mouse. Then the spatio-temporal context algorithm is used to get the tracking targets of the sequence of frames. During this process a similarity measure function based on perceptual hash algorithm is used to judge the tracking results. If tracking failed, reset the initial value of Mean Shift algorithm for the subsequent target tracking. Experiment results show that the proposed algorithm can achieve real-time and stable tracking when camera shaking or target occlusion.

Image velocimetry for clouds with relaxation labeling based on deformation consistency

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2017-08-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.

Associating optical measurements and estimating orbits of geocentric objects with a Genetic Algorithm: performance limitations.

NASA Astrophysics Data System (ADS)

Zittersteijn, Michiel; Schildknecht, Thomas; Vananti, Alessandro; Dolado Perez, Juan Carlos; Martinot, Vincent

2016-07-01

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention. This problem is also known as the Multiple Target Tracking (MTT) problem. The complexity of the MTT problem is defined by its dimension S. Current research tends to focus on the S = 2 MTT problem. The reason for this is that for S = 2 the problem has a P-complexity. However, with S = 2 the decision to associate a set of observations is based on the minimum amount of information, in ambiguous situations (e.g. satellite clusters) this will lead to incorrect associations. The S > 2 MTT problem is an NP-hard combinatorial optimization problem. In previous work an Elitist Genetic Algorithm (EGA) was proposed as a method to approximately solve this problem. It was shown that the EGA is able to find a good approximate solution with a polynomial time complexity. The EGA relies on solving the Lambert problem in order to perform the necessary orbit determinations. This means that the algorithm is restricted to orbits that are described by Keplerian motion. The work presented in this paper focuses on the impact that this restriction has on the algorithm performance.

A review of vision-based motion analysis in sport.

PubMed

Barris, Sian; Button, Chris

2008-01-01

Efforts at player motion tracking have traditionally involved a range of data collection techniques from live observation to post-event video analysis where player movement patterns are manually recorded and categorized to determine performance effectiveness. Due to the considerable time required to manually collect and analyse such data, research has tended to focus only on small numbers of players within predefined playing areas. Whilst notational analysis is a convenient, practical and typically inexpensive technique, the validity and reliability of the process can vary depending on a number of factors, including how many observers are used, their experience, and the quality of their viewing perspective. Undoubtedly the application of automated tracking technology to team sports has been hampered because of inadequate video and computational facilities available at sports venues. However, the complex nature of movement inherent to many physical activities also represents a significant hurdle to overcome. Athletes tend to exhibit quick and agile movements, with many unpredictable changes in direction and also frequent collisions with other players. Each of these characteristics of player behaviour violate the assumptions of smooth movement on which computer tracking algorithms are typically based. Systems such as TRAKUS, SoccerMan, TRAKPERFORMANCE, Pfinder and Prozone all provide extrinsic feedback information to coaches and athletes. However, commercial tracking systems still require a fair amount of operator intervention to process the data after capture and are often limited by the restricted capture environments that can be used and the necessity for individuals to wear tracking devices. Whilst some online tracking systems alleviate the requirements of manual tracking, to our knowledge a completely automated system suitable for sports performance is not yet commercially available. Automatic motion tracking has been used successfully in other domains outside of elite sport performance, notably for surveillance in the military and security industry where automatic recognition of moving objects is achievable because identification of the objects is not necessary. The current challenge is to obtain appropriate video sequences that can robustly identify and label people over time, in a cluttered environment containing multiple interacting people. This problem is often compounded by the quality of video capture, the relative size and occlusion frequency of people, and also changes in illumination. Potential applications of an automated motion detection system are offered, such as: planning tactics and strategies; measuring team organisation; providing meaningful kinematic feedback; and objective measures of intervention effectiveness in team sports, which could benefit coaches, players, and sports scientists.

Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

PubMed

Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

2017-10-01

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

A novel four-bar linkage prosthetic knee based on magnetorheological effect: principle, structure, simulation and control

NASA Astrophysics Data System (ADS)

Xu, Lei; Wang, Dai-Hua; Fu, Qiang; Yuan, Gang; Hu, Lei-Zi

2016-11-01

In this paper, the principle and structure of the four-bar linkage prosthetic knee based on the magnetorheological effect (FLPKME) are proposed and realized by individually integrating the upper and lower link rods of the four-bar linkage with the piston rod and the outer cylinder of the magnetorheological (MR) damper. The integrated MR damper, in which the MR fluid is operated in the shear mode, has a double-ended structure. The prototype of the FLPKME is designed and fabricated. Utilizing the developed FLPKME, the lower limb prosthesis is developed, modeled, and simulated. On these bases, the control algorithm for the FLPKME is developed. A test platform for the FLPKME is developed and the performance of the FLPKME with seven constant currents and controlled currents by the control algorithm developed in this paper are experimentally tested. The results show that the FLPKME with a constant current of 1.6 A possesses the basic stable gait, and the FLPKME with the controlled currents by the control algorithm developed in this paper is able to track the motions well and to imitate the natural motions of a healthy human knee joint.

A difference tracking algorithm based on discrete sine transform

NASA Astrophysics Data System (ADS)

Liu, HaoPeng; Yao, Yong; Lei, HeBing; Wu, HaoKun

2018-04-01

Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.

Loop shaping design for tracking performance in machine axes.

PubMed

Schinstock, Dale E; Wei, Zhouhong; Yang, Tao

2006-01-01

A modern interpretation of classical loop shaping control design methods is presented in the context of tracking control for linear motor stages. Target applications include noncontacting machines such as laser cutters and markers, water jet cutters, and adhesive applicators. The methods are directly applicable to the common PID controller and are pertinent to many electromechanical servo actuators other than linear motors. In addition to explicit design techniques a PID tuning algorithm stressing the importance of tracking is described. While the theory behind these techniques is not new, the analysis of their application to modern systems is unique in the research literature. The techniques and results should be important to control practitioners optimizing PID controller designs for tracking and in comparing results from classical designs to modern techniques. The methods stress high-gain controller design and interpret what this means for PID. Nothing in the methods presented precludes the addition of feedforward control methods for added improvements in tracking. Laboratory results from a linear motor stage demonstrate that with large open-loop gain very good tracking performance can be achieved. The resultant tracking errors compare very favorably to results from similar motions on similar systems that utilize much more complicated controllers.

Radiotherapy beyond cancer: Target localization in real-time MRI and treatment planning for cardiac radiosurgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ipsen, S.; Blanck, O.; Rades, D.

2014-12-15

Purpose: Atrial fibrillation (AFib) is the most common cardiac arrhythmia that affects millions of patients world-wide. AFib is usually treated with minimally invasive, time consuming catheter ablation techniques. While recently noninvasive radiosurgery to the pulmonary vein antrum (PVA) in the left atrium has been proposed for AFib treatment, precise target location during treatment is challenging due to complex respiratory and cardiac motion. A MRI linear accelerator (MRI-Linac) could solve the problems of motion tracking and compensation using real-time image guidance. In this study, the authors quantified target motion ranges on cardiac magnetic resonance imaging (MRI) and analyzed the dosimetric benefitsmore » of margin reduction assuming real-time motion compensation was applied. Methods: For the imaging study, six human subjects underwent real-time cardiac MRI under free breathing. The target motion was analyzed retrospectively using a template matching algorithm. The planning study was conducted on a CT of an AFib patient with a centrally located esophagus undergoing catheter ablation, representing an ideal case for cardiac radiosurgery. The target definition was similar to the ablation lesions at the PVA created during catheter treatment. Safety margins of 0 mm (perfect tracking) to 8 mm (untracked respiratory motion) were added to the target, defining the planning target volume (PTV). For each margin, a 30 Gy single fraction IMRT plan was generated. Additionally, the influence of 1 and 3 T magnetic fields on the treatment beam delivery was simulated using Monte Carlo calculations to determine the dosimetric impact of MRI guidance for two different Linac positions. Results: Real-time cardiac MRI showed mean respiratory target motion of 10.2 mm (superior–inferior), 2.4 mm (anterior–posterior), and 2 mm (left–right). The planning study showed that increasing safety margins to encompass untracked respiratory motion leads to overlapping structures even in the ideal scenario, compromising either normal tissue dose constraints or PTV coverage. The magnetic field caused a slight increase in the PTV dose with the in-line MRI-Linac configuration. Conclusions: The authors’ results indicate that real-time tracking and motion compensation are mandatory for cardiac radiosurgery and MRI-guidance is feasible, opening the possibility of treating cardiac arrhythmia patients completely noninvasively.« less

Role of quality of service metrics in visual target acquisition and tracking in resource constrained environments

NASA Astrophysics Data System (ADS)

Anderson, Monica; David, Phillip

2007-04-01

Implementation of an intelligent, automated target acquisition and tracking systems alleviates the need for operators to monitor video continuously. This system could identify situations that fatigued operators could easily miss. If an automated acquisition and tracking system plans motions to maximize a coverage metric, how does the performance of that system change when the user intervenes and manually moves the camera? How can the operator give input to the system about what is important and understand how that relates to the overall task balance between surveillance and coverage? In this paper, we address these issues by introducing a new formulation of the average linear uncovered length (ALUL) metric, specially designed for use in surveilling urban environments. This metric coordinates the often competing goals of acquiring new targets and tracking existing targets. In addition, it provides current system performance feedback to system users in terms of the system's theoretical maximum and minimum performance. We show the successful integration of the algorithm via simulation.

Dynamic MRI of Grid-Tagged Hyperpolarized Helium-3 for the Assessment of Lung Motion During Breathing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai Jing; Sheng Ke; Benedict, Stanley H.

2009-09-01

Purpose: To develop a dynamic magnetic resonance imaging (MRI) tagging technique using hyperpolarized helium-3 (HP He-3) to track lung motion. Methods and Materials: An accelerated non-Cartesian k-space trajectory was used to gain acquisition speed, at the cost of introducing image artifacts, providing a viable strategy for obtaining whole-lung coverage with adequate temporal resolution. Multiple-slice two-dimensional dynamic images of the lung were obtained in three healthy subjects after inhaling He-3 gas polarized to 35%-40%. Displacement, strain, and ventilation maps were computed from the observed motion of the grid peaks. Results: Both temporal and spatial variations of pulmonary mechanics were observed inmore » normal subjects, including shear motion between different lobes of the same lung. Conclusion: These initial results suggest that dynamic imaging of grid-tagged hyperpolarized magnetization may potentially be a powerful tool for observing and quantifying pulmonary biomechanics on a regional basis and for assessing, validating, and improving lung deformable image registration algorithms.« less

A Motion Tracking and Sensor Fusion Module for Medical Simulation.

PubMed

Shen, Yunhe; Wu, Fan; Tseng, Kuo-Shih; Ye, Ding; Raymond, John; Konety, Badrinath; Sweet, Robert

2016-01-01

Here we introduce a motion tracking or navigation module for medical simulation systems. Our main contribution is a sensor fusion method for proximity or distance sensors integrated with inertial measurement unit (IMU). Since IMU rotation tracking has been widely studied, we focus on the position or trajectory tracking of the instrument moving freely within a given boundary. In our experiments, we have found that this module reliably tracks instrument motion.

A Hierarchical Approach to Target Recognition and Tracking. Summary of Results for the Period April 1, 1989-November 30, 1989

DTIC Science & Technology

1990-02-07

performance assessment, human intervention, or operator training. Algorithms on different levels are allowed to deal with the world with different degrees...have on the decisions made by the driver are a complex combination of human factors, driving experience, mission objectives, tactics, etc., and...motion. The distinction here is that the decision making program may I 12 1 I not necessarily make its decisions based on the same factors as the human

Motion estimation of subcellular structures from fluorescence microscopy images.

PubMed

Vallmitjana, A; Civera-Tregon, A; Hoenicka, J; Palau, F; Benitez, R

2017-07-01

We present an automatic image processing framework to study moving intracellular structures from live cell fluorescence microscopy. The system includes the identification of static and dynamic structures from time-lapse images using data clustering as well as the identification of the trajectory of moving objects with a probabilistic tracking algorithm. The method has been successfully applied to study mitochondrial movement in neurons. The approach provides excellent performance under different experimental conditions and is robust to common sources of noise including experimental, molecular and biological fluctuations.

Registration of 4D time-series of cardiac images with multichannel Diffeomorphic Demons.

PubMed

Peyrat, Jean-Marc; Delingette, Hervé; Sermesant, Maxime; Pennec, Xavier; Xu, Chenyang; Ayache, Nicholas

2008-01-01

In this paper, we propose a generic framework for intersubject non-linear registration of 4D time-series images. In this framework, spatio-temporal registration is defined by mapping trajectories of physical points as opposed to spatial registration that solely aims at mapping homologous points. First, we determine the trajectories we want to register in each sequence using a motion tracking algorithm based on the Diffeomorphic Demons algorithm. Then, we perform simultaneously pairwise registrations of corresponding time-points with the constraint to map the same physical points over time. We show this trajectory registration can be formulated as a multichannel registration of 3D images. We solve it using the Diffeomorphic Demons algorithm extended to vector-valued 3D images. This framework is applied to the inter-subject non-linear registration of 4D cardiac CT sequences.

Kinematic Model-Based Pedestrian Dead Reckoning for Heading Correction and Lower Body Motion Tracking.

PubMed

Lee, Min Su; Ju, Hojin; Song, Jin Woo; Park, Chan Gook

2015-11-06

In this paper, we present a method for finding the enhanced heading and position of pedestrians by fusing the Zero velocity UPdaTe (ZUPT)-based pedestrian dead reckoning (PDR) and the kinematic constraints of the lower human body. ZUPT is a well known algorithm for PDR, and provides a sufficiently accurate position solution for short term periods, but it cannot guarantee a stable and reliable heading because it suffers from magnetic disturbance in determining heading angles, which degrades the overall position accuracy as time passes. The basic idea of the proposed algorithm is integrating the left and right foot positions obtained by ZUPTs with the heading and position information from an IMU mounted on the waist. To integrate this information, a kinematic model of the lower human body, which is calculated by using orientation sensors mounted on both thighs and calves, is adopted. We note that the position of the left and right feet cannot be apart because of the kinematic constraints of the body, so the kinematic model generates new measurements for the waist position. The Extended Kalman Filter (EKF) on the waist data that estimates and corrects error states uses these measurements and magnetic heading measurements, which enhances the heading accuracy. The updated position information is fed into the foot mounted sensors, and reupdate processes are performed to correct the position error of each foot. The proposed update-reupdate technique consequently ensures improved observability of error states and position accuracy. Moreover, the proposed method provides all the information about the lower human body, so that it can be applied more effectively to motion tracking. The effectiveness of the proposed algorithm is verified via experimental results, which show that a 1.25% Return Position Error (RPE) with respect to walking distance is achieved.

Development of a two photon microscope for tracking Drosophila larvae

NASA Astrophysics Data System (ADS)

Karagyozov, Doycho; Mihovilovic Skanata, Mirna; Gershow, Marc

Current in vivo methods for measuring neural activity in Drosophila larva require immobilization of the animal. Although we can record neural signals while stimulating the sensory organs, we cannot read the behavioral output because we have prevented the animal from moving. Many research questions cannot be answered without observation of neural activity in behaving (freely-moving) animals. We incorporated a Tunable Acoustic Gradient (TAG) lens into a two-photon microscope to achieve a 70kHz axial scan rate, enabling volumetric imaging at tens of hertz. We then implemented a tracking algorithm based on a Kalman filter to maintain the neurons of interest in the field of view and in focus during the rapid three dimensional motion of a free larva. Preliminary results show successful tracking of a neuron moving at speeds reaching 500 μm/s. NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

An adaptive trajectory tracking control of four rotor hover vehicle using extended normalized radial basis function network

NASA Astrophysics Data System (ADS)

ul Amin, Rooh; Aijun, Li; Khan, Muhammad Umer; Shamshirband, Shahaboddin; Kamsin, Amirrudin

2017-01-01

In this paper, an adaptive trajectory tracking controller based on extended normalized radial basis function network (ENRBFN) is proposed for 3-degree-of-freedom four rotor hover vehicle subjected to external disturbance i.e. wind turbulence. Mathematical model of four rotor hover system is developed using equations of motions and a new computational intelligence based technique ENRBFN is introduced to approximate the unmodeled dynamics of the hover vehicle. The adaptive controller based on the Lyapunov stability approach is designed to achieve tracking of the desired attitude angles of four rotor hover vehicle in the presence of wind turbulence. The adaptive weight update based on the Levenberg-Marquardt algorithm is used to avoid weight drift in case the system is exposed to external disturbances. The closed-loop system stability is also analyzed using Lyapunov stability theory. Simulations and experimental results are included to validate the effectiveness of the proposed control scheme.

Trans-dimensional MCMC methods for fully automatic motion analysis in tagged MRI.

PubMed

Smal, Ihor; Carranza-Herrezuelo, Noemí; Klein, Stefan; Niessen, Wiro; Meijering, Erik

2011-01-01

Tagged magnetic resonance imaging (tMRI) is a well-known noninvasive method allowing quantitative analysis of regional heart dynamics. Its clinical use has so far been limited, in part due to the lack of robustness and accuracy of existing tag tracking algorithms in dealing with low (and intrinsically time-varying) image quality. In this paper, we propose a novel probabilistic method for tag tracking, implemented by means of Bayesian particle filtering and a trans-dimensional Markov chain Monte Carlo (MCMC) approach, which efficiently combines information about the imaging process and tag appearance with prior knowledge about the heart dynamics obtained by means of non-rigid image registration. Experiments using synthetic image data (with ground truth) and real data (with expert manual annotation) from preclinical (small animal) and clinical (human) studies confirm that the proposed method yields higher consistency, accuracy, and intrinsic tag reliability assessment in comparison with other frequently used tag tracking methods.

Development of a real-time internal and external marker tracking system for particle therapy: a phantom study using patient tumor trajectory data.

PubMed

Cho, Junsang; Cheon, Wonjoong; Ahn, Sanghee; Jung, Hyunuk; Sheen, Heesoon; Park, Hee Chul; Han, Youngyih

2017-09-01

Target motion-induced uncertainty in particle therapy is more complicated than that in X-ray therapy, requiring more accurate motion management. Therefore, a hybrid motion-tracking system that can track internal tumor motion and as well as an external surrogate of tumor motion was developed. Recently, many correlation tests between internal and external markers in X-ray therapy have been developed; however, the accuracy of such internal/external marker tracking systems, especially in particle therapy, has not yet been sufficiently tested. In this article, the process of installing an in-house hybrid internal/external motion-tracking system is described and the accuracy level of tracking system was acquired. Our results demonstrated that the developed in-house external/internal combined tracking system has submillimeter accuracy, and can be clinically used as a particle therapy system as well as a simulation system for moving tumor treatment. © The Author 2017. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Facial motion parameter estimation and error criteria in model-based image coding

NASA Astrophysics Data System (ADS)

Liu, Yunhai; Yu, Lu; Yao, Qingdong

2000-04-01

Model-based image coding has been given extensive attention due to its high subject image quality and low bit-rates. But the estimation of object motion parameter is still a difficult problem, and there is not a proper error criteria for the quality assessment that are consistent with visual properties. This paper presents an algorithm of the facial motion parameter estimation based on feature point correspondence and gives the motion parameter error criteria. The facial motion model comprises of three parts. The first part is the global 3-D rigid motion of the head, the second part is non-rigid translation motion in jaw area, and the third part consists of local non-rigid expression motion in eyes and mouth areas. The feature points are automatically selected by a function of edges, brightness and end-node outside the blocks of eyes and mouth. The numbers of feature point are adjusted adaptively. The jaw translation motion is tracked by the changes of the feature point position of jaw. The areas of non-rigid expression motion can be rebuilt by using block-pasting method. The estimation approach of motion parameter error based on the quality of reconstructed image is suggested, and area error function and the error function of contour transition-turn rate are used to be quality criteria. The criteria reflect the image geometric distortion caused by the error of estimated motion parameters properly.

4D motion modeling of the coronary arteries from CT images for robotic assisted minimally invasive surgery

NASA Astrophysics Data System (ADS)

Zhang, Dong Ping; Edwards, Eddie; Mei, Lin; Rueckert, Daniel

2009-02-01

In this paper, we present a novel approach for coronary artery motion modeling from cardiac Computed Tomography( CT) images. The aim of this work is to develop a 4D motion model of the coronaries for image guidance in robotic-assisted totally endoscopic coronary artery bypass (TECAB) surgery. To utilize the pre-operative cardiac images to guide the minimally invasive surgery, it is essential to have a 4D cardiac motion model to be registered with the stereo endoscopic images acquired intraoperatively using the da Vinci robotic system. In this paper, we are investigating the extraction of the coronary arteries and the modelling of their motion from a dynamic sequence of cardiac CT. We use a multi-scale vesselness filter to enhance vessels in the cardiac CT images. The centerlines of the arteries are extracted using a ridge traversal algorithm. Using this method the coronaries can be extracted in near real-time as only local information is used in vessel tracking. To compute the deformation of the coronaries due to cardiac motion, the motion is extracted from a dynamic sequence of cardiac CT. Each timeframe in this sequence is registered to the end-diastole timeframe of the sequence using a non-rigid registration algorithm based on free-form deformations. Once the images have been registered a dynamic motion model of the coronaries can be obtained by applying the computed free-form deformations to the extracted coronary arteries. To validate the accuracy of the motion model we compare the actual position of the coronaries in each time frame with the predicted position of the coronaries as estimated from the non-rigid registration. We expect that this motion model of coronaries can facilitate the planning of TECAB surgery, and through the registration with real-time endoscopic video images it can reduce the conversion rate from TECAB to conventional procedures.

Learning Activity Models for Multiple Agents in a Smart Space

NASA Astrophysics Data System (ADS)

Crandall, Aaron; Cook, Diane J.

With the introduction of more complex intelligent environment systems, the possibilities for customizing system behavior have increased dramatically. Significant headway has been made in tracking individuals through spaces using wireless devices [1, 18, 26] and in recognizing activities within the space based on video data (see chapter by Brubaker et al. and [6, 8, 23]), motion sensor data [9, 25], wearable sensors [13] or other sources of information [14, 15, 22]. However, much of the theory and most of the algorithms are designed to handle one individual in the space at a time. Resident tracking, activity recognition, event prediction, and behavior automation becomes significantly more difficult for multi-agent situations, when there are multiple residents in the environment.

Stationary nonimaging lenses for solar concentration.

PubMed

Kotsidas, Panagiotis; Chatzi, Eleni; Modi, Vijay

2010-09-20

A novel approach for the design of refractive lenses is presented, where the lens is mounted on a stationary aperture and the Sun is tracked by a moving solar cell. The purpose of this work is to design a quasi-stationary concentrator by replacing the two-axis tracking of the Sun with internal motion of the miniaturized solar cell inside the module. Families of lenses are designed with a variation of the simultaneous multiple surface technique in which the sawtooth genetic algorithm is implemented to optimize the geometric variables of the optic in order to produce high fluxes for a range of incidence angles. Finally, we show examples of the technique for lenses with 60° and 30° acceptance half-angles, with low to medium attainable concentrations.

Adaptive mesh optimization and nonrigid motion recovery based image registration for wide-field-of-view ultrasound imaging.

PubMed

Tan, Chaowei; Wang, Bo; Liu, Paul; Liu, Dong

2008-01-01

Wide field of view (WFOV) imaging mode obtains an ultrasound image over an area much larger than the real time window normally available. As the probe is moved over the region of interest, new image frames are combined with prior frames to form a panorama image. Image registration techniques are used to recover the probe motion, eliminating the need for a position sensor. Speckle patterns, which are inherent in ultrasound imaging, change, or become decorrelated, as the scan plane moves, so we pre-smooth the image to reduce the effects of speckle in registration, as well as reducing effects from thermal noise. Because we wish to track the movement of features such as structural boundaries, we use an adaptive mesh over the entire smoothed image to home in on areas with feature. Motion estimation using blocks centered at the individual mesh nodes generates a field of motion vectors. After angular correction of motion vectors, we model the overall movement between frames as a nonrigid deformation. The polygon filling algorithm for precise, persistence-based spatial compounding constructs the final speckle reduced WFOV image.

SU-G-BRA-17: Tracking Multiple Targets with Independent Motion in Real-Time Using a Multi-Leaf Collimator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ge, Y; Keall, P; Poulsen, P

Purpose: Multiple targets with large intrafraction independent motion are often involved in advanced prostate, lung, abdominal, and head and neck cancer radiotherapy. Current standard of care treats these with the originally planned fields, jeopardizing the treatment outcomes. A real-time multi-leaf collimator (MLC) tracking method has been developed to address this problem for the first time. This study evaluates the geometric uncertainty of the multi-target tracking method. Methods: Four treatment scenarios are simulated based on a prostate IMAT plan to treat a moving prostate target and static pelvic node target: 1) real-time multi-target MLC tracking; 2) real-time prostate-only MLC tracking; 3)more » correcting for prostate interfraction motion at setup only; and 4) no motion correction. The geometric uncertainty of the treatment is assessed by the sum of the erroneously underexposed target area and overexposed healthy tissue areas for each individual target. Two patient-measured prostate trajectories of average 2 and 5 mm motion magnitude are used for simulations. Results: Real-time multi-target tracking accumulates the least uncertainty overall. As expected, it covers the static nodes similarly well as no motion correction treatment and covers the moving prostate similarly well as the real-time prostate-only tracking. Multi-target tracking reduces >90% of uncertainty for the static nodal target compared to the real-time prostate-only tracking or interfraction motion correction. For prostate target, depending on the motion trajectory which affects the uncertainty due to leaf-fitting, multi-target tracking may or may not perform better than correcting for interfraction prostate motion by shifting patient at setup, but it reduces ∼50% of uncertainty compared to no motion correction. Conclusion: The developed real-time multi-target MLC tracking can adapt for the independently moving targets better than other available treatment adaptations. This will enable PTV margin reduction to minimize health tissue toxicity while remain tumor coverage when treating advanced disease with independently moving targets involved. The authors acknowledge funding support from the Australian NHMRC Australia Fellowship and NHMRC Project Grant No. APP1042375.« less

Proper horizontal photospheric flows below an eruptive filament

NASA Astrophysics Data System (ADS)

Schmieder, Brigitte; Mein, Pierre; Mein, Nicole; Roudier, Thierry; Chandra, Ramseh

An analysis of the proper motions using SDO/HMI continuum images with the new version of the coherent structure tracking (CST) algorithm developed to track the granules as well as the large scale photospheric flows, was perfomed during three hours in a region containing a large filament channel on September 17, 2010. Supergranules were idenfied in the filament channel. Diverging flows inside the supergranules are similar in and out the filament channel. Using corks, we derived the passive scalar points and produced maps of cork distribution. The anchorage structures with the photosphere (feet) of the filament are located in the areas of converging flows with accumulations of corks. Averaging the velocity vectors for each latitude we defined a profile of the differential rotation. We conclude that the coupling between the convection and magnetic field in the photosphere is relatively strong. The filament experienced the convection motions through its feet. On a large scale point-of-view the differential rotation induced a shear of 0.1 km/s in the filament. On a small scale point-of-view convection motions favored the interaction/cancellation of the parasitic polarities at the base of the feet with the surrounding network explaining the brightenings,/jets and the eruption that were observed in the EUV filament.

Motion Cueing Algorithm Development: New Motion Cueing Program Implementation and Tuning

NASA Technical Reports Server (NTRS)

Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.; Kelly, Lon C.

2005-01-01

A computer program has been developed for the purpose of driving the NASA Langley Research Center Visual Motion Simulator (VMS). This program includes two new motion cueing algorithms, the optimal algorithm and the nonlinear algorithm. A general description of the program is given along with a description and flowcharts for each cueing algorithm, and also descriptions and flowcharts for subroutines used with the algorithms. Common block variable listings and a program listing are also provided. The new cueing algorithms have a nonlinear gain algorithm implemented that scales each aircraft degree-of-freedom input with a third-order polynomial. A description of the nonlinear gain algorithm is given along with past tuning experience and procedures for tuning the gain coefficient sets for each degree-of-freedom to produce the desired piloted performance. This algorithm tuning will be needed when the nonlinear motion cueing algorithm is implemented on a new motion system in the Cockpit Motion Facility (CMF) at the NASA Langley Research Center.

Disappearance of the inversion effect during memory-guided tracking of scrambled biological motion.

PubMed

Jiang, Changhao; Yue, Guang H; Chen, Tingting; Ding, Jinhong

2016-08-01

The human visual system is highly sensitive to biological motion. Even when a point-light walker is temporarily occluded from view by other objects, our eyes are still able to maintain tracking continuity. To investigate how the visual system establishes a correspondence between the biological-motion stimuli visible before and after the disruption, we used the occlusion paradigm with biological-motion stimuli that were intact or scrambled. The results showed that during visually guided tracking, both the observers' predicted times and predictive smooth pursuit were more accurate for upright biological motion (intact and scrambled) than for inverted biological motion. During memory-guided tracking, however, the processing advantage for upright as compared with inverted biological motion was not found in the scrambled condition, but in the intact condition only. This suggests that spatial location information alone is not sufficient to build and maintain the representational continuity of the biological motion across the occlusion, and that the object identity may act as an important information source in visual tracking. The inversion effect disappeared when the scrambled biological motion was occluded, which indicates that when biological motion is temporarily occluded and there is a complete absence of visual feedback signals, an oculomotor prediction is executed to maintain the tracking continuity, which is established not only by updating the target's spatial location, but also by the retrieval of identity information stored in long-term memory.

MapSentinel: Can the Knowledge of Space Use Improve Indoor Tracking Further?

PubMed Central

Jia, Ruoxi; Jin, Ming; Zou, Han; Yesilata, Yigitcan; Xie, Lihua; Spanos, Costas

2016-01-01

Estimating an occupant’s location is arguably the most fundamental sensing task in smart buildings. The applications for fine-grained, responsive building operations require the location sensing systems to provide location estimates in real time, also known as indoor tracking. Existing indoor tracking systems require occupants to carry specialized devices or install programs on their smartphone to collect inertial sensing data. In this paper, we propose MapSentinel, which performs non-intrusive location sensing based on WiFi access points and ultrasonic sensors. MapSentinel combines the noisy sensor readings with the floormap information to estimate locations. One key observation supporting our work is that occupants exhibit distinctive motion characteristics at different locations on the floormap, e.g., constrained motion along the corridor or in the cubicle zones, and free movement in the open space. While extensive research has been performed on using a floormap as a tool to obtain correct walking trajectories without wall-crossings, there have been few attempts to incorporate the knowledge of space use available from the floormap into the location estimation. This paper argues that the knowledge of space use as an additional information source presents new opportunities for indoor tracking. The fusion of heterogeneous information is theoretically formulated within the Factor Graph framework, and the Context-Augmented Particle Filtering algorithm is developed to efficiently solve real-time walking trajectories. Our evaluation in a large office space shows that the MapSentinel can achieve accuracy improvement of 31.3% compared with the purely WiFi-based tracking system. PMID:27049387

MapSentinel: Can the Knowledge of Space Use Improve Indoor Tracking Further?

PubMed

Jia, Ruoxi; Jin, Ming; Zou, Han; Yesilata, Yigitcan; Xie, Lihua; Spanos, Costas

2016-04-02

Estimating an occupant's location is arguably the most fundamental sensing task in smart buildings. The applications for fine-grained, responsive building operations require the location sensing systems to provide location estimates in real time, also known as indoor tracking. Existing indoor tracking systems require occupants to carry specialized devices or install programs on their smartphone to collect inertial sensing data. In this paper, we propose MapSentinel, which performs non-intrusive location sensing based on WiFi access points and ultrasonic sensors. MapSentinel combines the noisy sensor readings with the floormap information to estimate locations. One key observation supporting our work is that occupants exhibit distinctive motion characteristics at different locations on the floormap, e.g., constrained motion along the corridor or in the cubicle zones, and free movement in the open space. While extensive research has been performed on using a floormap as a tool to obtain correct walking trajectories without wall-crossings, there have been few attempts to incorporate the knowledge of space use available from the floormap into the location estimation. This paper argues that the knowledge of space use as an additional information source presents new opportunities for indoor tracking. The fusion of heterogeneous information is theoretically formulated within the Factor Graph framework, and the Context-Augmented Particle Filtering algorithm is developed to efficiently solve real-time walking trajectories. Our evaluation in a large office space shows that the MapSentinel can achieve accuracy improvement of 31.3% compared with the purely WiFi-based tracking system.

Active eye-tracking for an adaptive optics scanning laser ophthalmoscope

PubMed Central

Sheehy, Christy K.; Tiruveedhula, Pavan; Sabesan, Ramkumar; Roorda, Austin

2015-01-01

We demonstrate a system that combines a tracking scanning laser ophthalmoscope (TSLO) and an adaptive optics scanning laser ophthalmoscope (AOSLO) system resulting in both optical (hardware) and digital (software) eye-tracking capabilities. The hybrid system employs the TSLO for active eye-tracking at a rate up to 960 Hz for real-time stabilization of the AOSLO system. AOSLO videos with active eye-tracking signals showed, at most, an amplitude of motion of 0.20 arcminutes for horizontal motion and 0.14 arcminutes for vertical motion. Subsequent real-time digital stabilization limited residual motion to an average of only 0.06 arcminutes (a 95% reduction). By correcting for high amplitude, low frequency drifts of the eye, the active TSLO eye-tracking system enabled the AOSLO system to capture high-resolution retinal images over a larger range of motion than previously possible with just the AOSLO imaging system alone. PMID:26203370

Development and evaluation of a prototype tracking system using the treatment couch

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lang, Stephanie, E-mail: stephanie.lang@usz.ch; Riesterer, Oliver; Klöck, Stephan

2014-02-15

Purpose: Tumor motion increases safety margins around the clinical target volume and leads to an increased dose to the surrounding healthy tissue. The authors have developed and evaluated a one-dimensional treatment couch tracking system to counter steer respiratory tumor motion. Three different motion detection sensors with different lag times were evaluated. Methods: The couch tracking system consists of a motion detection sensor, which can be the topometrical system Topos (Cyber Technologies, Germany), the respiratory gating system RPM (Varian Medical Systems) or a laser triangulation system (Micro Epsilon), and the Protura treatment couch (Civco Medical Systems). The control of the treatmentmore » couch was implemented in the block diagram environment Simulink (MathWorks). To achieve real time performance, the Simulink models were executed on a real time engine, provided by Real-Time Windows Target (MathWorks). A proportional-integral control system was implemented. The lag time of the couch tracking system using the three different motion detection sensors was measured. The geometrical accuracy of the system was evaluated by measuring the mean absolute deviation from the reference (static position) during motion tracking. This deviation was compared to the mean absolute deviation without tracking and a reduction factor was defined. A hexapod system was moving according to seven respiration patterns previously acquired with the RPM system as well as according to a sin{sup 6} function with two different frequencies (0.33 and 0.17 Hz) and the treatment table compensated the motion. Results: A prototype system for treatment couch tracking of respiratory motion was developed. The laser based tracking system with a small lag time of 57 ms reduced the residual motion by a factor of 11.9 ± 5.5 (mean value ± standard deviation). An increase in delay time from 57 to 130 ms (RPM based system) resulted in a reduction by a factor of 4.7 ± 2.6. The Topos based tracking system with the largest lag time of 300 ms achieved a mean reduction by a factor of 3.4 ± 2.3. The increase in the penumbra of a profile (1 × 1 cm{sup 2}) for a motion of 6 mm was 1.4 mm. With tracking applied there was no increase in the penumbra. Conclusions: Couch tracking with the Protura treatment couch is achievable. To reliably track all possible respiration patterns without prediction filters a short lag time below 100 ms is needed. More scientific work is necessary to extend our prototype to tracking of internal motion.« less

Development of a real-time internal and external marker tracking system for particle therapy: a phantom study using patient tumor trajectory data

PubMed Central

Cho, Junsang; Cheon, Wonjoong; Ahn, Sanghee; Jung, Hyunuk; Sheen, Heesoon; Park, Hee Chul

2017-01-01

Abstract Target motion–induced uncertainty in particle therapy is more complicated than that in X-ray therapy, requiring more accurate motion management. Therefore, a hybrid motion-tracking system that can track internal tumor motion and as well as an external surrogate of tumor motion was developed. Recently, many correlation tests between internal and external markers in X-ray therapy have been developed; however, the accuracy of such internal/external marker tracking systems, especially in particle therapy, has not yet been sufficiently tested. In this article, the process of installing an in-house hybrid internal/external motion-tracking system is described and the accuracy level of tracking system was acquired. Our results demonstrated that the developed in-house external/internal combined tracking system has submillimeter accuracy, and can be clinically used as a particle therapy system as well as a simulation system for moving tumor treatment. PMID:28201522

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, W; Miften, M; Jones, B

Purpose: Pancreatic SBRT relies on extremely accurate delivery of ablative radiation doses to the target, and intra-fractional tracking of fiducial markers can facilitate improvements in dose delivery. However, this requires algorithms that are able to find fiducial markers with high speed and accuracy. The purpose of this study was to develop a novel marker tracking algorithm that is robust against many of the common errors seen with traditional template matching techniques. Methods: Using CBCT projection images, a method was developed to create detailed template images of fiducial marker clusters without prior knowledge of the number of markers, their positions, ormore » their orientations. Briefly, the method (i) enhances markers in projection images, (ii) stabilizes the cluster’s position, (iii) reconstructs the cluster in 3D, and (iv) precomputes a set of static template images dependent on gantry angle. Furthermore, breathing data were used to produce 4D reconstructions of clusters, yielding dynamic template images dependent on gantry angle and breathing amplitude. To test these two approaches, static and dynamic templates were used to track the motion of marker clusters in more than 66,000 projection images from 75 CBCT scans of 15 pancreatic SBRT patients. Results: For both static and dynamic templates, the new technique was able to locate marker clusters present in projection images 100% of the time. The algorithm was also able to correctly locate markers in several instances where only some of the markers were visible due to insufficient field-of-view. In cases where clusters exhibited deformation and/or rotation during breathing, dynamic templates resulted in cross-correlation scores up to 70% higher than static templates. Conclusion: Patient-specific templates provided complete tracking of fiducial marker clusters in CBCT scans, and dynamic templates helped to provide higher cross-correlation scores for deforming/rotating clusters. This novel algorithm provides an extremely accurate method to detect fiducial markers during treatment. Research funding provided by Varian Medical Systems to Miften and Jones.« less

An autonomous robot inspired by insect neurophysiology pursues moving features in natural environments

NASA Astrophysics Data System (ADS)

Bagheri, Zahra M.; Cazzolato, Benjamin S.; Grainger, Steven; O'Carroll, David C.; Wiederman, Steven D.

2017-08-01

Objective. Many computer vision and robotic applications require the implementation of robust and efficient target-tracking algorithms on a moving platform. However, deployment of a real-time system is challenging, even with the computational power of modern hardware. Lightweight and low-powered flying insects, such as dragonflies, track prey or conspecifics within cluttered natural environments, illustrating an efficient biological solution to the target-tracking problem. Approach. We used our recent recordings from ‘small target motion detector’ neurons in the dragonfly brain to inspire the development of a closed-loop target detection and tracking algorithm. This model exploits facilitation, a slow build-up of response to targets which move along long, continuous trajectories, as seen in our electrophysiological data. To test performance in real-world conditions, we implemented this model on a robotic platform that uses active pursuit strategies based on insect behaviour. Main results. Our robot performs robustly in closed-loop pursuit of targets, despite a range of challenging conditions used in our experiments; low contrast targets, heavily cluttered environments and the presence of distracters. We show that the facilitation stage boosts responses to targets moving along continuous trajectories, improving contrast sensitivity and detection of small moving targets against textured backgrounds. Moreover, the temporal properties of facilitation play a useful role in handling vibration of the robotic platform. We also show that the adoption of feed-forward models which predict the sensory consequences of self-movement can significantly improve target detection during saccadic movements. Significance. Our results provide insight into the neuronal mechanisms that underlie biological target detection and selection (from a moving platform), as well as highlight the effectiveness of our bio-inspired algorithm in an artificial visual system.

Assessing Upper Extremity Motor Function in Practice of Virtual Activities of Daily Living

PubMed Central

Adams, Richard J.; Lichter, Matthew D.; Krepkovich, Eileen T.; Ellington, Allison; White, Marga; Diamond, Paul T.

2015-01-01

A study was conducted to investigate the criterion validity of measures of upper extremity (UE) motor function derived during practice of virtual activities of daily living (ADLs). Fourteen hemiparetic stroke patients employed a Virtual Occupational Therapy Assistant (VOTA), consisting of a high-fidelity virtual world and a Kinect™ sensor, in four sessions of approximately one hour in duration. An Unscented Kalman Filter-based human motion tracking algorithm estimated UE joint kinematics in real-time during performance of virtual ADL activities, enabling both animation of the user’s avatar and automated generation of metrics related to speed and smoothness of motion. These metrics, aggregated over discrete sub-task elements during performance of virtual ADLs, were compared to scores from an established assessment of UE motor performance, the Wolf Motor Function Test (WMFT). Spearman’s rank correlation analysis indicates a moderate correlation between VOTA-derived metrics and the time-based WMFT assessments, supporting the criterion validity of VOTA measures as a means of tracking patient progress during an UE rehabilitation program that includes practice of virtual ADLs. PMID:25265612

Assessing upper extremity motor function in practice of virtual activities of daily living.

PubMed

Adams, Richard J; Lichter, Matthew D; Krepkovich, Eileen T; Ellington, Allison; White, Marga; Diamond, Paul T

2015-03-01

A study was conducted to investigate the criterion validity of measures of upper extremity (UE) motor function derived during practice of virtual activities of daily living (ADLs). Fourteen hemiparetic stroke patients employed a Virtual Occupational Therapy Assistant (VOTA), consisting of a high-fidelity virtual world and a Kinect™ sensor, in four sessions of approximately one hour in duration. An unscented Kalman Filter-based human motion tracking algorithm estimated UE joint kinematics in real-time during performance of virtual ADL activities, enabling both animation of the user's avatar and automated generation of metrics related to speed and smoothness of motion. These metrics, aggregated over discrete sub-task elements during performance of virtual ADLs, were compared to scores from an established assessment of UE motor performance, the Wolf Motor Function Test (WMFT). Spearman's rank correlation analysis indicates a moderate correlation between VOTA-derived metrics and the time-based WMFT assessments, supporting the criterion validity of VOTA measures as a means of tracking patient progress during an UE rehabilitation program that includes practice of virtual ADLs.

Cable-driven elastic parallel humanoid head with face tracking for Autism Spectrum Disorder interventions.

PubMed

Su, Hao; Dickstein-Fischer, Laurie; Harrington, Kevin; Fu, Qiushi; Lu, Weina; Huang, Haibo; Cole, Gregory; Fischer, Gregory S

2010-01-01

This paper presents the development of new prismatic actuation approach and its application in human-safe humanoid head design. To reduce actuator output impedance and mitigate unexpected external shock, the prismatic actuation method uses cables to drive a piston with preloaded spring. By leveraging the advantages of parallel manipulator and cable-driven mechanism, the developed neck has a parallel manipulator embodiment with two cable-driven limbs embedded with preloaded springs and one passive limb. The eye mechanism is adapted for low-cost webcam with succinct "ball-in-socket" structure. Based on human head anatomy and biomimetics, the neck has 3 degree of freedom (DOF) motion: pan, tilt and one decoupled roll while each eye has independent pan and synchronous tilt motion (3 DOF eyes). A Kalman filter based face tracking algorithm is implemented to interact with the human. This neck and eye structure is translatable to other human-safe humanoid robots. The robot's appearance reflects a non-threatening image of a penguin, which can be translated into a possible therapeutic intervention for children with Autism Spectrum Disorders.

Glue detection based on teaching points constraint and tracking model of pixel convolution

NASA Astrophysics Data System (ADS)

Geng, Lei; Ma, Xiao; Xiao, Zhitao; Wang, Wen

2018-01-01

On-line glue detection based on machine version is significant for rust protection and strengthening in car production. Shadow stripes caused by reflect light and unevenness of inside front cover of car reduce the accuracy of glue detection. In this paper, we propose an effective algorithm to distinguish the edges of the glue and shadow stripes. Teaching points are utilized to calculate slope between the two adjacent points. Then a tracking model based on pixel convolution along motion direction is designed to segment several local rectangular regions using distance. The distance is the height of rectangular region. The pixel convolution along the motion direction is proposed to extract edges of gules in local rectangular region. A dataset with different illumination and complexity shape stripes are used to evaluate proposed method, which include 500 thousand images captured from the camera of glue gun machine. Experimental results demonstrate that the proposed method can detect the edges of glue accurately. The shadow stripes are distinguished and removed effectively. Our method achieves the 99.9% accuracies for the image dataset.

Robotic Vision-Based Localization in an Urban Environment

NASA Technical Reports Server (NTRS)

Mchenry, Michael; Cheng, Yang; Matthies

2007-01-01

A system of electronic hardware and software, now undergoing development, automatically estimates the location of a robotic land vehicle in an urban environment using a somewhat imprecise map, which has been generated in advance from aerial imagery. This system does not utilize the Global Positioning System and does not include any odometry, inertial measurement units, or any other sensors except a stereoscopic pair of black-and-white digital video cameras mounted on the vehicle. Of course, the system also includes a computer running software that processes the video image data. The software consists mostly of three components corresponding to the three major image-data-processing functions: Visual Odometry This component automatically tracks point features in the imagery and computes the relative motion of the cameras between sequential image frames. This component incorporates a modified version of a visual-odometry algorithm originally published in 1989. The algorithm selects point features, performs multiresolution area-correlation computations to match the features in stereoscopic images, tracks the features through the sequence of images, and uses the tracking results to estimate the six-degree-of-freedom motion of the camera between consecutive stereoscopic pairs of images (see figure). Urban Feature Detection and Ranging Using the same data as those processed by the visual-odometry component, this component strives to determine the three-dimensional (3D) coordinates of vertical and horizontal lines that are likely to be parts of, or close to, the exterior surfaces of buildings. The basic sequence of processes performed by this component is the following: 1. An edge-detection algorithm is applied, yielding a set of linked lists of edge pixels, a horizontal-gradient image, and a vertical-gradient image. 2. Straight-line segments of edges are extracted from the linked lists generated in step 1. Any straight-line segments longer than an arbitrary threshold (e.g., 30 pixels) are assumed to belong to buildings or other artificial objects. 3. A gradient-filter algorithm is used to test straight-line segments longer than the threshold to determine whether they represent edges of natural or artificial objects. In somewhat oversimplified terms, the test is based on the assumption that the gradient of image intensity varies little along a segment that represents the edge of an artificial object.

Fast internal marker tracking algorithm for onboard MV and kV imaging systems

PubMed Central

Mao, W.; Wiersma, R. D.; Xing, L.

2008-01-01

Intrafraction organ motion can limit the advantage of highly conformal dose techniques such as intensity modulated radiation therapy (IMRT) due to target position uncertainty. To ensure high accuracy in beam targeting, real-time knowledge of the target location is highly desired throughout the beam delivery process. This knowledge can be gained through imaging of internally implanted radio-opaque markers with fluoroscopic or electronic portal imaging devices (EPID). In the case of MV based images, marker detection can be problematic due to the significantly lower contrast between different materials in comparison to their kV-based counterparts. This work presents a fully automated algorithm capable of detecting implanted metallic markers in both kV and MV images with high consistency. Using prior CT information, the algorithm predefines the volumetric search space without manual region-of-interest (ROI) selection by the user. Depending on the template selected, both spherical and cylindrical markers can be detected. Multiple markers can be simultaneously tracked without indexing confusion. Phantom studies show detection success rates of 100% for both kV and MV image data. In addition, application of the algorithm to real patient image data results in successful detection of all implanted markers for MV images. Near real-time operational speeds of ∼10 frames∕sec for the detection of five markers in a 1024×768 image are accomplished using an ordinary PC workstation. PMID:18561670

First Attempt of Orbit Determination of SLR Satellites and Space Debris Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Deleflie, F.; Coulot, D.; Descosta, R.; Fernier, A.; Richard, P.

2013-08-01

We present an orbit determination method based on genetic algorithms. Contrary to usual estimation methods mainly based on least-squares methods, these algorithms do not require any a priori knowledge of the initial state vector to be estimated. These algorithms can be applied when a new satellite is launched or for uncatalogued objects that appear in images obtained from robotic telescopes such as the TAROT ones. We show in this paper preliminary results obtained from an SLR satellite, for which tracking data acquired by the ILRS network enable to build accurate orbital arcs at a few centimeter level, which can be used as a reference orbit ; in this case, the basic observations are made up of time series of ranges, obtained from various tracking stations. We show as well the results obtained from the observations acquired by the two TAROT telescopes on the Telecom-2D satellite operated by CNES ; in that case, the observations are made up of time series of azimuths and elevations, seen from the two TAROT telescopes. The method is carried out in several steps: (i) an analytical propagation of the equations of motion, (ii) an estimation kernel based on genetic algorithms, which follows the usual steps of such approaches: initialization and evolution of a selected population, so as to determine the best parameters. Each parameter to be estimated, namely each initial keplerian element, has to be searched among an interval that is preliminary chosen. The algorithm is supposed to converge towards an optimum over a reasonable computational time.

A new performance index for the repetitive motion of mobile manipulators.

PubMed

Xiao, Lin; Zhang, Yunong

2014-02-01

A mobile manipulator is a robotic device composed of a mobile platform and a stationary manipulator fixed to the platform. To achieve the repetitive motion control of mobile manipulators, the mobile platform and the manipulator have to realize the repetitive motion simultaneously. To do so, a novel quadratic performance index is, for the first time, designed and presented in this paper, of which the effectiveness is analyzed by following a neural dynamics method. Then, a repetitive motion scheme is proposed by combining the criterion, physical constraints, and integrated kinematical equations of mobile manipulators, which is further reformulated as a quadratic programming (QP) subject to equality and bound constraints. In addition, two important Bridge theorems are established to prove that such a QP can be converted equivalently into a linear variational inequality, and then equivalently into a piecewise-linear projection equation (PLPE). A real-time numerical algorithm based on PLPE is thus developed and applied for the online solution of the resultant QP. Two tracking-path tasks demonstrate the effectiveness and accuracy of the repetitive motion scheme. In addition, comparisons between the nonrepetitive and repetitive motion further validate the superiority and novelty of the proposed scheme.

Self-Motion Impairs Multiple-Object Tracking

ERIC Educational Resources Information Center

Thomas, Laura E.; Seiffert, Adriane E.

2010-01-01

Investigations of multiple-object tracking aim to further our understanding of how people perform common activities such as driving in traffic. However, tracking tasks in the laboratory have overlooked a crucial component of much real-world object tracking: self-motion. We investigated the hypothesis that keeping track of one's own movement…

Real-Time Motion Tracking for Mobile Augmented/Virtual Reality Using Adaptive Visual-Inertial Fusion

PubMed Central

Fang, Wei; Zheng, Lianyu; Deng, Huanjun; Zhang, Hongbo

2017-01-01

In mobile augmented/virtual reality (AR/VR), real-time 6-Degree of Freedom (DoF) motion tracking is essential for the registration between virtual scenes and the real world. However, due to the limited computational capacity of mobile terminals today, the latency between consecutive arriving poses would damage the user experience in mobile AR/VR. Thus, a visual-inertial based real-time motion tracking for mobile AR/VR is proposed in this paper. By means of high frequency and passive outputs from the inertial sensor, the real-time performance of arriving poses for mobile AR/VR is achieved. In addition, to alleviate the jitter phenomenon during the visual-inertial fusion, an adaptive filter framework is established to cope with different motion situations automatically, enabling the real-time 6-DoF motion tracking by balancing the jitter and latency. Besides, the robustness of the traditional visual-only based motion tracking is enhanced, giving rise to a better mobile AR/VR performance when motion blur is encountered. Finally, experiments are carried out to demonstrate the proposed method, and the results show that this work is capable of providing a smooth and robust 6-DoF motion tracking for mobile AR/VR in real-time. PMID:28475145

Real-Time Motion Tracking for Mobile Augmented/Virtual Reality Using Adaptive Visual-Inertial Fusion.

PubMed

Fang, Wei; Zheng, Lianyu; Deng, Huanjun; Zhang, Hongbo

2017-05-05

In mobile augmented/virtual reality (AR/VR), real-time 6-Degree of Freedom (DoF) motion tracking is essential for the registration between virtual scenes and the real world. However, due to the limited computational capacity of mobile terminals today, the latency between consecutive arriving poses would damage the user experience in mobile AR/VR. Thus, a visual-inertial based real-time motion tracking for mobile AR/VR is proposed in this paper. By means of high frequency and passive outputs from the inertial sensor, the real-time performance of arriving poses for mobile AR/VR is achieved. In addition, to alleviate the jitter phenomenon during the visual-inertial fusion, an adaptive filter framework is established to cope with different motion situations automatically, enabling the real-time 6-DoF motion tracking by balancing the jitter and latency. Besides, the robustness of the traditional visual-only based motion tracking is enhanced, giving rise to a better mobile AR/VR performance when motion blur is encountered. Finally, experiments are carried out to demonstrate the proposed method, and the results show that this work is capable of providing a smooth and robust 6-DoF motion tracking for mobile AR/VR in real-time.

Orbit-attitude coupled motion around small bodies: Sun-synchronous orbits with Sun-tracking attitude motion

NASA Astrophysics Data System (ADS)

Kikuchi, Shota; Howell, Kathleen C.; Tsuda, Yuichi; Kawaguchi, Jun'ichiro

2017-11-01

The motion of a spacecraft in proximity to a small body is significantly perturbed due to its irregular gravity field and solar radiation pressure. In such a strongly perturbed environment, the coupling effect of the orbital and attitude motions exerts a large influence that cannot be neglected. However, natural orbit-attitude coupled dynamics around small bodies that are stationary in both orbital and attitude motions have yet to be observed. The present study therefore investigates natural coupled motion that involves both a Sun-synchronous orbit and Sun-tracking attitude motion. This orbit-attitude coupled motion enables a spacecraft to maintain its orbital geometry and attitude state with respect to the Sun without requiring active control. Therefore, the proposed method can reduce the use of an orbit and attitude control system. This paper first presents analytical conditions to achieve Sun-synchronous orbits and Sun-tracking attitude motion. These analytical solutions are then numerically propagated based on non-linear coupled orbit-attitude equations of motion. Consequently, the possibility of implementing Sun-synchronous orbits with Sun-tracking attitude motion is demonstrated.

Global Linking of Cell Tracks Using the Viterbi Algorithm

PubMed Central

Jaldén, Joakim; Gilbert, Penney M.; Blau, Helen M.

2016-01-01

Automated tracking of living cells in microscopy image sequences is an important and challenging problem. With this application in mind, we propose a global track linking algorithm, which links cell outlines generated by a segmentation algorithm into tracks. The algorithm adds tracks to the image sequence one at a time, in a way which uses information from the complete image sequence in every linking decision. This is achieved by finding the tracks which give the largest possible increases to a probabilistically motivated scoring function, using the Viterbi algorithm. We also present a novel way to alter previously created tracks when new tracks are created, thus mitigating the effects of error propagation. The algorithm can handle mitosis, apoptosis, and migration in and out of the imaged area, and can also deal with false positives, missed detections, and clusters of jointly segmented cells. The algorithm performance is demonstrated on two challenging datasets acquired using bright-field microscopy, but in principle, the algorithm can be used with any cell type and any imaging technique, presuming there is a suitable segmentation algorithm. PMID:25415983

A fast recognition method of warhead target in boost phase using kinematic features

NASA Astrophysics Data System (ADS)

Chen, Jian; Xu, Shiyou; Tian, Biao; Wu, Jianhua; Chen, Zengping

2015-12-01

The radar targets number increases from one to more when the ballistic missile is in the process of separating the lower stage rocket or casting covers or other components. It is vital to identify the warhead target quickly among these multiple targets for radar tracking. A fast recognition method of the warhead target is proposed to solve this problem by using kinematic features, utilizing fuzzy comprehensive method and information fusion method. In order to weaken the influence of radar measurement noise, an extended Kalman filter with constant jerk model (CJEKF) is applied to obtain more accurate target's motion information. The simulation shows the validity of the algorithm and the effects of the radar measurement precision upon the algorithm's performance.

Measurement of body joint angles for physical therapy based on mean shift tracking using two low cost Kinect images.

PubMed

Chen, Y C; Lee, H J; Lin, K H

2015-08-01

Range of motion (ROM) is commonly used to assess a patient's joint function in physical therapy. Because motion capture systems are generally very expensive, physical therapists mostly use simple rulers to measure patients' joint angles in clinical diagnosis, which will suffer from low accuracy, low reliability, and subjective. In this study we used color and depth image feature from two sets of low-cost Microsoft Kinect to reconstruct 3D joint positions, and then calculate moveable joint angles to assess the ROM. A Gaussian background model is first used to segment the human body from the depth images. The 3D coordinates of the joints are reconstructed from both color and depth images. To track the location of joints throughout the sequence more precisely, we adopt the mean shift algorithm to find out the center of voxels upon the joints. The two sets of Kinect are placed three meters away from each other and facing to the subject. The joint moveable angles and the motion data are calculated from the position of joints frame by frame. To verify the results of our system, we take the results from a motion capture system called VICON as golden standard. Our 150 test results showed that the deviation of joint moveable angles between those obtained by VICON and our system is about 4 to 8 degree in six different upper limb exercises, which are acceptable in clinical environment.

Multileaf collimator tracking integrated with a novel x-ray imaging system and external surrogate monitoring

NASA Astrophysics Data System (ADS)

Krauss, Andreas; Fast, Martin F.; Nill, Simeon; Oelfke, Uwe

2012-04-01

We have previously developed a tumour tracking system, which adapts the aperture of a Siemens 160 MLC to electromagnetically monitored target motion. In this study, we exploit the use of a novel linac-mounted kilovoltage x-ray imaging system for MLC tracking. The unique in-line geometry of the imaging system allows the detection of target motion perpendicular to the treatment beam (i.e. the directions usually featuring steep dose gradients). We utilized the imaging system either alone or in combination with an external surrogate monitoring system. We equipped a Siemens ARTISTE linac with two flat panel detectors, one directly underneath the linac head for motion monitoring and the other underneath the patient couch for geometric tracking accuracy assessments. A programmable phantom with an embedded metal marker reproduced three patient breathing traces. For MLC tracking based on x-ray imaging alone, marker position was detected at a frame rate of 7.1 Hz. For the combined external and internal motion monitoring system, a total of only 85 x-ray images were acquired prior to or in between the delivery of ten segments of an IMRT beam. External motion was monitored with a potentiometer. A correlation model between external and internal motion was established. The real-time component of the MLC tracking procedure then relied solely on the correlation model estimations of internal motion based on the external signal. Geometric tracking accuracies were 0.6 mm (1.1 mm) and 1.8 mm (1.6 mm) in directions perpendicular and parallel to the leaf travel direction for the x-ray-only (the combined external and internal) motion monitoring system in spite of a total system latency of ˜0.62 s (˜0.51 s). Dosimetric accuracy for a highly modulated IMRT beam-assessed through radiographic film dosimetry-improved substantially when tracking was applied, but depended strongly on the respective geometric tracking accuracy. In conclusion, we have for the first time integrated MLC tracking with x-ray imaging in the in-line geometry and demonstrated highly accurate respiratory motion tracking.

Advances in Doppler recognition for ground moving target indication

NASA Astrophysics Data System (ADS)

Kealey, Paul G.; Jahangir, Mohammed

2006-05-01

Ground Moving Target Indication (GMTI) radar provides a day/night, all-weather, wide-area surveillance capability to detect moving vehicles and personnel. Current GMTI radar sensors are limited to only detecting and tracking targets. The exploitation of GMTI data would be greatly enhanced by a capability to recognize accurately the detections as significant classes of target. Doppler classification exploits the differential internal motion of targets, e.g. due to the tracks, limbs and rotors. Recently, the QinetiQ Bayesian Doppler classifier has been extended to include a helicopter class in addition to wheeled, tracked and personnel classes. This paper presents the performance for these four classes using a traditional low-resolution GMTI surveillance waveform with an experimental radar system. We have determined the utility of an "unknown output decision" for enhancing the accuracy of the declared target classes. A confidence method has been derived, using a threshold of the difference in certainties, to assign uncertain classifications into an "unknown class". The trade-off between fraction of targets declared and accuracy of the classifier has been measured. To determine the operating envelope of a Doppler classification algorithm requires a detailed understanding of the Signal-to-Noise Ratio (SNR) performance of the algorithm. In this study the SNR dependence of the QinetiQ classifier has been determined.

Robust skin color-based moving object detection for video surveillance

NASA Astrophysics Data System (ADS)

Kaliraj, Kalirajan; Manimaran, Sudha

2016-07-01

Robust skin color-based moving object detection for video surveillance is proposed. The objective of the proposed algorithm is to detect and track the target under complex situations. The proposed framework comprises four stages, which include preprocessing, skin color-based feature detection, feature classification, and target localization and tracking. In the preprocessing stage, the input image frame is smoothed using averaging filter and transformed into YCrCb color space. In skin color detection, skin color regions are detected using Otsu's method of global thresholding. In the feature classification, histograms of both skin and nonskin regions are constructed and the features are classified into foregrounds and backgrounds based on Bayesian skin color classifier. The foreground skin regions are localized by a connected component labeling process. Finally, the localized foreground skin regions are confirmed as a target by verifying the region properties, and nontarget regions are rejected using the Euler method. At last, the target is tracked by enclosing the bounding box around the target region in all video frames. The experiment was conducted on various publicly available data sets and the performance was evaluated with baseline methods. It evidently shows that the proposed algorithm works well against slowly varying illumination, target rotations, scaling, fast, and abrupt motion changes.

Temporal Restricted Visual Tracking Via Reverse-Low-Rank Sparse Learning.

PubMed

Yang, Yehui; Hu, Wenrui; Xie, Yuan; Zhang, Wensheng; Zhang, Tianzhu

2017-02-01

An effective representation model, which aims to mine the most meaningful information in the data, plays an important role in visual tracking. Some recent particle-filter-based trackers achieve promising results by introducing the low-rank assumption into the representation model. However, their assumed low-rank structure of candidates limits the robustness when facing severe challenges such as abrupt motion. To avoid the above limitation, we propose a temporal restricted reverse-low-rank learning algorithm for visual tracking with the following advantages: 1) the reverse-low-rank model jointly represents target and background templates via candidates, which exploits the low-rank structure among consecutive target observations and enforces the temporal consistency of target in a global level; 2) the appearance consistency may be broken when target suffers from sudden changes. To overcome this issue, we propose a local constraint via l 1,2 mixed-norm, which can not only ensures the local consistency of target appearance, but also tolerates the sudden changes between two adjacent frames; and 3) to alleviate the inference of unreasonable representation values due to outlier candidates, an adaptive weighted scheme is designed to improve the robustness of the tracker. By evaluating on 26 challenge video sequences, the experiments show the effectiveness and favorable performance of the proposed algorithm against 12 state-of-the-art visual trackers.

Ego-Motion and Tracking for Continuous Object Learning: A Brief Survey

DTIC Science & Technology

2017-09-01

ARL-TR-8167• SEP 2017 US Army Research Laboratory Ego-motion and Tracking for ContinuousObject Learning: A Brief Survey by Jason Owens and Philip...SEP 2017 US Army Research Laboratory Ego-motion and Tracking for ContinuousObject Learning: A Brief Survey by Jason Owens and Philip OsteenVehicle...

Unsupervised markerless 3-DOF motion tracking in real time using a single low-budget camera.

PubMed

Quesada, Luis; León, Alejandro J

2012-10-01

Motion tracking is a critical task in many computer vision applications. Existing motion tracking techniques require either a great amount of knowledge on the target object or specific hardware. These requirements discourage the wide spread of commercial applications based on motion tracking. In this paper, we present a novel three degrees of freedom motion tracking system that needs no knowledge on the target object and that only requires a single low-budget camera that can be found installed in most computers and smartphones. Our system estimates, in real time, the three-dimensional position of a nonmodeled unmarked object that may be nonrigid, nonconvex, partially occluded, self-occluded, or motion blurred, given that it is opaque, evenly colored, enough contrasting with the background in each frame, and that it does not rotate. Our system is also able to determine the most relevant object to track in the screen. Our proposal does not impose additional constraints, therefore it allows a market-wide implementation of applications that require the estimation of the three position degrees of freedom of an object.

Motion-based prediction explains the role of tracking in motion extrapolation.

PubMed

Khoei, Mina A; Masson, Guillaume S; Perrinet, Laurent U

2013-11-01

During normal viewing, the continuous stream of visual input is regularly interrupted, for instance by blinks of the eye. Despite these frequents blanks (that is the transient absence of a raw sensory source), the visual system is most often able to maintain a continuous representation of motion. For instance, it maintains the movement of the eye such as to stabilize the image of an object. This ability suggests the existence of a generic neural mechanism of motion extrapolation to deal with fragmented inputs. In this paper, we have modeled how the visual system may extrapolate the trajectory of an object during a blank using motion-based prediction. This implies that using a prior on the coherency of motion, the system may integrate previous motion information even in the absence of a stimulus. In order to compare with experimental results, we simulated tracking velocity responses. We found that the response of the motion integration process to a blanked trajectory pauses at the onset of the blank, but that it quickly recovers the information on the trajectory after reappearance. This is compatible with behavioral and neural observations on motion extrapolation. To understand these mechanisms, we have recorded the response of the model to a noisy stimulus. Crucially, we found that motion-based prediction acted at the global level as a gain control mechanism and that we could switch from a smooth regime to a binary tracking behavior where the dot is tracked or lost. Our results imply that a local prior implementing motion-based prediction is sufficient to explain a large range of neural and behavioral results at a more global level. We show that the tracking behavior deteriorates for sensory noise levels higher than a certain value, where motion coherency and predictability fail to hold longer. In particular, we found that motion-based prediction leads to the emergence of a tracking behavior only when enough information from the trajectory has been accumulated. Then, during tracking, trajectory estimation is robust to blanks even in the presence of relatively high levels of noise. Moreover, we found that tracking is necessary for motion extrapolation, this calls for further experimental work exploring the role of noise in motion extrapolation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Adaptive block online learning target tracking based on super pixel segmentation

NASA Astrophysics Data System (ADS)

Cheng, Yue; Li, Jianzeng

2018-04-01

Video target tracking technology under the unremitting exploration of predecessors has made big progress, but there are still lots of problems not solved. This paper proposed a new algorithm of target tracking based on image segmentation technology. Firstly we divide the selected region using simple linear iterative clustering (SLIC) algorithm, after that, we block the area with the improved density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm. Each sub-block independently trained classifier and tracked, then the algorithm ignore the failed tracking sub-block while reintegrate the rest of the sub-blocks into tracking box to complete the target tracking. The experimental results show that our algorithm can work effectively under occlusion interference, rotation change, scale change and many other problems in target tracking compared with the current mainstream algorithms.

DMLC tracking and gating can improve dose coverage for prostate VMAT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Colvill, E.; Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW 2065; School of Physics, University of Sydney, NSW 2006

2014-09-15

Purpose: To assess and compare the dosimetric impact of dynamic multileaf collimator (DMLC) tracking and gating as motion correction strategies to account for intrafraction motion during conventionally fractionated prostate radiotherapy. Methods: A dose reconstruction method was used to retrospectively assess the dose distributions delivered without motion correction during volumetric modulated arc therapy fractions for 20 fractions of five prostate cancer patients who received conventionally fractionated radiotherapy. These delivered dose distributions were compared with the dose distributions which would have been delivered had DMLC tracking or gating motion correction strategies been implemented. The delivered dose distributions were constructed by incorporating themore » observed prostate motion with the patient's original treatment plan to simulate the treatment delivery. The DMLC tracking dose distributions were constructed using the same dose reconstruction method with the addition of MLC positions from Linac log files obtained during DMLC tracking simulations with the observed prostate motions input to the DMLC tracking software. The gating dose distributions were constructed by altering the prostate motion to simulate the application of a gating threshold of 3 mm for 5 s. Results: The delivered dose distributions showed that dosimetric effects of intrafraction prostate motion could be substantial for some fractions, with an estimated dose decrease of more than 19% and 34% from the planned CTVD{sub 99%} and PTV D{sub 95%} values, respectively, for one fraction. Evaluation of dose distributions for DMLC tracking and gating deliveries showed that both interventions were effective in improving the CTV D{sub 99%} for all of the selected fractions to within 4% of planned value for all fractions. For the delivered dose distributions the difference in rectum V{sub 65%} for the individual fractions from planned ranged from −44% to 101% and for the bladder V{sub 65%} the range was −61% to 26% from planned. The application of tracking decreased the maximum rectum and bladder V{sub 65%} difference to 6% and 4%, respectively. Conclusions: For the first time, the dosimetric impact of DMLC tracking and gating to account for intrafraction motion during prostate radiotherapy has been assessed and compared with no motion correction. Without motion correction intrafraction prostate motion can result in a significant decrease in target dose coverage for a small number of individual fractions. This is unlikely to effect the overall treatment for most patients undergoing conventionally fractionated treatments. Both DMLC tracking and gating demonstrate dose distributions for all assessed fractions that are robust to intrafraction motion.« less

Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic

NASA Astrophysics Data System (ADS)

Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; Breivik, L.-A.

2010-10-01

The retrieval of sea ice motion with the Maximum Cross-Correlation (MCC) method from low-resolution (10-15 km) spaceborne imaging sensors is challenged by a dominating quantization noise as the time span of displacement vectors is shortened. To allow investigating shorter displacements from these instruments, we introduce an alternative sea ice motion tracking algorithm that builds on the MCC method but relies on a continuous optimization step for computing the motion vector. The prime effect of this method is to effectively dampen the quantization noise, an artifact of the MCC. It allows for retrieving spatially smooth 48 h sea ice motion vector fields in the Arctic. Strategies to detect and correct erroneous vectors as well as to optimally merge several polarization channels of a given instrument are also described. A test processing chain is implemented and run with several active and passive microwave imagers (Advanced Microwave Scanning Radiometer-EOS (AMSR-E), Special Sensor Microwave Imager, and Advanced Scatterometer) during three Arctic autumn, winter, and spring seasons. Ice motion vectors are collocated to and compared with GPS positions of in situ drifters. Error statistics are shown to be ranging from 2.5 to 4.5 km (standard deviation for components of the vectors) depending on the sensor, without significant bias. We discuss the relative contribution of measurement and representativeness errors by analyzing monthly validation statistics. The 37 GHz channels of the AMSR-E instrument allow for the best validation statistics. The operational low-resolution sea ice drift product of the EUMETSAT OSI SAF (European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility) is based on the algorithms presented in this paper.

Nonlinear dynamics support a linear population code in a retinal target-tracking circuit.

PubMed

Leonardo, Anthony; Meister, Markus

2013-10-23

A basic task faced by the visual system of many organisms is to accurately track the position of moving prey. The retina is the first stage in the processing of such stimuli; the nature of the transformation here, from photons to spike trains, constrains not only the ultimate fidelity of the tracking signal but also the ease with which it can be extracted by other brain regions. Here we demonstrate that a population of fast-OFF ganglion cells in the salamander retina, whose dynamics are governed by a nonlinear circuit, serve to compute the future position of the target over hundreds of milliseconds. The extrapolated position of the target is not found by stimulus reconstruction but is instead computed by a weighted sum of ganglion cell outputs, the population vector average (PVA). The magnitude of PVA extrapolation varies systematically with target size, speed, and acceleration, such that large targets are tracked most accurately at high speeds, and small targets at low speeds, just as is seen in the motion of real prey. Tracking precision reaches the resolution of single photoreceptors, and the PVA algorithm performs more robustly than several alternative algorithms. If the salamander brain uses the fast-OFF cell circuit for target extrapolation as we suggest, the circuit dynamics should leave a microstructure on the behavior that may be measured in future experiments. Our analysis highlights the utility of simple computations that, while not globally optimal, are efficiently implemented and have close to optimal performance over a limited but ethologically relevant range of stimuli.

A Nonlinear, Six-Degree of Freedom Precision Formation Control Algorithm, Based on Restricted Three Body Dynamics

NASA Technical Reports Server (NTRS)

Bauer, Frank (Technical Monitor); Luquette, Richard J.; Sanner, Robert M.

2003-01-01

Precision Formation Flying is an enabling technology for a variety of proposed space-based observatories, including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), the associated MAXIM pathfinder mission, and the Stellar Imager. An essential element of the technology is the control algorithm. This paper discusses the development of a nonlinear, six-degree of freedom (6DOF) control algorithm for maintaining the relative position and attitude of a spacecraft within a formation. The translation dynamics are based on the equations of motion for the restricted three body problem. The control law guarantees the tracking error convergences to zero, based on a Lyapunov analysis. The simulation, modelled after the MAXIM Pathfinder mission, maintains the relative position and attitude of a Follower spacecraft with respect to a Leader spacecraft, stationed near the L2 libration point in the Sun-Earth system.

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras.

PubMed

Xu, Lan; Liu, Yebin; Cheng, Wei; Guo, Kaiwen; Zhou, Guyue; Dai, Qionghai; Fang, Lu

2017-07-18

Aiming at automatic, convenient and non-instrusive motion capture, this paper presents a new generation markerless motion capture technique, the FlyCap system, to capture surface motions of moving characters using multiple autonomous flying cameras (autonomous unmanned aerial vehicles(UAVs) each integrated with an RGBD video camera). During data capture, three cooperative flying cameras automatically track and follow the moving target who performs large-scale motions in a wide space. We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera. We leverage the using of visual-odometry information provided by the UAV platform, and formulate the surface tracking problem in a non-linear objective function that can be linearized and effectively minimized through a Gaussian-Newton method. Quantitative and qualitative experimental results demonstrate the plausible surface and motion reconstruction results.

Human body motion tracking based on quantum-inspired immune cloning algorithm

NASA Astrophysics Data System (ADS)

Han, Hong; Yue, Lichuan; Jiao, Licheng; Wu, Xing

2009-10-01

In a static monocular camera system, to gain a perfect 3D human body posture is a great challenge for Computer Vision technology now. This paper presented human postures recognition from video sequences using the Quantum-Inspired Immune Cloning Algorithm (QICA). The algorithm included three parts. Firstly, prior knowledge of human beings was used, the key joint points of human could be detected automatically from the human contours and skeletons which could be thinning from the contours; And due to the complexity of human movement, a forecasting mechanism of occlusion joint points was addressed to get optimum 2D key joint points of human body; And then pose estimation recovered by optimizing between the 2D projection of 3D human key joint points and 2D detection key joint points using QICA, which recovered the movement of human body perfectly, because this algorithm could acquire not only the global optimal solution, but the local optimal solution.

Clinical study of quantitative diagnosis of early cervical cancer based on the classification of acetowhitening kinetics

NASA Astrophysics Data System (ADS)

Wu, Tao; Cheung, Tak-Hong; Yim, So-Fan; Qu, Jianan Y.

2010-03-01

A quantitative colposcopic imaging system for the diagnosis of early cervical cancer is evaluated in a clinical study. This imaging technology based on 3-D active stereo vision and motion tracking extracts diagnostic information from the kinetics of acetowhitening process measured from the cervix of human subjects in vivo. Acetowhitening kinetics measured from 137 cervical sites of 57 subjects are analyzed and classified using multivariate statistical algorithms. Cross-validation methods are used to evaluate the performance of the diagnostic algorithms. The results show that an algorithm for screening precancer produced 95% sensitivity (SE) and 96% specificity (SP) for discriminating normal and human papillomavirus (HPV)-infected tissues from cervical intraepithelial neoplasia (CIN) lesions. For a diagnostic algorithm, 91% SE and 90% SP are achieved for discriminating normal tissue, HPV infected tissue, and low-grade CIN lesions from high-grade CIN lesions. The results demonstrate that the quantitative colposcopic imaging system could provide objective screening and diagnostic information for early detection of cervical cancer.

Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm

PubMed Central

Madan, Christopher R

2014-01-01

When studying animal behaviour within an open environment, movement-related data are often important for behavioural analyses. Therefore, simple and efficient techniques are needed to present and analyze the data of such movements. However, it is challenging to present both spatial and temporal information of movements within a two-dimensional image representation. To address this challenge, we developed the spectral time-lapse (STL) algorithm that re-codes an animal’s position at every time point with a time-specific color, and overlays it with a reference frame of the video, to produce a summary image. We additionally incorporated automated motion tracking, such that the animal’s position can be extracted and summary statistics such as path length and duration can be calculated, as well as instantaneous velocity and acceleration. Here we describe the STL algorithm and offer a freely available MATLAB toolbox that implements the algorithm and allows for a large degree of end-user control and flexibility. PMID:25580219

SU-G-BRA-01: A Real-Time Tumor Localization and Guidance Platform for Radiotherapy Using US and MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bednarz, B; Culberson, W; Bassetti, M

Purpose: To develop and validate a real-time motion management platform for radiotherapy that directly tracks tumor motion using ultrasound and MRI. This will be a cost-effective and non-invasive real-time platform combining the excellent temporal resolution of ultrasound with the excellent soft-tissue contrast of MRI. Methods: A 4D planar ultrasound acquisition during the treatment that is coupled to a pre-treatment calibration training image set consisting of a simultaneous 4D ultrasound and 4D MRI acquisition. The image sets will be rapidly matched using advanced image and signal processing algorithms, allowing the display of virtual MR images of the tumor/organ motion in real-timemore » from an ultrasound acquisition. Results: The completion of this work will result in several innovations including: a (2D) patch-like, MR and LINAC compatible 4D planar ultrasound transducer that is electronically steerable for hands-free operation to provide real-time virtual MR and ultrasound imaging for motion management during radiation therapy; a multi- modal tumor localization strategy that uses ultrasound and MRI; and fast and accurate image processing algorithms that provide real-time information about the motion and location of tumor or related soft-tissue structures within the patient. Conclusion: If successful, the proposed approach will provide real-time guidance for radiation therapy without degrading image or treatment plan quality. The approach would be equally suitable for image-guided proton beam or heavy ion-beam therapy. This work is partially funded by NIH grant R01CA190298.« less

Robust real-time horizon detection in full-motion video

NASA Astrophysics Data System (ADS)

Young, Grace B.; Bagnall, Bryan; Lane, Corey; Parameswaran, Shibin

2014-06-01

The ability to detect the horizon on a real-time basis in full-motion video is an important capability to aid and facilitate real-time processing of full-motion videos for the purposes such as object detection, recognition and other video/image segmentation applications. In this paper, we propose a method for real-time horizon detection that is designed to be used as a front-end processing unit for a real-time marine object detection system that carries out object detection and tracking on full-motion videos captured by ship/harbor-mounted cameras, Unmanned Aerial Vehicles (UAVs) or any other method of surveillance for Maritime Domain Awareness (MDA). Unlike existing horizon detection work, we cannot assume a priori the angle or nature (for e.g. straight line) of the horizon, due to the nature of the application domain and the data. Therefore, the proposed real-time algorithm is designed to identify the horizon at any angle and irrespective of objects appearing close to and/or occluding the horizon line (for e.g. trees, vehicles at a distance) by accounting for its non-linear nature. We use a simple two-stage hierarchical methodology, leveraging color-based features, to quickly isolate the region of the image containing the horizon and then perform a more ne-grained horizon detection operation. In this paper, we present our real-time horizon detection results using our algorithm on real-world full-motion video data from a variety of surveillance sensors like UAVs and ship mounted cameras con rming the real-time applicability of this method and its ability to detect horizon with no a priori assumptions.

SU-E-J-118: Verification of Intrafractional Positional Accuracy Using Ultrasound Autoscan Tracking for Prostate Cancer Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, S; Hristov, D; Phillips, T

Purpose: Transperineal ultrasound imaging is attractive option for imageguided radiation therapy as there is no need to implant fiducials, no extra imaging dose, and real time continuous imaging is possible during treatment. The aim of this study is to verify the tracking accuracy of a commercial ultrasound system under treatment conditions with a male pelvic phantom. Methods: A CT and ultrasound scan were acquired for the male pelvic phantom. The phantom was then placed in a treatment mimicking position on a motion platform. The axial and lateral tracking accuracy of the ultrasound system were verified using an independent optical trackingmore » system. The tracking accuracy was evaluated by tracking the phantom position detected by the ultrasound system, and comparing it to the optical tracking system under the conditions of beam on (15 MV), beam off, poor image quality with an acoustic shadow introduced, and different phantom motion cycles (10 and 20 second periods). Additionally, the time lag between the ultrasound-detected and actual phantom motion was investigated. Results: Displacement amplitudes reported by the ultrasound system and optical system were within 0.5 mm of each other for both directions and all conditions. The ultrasound tracking performance in axial direction was better than in lateral direction. Radiation did not interfere with ultrasound tracking while image quality affected tracking accuracy. The tracking accuracy was better for periodic motion with 20 second period. The time delay between the ultrasound tracking system and the phantom motion was clinically acceptable. Conclusion: Intrafractional prostate motion is a potential source of treatment error especially in the context of emerging SBRT regimens. It is feasible to use transperineal ultrasound daily to monitor prostate motion during treatment. Our results verify the tracking accuracy of a commercial ultrasound system to be better than 1 mm under typical external beam treatment conditions.« less

Covert enaction at work: Recording the continuous movements of visuospatial attention to visible or imagined targets by means of Steady-State Visual Evoked Potentials (SSVEPs).

PubMed

Gregori Grgič, Regina; Calore, Enrico; de'Sperati, Claudio

2016-01-01

Whereas overt visuospatial attention is customarily measured with eye tracking, covert attention is assessed by various methods. Here we exploited Steady-State Visual Evoked Potentials (SSVEPs) - the oscillatory responses of the visual cortex to incoming flickering stimuli - to record the movements of covert visuospatial attention in a way operatively similar to eye tracking (attention tracking), which allowed us to compare motion observation and motion extrapolation with and without eye movements. Observers fixated a central dot and covertly tracked a target oscillating horizontally and sinusoidally. In the background, the left and the right halves of the screen flickered at two different frequencies, generating two SSVEPs in occipital regions whose size varied reciprocally as observers attended to the moving target. The two signals were combined into a single quantity that was modulated at the target frequency in a quasi-sinusoidal way, often clearly visible in single trials. The modulation continued almost unchanged when the target was switched off and observers mentally extrapolated its motion in imagery, and also when observers pointed their finger at the moving target during covert tracking, or imagined doing so. The amplitude of modulation during covert tracking was ∼25-30% of that measured when observers followed the target with their eyes. We used 4 electrodes in parieto-occipital areas, but similar results were achieved with a single electrode in Oz. In a second experiment we tested ramp and step motion. During overt tracking, SSVEPs were remarkably accurate, showing both saccadic-like and smooth pursuit-like modulations of cortical responsiveness, although during covert tracking the modulation deteriorated. Covert tracking was better with sinusoidal motion than ramp motion, and better with moving targets than stationary ones. The clear modulation of cortical responsiveness recorded during both overt and covert tracking, identical for motion observation and motion extrapolation, suggests to include covert attention movements in enactive theories of mental imagery. Copyright © 2015 Elsevier Ltd. All rights reserved.

Motion Compensation in Extremity Cone-Beam CT Using a Penalized Image Sharpness Criterion

PubMed Central

Sisniega, A.; Stayman, J. W.; Yorkston, J.; Siewerdsen, J. H.; Zbijewski, W.

2017-01-01

Cone-beam CT (CBCT) for musculoskeletal imaging would benefit from a method to reduce the effects of involuntary patient motion. In particular, the continuing improvement in spatial resolution of CBCT may enable tasks such as quantitative assessment of bone microarchitecture (0.1 mm – 0.2 mm detail size), where even subtle, sub-mm motion blur might be detrimental. We propose a purely image based motion compensation method that requires no fiducials, tracking hardware or prior images. A statistical optimization algorithm (CMA-ES) is used to estimate a motion trajectory that optimizes an objective function consisting of an image sharpness criterion augmented by a regularization term that encourages smooth motion trajectories. The objective function is evaluated using a volume of interest (VOI, e.g. a single bone and surrounding area) where the motion can be assumed to be rigid. More complex motions can be addressed by using multiple VOIs. Gradient variance was found to be a suitable sharpness metric for this application. The performance of the compensation algorithm was evaluated in simulated and experimental CBCT data, and in a clinical dataset. Motion-induced artifacts and blurring were significantly reduced across a broad range of motion amplitudes, from 0.5 mm to 10 mm. Structure Similarity Index (SSIM) against a static volume was used in the simulation studies to quantify the performance of the motion compensation. In studies with translational motion, the SSIM improved from 0.86 before compensation to 0.97 after compensation for 0.5 mm motion, from 0.8 to 0.94 for 2 mm motion and from 0.52 to 0.87 for 10 mm motion (~70% increase). Similar reduction of artifacts was observed in a benchtop experiment with controlled translational motion of an anthropomorphic hand phantom, where SSIM (against a reconstruction of a static phantom) improved from 0.3 to 0.8 for 10 mm motion. Application to a clinical dataset of a lower extremity showed dramatic reduction of streaks and improvement in delineation of tissue boundaries and trabecular structures throughout the whole volume. The proposed method will support new applications of extremity CBCT in areas where patient motion may not be sufficiently managed by immobilization, such as imaging under load and quantitative assessment of subchondral bone architecture. PMID:28327471

Pupil Tracking for Real-Time Motion Corrected Anterior Segment Optical Coherence Tomography

PubMed Central

Carrasco-Zevallos, Oscar M.; Nankivil, Derek; Viehland, Christian; Keller, Brenton; Izatt, Joseph A.

2016-01-01

Volumetric acquisition with anterior segment optical coherence tomography (ASOCT) is necessary to obtain accurate representations of the tissue structure and to account for asymmetries of the anterior eye anatomy. Additionally, recent interest in imaging of anterior segment vasculature and aqueous humor flow resulted in application of OCT angiography techniques to generate en face and 3D micro-vasculature maps of the anterior segment. Unfortunately, ASOCT structural and vasculature imaging systems do not capture volumes instantaneously and are subject to motion artifacts due to involuntary eye motion that may hinder their accuracy and repeatability. Several groups have demonstrated real-time tracking for motion-compensated in vivo OCT retinal imaging, but these techniques are not applicable in the anterior segment. In this work, we demonstrate a simple and low-cost pupil tracking system integrated into a custom swept-source OCT system for real-time motion-compensated anterior segment volumetric imaging. Pupil oculography hardware coaxial with the swept-source OCT system enabled fast detection and tracking of the pupil centroid. The pupil tracking ASOCT system with a field of view of 15 x 15 mm achieved diffraction-limited imaging over a lateral tracking range of +/- 2.5 mm and was able to correct eye motion at up to 22 Hz. Pupil tracking ASOCT offers a novel real-time motion compensation approach that may facilitate accurate and reproducible anterior segment imaging. PMID:27574800

Applications of fuzzy logic to control and decision making

NASA Technical Reports Server (NTRS)

Lea, Robert N.; Jani, Yashvant

1991-01-01

Long range space missions will require high operational efficiency as well as autonomy to enhance the effectivity of performance. Fuzzy logic technology has been shown to be powerful and robust in interpreting imprecise measurements and generating appropriate control decisions for many space operations. Several applications are underway, studying the fuzzy logic approach to solving control and decision making problems. Fuzzy logic algorithms for relative motion and attitude control have been developed and demonstrated for proximity operations. Based on this experience, motion control algorithms that include obstacle avoidance were developed for a Mars Rover prototype for maneuvering during the sample collection process. A concept of an intelligent sensor system that can identify objects and track them continuously and learn from its environment is under development to support traffic management and proximity operations around the Space Station Freedom. For safe and reliable operation of Lunar/Mars based crew quarters, high speed controllers with ability to combine imprecise measurements from several sensors is required. A fuzzy logic approach that uses high speed fuzzy hardware chips is being studied.

Electromagnetic tracking of motion in the proximity of computer generated graphical stimuli: a tutorial.

PubMed

Schnabel, Ulf H; Hegenloh, Michael; Müller, Hermann J; Zehetleitner, Michael

2013-09-01

Electromagnetic motion-tracking systems have the advantage of capturing the tempo-spatial kinematics of movements independently of the visibility of the sensors. However, they are limited in that they cannot be used in the proximity of electromagnetic field sources, such as computer monitors. This prevents exploiting the tracking potential of the sensor system together with that of computer-generated visual stimulation. Here we present a solution for presenting computer-generated visual stimulation that does not distort the electromagnetic field required for precise motion tracking, by means of a back projection medium. In one experiment, we verify that cathode ray tube monitors, as well as thin-film-transistor monitors, distort electro-magnetic sensor signals even at a distance of 18 cm. Our back projection medium, by contrast, leads to no distortion of the motion-tracking signals even when the sensor is touching the medium. This novel solution permits combining the advantages of electromagnetic motion tracking with computer-generated visual stimulation.

A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

PubMed

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa; Hu, Yanle

2016-03-01

On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image-guided radiotherapy (MR-IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR-TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR-TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD-LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP-TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high-contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR-TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of different methods for optimal segmentation with the on-board MR-IGRT system. PACS number(s): 87.57.nm, 87.57.N-, 87.61.Tg. © 2016 The Authors.

A comparative study of automatic image segmentation algorithms for target tracking in MR‐IGRT

PubMed Central

Feng, Yuan; Kawrakow, Iwan; Olsen, Jeff; Parikh, Parag J.; Noel, Camille; Wooten, Omar; Du, Dongsu; Mutic, Sasa

2016-01-01

On‐board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real‐time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image‐guided radiotherapy (MR‐IGRT) system. Manual contours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k‐means (FKM), k‐harmonic means (KHM), and reaction‐diffusion level set evolution (RD‐LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR‐TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR‐TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD‐LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP‐TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high‐contrast images (i.e., kidney), the thresholding method provided the best speed (<1 ms) with a satisfying accuracy (Dice=0.95). When the image contrast was low, the VR‐TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of different methods for optimal segmentation with the on‐board MR‐IGRT system. PACS number(s): 87.57.nm, 87.57.N‐, 87.61.Tg

Equations for determining aircraft motions for accident data

NASA Technical Reports Server (NTRS)

Bach, R. E., Jr.; Wingrove, R. C.

1980-01-01

Procedures for determining a comprehensive accident scenario from a limited data set are reported. The analysis techniques accept and process data from either an Air Traffic Control radar tracking system or a foil flight data recorder. Local meteorological information at the time of the accident and aircraft performance data are also utilized. Equations for the desired aircraft motions and forces are given in terms of elements of the measurement set and certain of their time derivatives. The principal assumption made is that aircraft side force and side-slip angle are negligible. An estimation procedure is outlined for use with each data source. For the foil case, a discussion of exploiting measurement redundancy is given. Since either formulation requires estimates of measurement time derivatives, an algorithm for least squares smoothing is provided.

Software for Project-Based Learning of Robot Motion Planning

ERIC Educational Resources Information Center

Moll, Mark; Bordeaux, Janice; Kavraki, Lydia E.

2013-01-01

Motion planning is a core problem in robotics concerned with finding feasible paths for a given robot. Motion planning algorithms perform a search in the high-dimensional continuous space of robot configurations and exemplify many of the core algorithmic concepts of search algorithms and associated data structures. Motion planning algorithms can…

Repurposing video recordings for structure motion estimations

NASA Astrophysics Data System (ADS)

Khaloo, Ali; Lattanzi, David

2016-04-01

Video monitoring of public spaces is becoming increasingly ubiquitous, particularly near essential structures and facilities. During any hazard event that dynamically excites a structure, such as an earthquake or hurricane, proximal video cameras may inadvertently capture the motion time-history of the structure during the event. If this dynamic time-history could be extracted from the repurposed video recording it would become a valuable forensic analysis tool for engineers performing post-disaster structural evaluations. The difficulty is that almost all potential video cameras are not installed to monitor structure motions, leading to camera perspective distortions and other associated challenges. This paper presents a method for extracting structure motions from videos using a combination of computer vision techniques. Images from a video recording are first reprojected into synthetic images that eliminate perspective distortion, using as-built knowledge of a structure for calibration. The motion of the camera itself during an event is also considered. Optical flow, a technique for tracking per-pixel motion, is then applied to these synthetic images to estimate the building motion. The developed method was validated using the experimental records of the NEESHub earthquake database. The results indicate that the technique is capable of estimating structural motions, particularly the frequency content of the response. Further work will evaluate variants and alternatives to the optical flow algorithm, as well as study the impact of video encoding artifacts on motion estimates.

LabVIEW application for motion tracking using USB camera

NASA Astrophysics Data System (ADS)

Rob, R.; Tirian, G. O.; Panoiu, M.

2017-05-01

The technical state of the contact line and also the additional equipment in electric rail transport is very important for realizing the repairing and maintenance of the contact line. During its functioning, the pantograph motion must stay in standard limits. Present paper proposes a LabVIEW application which is able to track in real time the motion of a laboratory pantograph and also to acquire the tracking images. An USB webcam connected to a computer acquires the desired images. The laboratory pantograph contains an automatic system which simulates the real motion. The tracking parameters are the horizontally motion (zigzag) and the vertically motion which can be studied in separate diagrams. The LabVIEW application requires appropriate tool-kits for vision development. Therefore the paper describes the subroutines that are especially programmed for real-time image acquisition and also for data processing.

Markerless EPID image guided dynamic multi-leaf collimator tracking for lung tumors

NASA Astrophysics Data System (ADS)

Rottmann, J.; Keall, P.; Berbeco, R.

2013-06-01

Compensation of target motion during the delivery of radiotherapy has the potential to improve treatment accuracy, dose conformity and sparing of healthy tissue. We implement an online image guided therapy system based on soft tissue localization (STiL) of the target from electronic portal images and treatment aperture adaptation with a dynamic multi-leaf collimator (DMLC). The treatment aperture is moved synchronously and in real time with the tumor during the entire breathing cycle. The system is implemented and tested on a Varian TX clinical linear accelerator featuring an AS-1000 electronic portal imaging device (EPID) acquiring images at a frame rate of 12.86 Hz throughout the treatment. A position update cycle for the treatment aperture consists of four steps: in the first step at time t = t0 a frame is grabbed, in the second step the frame is processed with the STiL algorithm to get the tumor position at t = t0, in a third step the tumor position at t = ti + δt is predicted to overcome system latencies and in the fourth step, the DMLC control software calculates the required leaf motions and applies them at time t = ti + δt. The prediction model is trained before the start of the treatment with data representing the tumor motion. We analyze the system latency with a dynamic chest phantom (4D motion phantom, Washington University). We estimate the average planar position deviation between target and treatment aperture in a clinical setting by driving the phantom with several lung tumor trajectories (recorded from fiducial tracking during radiotherapy delivery to the lung). DMLC tracking for lung stereotactic body radiation therapy without fiducial markers was successfully demonstrated. The inherent system latency is found to be δt = (230 ± 11) ms for a MV portal image acquisition frame rate of 12.86 Hz. The root mean square deviation between tumor and aperture position is smaller than 1 mm. We demonstrate the feasibility of real-time markerless DMLC tracking with a standard LINAC-mounted (EPID).

Effects of motion base and g-seat cueing of simulator pilot performance

NASA Technical Reports Server (NTRS)

Ashworth, B. R.; Mckissick, B. T.; Parrish, R. V.

1984-01-01

In order to measure and analyze the effects of a motion plus g-seat cueing system, a manned-flight-simulation experiment was conducted utilizing a pursuit tracking task and an F-16 simulation model in the NASA Langley visual/motion simulator. This experiment provided the information necessary to determine whether motion and g-seat cues have an additive effect on the performance of this task. With respect to the lateral tracking error and roll-control stick force, the answer is affirmative. It is shown that presenting the two cues simultaneously caused significant reductions in lateral tracking error and that using the g-seat and motion base separately provided essentially equal reductions in the pilot's lateral tracking error.

Tracking colliding cells in vivo microscopy.

PubMed

Nguyen, Nhat H; Keller, Steven; Norris, Eric; Huynh, Toan T; Clemens, Mark G; Shin, Min C

2011-08-01

Leukocyte motion represents an important component in the innate immune response to infection. Intravital microscopy is a powerful tool as it enables in vivo imaging of leukocyte motion. Under inflammatory conditions, leukocytes may exhibit various motion behaviors, such as flowing, rolling, and adhering. With many leukocytes moving at a wide range of speeds, collisions occur. These collisions result in abrupt changes in the motion and appearance of leukocytes. Manual analysis is tedious, error prone,time consuming, and could introduce technician-related bias. Automatic tracking is also challenging due to the noise inherent in in vivo images and abrupt changes in motion and appearance due to collision. This paper presents a method to automatically track multiple cells undergoing collisions by modeling the appearance and motion for each collision state and testing collision hypotheses of possible transitions between states. The tracking results are demonstrated using in vivo intravital microscopy image sequences.We demonstrate that 1)71% of colliding cells are correctly tracked; (2) the improvement of the proposed method is enhanced when the duration of collision increases; and (3) given good detection results, the proposed method can correctly track 88% of colliding cells. The method minimizes the tracking failures under collisions and, therefore, allows more robust analysis in the study of leukocyte behaviors responding to inflammatory conditions.

Quantifying the degree of persistence in random amoeboid motion based on the Hurst exponent of fractional Brownian motion.

PubMed

Makarava, Natallia; Menz, Stephan; Theves, Matthias; Huisinga, Wilhelm; Beta, Carsten; Holschneider, Matthias

2014-10-01

Amoebae explore their environment in a random way, unless external cues like, e.g., nutrients, bias their motion. Even in the absence of cues, however, experimental cell tracks show some degree of persistence. In this paper, we analyzed individual cell tracks in the framework of a linear mixed effects model, where each track is modeled by a fractional Brownian motion, i.e., a Gaussian process exhibiting a long-term correlation structure superposed on a linear trend. The degree of persistence was quantified by the Hurst exponent of fractional Brownian motion. Our analysis of experimental cell tracks of the amoeba Dictyostelium discoideum showed a persistent movement for the majority of tracks. Employing a sliding window approach, we estimated the variations of the Hurst exponent over time, which allowed us to identify points in time, where the correlation structure was distorted ("outliers"). Coarse graining of track data via down-sampling allowed us to identify the dependence of persistence on the spatial scale. While one would expect the (mode of the) Hurst exponent to be constant on different temporal scales due to the self-similarity property of fractional Brownian motion, we observed a trend towards stronger persistence for the down-sampled cell tracks indicating stronger persistence on larger time scales.

A Nonlinear, Human-Centered Approach to Motion Cueing with a Neurocomputing Solver

NASA Technical Reports Server (NTRS)

Telban, Robert J.; Cardullo, Frank M.; Houck, Jacob A.

2002-01-01

This paper discusses the continuation of research into the development of new motion cueing algorithms first reported in 1999. In this earlier work, two viable approaches to motion cueing were identified: the coordinated adaptive washout algorithm or 'adaptive algorithm', and the 'optimal algorithm'. In this study, a novel approach to motion cueing is discussed that would combine features of both algorithms. The new algorithm is formulated as a linear optimal control problem, incorporating improved vestibular models and an integrated visual-vestibular motion perception model previously reported. A control law is generated from the motion platform states, resulting in a set of nonlinear cueing filters. The time-varying control law requires the matrix Riccati equation to be solved in real time. Therefore, in order to meet the real time requirement, a neurocomputing approach is used to solve this computationally challenging problem. Single degree-of-freedom responses for the nonlinear algorithm were generated and compared to the adaptive and optimal algorithms. Results for the heave mode show the nonlinear algorithm producing a motion cue with a time-varying washout, sustaining small cues for a longer duration and washing out larger cues more quickly. The addition of the optokinetic influence from the integrated perception model was shown to improve the response to a surge input, producing a specific force response with no steady-state washout. Improved cues are also observed for responses to a sway input. Yaw mode responses reveal that the nonlinear algorithm improves the motion cues by reducing the magnitude of negative cues. The effectiveness of the nonlinear algorithm as compared to the adaptive and linear optimal algorithms will be evaluated on a motion platform, the NASA Langley Research Center Visual Motion Simulator (VMS), and ultimately the Cockpit Motion Facility (CMF) with a series of pilot controlled maneuvers. A proposed experimental procedure is discussed. The results of this evaluation will be used to assess motion cueing performance.

Self-motion impairs multiple-object tracking.

PubMed

Thomas, Laura E; Seiffert, Adriane E

2010-10-01

Investigations of multiple-object tracking aim to further our understanding of how people perform common activities such as driving in traffic. However, tracking tasks in the laboratory have overlooked a crucial component of much real-world object tracking: self-motion. We investigated the hypothesis that keeping track of one's own movement impairs the ability to keep track of other moving objects. Participants attempted to track multiple targets while either moving around the tracking area or remaining in a fixed location. Participants' tracking performance was impaired when they moved to a new location during tracking, even when they were passively moved and when they did not see a shift in viewpoint. Self-motion impaired multiple-object tracking in both an immersive virtual environment and a real-world analog, but did not interfere with a difficult non-spatial tracking task. These results suggest that people use a common mechanism to track changes both to the location of moving objects around them and to keep track of their own location. Copyright 2010 Elsevier B.V. All rights reserved.

Evaluation of the TOPSAR performance by using passive and active calibrators

NASA Technical Reports Server (NTRS)

Alberti, G.; Moccia, A.; Ponte, S.; Vetrella, S.

1992-01-01

The preliminary analysis of the C-band cross-track interferometric data (XTI) acquired during the MAC Europe 1991 campaign over the Matera test site, in Southern Italy is presented. Twenty three passive calibrators (Corner Reflector, CR) and 3 active calibrators (Active Radar Calibrator, ARC) were deployed over an area characterized by homogeneous background. Contemporaneously to the flight, a ground truth data collection campaign was carried out. The research activity was focused on the development of motion compensation algorithms, in order to improve the height measurement accuracy of the TOPSAR system.