A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

Reference geometry-based detection of (4D-)CT motion artifacts: a feasibility study

NASA Astrophysics Data System (ADS)

Werner, René; Gauer, Tobias

2015-03-01

Respiration-correlated computed tomography (4D or 3D+t CT) can be considered as standard of care in radiation therapy treatment planning for lung and liver lesions. The decision about an application of motion management devices and the estimation of patient-specific motion effects on the dose distribution relies on precise motion assessment in the planning 4D CT data { which is impeded in case of CT motion artifacts. The development of image-based/post-processing approaches to reduce motion artifacts would benefit from precise detection and localization of the artifacts. Simple slice-by-slice comparison of intensity values and threshold-based analysis of related metrics suffer from- depending on the threshold- high false-positive or -negative rates. In this work, we propose exploiting prior knowledge about `ideal' (= artifact free) reference geometries to stabilize metric-based artifact detection by transferring (multi-)atlas-based concepts to this specific task. Two variants are introduced and evaluated: (S1) analysis and comparison of warped atlas data obtained by repeated non-linear atlas-to-patient registration with different levels of regularization; (S2) direct analysis of vector field properties (divergence, curl magnitude) of the atlas-to-patient transformation. Feasibility of approaches (S1) and (S2) is evaluated by motion-phantom data and intra-subject experiments (four patients) as well as - adopting a multi-atlas strategy- inter-subject investigations (twelve patients involved). It is demonstrated that especially sorting/double structure artifacts can be precisely detected and localized by (S1). In contrast, (S2) suffers from high false positive rates.

Motion-compensated detection of heart rate based on the time registration adaptive filter

NASA Astrophysics Data System (ADS)

Yang, Lei; Zhou, Jinsong; Jing, Juanjuan; Li, Yacan; Wei, Lidong; Feng, Lei; He, Xiaoying; Bu, Meixia; Fu, Xilu

2018-01-01

A non-contact heart rate detection method based on the dual-wavelength technique is proposed and demonstrated experimentally. The heart rate is obtained based on the PhotoPlethysmoGraphy (PPG). Each detection module uses the reflection detection probe which is composed of the LED and the photodiode. It is a well-known fact that the differences in the circuits of two detection modules result in different responses of two modules for motion artifacts. It will cause a time delay between the two signals. This poses a great challenge to compensate the motion artifacts during measurements. In order to solve this problem, we have firstly used the time registration and translated the signals to ensure that the two signals are consistent in time domain. Then the adaptive filter is used to compensate the motion artifacts. Moreover, the data obtained by using this non-contact detection system is compared with those of the conventional finger blood volume pulse (BVP) sensor by simultaneously measuring the heart rate of the subject. During the experiment, the left hand remains stationary and is detected by a conventional finger BVP sensor. Meanwhile, the moving palm of right hand is detected by the proposed system. The data obtained from the proposed non-contact system are consistent and comparable with that of the BVP sensor. This method can effectively suppress the interference caused by the two circuit differences and successfully compensate the motion artifacts. This technology can be used in medical and daily heart rate measurement.

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation.

PubMed

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-based sensor, the system is expected to be highly robust to sea weather conditions.

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation

NASA Astrophysics Data System (ADS)

Kim, Young-Keun; Kim, Kyung-Soo

2014-10-01

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-based sensor, the system is expected to be highly robust to sea weather conditions.

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.

Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Virtanen, Jaakko; Noponen, Tommi; Kotilahti, Kalle; Virtanen, Juha; Ilmoniemi, Risto J.

2011-08-01

In medical near-infrared spectroscopy (NIRS), movements of the subject often cause large step changes in the baselines of the measured light attenuation signals. This prevents comparison of hemoglobin concentration levels before and after movement. We present an accelerometer-based motion artifact removal (ABAMAR) algorithm for correcting such baseline motion artifacts (BMAs). ABAMAR can be easily adapted to various long-term monitoring applications of NIRS. We applied ABAMAR to NIRS data collected in 23 all-night sleep measurements and containing BMAs from involuntary movements during sleep. For reference, three NIRS researchers independently identified BMAs from the data. To determine whether the use of an accelerometer improves BMA detection accuracy, we compared ABAMAR to motion detection based on peaks in the moving standard deviation (SD) of NIRS data. The number of BMAs identified by ABAMAR was similar to the number detected by the humans, and 79% of the artifacts identified by ABAMAR were confirmed by at least two humans. While the moving SD of NIRS data could also be used for motion detection, on average 2 out of the 10 largest SD peaks in NIRS data each night occurred without the presence of movement. Thus, using an accelerometer improves BMA detection accuracy in NIRS.

Motion-Based Immunological Detection of Zika Virus Using Pt-Nanomotors and a Cellphone.

PubMed

Draz, Mohamed Shehata; Lakshminaraasimulu, Nivethitha Kota; Krishnakumar, Sanchana; Battalapalli, Dheerendranath; Vasan, Anish; Kanakasabapathy, Manoj Kumar; Sreeram, Aparna; Kallakuri, Shantanu; Thirumalaraju, Prudhvi; Li, Yudong; Hua, Stephane; Yu, Xu G; Kuritzkes, Daniel R; Shafiee, Hadi

2018-05-16

Zika virus (ZIKV) infection is an emerging pandemic threat to humans that can be fatal in newborns. Advances in digital health systems and nanoparticles can facilitate the development of sensitive and portable detection technologies for timely management of emerging viral infections. Here we report a nanomotor-based bead-motion cellphone (NBC) system for the immunological detection of ZIKV. The presence of virus in a testing sample results in the accumulation of platinum (Pt)-nanomotors on the surface of beads, causing their motion in H 2 O 2 solution. Then the virus concentration is detected in correlation with the change in beads motion. The developed NBC system was capable of detecting ZIKV in samples with virus concentrations as low as 1 particle/μL. The NBC system allowed a highly specific detection of ZIKV in the presence of the closely related dengue virus and other neurotropic viruses, such as herpes simplex virus type 1 and human cytomegalovirus. The NBC platform technology has the potential to be used in the development of point-of-care diagnostics for pathogen detection and disease management in developed and developing countries.

Detection of ground motions using high-rate GPS time-series

NASA Astrophysics Data System (ADS)

Psimoulis, Panos A.; Houlié, Nicolas; Habboub, Mohammed; Michel, Clotaire; Rothacher, Markus

2018-05-01

Monitoring surface deformation in real-time help at planning and protecting infrastructures and populations, manage sensitive production (i.e. SEVESO-type) and mitigate long-term consequences of modifications implemented. We present RT-SHAKE, an algorithm developed to detect ground motions associated with landslides, sub-surface collapses, subsidences, earthquakes or rock falls. RT-SHAKE detects first transient changes in individual GPS time series before investigating for spatial correlation(s) of observations made at neighbouring GPS sites and eventually issue a motion warning. In order to assess our algorithm on fast (seconds to minute), large (from 1 cm to meters) and spatially consistent surface motions, we use the 1 Hz GEONET GNSS network data of the Tohoku-Oki MW9.0 2011 as a test scenario. We show the delay of detection of seismic wave arrival by GPS records is of ˜10 seconds with respect to an identical analysis based on strong-motion data and this time delay depends on the level of the time-variable noise. Nevertheless, based on the analysis of the GPS network noise level and ground motion stochastic model, we show that RT-SHAKE can narrow the range of earthquake magnitude, by setting a lower threshold of detected earthquakes to MW6.5-7, if associated with a real-time automatic earthquake location system.

Two novel motion-based algorithms for surveillance video analysis on embedded platforms

NASA Astrophysics Data System (ADS)

Vijverberg, Julien A.; Loomans, Marijn J. H.; Koeleman, Cornelis J.; de With, Peter H. N.

2010-05-01

This paper proposes two novel motion-vector based techniques for target detection and target tracking in surveillance videos. The algorithms are designed to operate on a resource-constrained device, such as a surveillance camera, and to reuse the motion vectors generated by the video encoder. The first novel algorithm for target detection uses motion vectors to construct a consistent motion mask, which is combined with a simple background segmentation technique to obtain a segmentation mask. The second proposed algorithm aims at multi-target tracking and uses motion vectors to assign blocks to targets employing five features. The weights of these features are adapted based on the interaction between targets. These algorithms are combined in one complete analysis application. The performance of this application for target detection has been evaluated for the i-LIDS sterile zone dataset and achieves an F1-score of 0.40-0.69. The performance of the analysis algorithm for multi-target tracking has been evaluated using the CAVIAR dataset and achieves an MOTP of around 9.7 and MOTA of 0.17-0.25. On a selection of targets in videos from other datasets, the achieved MOTP and MOTA are 8.8-10.5 and 0.32-0.49 respectively. The execution time on a PC-based platform is 36 ms. This includes the 20 ms for generating motion vectors, which are also required by the video encoder.

Optical and Acoustic Sensor-Based 3D Ball Motion Estimation for Ball Sport Simulators †.

PubMed

Seo, Sang-Woo; Kim, Myunggyu; Kim, Yejin

2018-04-25

Estimation of the motion of ball-shaped objects is essential for the operation of ball sport simulators. In this paper, we propose an estimation system for 3D ball motion, including speed and angle of projection, by using acoustic vector and infrared (IR) scanning sensors. Our system is comprised of three steps to estimate a ball motion: sound-based ball firing detection, sound source localization, and IR scanning for motion analysis. First, an impulsive sound classification based on the mel-frequency cepstrum and feed-forward neural network is introduced to detect the ball launch sound. An impulsive sound source localization using a 2D microelectromechanical system (MEMS) microphones and delay-and-sum beamforming is presented to estimate the firing position. The time and position of a ball in 3D space is determined from a high-speed infrared scanning method. Our experimental results demonstrate that the estimation of ball motion based on sound allows a wider activity area than similar camera-based methods. Thus, it can be practically applied to various simulations in sports such as soccer and baseball.

Comparison of different detection methods for persistent multiple hypothesis tracking in wide area motion imagery

NASA Astrophysics Data System (ADS)

Hartung, Christine; Spraul, Raphael; Schuchert, Tobias

2017-10-01

Wide area motion imagery (WAMI) acquired by an airborne multicamera sensor enables continuous monitoring of large urban areas. Each image can cover regions of several square kilometers and contain thousands of vehicles. Reliable vehicle tracking in this imagery is an important prerequisite for surveillance tasks, but remains challenging due to low frame rate and small object size. Most WAMI tracking approaches rely on moving object detections generated by frame differencing or background subtraction. These detection methods fail when objects slow down or stop. Recent approaches for persistent tracking compensate for missing motion detections by combining a detection-based tracker with a second tracker based on appearance or local context. In order to avoid the additional complexity introduced by combining two trackers, we employ an alternative single tracker framework that is based on multiple hypothesis tracking and recovers missing motion detections with a classifierbased detector. We integrate an appearance-based similarity measure, merge handling, vehicle-collision tests, and clutter handling to adapt the approach to the specific context of WAMI tracking. We apply the tracking framework on a region of interest of the publicly available WPAFB 2009 dataset for quantitative evaluation; a comparison to other persistent WAMI trackers demonstrates state of the art performance of the proposed approach. Furthermore, we analyze in detail the impact of different object detection methods and detector settings on the quality of the output tracking results. For this purpose, we choose four different motion-based detection methods that vary in detection performance and computation time to generate the input detections. As detector parameters can be adjusted to achieve different precision and recall performance, we combine each detection method with different detector settings that yield (1) high precision and low recall, (2) high recall and low precision, and (3) best f-score. Comparing the tracking performance achieved with all generated sets of input detections allows us to quantify the sensitivity of the tracker to different types of detector errors and to derive recommendations for detector and parameter choice.

Bio-inspired motion detection in an FPGA-based smart camera module.

PubMed

Köhler, T; Röchter, F; Lindemann, J P; Möller, R

2009-03-01

Flying insects, despite their relatively coarse vision and tiny nervous system, are capable of carrying out elegant and fast aerial manoeuvres. Studies of the fly visual system have shown that this is accomplished by the integration of signals from a large number of elementary motion detectors (EMDs) in just a few global flow detector cells. We developed an FPGA-based smart camera module with more than 10,000 single EMDs, which is closely modelled after insect motion-detection circuits with respect to overall architecture, resolution and inter-receptor spacing. Input to the EMD array is provided by a CMOS camera with a high frame rate. Designed as an adaptable solution for different engineering applications and as a testbed for biological models, the EMD detector type and parameters such as the EMD time constants, the motion-detection directions and the angle between correlated receptors are reconfigurable online. This allows a flexible and simultaneous detection of complex motion fields such as translation, rotation and looming, such that various tasks, e.g., obstacle avoidance, height/distance control or speed regulation can be performed by the same compact device.

Doppler Radar Vital Signs Detection Method Based on Higher Order Cyclostationary.

PubMed

Yu, Zhibin; Zhao, Duo; Zhang, Zhiqiang

2017-12-26

Due to the non-contact nature, using Doppler radar sensors to detect vital signs such as heart and respiration rates of a human subject is getting more and more attention. However, the related detection-method research meets lots of challenges due to electromagnetic interferences, clutter and random motion interferences. In this paper, a novel third-order cyclic cummulant (TOCC) detection method, which is insensitive to Gaussian interference and non-cyclic signals, is proposed to investigate the heart and respiration rate based on continuous wave Doppler radars. The k -th order cyclostationary properties of the radar signal with hidden periodicities and random motions are analyzed. The third-order cyclostationary detection theory of the heart and respiration rate is studied. Experimental results show that the third-order cyclostationary approach has better estimation accuracy for detecting the vital signs from the received radar signal under low SNR, strong clutter noise and random motion interferences.

MRI-Based Nonrigid Motion Correction in Simultaneous PET/MRI

PubMed Central

Chun, Se Young; Reese, Timothy G.; Ouyang, Jinsong; Guerin, Bastien; Catana, Ciprian; Zhu, Xuping; Alpert, Nathaniel M.; El Fakhri, Georges

2014-01-01

Respiratory and cardiac motion is the most serious limitation to whole-body PET, resulting in spatial resolution close to 1 cm. Furthermore, motion-induced inconsistencies in the attenuation measurements often lead to significant artifacts in the reconstructed images. Gating can remove motion artifacts at the cost of increased noise. This paper presents an approach to respiratory motion correction using simultaneous PET/MRI to demonstrate initial results in phantoms, rabbits, and nonhuman primates and discusses the prospects for clinical application. Methods Studies with a deformable phantom, a free-breathing primate, and rabbits implanted with radioactive beads were performed with simultaneous PET/MRI. Motion fields were estimated from concurrently acquired tagged MR images using 2 B-spline nonrigid image registration methods and incorporated into a PET list-mode ordered-subsets expectation maximization algorithm. Using the measured motion fields to transform both the emission data and the attenuation data, we could use all the coincidence data to reconstruct any phase of the respiratory cycle. We compared the resulting SNR and the channelized Hotelling observer (CHO) detection signal-to-noise ratio (SNR) in the motion-corrected reconstruction with the results obtained from standard gating and uncorrected studies. Results Motion correction virtually eliminated motion blur without reducing SNR, yielding images with SNR comparable to those obtained by gating with 5–8 times longer acquisitions in all studies. The CHO study in dynamic phantoms demonstrated a significant improvement (166%–276%) in lesion detection SNR with MRI-based motion correction as compared with gating (P < 0.001). This improvement was 43%–92% for large motion compared with lesion detection without motion correction (P < 0.001). CHO SNR in the rabbit studies confirmed these results. Conclusion Tagged MRI motion correction in simultaneous PET/MRI significantly improves lesion detection compared with respiratory gating and no motion correction while reducing radiation dose. In vivo primate and rabbit studies confirmed the improvement in PET image quality and provide the rationale for evaluation in simultaneous whole-body PET/MRI clinical studies. PMID:22743250

Clustering Of Left Ventricular Wall Motion Patterns

NASA Astrophysics Data System (ADS)

Bjelogrlic, Z.; Jakopin, J.; Gyergyek, L.

1982-11-01

A method for detection of wall regions with similar motion was presented. A model based on local direction information was used to measure the left ventricular wall motion from cineangiographic sequence. Three time functions were used to define segmental motion patterns: distance of a ventricular contour segment from the mean contour, the velocity of a segment and its acceleration. Motion patterns were clustered by the UPGMA algorithm and by an algorithm based on K-nearest neighboor classification rule.

Optical Flow Estimation for Flame Detection in Videos

PubMed Central

Mueller, Martin; Karasev, Peter; Kolesov, Ivan; Tannenbaum, Allen

2014-01-01

Computational vision-based flame detection has drawn significant attention in the past decade with camera surveillance systems becoming ubiquitous. Whereas many discriminating features, such as color, shape, texture, etc., have been employed in the literature, this paper proposes a set of motion features based on motion estimators. The key idea consists of exploiting the difference between the turbulent, fast, fire motion, and the structured, rigid motion of other objects. Since classical optical flow methods do not model the characteristics of fire motion (e.g., non-smoothness of motion, non-constancy of intensity), two optical flow methods are specifically designed for the fire detection task: optimal mass transport models fire with dynamic texture, while a data-driven optical flow scheme models saturated flames. Then, characteristic features related to the flow magnitudes and directions are computed from the flow fields to discriminate between fire and non-fire motion. The proposed features are tested on a large video database to demonstrate their practical usefulness. Moreover, a novel evaluation method is proposed by fire simulations that allow for a controlled environment to analyze parameter influences, such as flame saturation, spatial resolution, frame rate, and random noise. PMID:23613042

Note: Reliable and non-contact 6D motion tracking system based on 2D laser scanners for cargo transportation

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

Kim, Young-Keun, E-mail: ykkim@handong.edu; Kim, Kyung-Soo

Maritime transportation demands an accurate measurement system to track the motion of oscillating container boxes in real time. However, it is a challenge to design a sensor system that can provide both reliable and non-contact methods of 6-DOF motion measurements of a remote object for outdoor applications. In the paper, a sensor system based on two 2D laser scanners is proposed for detecting the relative 6-DOF motion of a crane load in real time. Even without implementing a camera, the proposed system can detect the motion of a remote object using four laser beam points. Because it is a laser-basedmore » sensor, the system is expected to be highly robust to sea weather conditions.« less

A Kinect based intelligent e-rehabilitation system in physical therapy.

PubMed

Gal, Norbert; Andrei, Diana; Nemeş, Dan Ion; Nădăşan, Emanuela; Stoicu-Tivadar, Vasile

2015-01-01

This paper presents an intelligent Kinect and fuzzy inference system based e-rehabilitation system. The Kinect can detect the posture and motion of the patients while the fuzzy inference system can interpret the acquired data on the cognitive level. The system is capable to assess the initial posture and motion ranges of 20 joints. Using angles to describe the motion of the joints, exercise patterns can be developed for each patient. Using the exercise descriptors the fuzzy inference system can track the patient and deliver real-time feedback to maximize the efficiency of the rehabilitation. The first laboratory tests confirm the utility of this system for the initial posture detection, motion range and exercise tracking.

Automated detection of videotaped neonatal seizures based on motion segmentation methods.

PubMed

Karayiannis, Nicolaos B; Tao, Guozhi; Frost, James D; Wise, Merrill S; Hrachovy, Richard A; Mizrahi, Eli M

2006-07-01

This study was aimed at the development of a seizure detection system by training neural networks using quantitative motion information extracted by motion segmentation methods from short video recordings of infants monitored for seizures. The motion of the infants' body parts was quantified by temporal motion strength signals extracted from video recordings by motion segmentation methods based on optical flow computation. The area of each frame occupied by the infants' moving body parts was segmented by direct thresholding, by clustering of the pixel velocities, and by clustering the motion parameters obtained by fitting an affine model to the pixel velocities. The computational tools and procedures developed for automated seizure detection were tested and evaluated on 240 short video segments selected and labeled by physicians from a set of video recordings of 54 patients exhibiting myoclonic seizures (80 segments), focal clonic seizures (80 segments), and random infant movements (80 segments). The experimental study described in this paper provided the basis for selecting the most effective strategy for training neural networks to detect neonatal seizures as well as the decision scheme used for interpreting the responses of the trained neural networks. Depending on the decision scheme used for interpreting the responses of the trained neural networks, the best neural networks exhibited sensitivity above 90% or specificity above 90%. The best among the motion segmentation methods developed in this study produced quantitative features that constitute a reliable basis for detecting myoclonic and focal clonic neonatal seizures. The performance targets of this phase of the project may be achieved by combining the quantitative features described in this paper with those obtained by analyzing motion trajectory signals produced by motion tracking methods. A video system based upon automated analysis potentially offers a number of advantages. Infants who are at risk for seizures could be monitored continuously using relatively inexpensive and non-invasive video techniques that supplement direct observation by nursery personnel. This would represent a major advance in seizure surveillance and offers the possibility for earlier identification of potential neurological problems and subsequent intervention.

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.

Figure-ground segregation can rely on differences in motion direction.

PubMed

Kandil, Farid I; Fahle, Manfred

2004-12-01

If the elements within a figure move synchronously while those in the surround move at a different time, the figure is easily segregated from the surround and thus perceived. Lee and Blake (1999) [Visual form created solely from temporal structure. Science, 284, 1165-1168] demonstrated that this figure-ground separation may be based not only on time differences between motion onsets, but also on the differences between reversals of motion direction. However, Farid and Adelson (2001) [Synchrony does not promote grouping in temporally structured displays. Nature Neuroscience, 4, 875-876] argued that figure-ground segregation in the motion-reversal experiment might have been based on a contrast artefact and concluded that (a)synchrony as such was 'not responsible for the perception of form in these or earlier displays'. Here, we present experiments that avoid contrast artefacts but still produce figure-ground segregation based on purely temporal cues. Our results show that subjects can segregate figure from ground even though being unable to use motion reversals as such. Subjects detect the figure when either (i) motion stops (leading to contrast artefacts), or (ii) motion directions differ between figure and ground. Segregation requires minimum delays of about 15 ms. We argue that whatever the underlying cues and mechanisms, a second stage beyond motion detection is required to globally compare the outputs of local motion detectors and to segregate figure from ground. Since analogous changes take place in both figure and ground in rapid succession, this second stage has to detect the asynchrony with high temporal precision.

Value of automatic patient motion detection and correction in myocardial perfusion imaging using a CZT-based SPECT camera.

PubMed

van Dijk, Joris D; van Dalen, Jorn A; Mouden, Mohamed; Ottervanger, Jan Paul; Knollema, Siert; Slump, Cornelis H; Jager, Pieter L

2018-04-01

Correction of motion has become feasible on cadmium-zinc-telluride (CZT)-based SPECT cameras during myocardial perfusion imaging (MPI). Our aim was to quantify the motion and to determine the value of automatic correction using commercially available software. We retrospectively included 83 consecutive patients who underwent stress-rest MPI CZT-SPECT and invasive fractional flow reserve (FFR) measurement. Eight-minute stress acquisitions were reformatted into 1.0- and 20-second bins to detect respiratory motion (RM) and patient motion (PM), respectively. RM and PM were quantified and scans were automatically corrected. Total perfusion deficit (TPD) and SPECT interpretation-normal, equivocal, or abnormal-were compared between the noncorrected and corrected scans. Scans with a changed SPECT interpretation were compared with FFR, the reference standard. Average RM was 2.5 ± 0.4 mm and maximal PM was 4.5 ± 1.3 mm. RM correction influenced the diagnostic outcomes in two patients based on TPD changes ≥7% and in nine patients based on changed visual interpretation. In only four of these patients, the changed SPECT interpretation corresponded with FFR measurements. Correction for PM did not influence the diagnostic outcomes. Respiratory motion and patient motion were small. Motion correction did not appear to improve the diagnostic outcome and, hence, the added value seems limited in MPI using CZT-based SPECT cameras.

Structure from Motion

DTIC Science & Technology

1988-11-17

NOTATION 17. COSATI CODES 18. SUBJECT TERMS (Continue on reverse if ntcestary and identify by block number) FIELD GROUP SUB-GROUP ,-.:image...ambiguity in the recognition of partially occluded objects. V 1 , t : ., , ’ -, L: \\ : _ 20. DISTRIBUTION/AVAILABILITY OF ABSTRACT 21. ABSTRACT...constraints involved in the problem. More information can be found in [ 1 ]. Motion-based segmentation. Edge detection algorithms based on visual motion

Constrained motion model of mobile robots and its applications.

PubMed

Zhang, Fei; Xi, Yugeng; Lin, Zongli; Chen, Weidong

2009-06-01

Target detecting and dynamic coverage are fundamental tasks in mobile robotics and represent two important features of mobile robots: mobility and perceptivity. This paper establishes the constrained motion model and sensor model of a mobile robot to represent these two features and defines the k -step reachable region to describe the states that the robot may reach. We show that the calculation of the k-step reachable region can be reduced from that of 2(k) reachable regions with the fixed motion styles to k + 1 such regions and provide an algorithm for its calculation. Based on the constrained motion model and the k -step reachable region, the problems associated with target detecting and dynamic coverage are formulated and solved. For target detecting, the k-step detectable region is used to describe the area that the robot may detect, and an algorithm for detecting a target and planning the optimal path is proposed. For dynamic coverage, the k-step detected region is used to represent the area that the robot has detected during its motion, and the dynamic-coverage strategy and algorithm are proposed. Simulation results demonstrate the efficiency of the coverage algorithm in both convex and concave environments.

Macro-motion detection using ultra-wideband impulse radar.

PubMed

Xin Li; Dengyu Qiao; Ye Li

2014-01-01

Radar has the advantage of being able to detect hidden individuals, which can be used in homeland security, disaster rescue, and healthcare monitoring-related applications. Human macro-motion detection using ultra-wideband impulse radar is studied in this paper. First, a frequency domain analysis is carried out to show that the macro-motion yields a bandpass signal in slow-time. Second, the FTFW (fast-time frequency windowing), which has the advantage of avoiding the measuring range reduction, and the HLF (high-pass linear-phase filter), which can preserve the motion signal effectively, are proposed to preprocess the radar echo. Last, a threshold decision method, based on the energy detector structure, is presented.

Micromotor-based on-off fluorescence detection of sarin and soman simulants.

PubMed

Singh, Virendra V; Kaufmann, Kevin; Orozco, Jahir; Li, Jinxing; Galarnyk, Michael; Arya, Gaurav; Wang, Joseph

2015-06-30

Self-propelled micromotor-based fluorescent "On-Off" detection of nerve agents is described. The motion-based assay utilizes Si/Pt Janus micromotors coated with fluoresceinamine toward real-time "on-the-fly" field detection of sarin and soman simulants.

Statistics and Machine Learning based Outlier Detection Techniques for Exoplanets

NASA Astrophysics Data System (ADS)

Goel, Amit; Montgomery, Michele

2015-08-01

Architectures of planetary systems are observable snapshots in time that can indicate formation and dynamic evolution of planets. The observable key parameters that we consider are planetary mass and orbital period. If planet masses are significantly less than their host star masses, then Keplerian Motion is defined as P^2 = a^3 where P is the orbital period in units of years and a is the orbital period in units of Astronomical Units (AU). Keplerian motion works on small scales such as the size of the Solar System but not on large scales such as the size of the Milky Way Galaxy. In this work, for confirmed exoplanets of known stellar mass, planetary mass, orbital period, and stellar age, we analyze Keplerian motion of systems based on stellar age to seek if Keplerian motion has an age dependency and to identify outliers. For detecting outliers, we apply several techniques based on statistical and machine learning methods such as probabilistic, linear, and proximity based models. In probabilistic and statistical models of outliers, the parameters of a closed form probability distributions are learned in order to detect the outliers. Linear models use regression analysis based techniques for detecting outliers. Proximity based models use distance based algorithms such as k-nearest neighbour, clustering algorithms such as k-means, or density based algorithms such as kernel density estimation. In this work, we will use unsupervised learning algorithms with only the proximity based models. In addition, we explore the relative strengths and weaknesses of the various techniques by validating the outliers. The validation criteria for the outliers is if the ratio of planetary mass to stellar mass is less than 0.001. In this work, we present our statistical analysis of the outliers thus detected.

Detection of cyclic-fold bifurcation in electrostatic MEMS transducers by motion-induced current

NASA Astrophysics Data System (ADS)

Park, Sangtak; Khater, Mahmoud; Effa, David; Abdel-Rahman, Eihab; Yavuz, Mustafa

2017-08-01

This paper presents a new detection method of cyclic-fold bifurcations in electrostatic MEMS transducers based on a variant of the harmonic detection of resonance method. The electrostatic transducer is driven by an unbiased harmonic signal at half its natural frequency, ω a   =  1/2 ω o . The response of the transducer consists of static displacement and a series of harmonics at 2 ω a , 4 ω a , and so on. Its motion-induced current is shifted by the excitation frequency, ω a , to appear at 3 ω a , 5 ω a , and higher odd harmonics, providing higher sensitivity to the measurement of harmonic motions. With this method, we successfully detected the variation in the location of the cyclic-fold bifurcation of an encapsulated electrostatic MEMS transducer. We also detected a regime of tapping mode motions subsequent to the bifurcation.

Exploitation of Ubiquitous Wi-Fi Devices as Building Blocks for Improvised Motion Detection Systems.

PubMed

Soldovieri, Francesco; Gennarelli, Gianluca

2016-02-27

This article deals with a feasibility study on the detection of human movements in indoor scenarios based on radio signal strength variations. The sensing principle exploits the fact that the human body interacts with wireless signals, introducing variations of the radiowave fields due to shadowing and multipath phenomena. As a result, human motion can be inferred from fluctuations of radiowave power collected by a receiving terminal. In this paper, we investigate the potentialities of widely available wireless communication devices in order to develop an improvised motion detection system (IMDS). Experimental tests are performed in an indoor environment by using a smartphone as a Wi-Fi access point and a laptop with dedicated software as a receiver. Simple detection strategies tailored for real-time operation are implemented to process the received signal strength measurements. The achieved results confirm the potentialities of the simple system here proposed to reliably detect human motion in operational conditions.

Motion camera based on a custom vision sensor and an FPGA architecture

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel

1998-09-01

A digital camera for custom focal plane arrays was developed. The camera allows the test and development of analog or mixed-mode arrays for focal plane processing. The camera is used with a custom sensor for motion detection to implement a motion computation system. The custom focal plane sensor detects moving edges at the pixel level using analog VLSI techniques. The sensor communicates motion events using the event-address protocol associated to a temporal reference. In a second stage, a coprocessing architecture based on a field programmable gate array (FPGA) computes the time-of-travel between adjacent pixels. The FPGA allows rapid prototyping and flexible architecture development. Furthermore, the FPGA interfaces the sensor to a compact PC computer which is used for high level control and data communication to the local network. The camera could be used in applications such as self-guided vehicles, mobile robotics and smart surveillance systems. The programmability of the FPGA allows the exploration of further signal processing like spatial edge detection or image segmentation tasks. The article details the motion algorithm, the sensor architecture, the use of the event- address protocol for velocity vector computation and the FPGA architecture used in the motion camera system.

Detecting and Reducing Science Teacher Candidate’s (STC) Misconception About Motion and Force By Using Force Concept Inventory (FCI) and problem Based Learning (PBL)

NASA Astrophysics Data System (ADS)

Oktarisa, Y.; Utami, I. S.; Denny, Y. R.

2017-02-01

This study has been done to 34 science teacher candidates of Teachers’ Training and Education Faculty of Sultan Ageng Tirtayasa University at their first year of study during 2015-2016 school years. This research focused on student’s misconception about motion and force and how Problem Based Learning (PBL) reducing it. Diagnostic test of misconception about motion and force has been detected by using Force Concept Inventory (FCI). FCI had been used in pretest and posttest, and to find the reducing of students’ misconception N-Gain pretest and posttest of each student had been calculated. Quasi experiment one group pretest and posttest had been used as the research method, and Problem Based Learning (PBL) used as the treatment of manipulation. After two weeks learning motion and force with PBL approach, N-gain which obtained prove that misconception about motion and force had been reducing.

A method of immediate detection of objects with a near-zero apparent motion in series of CCD-frames

NASA Astrophysics Data System (ADS)

Savanevych, V. E.; Khlamov, S. V.; Vavilova, I. B.; Briukhovetskyi, A. B.; Pohorelov, A. V.; Mkrtichian, D. E.; Kudak, V. I.; Pakuliak, L. K.; Dikov, E. N.; Melnik, R. G.; Vlasenko, V. P.; Reichart, D. E.

2018-01-01

The paper deals with a computational method for detection of the solar system minor bodies (SSOs), whose inter-frame shifts in series of CCD-frames during the observation are commensurate with the errors in measuring their positions. These objects have velocities of apparent motion between CCD-frames not exceeding three rms errors (3σ) of measurements of their positions. About 15% of objects have a near-zero apparent motion in CCD-frames, including the objects beyond the Jupiter's orbit as well as the asteroids heading straight to the Earth. The proposed method for detection of the object's near-zero apparent motion in series of CCD-frames is based on the Fisher f-criterion instead of using the traditional decision rules that are based on the maximum likelihood criterion. We analyzed the quality indicators of detection of the object's near-zero apparent motion applying statistical and in situ modeling techniques in terms of the conditional probability of the true detection of objects with a near-zero apparent motion. The efficiency of method being implemented as a plugin for the Collection Light Technology (CoLiTec) software for automated asteroids and comets detection has been demonstrated. Among the objects discovered with this plugin, there was the sungrazing comet C/2012 S1 (ISON). Within 26 min of the observation, the comet's image has been moved by three pixels in a series of four CCD-frames (the velocity of its apparent motion at the moment of discovery was equal to 0.8 pixels per CCD-frame; the image size on the frame was about five pixels). Next verification in observations of asteroids with a near-zero apparent motion conducted with small telescopes has confirmed an efficiency of the method even in bad conditions (strong backlight from the full Moon). So, we recommend applying the proposed method for series of observations with four or more frames.

Automatic detection of a hand-held needle in ultrasound via phased-based analysis of the tremor motion

NASA Astrophysics Data System (ADS)

Beigi, Parmida; Salcudean, Septimiu E.; Rohling, Robert; Ng, Gary C.

2016-03-01

This paper presents an automatic localization method for a standard hand-held needle in ultrasound based on temporal motion analysis of spatially decomposed data. Subtle displacement arising from tremor motion has a periodic pattern which is usually imperceptible in the intensity image but may convey information in the phase image. Our method aims to detect such periodic motion of a hand-held needle and distinguish it from intrinsic tissue motion, using a technique inspired by video magnification. Complex steerable pyramids allow specific design of the wavelets' orientations according to the insertion angle as well as the measurement of the local phase. We therefore use steerable pairs of even and odd Gabor wavelets to decompose the ultrasound B-mode sequence into various spatial frequency bands. Variations of the local phase measurements in the spatially decomposed input data is then temporally analyzed using a finite impulse response bandpass filter to detect regions with a tremor motion pattern. Results obtained from different pyramid levels are then combined and thresholded to generate the binary mask input for the Hough transform, which determines an estimate of the direction angle and discards some of the outliers. Polynomial fitting is used at the final stage to remove any remaining outliers and improve the trajectory detection. The detected needle is finally added back to the input sequence as an overlay of a cloud of points. We demonstrate the efficiency of our approach to detect the needle using subtle tremor motion in an agar phantom and in-vivo porcine cases where intrinsic motion is also present. The localization accuracy was calculated by comparing to expert manual segmentation, and presented in (mean, standard deviation and root-mean-square error) of (0.93°, 1.26° and 0.87°) and (1.53 mm, 1.02 mm and 1.82 mm) for the trajectory and the tip, respectively.

Astrometric detectability of systems with unseen companions: effects of the Earth orbital motion

NASA Astrophysics Data System (ADS)

Butkevich, Alexey G.

2018-06-01

The astrometric detection of an unseen companion is based on an analysis of the apparent motion of its host star around the system's barycentre. Systems with an orbital period close to 1 yr may escape detection if the orbital motion of their host stars is observationally indistinguishable from the effects of parallax. Additionally, an astrometric solution may produce a biased parallax estimation for such systems. We examine the effects of the orbital motion of the Earth on astrometric detectability in terms of a correlation between the Earth's orbital position and the position of the star relative to its system barycentre. The χ2 statistic for parallax estimation is calculated analytically, leading to expressions that relate the decrease in detectability and accompanying parallax bias to the position correlation function. The impact of the Earth's motion critically depends on the exoplanet's orbital period, diminishing rapidly as the period deviates from 1 yr. Selection effects against 1-yr-period systems is, therefore, expected. Statistical estimation shows that the corresponding loss of sensitivity results in a typical 10 per cent increase in the detection threshold. Consideration of eccentric orbits shows that the Earth's motion has no effect on detectability for e≳ 0.5. The dependence of the detectability on other parameters, such as orbital phases and inclination of the orbital plane to the ecliptic, are smooth and monotonic because they are described by simple trigonometric functions.

Smart Sensor-Based Motion Detection System for Hand Movement Training in Open Surgery.

PubMed

Sun, Xinyao; Byrns, Simon; Cheng, Irene; Zheng, Bin; Basu, Anup

2017-02-01

We introduce a smart sensor-based motion detection technique for objective measurement and assessment of surgical dexterity among users at different experience levels. The goal is to allow trainees to evaluate their performance based on a reference model shared through communication technology, e.g., the Internet, without the physical presence of an evaluating surgeon. While in the current implementation we used a Leap Motion Controller to obtain motion data for analysis, our technique can be applied to motion data captured by other smart sensors, e.g., OptiTrack. To differentiate motions captured from different participants, measurement and assessment in our approach are achieved using two strategies: (1) low level descriptive statistical analysis, and (2) Hidden Markov Model (HMM) classification. Based on our surgical knot tying task experiment, we can conclude that finger motions generated from users with different surgical dexterity, e.g., expert and novice performers, display differences in path length, number of movements and task completion time. In order to validate the discriminatory ability of HMM for classifying different movement patterns, a non-surgical task was included in our analysis. Experimental results demonstrate that our approach had 100 % accuracy in discriminating between expert and novice performances. Our proposed motion analysis technique applied to open surgical procedures is a promising step towards the development of objective computer-assisted assessment and training systems.

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.

Computerized method to compensate for breathing body motion in dynamic chest radiographs

NASA Astrophysics Data System (ADS)

Matsuda, H.; Tanaka, R.; Sanada, S.

2017-03-01

Dynamic chest radiography combined with computer analysis allows quantitative analyses on pulmonary function and rib motion. The accuracy of kinematic analysis is directly linked to diagnostic accuracy, and thus body motion compensation is a major concern. Our purpose in this study was to develop a computerized method to reduce a breathing body motion in dynamic chest radiographs. Dynamic chest radiographs of 56 patients were obtained using a dynamic flat-panel detector. The images were divided into a 1 cm-square and the squares on body counter were used to detect the body motion. Velocity vector was measured using cross-correlation method on the body counter and the body motion was then determined on the basis of the summation of motion vector. The body motion was then compensated by shifting the images based on the measured vector. By using our method, the body motion was accurately detected by the order of a few pixels in clinical cases, mean 82.5% in right and left directions. In addition, our method detected slight body motion which was not able to be identified by human observations. We confirmed our method effectively worked in kinetic analysis of rib motion. The present method would be useful for the reduction of a breathing body motion in dynamic chest radiography.

Detecting coupled collective motions in protein by independent subspace analysis

NASA Astrophysics Data System (ADS)

Sakuraba, Shun; Joti, Yasumasa; Kitao, Akio

2010-11-01

Protein dynamics evolves in a high-dimensional space, comprising aharmonic, strongly correlated motional modes. Such correlation often plays an important role in analyzing protein function. In order to identify significantly correlated collective motions, here we employ independent subspace analysis based on the subspace joint approximate diagonalization of eigenmatrices algorithm for the analysis of molecular dynamics (MD) simulation trajectories. From the 100 ns MD simulation of T4 lysozyme, we extract several independent subspaces in each of which collective modes are significantly correlated, and identify the other modes as independent. This method successfully detects the modes along which long-tailed non-Gaussian probability distributions are obtained. Based on the time cross-correlation analysis, we identified a series of events among domain motions and more localized motions in the protein, indicating the connection between the functionally relevant phenomena which have been independently revealed by experiments.

Infrared video based gas leak detection method using modified FAST features

NASA Astrophysics Data System (ADS)

Wang, Min; Hong, Hanyu; Huang, Likun

2018-03-01

In order to detect the invisible leaking gas that is usually dangerous and easily leads to fire or explosion in time, many new technologies have arisen in the recent years, among which the infrared video based gas leak detection is widely recognized as a viable tool. However, all the moving regions of a video frame can be detected as leaking gas regions by the existing infrared video based gas leak detection methods, without discriminating the property of each detected region, e.g., a walking person in a video frame may be also detected as gas by the current gas leak detection methods.To solve this problem, we propose a novel infrared video based gas leak detection method in this paper, which is able to effectively suppress strong motion disturbances.Firstly, the Gaussian mixture model(GMM) is used to establish the background model.Then due to the observation that the shapes of gas regions are different from most rigid moving objects, we modify the Features From Accelerated Segment Test (FAST) algorithm and use the modified FAST (mFAST) features to describe each connected component. In view of the fact that the statistical property of the mFAST features extracted from gas regions is different from that of other motion regions, we propose the Pixel-Per-Points (PPP) condition to further select candidate connected components.Experimental results show that the algorithm is able to effectively suppress most strong motion disturbances and achieve real-time leaking gas detection.

Efficient subtle motion detection from high-speed video for sound recovery and vibration analysis using singular value decomposition-based approach

NASA Astrophysics Data System (ADS)

Zhang, Dashan; Guo, Jie; Jin, Yi; Zhu, Chang'an

2017-09-01

High-speed cameras provide full field measurement of structure motions and have been applied in nondestructive testing and noncontact structure monitoring. Recently, a phase-based method has been proposed to extract sound-induced vibrations from phase variations in videos, and this method provides insights into the study of remote sound surveillance and material analysis. An efficient singular value decomposition (SVD)-based approach is introduced to detect sound-induced subtle motions from pixel intensities in silent high-speed videos. A high-speed camera is initially applied to capture a video of the vibrating objects stimulated by sound fluctuations. Then, subimages collected from a small region on the captured video are reshaped into vectors and reconstructed to form a matrix. Orthonormal image bases (OIBs) are obtained from the SVD of the matrix; available vibration signal can then be obtained by projecting subsequent subimages onto specific OIBs. A simulation test is initiated to validate the effectiveness and efficiency of the proposed method. Two experiments are conducted to demonstrate the potential applications in sound recovery and material analysis. Results show that the proposed method efficiently detects subtle motions from the video.

Motion-compensated optical coherence tomography using envelope-based surface detection and Kalman-based prediction

NASA Astrophysics Data System (ADS)

Irsch, Kristina; Lee, Soohyun; Bose, Sanjukta N.; Kang, Jin U.

2018-02-01

We present an optical coherence tomography (OCT) imaging system that effectively compensates unwanted axial motion with micron-scale accuracy. The OCT system is based on a swept-source (SS) engine (1060-nm center wavelength, 100-nm full-width sweeping bandwidth, and 100-kHz repetition rate), with axial and lateral resolutions of about 4.5 and 8.5 microns respectively. The SS-OCT system incorporates a distance sensing method utilizing an envelope-based surface detection algorithm. The algorithm locates the target surface from the B-scans, taking into account not just the first or highest peak but the entire signature of sequential A-scans. Subsequently, a Kalman filter is applied as predictor to make up for system latencies, before sending the calculated position information to control a linear motor, adjusting and maintaining a fixed system-target distance. To test system performance, the motioncorrection algorithm was compared to earlier, more basic peak-based surface detection methods and to performing no motion compensation. Results demonstrate increased robustness and reproducibility, particularly noticeable in multilayered tissues, while utilizing the novel technique. Implementing such motion compensation into clinical OCT systems may thus improve the reliability of objective and quantitative information that can be extracted from OCT measurements.

A hybrid spatiotemporal and Hough-based motion estimation approach applied to magnetic resonance cardiac images

NASA Astrophysics Data System (ADS)

Carranza, N.; Cristóbal, G.; Sroubek, F.; Ledesma-Carbayo, M. J.; Santos, A.

2006-08-01

Myocardial motion analysis and quantification is of utmost importance for analyzing contractile heart abnormalities and it can be a symptom of a coronary artery disease. A fundamental problem in processing sequences of images is the computation of the optical flow, which is an approximation to the real image motion. This paper presents a new algorithm for optical flow estimation based on a spatiotemporal-frequency (STF) approach, more specifically on the computation of the Wigner-Ville distribution (WVD) and the Hough Transform (HT) of the motion sequences. The later is a well-known line and shape detection method very robust against incomplete data and noise. The rationale of using the HT in this context is because it provides a value of the displacement field from the STF representation. In addition, a probabilistic approach based on Gaussian mixtures has been implemented in order to improve the accuracy of the motion detection. Experimental results with synthetic sequences are compared against an implementation of the variational technique for local and global motion estimation, where it is shown that the results obtained here are accurate and robust to noise degradations. Real cardiac magnetic resonance images have been tested and evaluated with the current method.

Similar effects of feature-based attention on motion perception and pursuit eye movements at different levels of awareness

PubMed Central

Spering, Miriam; Carrasco, Marisa

2012-01-01

Feature-based attention enhances visual processing and improves perception, even for visual features that we are not aware of. Does feature-based attention also modulate motor behavior in response to visual information that does or does not reach awareness? Here we compare the effect of feature-based attention on motion perception and smooth pursuit eye movements in response to moving dichoptic plaids–stimuli composed of two orthogonally-drifting gratings, presented separately to each eye–in human observers. Monocular adaptation to one grating prior to the presentation of both gratings renders the adapted grating perceptually weaker than the unadapted grating and decreases the level of awareness. Feature-based attention was directed to either the adapted or the unadapted grating’s motion direction or to both (neutral condition). We show that observers were better in detecting a speed change in the attended than the unattended motion direction, indicating that they had successfully attended to one grating. Speed change detection was also better when the change occurred in the unadapted than the adapted grating, indicating that the adapted grating was perceptually weaker. In neutral conditions, perception and pursuit in response to plaid motion were dissociated: While perception followed one grating’s motion direction almost exclusively (component motion), the eyes tracked the average of both gratings (pattern motion). In attention conditions, perception and pursuit were shifted towards the attended component. These results suggest that attention affects perception and pursuit similarly even though only the former reflects awareness. The eyes can track an attended feature even if observers do not perceive it. PMID:22649238

Similar effects of feature-based attention on motion perception and pursuit eye movements at different levels of awareness.

PubMed

Spering, Miriam; Carrasco, Marisa

2012-05-30

Feature-based attention enhances visual processing and improves perception, even for visual features that we are not aware of. Does feature-based attention also modulate motor behavior in response to visual information that does or does not reach awareness? Here we compare the effect of feature-based attention on motion perception and smooth-pursuit eye movements in response to moving dichoptic plaids--stimuli composed of two orthogonally drifting gratings, presented separately to each eye--in human observers. Monocular adaptation to one grating before the presentation of both gratings renders the adapted grating perceptually weaker than the unadapted grating and decreases the level of awareness. Feature-based attention was directed to either the adapted or the unadapted grating's motion direction or to both (neutral condition). We show that observers were better at detecting a speed change in the attended than the unattended motion direction, indicating that they had successfully attended to one grating. Speed change detection was also better when the change occurred in the unadapted than the adapted grating, indicating that the adapted grating was perceptually weaker. In neutral conditions, perception and pursuit in response to plaid motion were dissociated: While perception followed one grating's motion direction almost exclusively (component motion), the eyes tracked the average of both gratings (pattern motion). In attention conditions, perception and pursuit were shifted toward the attended component. These results suggest that attention affects perception and pursuit similarly even though only the former reflects awareness. The eyes can track an attended feature even if observers do not perceive it.

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.

Impact of respiratory motion correction and spatial resolution on lesion detection in PET: a simulation study based on real MR dynamic data

NASA Astrophysics Data System (ADS)

Polycarpou, Irene; Tsoumpas, Charalampos; King, Andrew P.; Marsden, Paul K.

2014-02-01

The aim of this study is to investigate the impact of respiratory motion correction and spatial resolution on lesion detectability in PET as a function of lesion size and tracer uptake. Real respiratory signals describing different breathing types are combined with a motion model formed from real dynamic MR data to simulate multiple dynamic PET datasets acquired from a continuously moving subject. Lung and liver lesions were simulated with diameters ranging from 6 to 12 mm and lesion to background ratio ranging from 3:1 to 6:1. Projection data for 6 and 3 mm PET scanner resolution were generated using analytic simulations and reconstructed without and with motion correction. Motion correction was achieved using motion compensated image reconstruction. The detectability performance was quantified by a receiver operating characteristic (ROC) analysis obtained using a channelized Hotelling observer and the area under the ROC curve (AUC) was calculated as the figure of merit. The results indicate that respiratory motion limits the detectability of lung and liver lesions, depending on the variation of the breathing cycle length and amplitude. Patients with large quiescent periods had a greater AUC than patients with regular breathing cycles and patients with long-term variability in respiratory cycle or higher motion amplitude. In addition, small (less than 10 mm diameter) or low contrast (3:1) lesions showed the greatest improvement in AUC as a result of applying motion correction. In particular, after applying motion correction the AUC is improved by up to 42% with current PET resolution (i.e. 6 mm) and up to 51% for higher PET resolution (i.e. 3 mm). Finally, the benefit of increasing the scanner resolution is small unless motion correction is applied. This investigation indicates high impact of respiratory motion correction on lesion detectability in PET and highlights the importance of motion correction in order to benefit from the increased resolution of future PET scanners.

Human motion analysis with detection of subpart deformations

NASA Astrophysics Data System (ADS)

Wang, Juhui; Lorette, Guy; Bouthemy, Patrick

1992-06-01

One essential constraint used in 3-D motion estimation from optical projections is the rigidity assumption. Because of muscle deformations in human motion, this rigidity requirement is often violated for some regions on the human body. Global methods usually fail to bring stable solutions. This paper presents a model-based approach to combating the effect of muscle deformations in human motion analysis. The approach developed is based on two main stages. In the first stage, the human body is partitioned into different areas, where each area is consistent with a general motion model (not necessarily corresponding to a physical existing motion pattern). In the second stage, the regions are eliminated under the hypothesis that they are not induced by a specific human motion pattern. Each hypothesis is generated by making use of specific knowledge about human motion. A global method is used to estimate the 3-D motion parameters in basis of valid segments. Experiments based on a cycling motion sequence are presented.

Inertial Sensor-Based Motion Analysis of Lower Limbs for Rehabilitation Treatments

PubMed Central

Sun, Tongyang; Duan, Lihong; Wang, Yulong

2017-01-01

The hemiplegic rehabilitation state diagnosing performed by therapists can be biased due to their subjective experience, which may deteriorate the rehabilitation effect. In order to improve this situation, a quantitative evaluation is proposed. Though many motion analysis systems are available, they are too complicated for practical application by therapists. In this paper, a method for detecting the motion of human lower limbs including all degrees of freedom (DOFs) via the inertial sensors is proposed, which permits analyzing the patient's motion ability. This method is applicable to arbitrary walking directions and tracks of persons under study, and its results are unbiased, as compared to therapist qualitative estimations. Using the simplified mathematical model of a human body, the rotation angles for each lower limb joint are calculated from the input signals acquired by the inertial sensors. Finally, the rotation angle versus joint displacement curves are constructed, and the estimated values of joint motion angle and motion ability are obtained. The experimental verification of the proposed motion detection and analysis method was performed, which proved that it can efficiently detect the differences between motion behaviors of disabled and healthy persons and provide a reliable quantitative evaluation of the rehabilitation state. PMID:29065575

A novel procedure for detecting and focusing moving objects with SAR based on the Wigner-Ville distribution

NASA Astrophysics Data System (ADS)

Barbarossa, S.; Farina, A.

A novel scheme for detecting moving targets with synthetic aperture radar (SAR) is presented. The proposed approach is based on the use of the Wigner-Ville distribution (WVD) for simultaneously detecting moving targets and estimating their motion kinematic parameters. The estimation plays a key role for focusing the target and correctly locating it with respect to the stationary background. The method has a number of advantages: (i) the detection is efficiently performed on the samples in the time-frequency domain, provided the WVD, without resorting to the use of a bank of filters, each one matched to possible values of the unknown target motion parameters; (ii) the estimation of the target motion parameters can be done on the same time-frequency domain by locating the line where the maximum energy of the WVD is concentrated. A validation of the approach is given by both analytical and simulation means. In addition, the estimation of the target kinematic parameters and the corresponding image focusing are also demonstrated.

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

Video-based respiration monitoring with automatic region of interest detection.

PubMed

Janssen, Rik; Wang, Wenjin; Moço, Andreia; de Haan, Gerard

2016-01-01

Vital signs monitoring is ubiquitous in clinical environments and emerging in home-based healthcare applications. Still, since current monitoring methods require uncomfortable sensors, respiration rate remains the least measured vital sign. In this paper, we propose a video-based respiration monitoring method that automatically detects a respiratory region of interest (RoI) and signal using a camera. Based on the observation that respiration induced chest/abdomen motion is an independent motion system in a video, our basic idea is to exploit the intrinsic properties of respiration to find the respiratory RoI and extract the respiratory signal via motion factorization. We created a benchmark dataset containing 148 video sequences obtained on adults under challenging conditions and also neonates in the neonatal intensive care unit (NICU). The measurements obtained by the proposed video respiration monitoring (VRM) method are not significantly different from the reference methods (guided breathing or contact-based ECG; p-value  =  0.6), and explain more than 99% of the variance of the reference values with low limits of agreement (-2.67 to 2.81 bpm). VRM seems to provide a valid solution to ECG in confined motion scenarios, though precision may be reduced for neonates. More studies are needed to validate VRM under challenging recording conditions, including upper-body motion types.

POCS-enhanced correction of motion artifacts in parallel MRI.

PubMed

Samsonov, Alexey A; Velikina, Julia; Jung, Youngkyoo; Kholmovski, Eugene G; Johnson, Chris R; Block, Walter F

2010-04-01

A new method for correction of MRI motion artifacts induced by corrupted k-space data, acquired by multiple receiver coils such as phased arrays, is presented. In our approach, a projections onto convex sets (POCS)-based method for reconstruction of sensitivity encoded MRI data (POCSENSE) is employed to identify corrupted k-space samples. After the erroneous data are discarded from the dataset, the artifact-free images are restored from the remaining data using coil sensitivity profiles. The error detection and data restoration are based on informational redundancy of phased-array data and may be applied to full and reduced datasets. An important advantage of the new POCS-based method is that, in addition to multicoil data redundancy, it can use a priori known properties about the imaged object for improved MR image artifact correction. The use of such information was shown to improve significantly k-space error detection and image artifact correction. The method was validated on data corrupted by simulated and real motion such as head motion and pulsatile flow.

Image Corruption Detection in Diffusion Tensor Imaging for Post-Processing and Real-Time Monitoring

PubMed Central

Li, Yue; Shea, Steven M.; Lorenz, Christine H.; Jiang, Hangyi; Chou, Ming-Chung; Mori, Susumu

2013-01-01

Due to the high sensitivity of diffusion tensor imaging (DTI) to physiological motion, clinical DTI scans often suffer a significant amount of artifacts. Tensor-fitting-based, post-processing outlier rejection is often used to reduce the influence of motion artifacts. Although it is an effective approach, when there are multiple corrupted data, this method may no longer correctly identify and reject the corrupted data. In this paper, we introduce a new criterion called “corrected Inter-Slice Intensity Discontinuity” (cISID) to detect motion-induced artifacts. We compared the performance of algorithms using cISID and other existing methods with regard to artifact detection. The experimental results show that the integration of cISID into fitting-based methods significantly improves the retrospective detection performance at post-processing analysis. The performance of the cISID criterion, if used alone, was inferior to the fitting-based methods, but cISID could effectively identify severely corrupted images with a rapid calculation time. In the second part of this paper, an outlier rejection scheme was implemented on a scanner for real-time monitoring of image quality and reacquisition of the corrupted data. The real-time monitoring, based on cISID and followed by post-processing, fitting-based outlier rejection, could provide a robust environment for routine DTI studies. PMID:24204551

Methods to detect, characterize, and remove motion artifact in resting state fMRI

PubMed Central

Power, Jonathan D; Mitra, Anish; Laumann, Timothy O; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

2013-01-01

Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10 seconds after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects. PMID:23994314

Noise and range considerations for close-range radar sensing of life signs underwater.

PubMed

Hafner, Noah; Lubecke, Victor

2011-01-01

Close-range underwater sensing of motion-based life signs can be performed with low power Doppler radar and ultrasound techniques. Corresponding noise and range performance trade-offs are examined here, with regard to choice of frequency and technology. The frequency range examined includes part of the UHF and microwave spectrum. Underwater detection of motion by radar in freshwater and saltwater are demonstrated. Radar measurements exhibited reduced susceptibility to noise as compared to ultrasound. While higher frequency radar exhibited better signal to noise ratio, propagation was superior for lower frequencies. Radar detection of motion through saltwater was also demonstrated at restricted ranges (1-2 cm) with low power transmission (10 dBm). The results facilitate the establishment of guidelines for optimal choice in technology for the underwater measurement motion-based life signs, with respect to trade offs involving range and noise.

Variance change point detection for fractional Brownian motion based on the likelihood ratio test

NASA Astrophysics Data System (ADS)

Kucharczyk, Daniel; Wyłomańska, Agnieszka; Sikora, Grzegorz

2018-01-01

Fractional Brownian motion is one of the main stochastic processes used for describing the long-range dependence phenomenon for self-similar processes. It appears that for many real time series, characteristics of the data change significantly over time. Such behaviour one can observe in many applications, including physical and biological experiments. In this paper, we present a new technique for the critical change point detection for cases where the data under consideration are driven by fractional Brownian motion with a time-changed diffusion coefficient. The proposed methodology is based on the likelihood ratio approach and represents an extension of a similar methodology used for Brownian motion, the process with independent increments. Here, we also propose a statistical test for testing the significance of the estimated critical point. In addition to that, an extensive simulation study is provided to test the performance of the proposed method.

Image-based evaluation of contraction-relaxation kinetics of human-induced pluripotent stem cell-derived cardiomyocytes: Correlation and complementarity with extracellular electrophysiology.

PubMed

Hayakawa, Tomohiro; Kunihiro, Takeshi; Ando, Tomoko; Kobayashi, Seiji; Matsui, Eriko; Yada, Hiroaki; Kanda, Yasunari; Kurokawa, Junko; Furukawa, Tetsushi

2014-12-01

In this study, we used high-speed video microscopy with motion vector analysis to investigate the contractile characteristics of hiPS-CM monolayer, in addition to further characterizing the motion with extracellular field potential (FP), traction force and the Ca(2+) transient. Results of our traction force microscopy demonstrated that the force development of hiPS-CMs correlated well with the cellular deformation detected by the video microscopy with motion vector analysis. In the presence of verapamil and isoproterenol, contractile motion of hiPS-CMs showed alteration in accordance with the changes in fluorescence peak of the Ca(2+) transient, i.e., upstroke, decay, amplitude and full-width at half-maximum. Simultaneously recorded hiPS-CM motion and FP showed that there was a linear correlation between changes in the motion and field potential duration in response to verapamil (30-150nM), isoproterenol (0.1-10μM) and E-4031 (10-50nM). In addition, tetrodotoxin (3-30μM)-induced delay of sodium current was corresponded with the delay of the contraction onset of hiPS-CMs. These results indicate that the electrophysiological and functional behaviors of hiPS-CMs are quantitatively reflected in the contractile motion detected by this image-based technique. In the presence of 100nM E-4031, the occurrence of early after-depolarization-like negative deflection in FP was also detected in the hiPS-CM motion as a characteristic two-step relaxation pattern. These findings offer insights into the interpretation of the motion kinetics of the hiPS-CMs, and are relevant for understanding electrical and mechanical relationship in hiPS-CMs. Copyright © 2014. Published by Elsevier Ltd.

Detecting multiple moving objects in crowded environments with coherent motion regions

DOEpatents

Cheriyadat, Anil M.; Radke, Richard J.

2013-06-11

Coherent motion regions extend in time as well as space, enforcing consistency in detected objects over long time periods and making the algorithm robust to noisy or short point tracks. As a result of enforcing the constraint that selected coherent motion regions contain disjoint sets of tracks defined in a three-dimensional space including a time dimension. An algorithm operates directly on raw, unconditioned low-level feature point tracks, and minimizes a global measure of the coherent motion regions. At least one discrete moving object is identified in a time series of video images based on the trajectory similarity factors, which is a measure of a maximum distance between a pair of feature point tracks.

Automated detection of videotaped neonatal seizures of epileptic origin.

PubMed

Karayiannis, Nicolaos B; Xiong, Yaohua; Tao, Guozhi; Frost, James D; Wise, Merrill S; Hrachovy, Richard A; Mizrahi, Eli M

2006-06-01

This study aimed at the development of a seizure-detection system by training neural networks with quantitative motion information extracted from short video segments of neonatal seizures of the myoclonic and focal clonic types and random infant movements. The motion of the infants' body parts was quantified by temporal motion-strength signals extracted from video segments by motion-segmentation methods based on optical flow computation. The area of each frame occupied by the infants' moving body parts was segmented by clustering the motion parameters obtained by fitting an affine model to the pixel velocities. The motion of the infants' body parts also was quantified by temporal motion-trajectory signals extracted from video recordings by robust motion trackers based on block-motion models. These motion trackers were developed to adjust autonomously to illumination and contrast changes that may occur during the video-frame sequence. Video segments were represented by quantitative features obtained by analyzing motion-strength and motion-trajectory signals in both the time and frequency domains. Seizure recognition was performed by conventional feed-forward neural networks, quantum neural networks, and cosine radial basis function neural networks, which were trained to detect neonatal seizures of the myoclonic and focal clonic types and to distinguish them from random infant movements. The computational tools and procedures developed for automated seizure detection were evaluated on a set of 240 video segments of 54 patients exhibiting myoclonic seizures (80 segments), focal clonic seizures (80 segments), and random infant movements (80 segments). Regardless of the decision scheme used for interpreting the responses of the trained neural networks, all the neural network models exhibited sensitivity and specificity>90%. For one of the decision schemes proposed for interpreting the responses of the trained neural networks, the majority of the trained neural-network models exhibited sensitivity>90% and specificity>95%. In particular, cosine radial basis function neural networks achieved the performance targets of this phase of the project (i.e., sensitivity>95% and specificity>95%). The best among the motion segmentation and tracking methods developed in this study produced quantitative features that constitute a reliable basis for detecting neonatal seizures. The performance targets of this phase of the project were achieved by combining the quantitative features obtained by analyzing motion-strength signals with those produced by analyzing motion-trajectory signals. The computational procedures and tools developed in this study to perform off-line analysis of short video segments will be used in the next phase of this project, which involves the integration of these procedures and tools into a system that can process and analyze long video recordings of infants monitored for seizures in real time.

Contrasting accounts of direction and shape perception in short-range motion: Counterchange compared with motion energy detection.

PubMed

Norman, Joseph; Hock, Howard; Schöner, Gregor

2014-07-01

It has long been thought (e.g., Cavanagh & Mather, 1989) that first-order motion-energy extraction via space-time comparator-type models (e.g., the elaborated Reichardt detector) is sufficient to account for human performance in the short-range motion paradigm (Braddick, 1974), including the perception of reverse-phi motion when the luminance polarity of the visual elements is inverted during successive frames. Human observers' ability to discriminate motion direction and use coherent motion information to segregate a region of a random cinematogram and determine its shape was tested; they performed better in the same-, as compared with the inverted-, polarity condition. Computational analyses of short-range motion perception based on the elaborated Reichardt motion energy detector (van Santen & Sperling, 1985) predict, incorrectly, that symmetrical results will be obtained for the same- and inverted-polarity conditions. In contrast, the counterchange detector (Hock, Schöner, & Gilroy, 2009) predicts an asymmetry quite similar to that of human observers in both motion direction and shape discrimination. The further advantage of counterchange, as compared with motion energy, detection for the perception of spatial shape- and depth-from-motion is discussed.

High-level, but not low-level, motion perception is impaired in patients with schizophrenia.

PubMed

Kandil, Farid I; Pedersen, Anya; Wehnes, Jana; Ohrmann, Patricia

2013-01-01

Smooth pursuit eye movements are compromised in patients with schizophrenia and their first-degree relatives. Although research has demonstrated that the motor components of smooth pursuit eye movements are intact, motion perception has been shown to be impaired. In particular, studies have consistently revealed deficits in performance on tasks specific to the high-order motion area V5 (middle temporal area, MT) in patients with schizophrenia. In contrast, data from low-level motion detectors in the primary visual cortex (V1) have been inconsistent. To differentiate between low-level and high-level visual motion processing, we applied a temporal-order judgment task for motion events and a motion-defined figure-ground segregation task using patients with schizophrenia and healthy controls. Successful judgments in both tasks rely on the same low-level motion detectors in the V1; however, the first task is further processed in the higher-order motion area MT in the magnocellular (dorsal) pathway, whereas the second task requires subsequent computations in the parvocellular (ventral) pathway in visual area V4 and the inferotemporal cortex (IT). These latter structures are supposed to be intact in schizophrenia. Patients with schizophrenia revealed a significantly impaired temporal resolution on the motion-based temporal-order judgment task but only mild impairment in the motion-based segregation task. These results imply that low-level motion detection in V1 is not, or is only slightly, compromised; furthermore, our data restrain the locus of the well-known deficit in motion detection to areas beyond the primary visual cortex.

Using optical flow for the detection of floating mines in IR image sequences

NASA Astrophysics Data System (ADS)

Borghgraef, Alexander; Acheroy, Marc

2006-09-01

In the first Gulf War, unmoored floating mines proved to be a real hazard for shipping traffic. An automated system capable of detecting these and other free-floating small objects, using readily available sensors such as infra-red cameras, would prove to be a valuable mine-warfare asset, and could double as a collision avoidance mechanism, and a search-and-rescue aid. The noisy background provided by the sea surface, and occlusion by waves make it difficult to detect small floating objects using only algorithms based upon the intensity, size or shape of the target. This leads us to look at the sequence of images for temporal detection characteristics. The target's apparent motion is such a determinant, given the contrast between the bobbing motion of the floating object and the strong horizontal component present in the propagation of the wavefronts. We have applied the Proesmans optical flow algorithm to IR video footage of practice mines, in order to extract the motion characteristic and a threshold on the vertical motion characteristic is then imposed to detect the floating targets.

The Temporal Tuning of the Drosophila Motion Detectors Is Determined by the Dynamics of Their Input Elements.

PubMed

Arenz, Alexander; Drews, Michael S; Richter, Florian G; Ammer, Georg; Borst, Alexander

2017-04-03

Detecting the direction of motion contained in the visual scene is crucial for many behaviors. However, because single photoreceptors only signal local luminance changes, motion detection requires a comparison of signals from neighboring photoreceptors across time in downstream neuronal circuits. For signals to coincide on readout neurons that thus become motion and direction selective, different input lines need to be delayed with respect to each other. Classical models of motion detection rely on non-linear interactions between two inputs after different temporal filtering. However, recent studies have suggested the requirement for at least three, not only two, input signals. Here, we comprehensively characterize the spatiotemporal response properties of all columnar input elements to the elementary motion detectors in the fruit fly, T4 and T5 cells, via two-photon calcium imaging. Between these input neurons, we find large differences in temporal dynamics. Based on this, computer simulations show that only a small subset of possible arrangements of these input elements maps onto a recently proposed algorithmic three-input model in a way that generates a highly direction-selective motion detector, suggesting plausible network architectures. Moreover, modulating the motion detection system by octopamine-receptor activation, we find the temporal tuning of T4 and T5 cells to be shifted toward higher frequencies, and this shift can be fully explained by the concomitant speeding of the input elements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Image Motion Detection And Estimation: The Modified Spatio-Temporal Gradient Scheme

NASA Astrophysics Data System (ADS)

Hsin, Cheng-Ho; Inigo, Rafael M.

1990-03-01

The detection and estimation of motion are generally involved in computing a velocity field of time-varying images. A completely new modified spatio-temporal gradient scheme to determine motion is proposed. This is derived by using gradient methods and properties of biological vision. A set of general constraints is proposed to derive motion constraint equations. The constraints are that the second directional derivatives of image intensity at an edge point in the smoothed image will be constant at times t and t+L . This scheme basically has two stages: spatio-temporal filtering, and velocity estimation. Initially, image sequences are processed by a set of oriented spatio-temporal filters which are designed using a Gaussian derivative model. The velocity is then estimated for these filtered image sequences based on the gradient approach. From a computational stand point, this scheme offers at least three advantages over current methods. The greatest advantage of the modified spatio-temporal gradient scheme over the traditional ones is that an infinite number of motion constraint equations are derived instead of only one. Therefore, it solves the aperture problem without requiring any additional assumptions and is simply a local process. The second advantage is that because of the spatio-temporal filtering, the direct computation of image gradients (discrete derivatives) is avoided. Therefore the error in gradients measurement is reduced significantly. The third advantage is that during the processing of motion detection and estimation algorithm, image features (edges) are produced concurrently with motion information. The reliable range of detected velocity is determined by parameters of the oriented spatio-temporal filters. Knowing the velocity sensitivity of a single motion detection channel, a multiple-channel mechanism for estimating image velocity, seldom addressed by other motion schemes in machine vision, can be constructed by appropriately choosing and combining different sets of parameters. By applying this mechanism, a great range of velocity can be detected. The scheme has been tested for both synthetic and real images. The results of simulations are very satisfactory.

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.

Information fusion performance evaluation for motion imagery data using mutual information: initial study

NASA Astrophysics Data System (ADS)

Grieggs, Samuel M.; McLaughlin, Michael J.; Ezekiel, Soundararajan; Blasch, Erik

2015-06-01

As technology and internet use grows at an exponential rate, video and imagery data is becoming increasingly important. Various techniques such as Wide Area Motion imagery (WAMI), Full Motion Video (FMV), and Hyperspectral Imaging (HSI) are used to collect motion data and extract relevant information. Detecting and identifying a particular object in imagery data is an important step in understanding visual imagery, such as content-based image retrieval (CBIR). Imagery data is segmented and automatically analyzed and stored in dynamic and robust database. In our system, we seek utilize image fusion methods which require quality metrics. Many Image Fusion (IF) algorithms have been proposed based on different, but only a few metrics, used to evaluate the performance of these algorithms. In this paper, we seek a robust, objective metric to evaluate the performance of IF algorithms which compares the outcome of a given algorithm to ground truth and reports several types of errors. Given the ground truth of a motion imagery data, it will compute detection failure, false alarm, precision and recall metrics, background and foreground regions statistics, as well as split and merge of foreground regions. Using the Structural Similarity Index (SSIM), Mutual Information (MI), and entropy metrics; experimental results demonstrate the effectiveness of the proposed methodology for object detection, activity exploitation, and CBIR.

Restoration of Motion-Blurred Image Based on Border Deformation Detection: A Traffic Sign Restoration Model

PubMed Central

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently. PMID:25849350

Restoration of motion-blurred image based on border deformation detection: a traffic sign restoration model.

PubMed

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation

NASA Technical Reports Server (NTRS)

Roberts, Barry; Bhanu, Bir

1992-01-01

Recent work on INS integrated motion analysis is described. Results were obtained with a maximally passive system of obstacle detection (OD) for ground-based vehicles and rotorcraft. The OD approach involves motion analysis of imagery acquired by a passive sensor in the course of vehicle travel to generate range measurements to world points within the sensor FOV. INS data and scene analysis results are used to enhance interest point selection, the matching of the interest points, and the subsequent motion-based computations, tracking, and OD. The most important lesson learned from the research described here is that the incorporation of inertial data into the motion analysis program greatly improves the analysis and makes the process more robust.

Assessing the effects of subject motion on T2 relaxation under spin tagging (TRUST) cerebral oxygenation measurements using volume navigators.

PubMed

Stout, Jeffrey N; Tisdall, M Dylan; McDaniel, Patrick; Gagoski, Borjan; Bolar, Divya S; Grant, Patricia Ellen; Adalsteinsson, Elfar

2017-12-01

Subject motion may cause errors in estimates of blood T 2 when using the T 2 -relaxation under spin tagging (TRUST) technique on noncompliant subjects like neonates. By incorporating 3D volume navigators (vNavs) into the TRUST pulse sequence, independent measurements of motion during scanning permit evaluation of these errors. The effects of integrated vNavs on TRUST-based T 2 estimates were evaluated using simulations and in vivo subject data. Two subjects were scanned with the TRUST+vNav sequence during prescribed movements. Mean motion scores were derived from vNavs and TRUST images, along with a metric of exponential fit quality. Regression analysis was performed between T 2 estimates and mean motion scores. Also, motion scores were determined from independent neonatal scans. vNavs negligibly affected venous blood T 2 estimates and better detected subject motion than fit quality metrics. Regression analysis showed that T 2 is biased upward by 4.1 ms per 1 mm of mean motion score. During neonatal scans, mean motion scores of 0.6 to 2.0 mm were detected. Motion during TRUST causes an overestimate of T 2 , which suggests a cautious approach when comparing TRUST-based cerebral oxygenation measurements of noncompliant subjects. Magn Reson Med 78:2283-2289, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Image Processing Occupancy Sensor

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

The Image Processing Occupancy Sensor, or IPOS, is a novel sensor technology developed at the National Renewable Energy Laboratory (NREL). The sensor is based on low-cost embedded microprocessors widely used by the smartphone industry and leverages mature open-source computer vision software libraries. Compared to traditional passive infrared and ultrasonic-based motion sensors currently used for occupancy detection, IPOS has shown the potential for improved accuracy and a richer set of feedback signals for occupant-optimized lighting, daylighting, temperature setback, ventilation control, and other occupancy and location-based uses. Unlike traditional passive infrared (PIR) or ultrasonic occupancy sensors, which infer occupancy based only onmore » motion, IPOS uses digital image-based analysis to detect and classify various aspects of occupancy, including the presence of occupants regardless of motion, their number, location, and activity levels of occupants, as well as the illuminance properties of the monitored space. The IPOS software leverages the recent availability of low-cost embedded computing platforms, computer vision software libraries, and camera elements.« less

Collision-free motion of two robot arms in a common workspace

NASA Technical Reports Server (NTRS)

Basta, Robert A.; Mehrotra, Rajiv; Varanasi, Murali R.

1987-01-01

Collision-free motion of two robot arms in a common workspace is investigated. A collision-free motion is obtained by detecting collisions along the preplanned trajectories using a sphere model for the wrist of each robot and then modifying the paths and/or trajectories of one or both robots to avoid the collision. Detecting and avoiding collisions are based on the premise that: preplanned trajectories of the robots follow a straight line; collisions are restricted to between the wrists of the two robots (which corresponds to the upper three links of PUMA manipulators); and collisions never occur between the beginning points or end points on the straight line paths. The collision detection algorithm is described and some approaches to collision avoidance are discussed.

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.

Clinical applications of a quantitative analysis of regional lift ventricular wall motion

NASA Technical Reports Server (NTRS)

Leighton, R. F.; Rich, J. M.; Pollack, M. E.; Altieri, P. I.

1975-01-01

Observations were summarized which may have clinical application. These were obtained from a quantitative analysis of wall motion that was used to detect both hypokinesis and tardokinesis in left ventricular cineangiograms. The method was based on statistical comparisons with normal values for regional wall motion derived from the cineangiograms of patients who were found not to have heart disease.

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection.

PubMed

Power, Jonathan D; Plitt, Mark; Kundu, Prantik; Bandettini, Peter A; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10-50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion).

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection

PubMed Central

Plitt, Mark; Kundu, Prantik; Bandettini, Peter A.; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10–50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion). PMID:28880888

Motion estimation of magnetic resonance cardiac images using the Wigner-Ville and hough transforms

NASA Astrophysics Data System (ADS)

Carranza, N.; Cristóbal, G.; Bayerl, P.; Neumann, H.

2007-12-01

Myocardial motion analysis and quantification is of utmost importance for analyzing contractile heart abnormalities and it can be a symptom of a coronary artery disease. A fundamental problem in processing sequences of images is the computation of the optical flow, which is an approximation of the real image motion. This paper presents a new algorithm for optical flow estimation based on a spatiotemporal-frequency (STF) approach. More specifically it relies on the computation of the Wigner-Ville distribution (WVD) and the Hough Transform (HT) of the motion sequences. The latter is a well-known line and shape detection method that is highly robust against incomplete data and noise. The rationale of using the HT in this context is that it provides a value of the displacement field from the STF representation. In addition, a probabilistic approach based on Gaussian mixtures has been implemented in order to improve the accuracy of the motion detection. Experimental results in the case of synthetic sequences are compared with an implementation of the variational technique for local and global motion estimation, where it is shown that the results are accurate and robust to noise degradations. Results obtained with real cardiac magnetic resonance images are presented.

A wearable strain sensor based on a carbonized nano-sponge/silicone composite for human motion detection.

PubMed

Yu, Xiao-Guang; Li, Yuan-Qing; Zhu, Wei-Bin; Huang, Pei; Wang, Tong-Tong; Hu, Ning; Fu, Shao-Yun

2017-05-25

Melamine sponge, also known as nano-sponge, is widely used as an abrasive cleaner in our daily life. In this work, the fabrication of a wearable strain sensor for human motion detection is first demonstrated with a commercially available nano-sponge as a starting material. The key resistance sensitive material in the wearable strain sensor is obtained by the encapsulation of a carbonized nano-sponge (CNS) with silicone resin. The as-fabricated CNS/silicone sensor is highly sensitive to strain with a maximum gauge factor of 18.42. In addition, the CNS/silicone sensor exhibits a fast and reliable response to various cyclic loading within a strain range of 0-15% and a loading frequency range of 0.01-1 Hz. Finally, the CNS/silicone sensor as a wearable device for human motion detection including joint motion, eye blinking, blood pulse and breathing is demonstrated by attaching the sensor to the corresponding parts of the human body. In consideration of the simple fabrication technique, low material cost and excellent strain sensing performance, the CNS/silicone sensor is believed to have great potential in the next-generation of wearable devices for human motion detection.

A telemedicine instrument for Internet-based home monitoring of thoracoabdominal motion in patients with respiratory diseases

NASA Astrophysics Data System (ADS)

da Silva Junior, Evert Pereira; Esteves, Guilherme Pompeu; Dames, Karla Kristine; Melo, Pedro Lopes de

2011-01-01

Changes in thoracoabdominal motion are highly prevalent in patients with chronic respiratory diseases. Home care services that use telemedicine techniques and Internet-based monitoring have the potential to improve the management of these patients. However, there is no detailed description in the literature of a system for Internet-based monitoring of patients with disturbed thoracoabdominal motion. The purpose of this work was to describe the development of a new telemedicine instrument for Internet-based home monitoring of thoracoabdominal movement. The instrument directly measures changes in the thorax and abdomen circumferences and transfers data through a transmission control protocol/Internet protocol connection. After the design details are described, the accuracy of the electronic and software processing units of the instrument is evaluated by using electronic signals simulating normal subjects and individuals with thoracoabdominal motion disorders. The results obtained during in vivo studies on normal subjects simulating thoracoabdominal motion disorders showed that this new system is able to detect a reduction in abdominal movement that is associated with abnormal thoracic breathing (p < 0.0001) and the reduction in thoracic movement during abnormal abdominal breathing (p < 0.005). Simulated asynchrony in thoracoabdominal motion was also adequately detected by the system (p < 0.0001). The experimental results obtained for patients with respiratory diseases were in close agreement with the expected values, providing evidence that this instrument can be a useful tool for the evaluation of thoracoabdominal motion. The Internet transmission tests showed that the acquisition and analysis of the thoracoabdominal motion signals can be performed remotely. The user can also receive medical recommendations. The proposed system can be used in a spectrum of telemedicine scenarios, which can reduce the costs of assistance offered to patients with respiratory diseases.

Molecular sensing with magnetic nanoparticles using magnetic spectroscopy of nanoparticle Brownian motion.

PubMed

Zhang, Xiaojuan; Reeves, Daniel B; Perreard, Irina M; Kett, Warren C; Griswold, Karl E; Gimi, Barjor; Weaver, John B

2013-12-15

Functionalized magnetic nanoparticles (mNPs) have shown promise in biosensing and other biomedical applications. Here we use functionalized mNPs to develop a highly sensitive, versatile sensing strategy required in practical biological assays and potentially in vivo analysis. We demonstrate a new sensing scheme based on magnetic spectroscopy of nanoparticle Brownian motion (MSB) to quantitatively detect molecular targets. MSB uses the harmonics of oscillating mNPs as a metric for the freedom of rotational motion, thus reflecting the bound state of the mNP. The harmonics can be detected in vivo from nanogram quantities of iron within 5s. Using a streptavidin-biotin binding system, we show that the detection limit of the current MSB technique is lower than 150 pM (0.075 pmole), which is much more sensitive than previously reported techniques based on mNP detection. Using mNPs conjugated with two anti-thrombin DNA aptamers, we show that thrombin can be detected with high sensitivity (4 nM or 2 pmole). A DNA-DNA interaction was also investigated. The results demonstrated that sequence selective DNA detection can be achieved with 100 pM (0.05 pmole) sensitivity. The results of using MSB to sense these interactions, show that the MSB based sensing technique can achieve rapid measurement (within 10s), and is suitable for detecting and quantifying a wide range of biomarkers or analytes. It has the potential to be applied in variety of biomedical applications or diagnostic analyses. © 2013 Elsevier B.V. All rights reserved.

Mobile technology and telemedicine for shoulder range of motion: validation of a motion-based machine-learning software development kit.

PubMed

Ramkumar, Prem N; Haeberle, Heather S; Navarro, Sergio M; Sultan, Assem A; Mont, Michael A; Ricchetti, Eric T; Schickendantz, Mark S; Iannotti, Joseph P

2018-03-07

Mobile technology offers the prospect of delivering high-value care with increased patient access and reduced costs. Advances in mobile health (mHealth) and telemedicine have been inhibited by the lack of interconnectivity between devices and software and inability to process consumer sensor data. The objective of this study was to preliminarily validate a motion-based machine learning software development kit (SDK) for the shoulder compared with a goniometer for 4 arcs of motion: (1) abduction, (2) forward flexion, (3) internal rotation, and (4) external rotation. A mobile application for the SDK was developed and "taught" 4 arcs of shoulder motion. Ten subjects without shoulder pain or prior shoulder surgery performed the arcs of motion for 5 repetitions. Each motion was measured by the SDK and compared with a physician-measured manual goniometer measurement. Angular differences between SDK and goniometer measurements were compared with univariate and power analyses. The comparison between the SDK and goniometer measurement detected a mean difference of less than 5° for all arcs of motion (P > .05), with a 94% chance of detecting a large effect size from a priori power analysis. Mean differences for the arcs of motion were: abduction, -3.7° ± 3.2°; forward flexion, -4.9° ± 2.5°; internal rotation, -2.4° ± 3.7°; and external rotation -2.6° ± 3.4°. The SDK has the potential to remotely substitute for a shoulder range of motion examination within 5° of goniometer measurements. An open-source motion-based SDK that can learn complex movements, including clinical shoulder range of motion, from consumer sensors offers promise for the future of mHealth, particularly in telemonitoring before and after orthopedic surgery. Copyright © 2018 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Development of a vision non-contact sensing system for telerobotic applications

NASA Astrophysics Data System (ADS)

Karkoub, M.; Her, M.-G.; Ho, M.-I.; Huang, C.-C.

2013-08-01

The study presented here describes a novel vision-based motion detection system for telerobotic operations such as distant surgical procedures. The system uses a CCD camera and image processing to detect the motion of a master robot or operator. Colour tags are placed on the arm and head of a human operator to detect the up/down, right/left motion of the head as well as the right/left motion of the arm. The motion of the colour tags are used to actuate a slave robot or a remote system. The determination of the colour tags' motion is achieved through image processing using eigenvectors and colour system morphology and the relative head, shoulder and wrist rotation angles through inverse dynamics and coordinate transformation. A program is used to transform this motion data into motor control commands and transmit them to a slave robot or remote system through wireless internet. The system performed well even in complex environments with errors that did not exceed 2 pixels with a response time of about 0.1 s. The results of the experiments are available at: http://www.youtube.com/watch?v=yFxLaVWE3f8 and http://www.youtube.com/watch?v=_nvRcOzlWHw

Motion-based threat detection using microrods: experiments and numerical simulations.

PubMed

Ezhilan, Barath; Gao, Wei; Pei, Allen; Rozen, Isaac; Dong, Renfeng; Jurado-Sanchez, Beatriz; Wang, Joseph; Saintillan, David

2015-05-07

Motion-based chemical sensing using microscale particles has attracted considerable recent attention. In this paper, we report on new experiments and Brownian dynamics simulations that cast light on the dynamics of both passive and active microrods (gold wires and gold-platinum micromotors) in a silver ion gradient. We demonstrate that such microrods can be used for threat detection in the form of a silver ion source, allowing for the determination of both the location of the source and concentration of silver. This threat detection strategy relies on the diffusiophoretic motion of both passive and active microrods in the ionic gradient and on the speed acceleration of the Au-Pt micromotors in the presence of silver ions. A Langevin model describing the microrod dynamics and accounting for all of these effects is presented, and key model parameters are extracted from the experimental data, thereby providing a reliable estimate for the full spatiotemporal distribution of the silver ions in the vicinity of the source.

Multifunctional devices based on SnO2@rGO-coated fibers for human motion monitoring, ethanol detection, and photo response

NASA Astrophysics Data System (ADS)

Mi, Qing; Wang, Qi; Zang, Siyao; Chai, Zhaoer; Zhang, Jinnan; Ren, Xiaomin

2018-05-01

In this study, we developed a multifunctional device based on SnO2@rGO-coated fibers utilizing plasma treatment, dip coating, and microwave irradiation in sequence, and finally realized highly sensitive human motion monitoring, relatively good ethanol detection, and an obvious photo response. Moreover, the high level of comfort and compactness derived from highly elastic and comfortable fabrics contributes to the long-term availability and test accuracy. As an attempt at multifunctional integration of smart clothing, this work provides an attractive and relatively practical research direction.

Multifunctional devices based on SnO2@rGO-coated fibers for human motion monitoring, ethanol detection, and photo response.

PubMed

Mi, Qing; Wang, Qi; Zang, Siyao; Chai, Zhaoer; Zhang, Jinnan; Ren, Xiaomin

2018-05-11

In this study, we developed a multifunctional device based on SnO 2 @rGO-coated fibers utilizing plasma treatment, dip coating, and microwave irradiation in sequence, and finally realized highly sensitive human motion monitoring, relatively good ethanol detection, and an obvious photo response. Moreover, the high level of comfort and compactness derived from highly elastic and comfortable fabrics contributes to the long-term availability and test accuracy. As an attempt at multifunctional integration of smart clothing, this work provides an attractive and relatively practical research direction.

Efficient region-based approach for blotch detection in archived video using texture information

NASA Astrophysics Data System (ADS)

Yous, Hamza; Serir, Amina

2017-03-01

We propose a method for blotch detection in archived videos by modeling their spatiotemporal properties. We introduce an adaptive spatiotemporal segmentation to extract candidate regions that can be classified as blotches. Then, the similarity between the preselected regions and their corresponding motion-compensated regions in the adjacent frames is assessed by means of motion trajectory estimation and textural information analysis. Perceived ground truth based on just noticeable contrast is employed for the evaluation of our approach against the state-of-the-art, and the reported results show a better performance for our approach.

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

Detection of motion artifact patterns in photoplethysmographic signals based on time and period domain analysis.

PubMed

Couceiro, R; Carvalho, P; Paiva, R P; Henriques, J; Muehlsteff, J

2014-12-01

The presence of motion artifacts in photoplethysmographic (PPG) signals is one of the major obstacles in the extraction of reliable cardiovascular parameters in continuous monitoring applications. In the current paper we present an algorithm for motion artifact detection based on the analysis of the variations in the time and the period domain characteristics of the PPG signal. The extracted features are ranked using a normalized mutual information feature selection algorithm and the best features are used in a support vector machine classification model to distinguish between clean and corrupted sections of the PPG signal. The proposed method has been tested in healthy and cardiovascular diseased volunteers, considering 11 different motion artifact sources. The results achieved by the current algorithm (sensitivity--SE: 84.3%, specificity--SP: 91.5% and accuracy--ACC: 88.5%) show that the current methodology is able to identify both corrupted and clean PPG sections with high accuracy in both healthy (ACC: 87.5%) and cardiovascular diseases (ACC: 89.5%) context.

Flexible Piezoelectric Sensor-Based Gait Recognition.

PubMed

Cha, Youngsu; Kim, Hojoon; Kim, Doik

2018-02-05

Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.

Evidence of small-scale magnetic concentrations dragged by vortex motion of solar photospheric plasma

NASA Astrophysics Data System (ADS)

Balmaceda, L.; Vargas Domínguez, S.; Palacios, J.; Cabello, I.; Domingo, V.

2010-04-01

Vortex-type motions have been measured by tracking bright points in high-resolution observations of the solar photosphere. These small-scale motions are thought to be determinant in the evolution of magnetic footpoints and their interaction with plasma and therefore likely to play a role in heating the upper solar atmosphere by twisting magnetic flux tubes. We report the observation of magnetic concentrations being dragged towards the center of a convective vortex motion in the solar photosphere from high-resolution ground-based and space-borne data. We describe this event by analyzing a series of images at different solar atmospheric layers. By computing horizontal proper motions, we detect a vortex whose center appears to be the draining point for the magnetic concentrations detected in magnetograms and well-correlated with the locations of bright points seen in G-band and CN images.

Detecting persons concealed in a vehicle

DOEpatents

Tucker, Jr., Raymond W.

2005-03-29

An improved method for detecting the presence of humans or animals concealed within in a vehicle uses a combination of the continuous wavelet transform and a ratio-based energy calculation to determine whether the motion detected using seismic sensors placed on the vehicle is due to the presence of a heartbeat within the vehicle or is the result of motion caused by external factors such as the wind. The method performs well in the presence of light to moderate ambient wind levels, producing far fewer false alarm indications. The new method significantly improves the range of ambient environmental conditions under which human presence detection systems can reliably operate.

Detection of abnormal living patterns for elderly living alone using support vector data description.

PubMed

Shin, Jae Hyuk; Lee, Boreom; Park, Kwang Suk

2011-05-01

In this study, we developed an automated behavior analysis system using infrared (IR) motion sensors to assist the independent living of the elderly who live alone and to improve the efficiency of their healthcare. An IR motion-sensor-based activity-monitoring system was installed in the houses of the elderly subjects to collect motion signals and three different feature values, activity level, mobility level, and nonresponse interval (NRI). These factors were calculated from the measured motion signals. The support vector data description (SVDD) method was used to classify normal behavior patterns and to detect abnormal behavioral patterns based on the aforementioned three feature values. The simulation data and real data were used to verify the proposed method in the individual analysis. A robust scheme is presented in this paper for optimally selecting the values of different parameters especially that of the scale parameter of the Gaussian kernel function involving in the training of the SVDD window length, T of the circadian rhythmic approach with the aim of applying the SVDD to the daily behavior patterns calculated over 24 h. Accuracies by positive predictive value (PPV) were 95.8% and 90.5% for the simulation and real data, respectively. The results suggest that the monitoring system utilizing the IR motion sensors and abnormal-behavior-pattern detection with SVDD are effective methods for home healthcare of elderly people living alone.

Automated multiple target detection and tracking in UAV videos

NASA Astrophysics Data System (ADS)

Mao, Hongwei; Yang, Chenhui; Abousleman, Glen P.; Si, Jennie

2010-04-01

In this paper, a novel system is presented to detect and track multiple targets in Unmanned Air Vehicles (UAV) video sequences. Since the output of the system is based on target motion, we first segment foreground moving areas from the background in each video frame using background subtraction. To stabilize the video, a multi-point-descriptor-based image registration method is performed where a projective model is employed to describe the global transformation between frames. For each detected foreground blob, an object model is used to describe its appearance and motion information. Rather than immediately classifying the detected objects as targets, we track them for a certain period of time and only those with qualified motion patterns are labeled as targets. In the subsequent tracking process, a Kalman filter is assigned to each tracked target to dynamically estimate its position in each frame. Blobs detected at a later time are used as observations to update the state of the tracked targets to which they are associated. The proposed overlap-rate-based data association method considers the splitting and merging of the observations, and therefore is able to maintain tracks more consistently. Experimental results demonstrate that the system performs well on real-world UAV video sequences. Moreover, careful consideration given to each component in the system has made the proposed system feasible for real-time applications.

Man-systems evaluation of moving base vehicle simulation motion cues. [human acceleration perception involving visual feedback

NASA Technical Reports Server (NTRS)

Kirkpatrick, M.; Brye, R. G.

1974-01-01

A motion cue investigation program is reported that deals with human factor aspects of high fidelity vehicle simulation. General data on non-visual motion thresholds and specific threshold values are established for use as washout parameters in vehicle simulation. A general purpose similator is used to test the contradictory cue hypothesis that acceleration sensitivity is reduced during a vehicle control task involving visual feedback. The simulator provides varying acceleration levels. The method of forced choice is based on the theory of signal detect ability.

A motion-constraint logic for moving-base simulators based on variable filter parameters

NASA Technical Reports Server (NTRS)

Miller, G. K., Jr.

1974-01-01

A motion-constraint logic for moving-base simulators has been developed that is a modification to the linear second-order filters generally employed in conventional constraints. In the modified constraint logic, the filter parameters are not constant but vary with the instantaneous motion-base position to increase the constraint as the system approaches the positional limits. With the modified constraint logic, accelerations larger than originally expected are limited while conventional linear filters would result in automatic shutdown of the motion base. In addition, the modified washout logic has frequency-response characteristics that are an improvement over conventional linear filters with braking for low-frequency pilot inputs. During simulated landing approaches of an externally blown flap short take-off and landing (STOL) transport using decoupled longitudinal controls, the pilots were unable to detect much difference between the modified constraint logic and the logic based on linear filters with braking.

Human visual system-based smoking event detection

NASA Astrophysics Data System (ADS)

Odetallah, Amjad D.; Agaian, Sos S.

2012-06-01

Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

PubMed

Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad

2017-01-01

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.

Algorithm architecture co-design for ultra low-power image sensor

NASA Astrophysics Data System (ADS)

Laforest, T.; Dupret, A.; Verdant, A.; Lattard, D.; Villard, P.

2012-03-01

In a context of embedded video surveillance, stand alone leftbehind image sensors are used to detect events with high level of confidence, but also with a very low power consumption. Using a steady camera, motion detection algorithms based on background estimation to find regions in movement are simple to implement and computationally efficient. To reduce power consumption, the background is estimated using a down sampled image formed of macropixels. In order to extend the class of moving objects to be detected, we propose an original mixed mode architecture developed thanks to an algorithm architecture co-design methodology. This programmable architecture is composed of a vector of SIMD processors. A basic RISC architecture was optimized in order to implement motion detection algorithms with a dedicated set of 42 instructions. Definition of delta modulation as a calculation primitive has allowed to implement algorithms in a very compact way. Thereby, a 1920x1080@25fps CMOS image sensor performing integrated motion detection is proposed with a power estimation of 1.8 mW.

A neural model of the temporal dynamics of figure-ground segregation in motion perception.

PubMed

Raudies, Florian; Neumann, Heiko

2010-03-01

How does the visual system manage to segment a visual scene into surfaces and objects and manage to attend to a target object? Based on psychological and physiological investigations, it has been proposed that the perceptual organization and segmentation of a scene is achieved by the processing at different levels of the visual cortical hierarchy. According to this, motion onset detection, motion-defined shape segregation, and target selection are accomplished by processes which bind together simple features into fragments of increasingly complex configurations at different levels in the processing hierarchy. As an alternative to this hierarchical processing hypothesis, it has been proposed that the processing stages for feature detection and segregation are reflected in different temporal episodes in the response patterns of individual neurons. Such temporal epochs have been observed in the activation pattern of neurons as low as in area V1. Here, we present a neural network model of motion detection, figure-ground segregation and attentive selection which explains these response patterns in an unifying framework. Based on known principles of functional architecture of the visual cortex, we propose that initial motion and motion boundaries are detected at different and hierarchically organized stages in the dorsal pathway. Visual shapes that are defined by boundaries, which were generated from juxtaposed opponent motions, are represented at different stages in the ventral pathway. Model areas in the different pathways interact through feedforward and modulating feedback, while mutual interactions enable the communication between motion and form representations. Selective attention is devoted to shape representations by sending modulating feedback signals from higher levels (working memory) to intermediate levels to enhance their responses. Areas in the motion and form pathway are coupled through top-down feedback with V1 cells at the bottom end of the hierarchy. We propose that the different temporal episodes in the response pattern of V1 cells, as recorded in recent experiments, reflect the strength of modulating feedback signals. This feedback results from the consolidated shape representations from coherent motion patterns and the attentive modulation of responses along the cortical hierarchy. The model makes testable predictions concerning the duration and delay of the temporal episodes of V1 cell responses as well as their response variations that were caused by modulating feedback signals. Copyright 2009 Elsevier Ltd. All rights reserved.

A new smart traffic monitoring method using embedded cement-based piezoelectric sensors

NASA Astrophysics Data System (ADS)

Zhang, Jinrui; Lu, Youyuan; Lu, Zeyu; Liu, Chao; Sun, Guoxing; Li, Zongjin

2015-02-01

Cement-based piezoelectric composites are employed as the sensing elements of a new smart traffic monitoring system. The piezoelectricity of the cement-based piezoelectric sensors enables powerful and accurate real-time detection of the pressure induced by the traffic flow. To describe the mechanical-electrical conversion mechanism between traffic flow and the electrical output of the embedded piezoelectric sensors, a mathematical model is established based on Duhamel’s integral, the constitutive law and the charge-leakage characteristics of the piezoelectric composite. Laboratory tests show that the voltage magnitude of the sensor is linearly proportional to the applied pressure, which ensures the reliability of the cement-based piezoelectric sensors for traffic monitoring. A series of on-site road tests by a 10 tonne truck and a 6.8 tonne van show that vehicle weight-in-motion can be predicted based on the mechanical-electrical model by taking into account the vehicle speed and the charge-leakage property of the piezoelectric sensor. In the speed range from 20 km h-1 to 70 km h-1, the error of the repeated weigh-in-motion measurements of the 6.8 tonne van is less than 1 tonne. The results indicate that the embedded cement-based piezoelectric sensors and associated measurement setup have good capability of smart traffic monitoring, such as traffic flow detection, vehicle speed detection and weigh-in-motion measurement.

Embedded security system for multi-modal surveillance in a railway carriage

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Audigier, Romaric; Ambellouis, Sébastien; Capman, François; Benhadda, Hamid; Joudrier, Stéphanie; Sodoyer, David; Lamarque, Thierry

2015-10-01

Public transport security is one of the main priorities of the public authorities when fighting against crime and terrorism. In this context, there is a great demand for autonomous systems able to detect abnormal events such as violent acts aboard passenger cars and intrusions when the train is parked at the depot. To this end, we present an innovative approach which aims at providing efficient automatic event detection by fusing video and audio analytics and reducing the false alarm rate compared to classical stand-alone video detection. The multi-modal system is composed of two microphones and one camera and integrates onboard video and audio analytics and fusion capabilities. On the one hand, for detecting intrusion, the system relies on the fusion of "unusual" audio events detection with intrusion detections from video processing. The audio analysis consists in modeling the normal ambience and detecting deviation from the trained models during testing. This unsupervised approach is based on clustering of automatically extracted segments of acoustic features and statistical Gaussian Mixture Model (GMM) modeling of each cluster. The intrusion detection is based on the three-dimensional (3D) detection and tracking of individuals in the videos. On the other hand, for violent events detection, the system fuses unsupervised and supervised audio algorithms with video event detection. The supervised audio technique detects specific events such as shouts. A GMM is used to catch the formant structure of a shout signal. Video analytics use an original approach for detecting aggressive motion by focusing on erratic motion patterns specific to violent events. As data with violent events is not easily available, a normality model with structured motions from non-violent videos is learned for one-class classification. A fusion algorithm based on Dempster-Shafer's theory analyses the asynchronous detection outputs and computes the degree of belief of each probable event.

Motion video analysis using planar parallax

NASA Astrophysics Data System (ADS)

Sawhney, Harpreet S.

1994-04-01

Motion and structure analysis in video sequences can lead to efficient descriptions of objects and their motions. Interesting events in videos can be detected using such an analysis--for instance independent object motion when the camera itself is moving, figure-ground segregation based on the saliency of a structure compared to its surroundings. In this paper we present a method for 3D motion and structure analysis that uses a planar surface in the environment as a reference coordinate system to describe a video sequence. The motion in the video sequence is described as the motion of the reference plane, and the parallax motion of all the non-planar components of the scene. It is shown how this method simplifies the otherwise hard general 3D motion analysis problem. In addition, a natural coordinate system in the environment is used to describe the scene which can simplify motion based segmentation. This work is a part of an ongoing effort in our group towards video annotation and analysis for indexing and retrieval. Results from a demonstration system being developed are presented.

Phase-based motion magnification video for monitoring of vital signals using the Hermite transform

NASA Astrophysics Data System (ADS)

Brieva, Jorge; Moya-Albor, Ernesto

2017-11-01

In this paper we present a new Eulerian phase-based motion magnification technique using the Hermite Transform (HT) decomposition that is inspired in the Human Vision System (HVS). We test our method in one sequence of the breathing of a newborn baby and on a video sequence that shows the heartbeat on the wrist. We detect and magnify the heart pulse applying our technique. Our motion magnification approach is compared to the Laplacian phase based approach by means of quantitative metrics (based on the RMS error and the Fourier transform) to measure the quality of both reconstruction and magnification. In addition a noise robustness analysis is performed for the two methods.

Enhanced Ultrasound Visualization of Brachytherapy Seeds by a Novel Magnetically Induced Motion Imaging Method

DTIC Science & Technology

2007-04-01

We report our progress in developing Magnetically Induced Motion Imaging (MIMI) for unambiguous identification and localization brachytherapy seeds ...tail artifacts in segmented seed images. The second is a method for joining ends of seeds in segmented seed images based on the phase of the detected

Algorithm-Based Motion Magnification for Video Processing in Urological Laparoscopy.

PubMed

Adams, Fabian; Schoelly, Reto; Schlager, Daniel; Schoenthaler, Martin; Schoeb, Dominik S; Wilhelm, Konrad; Hein, Simon; Wetterauer, Ulrich; Miernik, Arkadiusz

2017-06-01

Minimally invasive surgery is in constant further development and has replaced many conventional operative procedures. If vascular structure movement could be detected during these procedures, it could reduce the risk of vascular injury and conversion to open surgery. The recently proposed motion-amplifying algorithm, Eulerian Video Magnification (EVM), has been shown to substantially enhance minimal object changes in digitally recorded video that is barely perceptible to the human eye. We adapted and examined this technology for use in urological laparoscopy. Video sequences of routine urological laparoscopic interventions were recorded and further processed using spatial decomposition and filtering algorithms. The freely available EVM algorithm was investigated for its usability in real-time processing. In addition, a new image processing technology, the CRS iimotion Motion Magnification (CRSMM) algorithm, was specifically adjusted for endoscopic requirements, applied, and validated by our working group. Using EVM, no significant motion enhancement could be detected without severe impairment of the image resolution, motion, and color presentation. The CRSMM algorithm significantly improved image quality in terms of motion enhancement. In particular, the pulsation of vascular structures could be displayed more accurately than in EVM. Motion magnification image processing technology has the potential for clinical importance as a video optimizing modality in endoscopic and laparoscopic surgery. Barely detectable (micro)movements can be visualized using this noninvasive marker-free method. Despite these optimistic results, the technology requires considerable further technical development and clinical tests.

A benchmark for vehicle detection on wide area motion imagery

NASA Astrophysics Data System (ADS)

Catrambone, Joseph; Amzovski, Ismail; Liang, Pengpeng; Blasch, Erik; Sheaff, Carolyn; Wang, Zhonghai; Chen, Genshe; Ling, Haibin

2015-05-01

Wide area motion imagery (WAMI) has been attracting an increased amount of research attention due to its large spatial and temporal coverage. An important application includes moving target analysis, where vehicle detection is often one of the first steps before advanced activity analysis. While there exist many vehicle detection algorithms, a thorough evaluation of them on WAMI data still remains a challenge mainly due to the lack of an appropriate benchmark data set. In this paper, we address a research need by presenting a new benchmark for wide area motion imagery vehicle detection data. The WAMI benchmark is based on the recently available Wright-Patterson Air Force Base (WPAFB09) dataset and the Temple Resolved Uncertainty Target History (TRUTH) associated target annotation. Trajectory annotations were provided in the original release of the WPAFB09 dataset, but detailed vehicle annotations were not available with the dataset. In addition, annotations of static vehicles, e.g., in parking lots, are also not identified in the original release. Addressing these issues, we re-annotated the whole dataset with detailed information for each vehicle, including not only a target's location, but also its pose and size. The annotated WAMI data set should be useful to community for a common benchmark to compare WAMI detection, tracking, and identification methods.

Coherent Lagrangian swirls among submesoscale motions.

PubMed

Beron-Vera, F J; Hadjighasem, A; Xia, Q; Olascoaga, M J; Haller, G

2018-03-05

The emergence of coherent Lagrangian swirls (CLSs) among submesoscale motions in the ocean is illustrated. This is done by applying recent nonlinear dynamics tools for Lagrangian coherence detection on a surface flow realization produced by a data-assimilative submesoscale-permitting ocean general circulation model simulation of the Gulf of Mexico. Both mesoscale and submesoscale CLSs are extracted. These extractions prove the relevance of coherent Lagrangian eddies detected in satellite-altimetry-based geostrophic flow data for the arguably more realistic ageostrophic multiscale flow.

Shape-based human detection for threat assessment

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Zhan, Pengcheng; Thomas, Aaron; Schoenberger, Robert B.

2004-07-01

Detection of intrusions for early threat assessment requires the capability of distinguishing whether the intrusion is a human, an animal, or other objects. Most low-cost security systems use simple electronic motion detection sensors to monitor motion or the location of objects within the perimeter. Although cost effective, these systems suffer from high rates of false alarm, especially when monitoring open environments. Any moving objects including animals can falsely trigger the security system. Other security systems that utilize video equipment require human interpretation of the scene in order to make real-time threat assessment. Shape-based human detection technique has been developed for accurate early threat assessments for open and remote environment. Potential threats are isolated from the static background scene using differential motion analysis and contours of the intruding objects are extracted for shape analysis. Contour points are simplified by removing redundant points connecting short and straight line segments and preserving only those with shape significance. Contours are represented in tangent space for comparison with shapes stored in database. Power cepstrum technique has been developed to search for the best matched contour in database and to distinguish a human from other objects from different viewing angles and distances.

Detecting Lateral Motion using Light's Orbital Angular Momentum.

PubMed

Cvijetic, Neda; Milione, Giovanni; Ip, Ezra; Wang, Ting

2015-10-23

Interrogating an object with a light beam and analyzing the scattered light can reveal kinematic information about the object, which is vital for applications ranging from autonomous vehicles to gesture recognition and virtual reality. We show that by analyzing the change in the orbital angular momentum (OAM) of a tilted light beam eclipsed by a moving object, lateral motion of the object can be detected in an arbitrary direction using a single light beam and without object image reconstruction. We observe OAM spectral asymmetry that corresponds to the lateral motion direction along an arbitrary axis perpendicular to the plane containing the light beam and OAM measurement axes. These findings extend OAM-based remote sensing to detection of non-rotational qualities of objects and may also have extensions to other electromagnetic wave regimes, including radio and sound.

Detecting Lateral Motion using Light’s Orbital Angular Momentum

PubMed Central

Cvijetic, Neda; Milione, Giovanni; Ip, Ezra; Wang, Ting

2015-01-01

Interrogating an object with a light beam and analyzing the scattered light can reveal kinematic information about the object, which is vital for applications ranging from autonomous vehicles to gesture recognition and virtual reality. We show that by analyzing the change in the orbital angular momentum (OAM) of a tilted light beam eclipsed by a moving object, lateral motion of the object can be detected in an arbitrary direction using a single light beam and without object image reconstruction. We observe OAM spectral asymmetry that corresponds to the lateral motion direction along an arbitrary axis perpendicular to the plane containing the light beam and OAM measurement axes. These findings extend OAM-based remote sensing to detection of non-rotational qualities of objects and may also have extensions to other electromagnetic wave regimes, including radio and sound. PMID:26493681

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.

Optimized static and video EEG rapid serial visual presentation (RSVP) paradigm based on motion surprise computation

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Huber, David J.; Bhattacharyya, Rajan

2017-05-01

In this paper, we describe an algorithm and system for optimizing search and detection performance for "items of interest" (IOI) in large-sized images and videos that employ the Rapid Serial Visual Presentation (RSVP) based EEG paradigm and surprise algorithms that incorporate motion processing to determine whether static or video RSVP is used. The system works by first computing a motion surprise map on image sub-regions (chips) of incoming sensor video data and then uses those surprise maps to label the chips as either "static" or "moving". This information tells the system whether to use a static or video RSVP presentation and decoding algorithm in order to optimize EEG based detection of IOI in each chip. Using this method, we are able to demonstrate classification of a series of image regions from video with an azimuth value of 1, indicating perfect classification, over a range of display frequencies and video speeds.

Motion detection using extended fractional Fourier transform and digital speckle photography.

PubMed

Bhaduri, Basanta; Tay, C J; Quan, C; Sheppard, Colin J R

2010-05-24

Digital speckle photography is a useful tool for measuring the motion of optically rough surfaces from the speckle shift that takes place at the recording plane. A simple correlation based digital speckle photographic system has been proposed that implements two simultaneous optical extended fractional Fourier transforms (EFRTs) of different orders using only a single lens and detector to simultaneously detect both the magnitude and direction of translation and tilt by capturing only two frames: one before and another after the object motion. The dynamic range and sensitivity of the measurement can be varied readily by altering the position of the mirror/s used in the optical setup. Theoretical analysis and experiment results are presented.

Satellite radar interferometry for monitoring ice sheet motion: application to an antarctic ice stream.

PubMed

Goldstein, R M; Engelhardt, H; Kamb, B; Frolich, R M

1993-12-03

Satellite radar interferometry (SRI) provides a sensitive means of monitoring the flow velocities and grounding-line positions of ice streams, which are indicators of response of the ice sheets to climatic change or internal instability. The detection limit is about 1.5 millimeters for vertical motions and about 4 millimeters for horizontal motions in the radar beam direction. The grounding line, detected by tidal motions where the ice goes afloat, can be mapped at a resolution of approximately 0.5 kilometer. The SRI velocities and grounding line of the Rutford Ice Stream, Antarctica, agree fairly well with earlier ground-based data. The combined use of SRI and other satellite methods is expected to provide data that will enhance the understanding of ice stream mechanics and help make possible the prediction of ice sheet behavior.

Automatic 3D registration of dynamic stress and rest (82)Rb and flurpiridaz F 18 myocardial perfusion PET data for patient motion detection and correction.

PubMed

Woo, Jonghye; Tamarappoo, Balaji; Dey, Damini; Nakazato, Ryo; Le Meunier, Ludovic; Ramesh, Amit; Lazewatsky, Joel; Germano, Guido; Berman, Daniel S; Slomka, Piotr J

2011-11-01

The authors aimed to develop an image-based registration scheme to detect and correct patient motion in stress and rest cardiac positron emission tomography (PET)/CT images. The patient motion correction was of primary interest and the effects of patient motion with the use of flurpiridaz F 18 and (82)Rb were demonstrated. The authors evaluated stress/rest PET myocardial perfusion imaging datasets in 30 patients (60 datasets in total, 21 male and 9 female) using a new perfusion agent (flurpiridaz F 18) (n = 16) and (82)Rb (n = 14), acquired on a Siemens Biograph-64 scanner in list mode. Stress and rest images were reconstructed into 4 ((82)Rb) or 10 (flurpiridaz F 18) dynamic frames (60 s each) using standard reconstruction (2D attenuation weighted ordered subsets expectation maximization). Patient motion correction was achieved by an image-based registration scheme optimizing a cost function using modified normalized cross-correlation that combined global and local features. For comparison, visual scoring of motion was performed on the scale of 0 to 2 (no motion, moderate motion, and large motion) by two experienced observers. The proposed registration technique had a 93% success rate in removing left ventricular motion, as visually assessed. The maximum detected motion extent for stress and rest were 5.2 mm and 4.9 mm for flurpiridaz F 18 perfusion and 3.0 mm and 4.3 mm for (82)Rb perfusion studies, respectively. Motion extent (maximum frame-to-frame displacement) obtained for stress and rest were (2.2 ± 1.1, 1.4 ± 0.7, 1.9 ± 1.3) mm and (2.0 ± 1.1, 1.2 ±0 .9, 1.9 ± 0.9) mm for flurpiridaz F 18 perfusion studies and (1.9 ± 0.7, 0.7 ± 0.6, 1.3 ± 0.6) mm and (2.0 ± 0.9, 0.6 ± 0.4, 1.2 ± 1.2) mm for (82)Rb perfusion studies, respectively. A visually detectable patient motion threshold was established to be ≥2.2 mm, corresponding to visual user scores of 1 and 2. After motion correction, the average increases in contrast-to-noise ratio (CNR) from all frames for larger than the motion threshold were 16.2% in stress flurpiridaz F 18 and 12.2% in rest flurpiridaz F 18 studies. The average increases in CNR were 4.6% in stress (82)Rb studies and 4.3% in rest (82)Rb studies. Fully automatic motion correction of dynamic PET frames can be performed accurately, potentially allowing improved image quantification of cardiac PET data.

Touch-free, gesture-based control of medical devices and software based on the leap motion controller.

PubMed

Mauser, Stanislas; Burgert, Oliver

2014-01-01

There are several intra-operative use cases which require the surgeon to interact with medical devices. We used the Leap Motion Controller as input device and implemented two use-cases: 2D-Interaction (e.g. advancing EPR data) and selection of a value (e.g. room illumination brightness). The gesture detection was successful and we mapped its output to several devices and systems.

Ultra-wideband radar motion sensor

DOEpatents

McEwan, Thomas E.

1994-01-01

A motion sensor is based on ultra-wideband (UWB) radar. UWB radar range is determined by a pulse-echo interval. For motion detection, the sensors operate by staring at a fixed range and then sensing any change in the averaged radar reflectivity at that range. A sampling gate is opened at a fixed delay after the emission of a transmit pulse. The resultant sampling gate output is averaged over repeated pulses. Changes in the averaged sampling gate output represent changes in the radar reflectivity at a particular range, and thus motion.

Ultra-wideband radar motion sensor

DOEpatents

McEwan, T.E.

1994-11-01

A motion sensor is based on ultra-wideband (UWB) radar. UWB radar range is determined by a pulse-echo interval. For motion detection, the sensors operate by staring at a fixed range and then sensing any change in the averaged radar reflectivity at that range. A sampling gate is opened at a fixed delay after the emission of a transmit pulse. The resultant sampling gate output is averaged over repeated pulses. Changes in the averaged sampling gate output represent changes in the radar reflectivity at a particular range, and thus motion. 15 figs.

Doppler ultrasound-based measurement of tendon velocity and displacement for application toward detecting user-intended motion.

PubMed

Stegman, Kelly J; Park, Edward J; Dechev, Nikolai

2012-07-01

The motivation of this research is to non-invasively monitor the wrist tendon's displacement and velocity, for purposes of controlling a prosthetic device. This feasibility study aims to determine if the proposed technique using Doppler ultrasound is able to accurately estimate the tendon's instantaneous velocity and displacement. This study is conducted with a tendon mimicking experiment consisting of two different materials: a commercial ultrasound scanner, and a reference linear motion stage set-up. Audio-based output signals are acquired from the ultrasound scanner, and are processed with our proposed Fourier technique to obtain the tendon's velocity and displacement estimates. We then compare our estimates to an external reference system, and also to the ultrasound scanner's own estimates based on its proprietary software. The proposed tendon motion estimation method has been shown to be repeatable, effective and accurate in comparison to the external reference system, and is generally more accurate than the scanner's own estimates. After establishing this feasibility study, future testing will include cadaver-based studies to test the technique on the human arm tendon anatomy, and later on live human test subjects in order to further refine the proposed method for the novel purpose of detecting user-intended tendon motion for controlling wearable prosthetic devices.

Independent motion detection with a rival penalized adaptive particle filter

NASA Astrophysics Data System (ADS)

Becker, Stefan; Hübner, Wolfgang; Arens, Michael

2014-10-01

Aggregation of pixel based motion detection into regions of interest, which include views of single moving objects in a scene is an essential pre-processing step in many vision systems. Motion events of this type provide significant information about the object type or build the basis for action recognition. Further, motion is an essential saliency measure, which is able to effectively support high level image analysis. When applied to static cameras, background subtraction methods achieve good results. On the other hand, motion aggregation on freely moving cameras is still a widely unsolved problem. The image flow, measured on a freely moving camera is the result from two major motion types. First the ego-motion of the camera and second object motion, that is independent from the camera motion. When capturing a scene with a camera these two motion types are adverse blended together. In this paper, we propose an approach to detect multiple moving objects from a mobile monocular camera system in an outdoor environment. The overall processing pipeline consists of a fast ego-motion compensation algorithm in the preprocessing stage. Real-time performance is achieved by using a sparse optical flow algorithm as an initial processing stage and a densely applied probabilistic filter in the post-processing stage. Thereby, we follow the idea proposed by Jung and Sukhatme. Normalized intensity differences originating from a sequence of ego-motion compensated difference images represent the probability of moving objects. Noise and registration artefacts are filtered out, using a Bayesian formulation. The resulting a posteriori distribution is located on image regions, showing strong amplitudes in the difference image which are in accordance with the motion prediction. In order to effectively estimate the a posteriori distribution, a particle filter is used. In addition to the fast ego-motion compensation, the main contribution of this paper is the design of the probabilistic filter for real-time detection and tracking of independently moving objects. The proposed approach introduces a competition scheme between particles in order to ensure an improved multi-modality. Further, the filter design helps to generate a particle distribution which is homogenous even in the presence of multiple targets showing non-rigid motion patterns. The effectiveness of the method is shown on exemplary outdoor sequences.

3-d brownian motion simulator for high-sensitivity nanobiotechnological applications.

PubMed

Toth, Arpád; Banky, Dániel; Grolmusz, Vince

2011-12-01

A wide variety of nanobiotechnologic applications are being developed for nanoparticle based in vitro diagnostic and imaging systems. Some of these systems make possible highly sensitive detection of molecular biomarkers. Frequently, the very low concentration of the biomarkers makes impossible the classical, partial differential equation-based mathematical simulation of the motion of the nanoparticles involved. We present a three-dimensional Brownian motion simulation tool for the prediction of the movement of nanoparticles in various thermal, viscosity, and geometric settings in a rectangular cuvette. For nonprofit users the server is freely available at the site http://brownian.pitgroup.org.

Image motion environments: background noise for movement-based animal signals.

PubMed

Peters, Richard; Hemmi, Jan; Zeil, Jochen

2008-05-01

Understanding the evolution of animal signals has to include consideration of the structure of signal and noise, and the sensory mechanisms that detect the signals. Considerable progress has been made in understanding sounds and colour signals, however, the degree to which movement-based signals are constrained by the particular patterns of environmental image motion is poorly understood. Here we have quantified the image motion generated by wind-blown plants at 12 sites in the coastal habitat of the Australian lizard Amphibolurus muricatus. Sampling across different plant communities and meteorological conditions revealed distinct image motion environments. At all locations, image motion became more directional and apparent speed increased as wind speeds increased. The magnitude of these changes and the spatial distribution of image motion, however, varied between locations probably as a function of plant structure and the topographic location. In addition, we show that the background motion noise depends strongly on the particular depth-structure of the environment and argue that such micro-habitat differences suggest specific strategies to preserve signal efficacy. Movement-based signals and motion processing mechanisms, therefore, may reveal the same type of habitat specific structural variation that we see for signals from other modalities.

Design and development of LED-based irregular leather area measuring machine

NASA Astrophysics Data System (ADS)

Adil, Rehan; Khan, Sarah Jamal

2012-01-01

Using optical sensor array, a precision motion control system in a conveyer follows the irregular shaped leather sheet to measure its surface area. In operation, irregular shaped leather sheet passes on conveyer belt and optical sensor array detects the leather sheet edge. In this way outside curvature of the leather sheet is detected and is then feed to the controller to measure its approximate area. Such system can measure irregular shapes, by neglecting rounded corners, ellipses etc. To minimize the error in calculating surface area of irregular curve to the above mentioned system, the motion control system only requires the footprint of the optical sensor to be small and the distance between the sensors is to be minimized. In the proposed technique surface area measurement of irregular shaped leather sheet is done by defining velocity and detecting position of the move. The motion controller takes the information and creates the necessary edge profile on point-to-point bases. As a result irregular shape of leather sheet is mapped and is then feed to the controller to calculate surface area.

Self-powering/self-cleaning electronic-skin basing on PVDF/TiO2 nanofibers for actively detecting body motion and degrading organic pollutants

NASA Astrophysics Data System (ADS)

Dong, Chuanyi; Fu, Yongming; Zang, Weili; He, Haoxuan; Xing, Lili; Xue, Xinyu

2017-09-01

A flexible self-powering/self-cleaning electronic-skin (e-skin) for actively detecting body motion and degrading organic pollutants has been fabricated from PVDF/TiO2 nanofibers. PVDF/TiO2 nanofibers are synthesized by high voltage electrospinning method. The e-skin can be driven by external mechanical vibration, and actively output piezoelectric impulse. The outputting piezoelectric voltage can be significantly influenced by different applied deformation, acting as both the body-motion-detecting signal and the electricity power for driving the device. The e-skin can detect various body motions, such as pressing, stretching, bending finger and clenching fist. The e-skin also has distinct self-cleaning characteristic through piezo-photocatalytic coupling process. The photocatalytic activity of TiO2 and the piezoelectric effect of PVDF are coupled in a single physical/chemical process, which can efficiently degrade organic pollutants on the e-skin. For example, methylene blue (MB) can be completely degraded within 40 min under UV/ultrasonic irradiation. The present results could provoke a possible new research direction for realizing self-powering multifunctional e-skin.

Effect of pressure and padding on motion artifact of textile electrodes.

PubMed

Cömert, Alper; Honkala, Markku; Hyttinen, Jari

2013-04-08

With the aging population and rising healthcare costs, wearable monitoring is gaining importance. The motion artifact affecting dry electrodes is one of the main challenges preventing the widespread use of wearable monitoring systems. In this paper we investigate the motion artifact and ways of making a textile electrode more resilient against motion artifact. Our aim is to study the effects of the pressure exerted onto the electrode, and the effects of inserting padding between the applied pressure and the electrode. We measure real time electrode-skin interface impedance, ECG from two channels, the motion artifact related surface potential, and exerted pressure during controlled motion by a measurement setup designed to estimate the relation of motion artifact to the signals. We use different foam padding materials with various mechanical properties and apply electrode pressures between 5 and 25 mmHg to understand their effect. A QRS and noise detection algorithm based on a modified Pan-Tompkins QRS detection algorithm estimates the electrode behaviour in respect to the motion artifact from two channels; one dominated by the motion artifact and one containing both the motion artifact and the ECG. This procedure enables us to quantify a given setup's susceptibility to the motion artifact. Pressure is found to strongly affect signal quality as is the use of padding. In general, the paddings reduce the motion artifact. However the shape and frequency components of the motion artifact vary for different paddings, and their material and physical properties. Electrode impedance at 100 kHz correlates in some cases with the motion artifact but it is not a good predictor of the motion artifact. From the results of this study, guidelines for improving electrode design regarding padding and pressure can be formulated as paddings are a necessary part of the system for reducing the motion artifact, and further, their effect maximises between 15 mmHg and 20 mmHg of exerted pressure. In addition, we present new methods for evaluating electrode sensitivity to motion, utilizing the detection of noise peaks that fall into the same frequency band as R-peaks.

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

Intelligence Surveillance And Reconnaissance Full Motion Video Automatic Anomaly Detection Of Crowd Movements: System Requirements For Airborne Application

DTIC Science & Technology

The collection of Intelligence , Surveillance, and Reconnaissance (ISR) Full Motion Video (FMV) is growing at an exponential rate, and the manual... intelligence for the warfighter. This paper will address the question of how can automatic pattern extraction, based on computer vision, extract anomalies in

A self-adaptive algorithm for traffic sign detection in motion image based on color and shape features

NASA Astrophysics Data System (ADS)

Zhang, Ka; Sheng, Yehua; Gong, Zhijun; Ye, Chun; Li, Yongqiang; Liang, Cheng

2007-06-01

As an important sub-system in intelligent transportation system (ITS), the detection and recognition of traffic signs from mobile images is becoming one of the hot spots in the international research field of ITS. Considering the problem of traffic sign automatic detection in motion images, a new self-adaptive algorithm for traffic sign detection based on color and shape features is proposed in this paper. Firstly, global statistical color features of different images are computed based on statistics theory. Secondly, some self-adaptive thresholds and special segmentation rules for image segmentation are designed according to these global color features. Then, for red, yellow and blue traffic signs, the color image is segmented to three binary images by these thresholds and rules. Thirdly, if the number of white pixels in the segmented binary image exceeds the filtering threshold, the binary image should be further filtered. Fourthly, the method of gray-value projection is used to confirm top, bottom, left and right boundaries for candidate regions of traffic signs in the segmented binary image. Lastly, if the shape feature of candidate region satisfies the need of real traffic sign, this candidate region is confirmed as the detected traffic sign region. The new algorithm is applied to actual motion images of natural scenes taken by a CCD camera of the mobile photogrammetry system in Nanjing at different time. The experimental results show that the algorithm is not only simple, robust and more adaptive to natural scene images, but also reliable and high-speed on real traffic sign detection.

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.

Heterogeneous CPU-GPU moving targets detection for UAV video

NASA Astrophysics Data System (ADS)

Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan

2017-07-01

Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

An optical MEMS accelerometer fabricated using double-sided deep reactive ion etching on silicon-on-insulator wafer

NASA Astrophysics Data System (ADS)

Teo, Adrian J. T.; Li, Holden; Tan, Say Hwa; Yoon, Yong-Jin

2017-06-01

Optical MEMS devices provide fast detection, electromagnetic resilience and high sensitivity. Using this technology, an optical gratings based accelerometer design concept was developed for seismic motion detection purposes that provides miniaturization, high manufacturability, low costs and high sensitivity. Detailed in-house fabrication procedures of a double-sided deep reactive ion etching (DRIE) on a silicon-on-insulator (SOI) wafer for a micro opto electro mechanical system (MOEMS) device are presented and discussed. Experimental results obtained show that the conceptual device successfully captured motion similar to a commercial accelerometer with an average sensitivity of 13.6 mV G-1, and a highest recorded sensitivity of 44.1 mV G-1. A noise level of 13.5 mV was detected due to experimental setup limitations. This is the first MOEMS accelerometer developed using double-sided DRIE on SOI wafer for the application of seismic motion detection, and is a breakthrough technology platform to open up options for lower cost MOEMS devices.

Towards Contactless Silent Speech Recognition Based on Detection of Active and Visible Articulators Using IR-UWB Radar

PubMed Central

Shin, Young Hoon; Seo, Jiwon

2016-01-01

People with hearing or speaking disabilities are deprived of the benefits of conventional speech recognition technology because it is based on acoustic signals. Recent research has focused on silent speech recognition systems that are based on the motions of a speaker’s vocal tract and articulators. Because most silent speech recognition systems use contact sensors that are very inconvenient to users or optical systems that are susceptible to environmental interference, a contactless and robust solution is hence required. Toward this objective, this paper presents a series of signal processing algorithms for a contactless silent speech recognition system using an impulse radio ultra-wide band (IR-UWB) radar. The IR-UWB radar is used to remotely and wirelessly detect motions of the lips and jaw. In order to extract the necessary features of lip and jaw motions from the received radar signals, we propose a feature extraction algorithm. The proposed algorithm noticeably improved speech recognition performance compared to the existing algorithm during our word recognition test with five speakers. We also propose a speech activity detection algorithm to automatically select speech segments from continuous input signals. Thus, speech recognition processing is performed only when speech segments are detected. Our testbed consists of commercial off-the-shelf radar products, and the proposed algorithms are readily applicable without designing specialized radar hardware for silent speech processing. PMID:27801867

Towards Contactless Silent Speech Recognition Based on Detection of Active and Visible Articulators Using IR-UWB Radar.

PubMed

Shin, Young Hoon; Seo, Jiwon

2016-10-29

People with hearing or speaking disabilities are deprived of the benefits of conventional speech recognition technology because it is based on acoustic signals. Recent research has focused on silent speech recognition systems that are based on the motions of a speaker's vocal tract and articulators. Because most silent speech recognition systems use contact sensors that are very inconvenient to users or optical systems that are susceptible to environmental interference, a contactless and robust solution is hence required. Toward this objective, this paper presents a series of signal processing algorithms for a contactless silent speech recognition system using an impulse radio ultra-wide band (IR-UWB) radar. The IR-UWB radar is used to remotely and wirelessly detect motions of the lips and jaw. In order to extract the necessary features of lip and jaw motions from the received radar signals, we propose a feature extraction algorithm. The proposed algorithm noticeably improved speech recognition performance compared to the existing algorithm during our word recognition test with five speakers. We also propose a speech activity detection algorithm to automatically select speech segments from continuous input signals. Thus, speech recognition processing is performed only when speech segments are detected. Our testbed consists of commercial off-the-shelf radar products, and the proposed algorithms are readily applicable without designing specialized radar hardware for silent speech processing.

Improved Shear Wave Motion Detection Using Pulse-Inversion Harmonic Imaging with a Phased Array Transducer

PubMed Central

Song, Pengfei; Zhao, Heng; Urban, Matthew W.; Manduca, Armando; Pislaru, Sorin V.; Kinnick, Randall R.; Pislaru, Cristina; Greenleaf, James F.; Chen, Shigao

2013-01-01

Ultrasound tissue harmonic imaging is widely used to improve ultrasound B-mode imaging quality thanks to its effectiveness in suppressing imaging artifacts associated with ultrasound reverberation, phase aberration, and clutter noise. In ultrasound shear wave elastography (SWE), because the shear wave motion signal is extracted from the ultrasound signal, these noise sources can significantly deteriorate the shear wave motion tracking process and consequently result in noisy and biased shear wave motion detection. This situation is exacerbated in in vivo SWE applications such as heart, liver, and kidney. This paper, therefore, investigated the possibility of implementing harmonic imaging, specifically pulse-inversion harmonic imaging, in shear wave tracking, with the hypothesis that harmonic imaging can improve shear wave motion detection based on the same principles that apply to general harmonic B-mode imaging. We first designed an experiment with a gelatin phantom covered by an excised piece of pork belly and show that harmonic imaging can significantly improve shear wave motion detection by producing less underestimated shear wave motion and more consistent shear wave speed measurements than fundamental imaging. Then, a transthoracic heart experiment on a freshly sacrificed pig showed that harmonic imaging could robustly track the shear wave motion and give consistent shear wave speed measurements while fundamental imaging could not. Finally, an in vivo transthoracic study of seven healthy volunteers showed that the proposed harmonic imaging tracking sequence could provide consistent estimates of the left ventricular myocardium stiffness in end-diastole with a general success rate of 80% and a success rate of 93.3% when excluding the subject with Body Mass Index (BMI) higher than 25. These promising results indicate that pulse-inversion harmonic imaging can significantly improve shear wave motion tracking and thus potentially facilitate more robust assessment of tissue elasticity by SWE. PMID:24021638

Scale Changes Provide an Alternative Cue For the Discrimination of Heading, But Not Object Motion

PubMed Central

Calabro, Finnegan J.; Vaina, Lucia Maria

2016-01-01

Background Understanding the dynamics of our surrounding environments is a task usually attributed to the detection of motion based on changes in luminance across space. Yet a number of other cues, both dynamic and static, have been shown to provide useful information about how we are moving and how objects around us move. One such cue, based on changes in spatial frequency, or scale, over time has been shown to be useful in conveying motion in depth even in the absence of a coherent, motion-defined flow field (optic flow). Material/Methods 16 right handed healthy observers (ages 18–28) participated in the behavioral experiments described in this study. Using analytical behavioral methods we investigate the functional specificity of this cue by measuring the ability of observers to perform tasks of heading (direction of self-motion) and 3D trajectory discrimination on the basis of scale changes and optic flow. Results Statistical analyses of performance on the test-experiments in comparison to the control experiments suggests that while scale changes may be involved in the detection of heading, they are not correctly integrated with translational motion and, thus, do not provide a correct discrimination of 3D object trajectories. Conclusions These results have the important implication for the type of visual guided navigation that can be done by an observer blind to optic flow. Scale change is an important alternative cue for self-motion. PMID:27231114

Scale Changes Provide an Alternative Cue For the Discrimination of Heading, But Not Object Motion.

PubMed

Calabro, Finnegan J; Vaina, Lucia Maria

2016-05-27

BACKGROUND Understanding the dynamics of our surrounding environments is a task usually attributed to the detection of motion based on changes in luminance across space. Yet a number of other cues, both dynamic and static, have been shown to provide useful information about how we are moving and how objects around us move. One such cue, based on changes in spatial frequency, or scale, over time has been shown to be useful in conveying motion in depth even in the absence of a coherent, motion-defined flow field (optic flow). MATERIAL AND METHODS 16 right handed healthy observers (ages 18-28) participated in the behavioral experiments described in this study. Using analytical behavioral methods we investigate the functional specificity of this cue by measuring the ability of observers to perform tasks of heading (direction of self-motion) and 3D trajectory discrimination on the basis of scale changes and optic flow. RESULTS Statistical analyses of performance on the test-experiments in comparison to the control experiments suggests that while scale changes may be involved in the detection of heading, they are not correctly integrated with translational motion and, thus, do not provide a correct discrimination of 3D object trajectories. CONCLUSIONS These results have the important implication for the type of visual guided navigation that can be done by an observer blind to optic flow. Scale change is an important alternative cue for self-motion.

Early Detection of Infection in Pigs through an Online Monitoring System.

PubMed

Martínez-Avilés, M; Fernández-Carrión, E; López García-Baones, J M; Sánchez-Vizcaíno, J M

2017-04-01

Late detection of emergency diseases causes significant economic losses for pig producers and governments. As the first signs of animal infection are usually fever and reduced motion that lead to reduced consumption of water and feed, we developed a novel smart system to monitor body temperature and motion in real time, facilitating the early detection of infectious diseases. In this study, carried out within the framework of the European Union research project Rapidia Field, we tested the smart system on 10 pigs experimentally infected with two doses of an attenuated strain of African swine fever. Biosensors and an accelerometer embedded in an eartag captured data before and after infection, and video cameras were used to monitor the animals 24 h per day. The results showed that in 8 of 9 cases, the monitoring system detected infection onset as an increase in body temperature and decrease in movement before or simultaneously with fever detection based on rectal temperature measurement, observation of clinical signs, the decrease in water consumption or positive qPCR detection of virus. In addition, this decrease in movement was reliably detected using automatic analysis of video images therefore providing an inexpensive alternative to direct motion measurement. The system can be set up to alert staff when high fever, reduced motion or both are detected in one or more animals. This system may be useful for monitoring sentinel herds in real time, considerably reducing the financial and logistical costs of periodic sampling and increasing the chances of early detection of infection. © 2015 Blackwell Verlag GmbH.

Antimicrobial Susceptibility Test with Plasmonic Imaging and Tracking of Single Bacterial Motions on Nanometer Scale.

PubMed

Syal, Karan; Iriya, Rafael; Yang, Yunze; Yu, Hui; Wang, Shaopeng; Haydel, Shelley E; Chen, Hong-Yuan; Tao, Nongjian

2016-01-26

Antimicrobial susceptibility tests (ASTs) are important for confirming susceptibility to empirical antibiotics and detecting resistance in bacterial isolates. Currently, most ASTs performed in clinical microbiology laboratories are based on bacterial culturing, which take days to complete for slowly growing microorganisms. A faster AST will reduce morbidity and mortality rates and help healthcare providers administer narrow spectrum antibiotics at the earliest possible treatment stage. We report the development of a nonculture-based AST using a plasmonic imaging and tracking (PIT) technology. We track the motion of individual bacterial cells tethered to a surface with nanometer (nm) precision and correlate the phenotypic motion with bacterial metabolism and antibiotic action. We show that antibiotic action significantly slows down bacterial motion, which can be quantified for development of a rapid phenotypic-based AST.

Automatic 3D motion estimation of left ventricle from C-arm rotational angiocardiography using a prior motion model and learning based boundary detector.

PubMed

Chen, Mingqing; Zheng, Yefeng; Wang, Yang; Mueller, Kerstin; Lauritsch, Guenter

2013-01-01

Compared to pre-operative imaging modalities, it is more convenient to estimate the current cardiac physiological status from C-arm angiocardiography since C-arm is a widely used intra-operative imaging modality to guide many cardiac interventions. The 3D shape and motion of the left ventricle (LV) estimated from rotational angiocardiography provide important cardiac function measurements, e.g., ejection fraction and myocardium motion dyssynchrony. However, automatic estimation of the 3D LV motion is difficult since all anatomical structures overlap on the 2D X-ray projections and the nearby confounding strong image boundaries (e.g., pericardium) often cause ambiguities to LV endocardium boundary detection. In this paper, a new framework is proposed to overcome the aforementioned difficulties: (1) A new learning-based boundary detector is developed by training a boosting boundary classifier combined with the principal component analysis of a local image patch; (2) The prior LV motion model is learned from a set of dynamic cardiac computed tomography (CT) sequences to provide a good initial estimate of the 3D LV shape of different cardiac phases; (3) The 3D motion trajectory is learned for each mesh point; (4) All these components are integrated into a multi-surface graph optimization method to extract the globally coherent motion. The method is tested on seven patient scans, showing significant improvement on the ambiguous boundary cases with a detection accuracy of 2.87 +/- 1.00 mm on LV endocardium boundary delineation in the 2D projections.

Video-based real-time on-street parking occupancy detection system

NASA Astrophysics Data System (ADS)

Bulan, Orhan; Loce, Robert P.; Wu, Wencheng; Wang, YaoRong; Bernal, Edgar A.; Fan, Zhigang

2013-10-01

Urban parking management is receiving significant attention due to its potential to reduce traffic congestion, fuel consumption, and emissions. Real-time parking occupancy detection is a critical component of on-street parking management systems, where occupancy information is relayed to drivers via smart phone apps, radio, Internet, on-road signs, or global positioning system auxiliary signals. Video-based parking occupancy detection systems can provide a cost-effective solution to the sensing task while providing additional functionality for traffic law enforcement and surveillance. We present a video-based on-street parking occupancy detection system that can operate in real time. Our system accounts for the inherent challenges that exist in on-street parking settings, including illumination changes, rain, shadows, occlusions, and camera motion. Our method utilizes several components from video processing and computer vision for motion detection, background subtraction, and vehicle detection. We also present three traffic law enforcement applications: parking angle violation detection, parking boundary violation detection, and exclusion zone violation detection, which can be integrated into the parking occupancy cameras as a value-added option. Our experimental results show that the proposed parking occupancy detection method performs in real-time at 5 frames/s and achieves better than 90% detection accuracy across several days of videos captured in a busy street block under various weather conditions such as sunny, cloudy, and rainy, among others.

Robust real-time extraction of respiratory signals from PET list-mode data.

PubMed

Salomon, Andre; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-05-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions' detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting ("binning") of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signalsdirectly from the acquired PET data simplifies the clinical workflow as it avoids to handle additional signal measurement equipment. We introduce a new data-driven method "Combined Local Motion Detection" (CLMD). It uses the Time-of-Flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using 7 measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware. © 2018 Institute of Physics and Engineering in Medicine.

Event Recognition for Contactless Activity Monitoring Using Phase-Modulated Continuous Wave Radar.

PubMed

Forouzanfar, Mohamad; Mabrouk, Mohamed; Rajan, Sreeraman; Bolic, Miodrag; Dajani, Hilmi R; Groza, Voicu Z

2017-02-01

The use of remote sensing technologies such as radar is gaining popularity as a technique for contactless detection of physiological signals and analysis of human motion. This paper presents a methodology for classifying different events in a collection of phase modulated continuous wave radar returns. The primary application of interest is to monitor inmates where the presence of human vital signs amidst different, interferences needs to be identified. A comprehensive set of features is derived through time and frequency domain analyses of the radar returns. The Bhattacharyya distance is used to preselect the features with highest class separability as the possible candidate features for use in the classification process. The uncorrelated linear discriminant analysis is performed to decorrelate, denoise, and reduce the dimension of the candidate feature set. Linear and quadratic Bayesian classifiers are designed to distinguish breathing, different human motions, and nonhuman motions. The performance of these classifiers is evaluated on a pilot dataset of radar returns that contained different events including breathing, stopped breathing, simple human motions, and movement of fan and water. Our proposed pattern classification system achieved accuracies of up to 93% in stationary subject detection, 90% in stop-breathing detection, and 86% in interference detection. Our proposed radar pattern recognition system was able to accurately distinguish the predefined events amidst interferences. Besides inmate monitoring and suicide attempt detection, this paper can be extended to other radar applications such as home-based monitoring of elderly people, apnea detection, and home occupancy detection.

An effective and robust method for tracking multiple fish in video image based on fish head detection.

PubMed

Qian, Zhi-Ming; Wang, Shuo Hong; Cheng, Xi En; Chen, Yan Qiu

2016-06-23

Fish tracking is an important step for video based analysis of fish behavior. Due to severe body deformation and mutual occlusion of multiple swimming fish, accurate and robust fish tracking from video image sequence is a highly challenging problem. The current tracking methods based on motion information are not accurate and robust enough to track the waving body and handle occlusion. In order to better overcome these problems, we propose a multiple fish tracking method based on fish head detection. The shape and gray scale characteristics of the fish image are employed to locate the fish head position. For each detected fish head, we utilize the gray distribution of the head region to estimate the fish head direction. Both the position and direction information from fish detection are then combined to build a cost function of fish swimming. Based on the cost function, global optimization method can be applied to associate the target between consecutive frames. Results show that our method can accurately detect the position and direction information of fish head, and has a good tracking performance for dozens of fish. The proposed method can successfully obtain the motion trajectories for dozens of fish so as to provide more precise data to accommodate systematic analysis of fish behavior.

Reconstructing 3-D skin surface motion for the DIET breast cancer screening system.

PubMed

Botterill, Tom; Lotz, Thomas; Kashif, Amer; Chase, J Geoffrey

2014-05-01

Digital image-based elasto-tomography (DIET) is a prototype system for breast cancer screening. A breast is imaged while being vibrated, and the observed surface motion is used to infer the internal stiffness of the breast, hence identifying tumors. This paper describes a computer vision system for accurately measuring 3-D surface motion. A model-based segmentation is used to identify the profile of the breast in each image, and the 3-D surface is reconstructed by fitting a model to the profiles. The surface motion is measured using a modern optical flow implementation customized to the application, then trajectories of points on the 3-D surface are given by fusing the optical flow with the reconstructed surfaces. On data from human trials, the system is shown to exceed the performance of an earlier marker-based system at tracking skin surface motion. We demonstrate that the system can detect a 10 mm tumor in a silicone phantom breast.

Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification

NASA Astrophysics Data System (ADS)

Sarrafi, Aral; Mao, Zhu; Niezrecki, Christopher; Poozesh, Peyman

2018-05-01

Vibration-based Structural Health Monitoring (SHM) techniques are among the most common approaches for structural damage identification. The presence of damage in structures may be identified by monitoring the changes in dynamic behavior subject to external loading, and is typically performed by using experimental modal analysis (EMA) or operational modal analysis (OMA). These tools for SHM normally require a limited number of physically attached transducers (e.g. accelerometers) in order to record the response of the structure for further analysis. Signal conditioners, wires, wireless receivers and a data acquisition system (DAQ) are also typical components of traditional sensing systems used in vibration-based SHM. However, instrumentation of lightweight structures with contact sensors such as accelerometers may induce mass-loading effects, and for large-scale structures, the instrumentation is labor intensive and time consuming. Achieving high spatial measurement resolution for a large-scale structure is not always feasible while working with traditional contact sensors, and there is also the potential for a lack of reliability associated with fixed contact sensors in outliving the life-span of the host structure. Among the state-of-the-art non-contact measurements, digital video cameras are able to rapidly collect high-density spatial information from structures remotely. In this paper, the subtle motions from recorded video (i.e. a sequence of images) are extracted by means of Phase-based Motion Estimation (PME) and the extracted information is used to conduct damage identification on a 2.3-m long Skystream® wind turbine blade (WTB). The PME and phased-based motion magnification approach estimates the structural motion from the captured sequence of images for both a baseline and damaged test cases on a wind turbine blade. Operational deflection shapes of the test articles are also quantified and compared for the baseline and damaged states. In addition, having proper lighting while working with high-speed cameras can be an issue, therefore image enhancement and contrast manipulation has also been performed to enhance the raw images. Ultimately, the extracted resonant frequencies and operational deflection shapes are used to detect the presence of damage, demonstrating the feasibility of implementing non-contact video measurements to perform realistic structural damage detection.

Angle-independent measure of motion for image-based gating in 3D coronary angiography

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

Lehmann, Glen C.; Holdsworth, David W.; Drangova, Maria

2006-05-15

The role of three-dimensional (3D) image guidance for interventional procedures and minimally invasive surgeries is increasing for the treatment of vascular disease. Currently, most interventional procedures are guided by two-dimensional x-ray angiography, but computed rotational angiography has the potential to provide 3D geometric information about the coronary arteries. The creation of 3D angiographic images of the coronary arteries requires synchronization of data acquisition with respect to the cardiac cycle, in order to minimize motion artifacts. This can be achieved by inferring the extent of motion from a patient's electrocardiogram (ECG) signal. However, a direct measurement of motion (from the 2Dmore » angiograms) has the potential to improve the 3D angiographic images by ensuring that only projections acquired during periods of minimal motion are included in the reconstruction. This paper presents an image-based metric for measuring the extent of motion in 2D x-ray angiographic images. Adaptive histogram equalization was applied to projection images to increase the sharpness of coronary arteries and the superior-inferior component of the weighted centroid (SIC) was measured. The SIC constitutes an image-based metric that can be used to track vessel motion, independent of apparent motion induced by the rotational acquisition. To evaluate the technique, six consecutive patients scheduled for routine coronary angiography procedures were studied. We compared the end of the SIC rest period ({rho}) to R-waves (R) detected in the patient's ECG and found a mean difference of 14{+-}80 ms. Two simultaneous angular positions were acquired and {rho} was detected for each position. There was no statistically significant difference (P=0.79) between {rho} in the two simultaneously acquired angular positions. Thus we have shown the SIC to be independent of view angle, which is critical for rotational angiography. A preliminary image-based gating strategy that employed the SIC was compared to an ECG-based gating strategy in a porcine model. The image-based gating strategy selected 61 projection images, compared to 45 selected by the ECG-gating strategy. Qualitative comparison revealed that although both the SIC-based and ECG-gated reconstructions decreased motion artifact compared to reconstruction with no gating, the SIC-based gating technique increased the conspicuity of smaller vessels when compared to ECG gating in maximum intensity projections of the reconstructions and increased the sharpness of a vessel cross section in multi-planar reformats of the reconstruction.« less

Piecewise-Planar StereoScan: Sequential Structure and Motion using Plane Primitives.

PubMed

Raposo, Carolina; Antunes, Michel; P Barreto, Joao

2017-08-09

The article describes a pipeline that receives as input a sequence of stereo images, and outputs the camera motion and a Piecewise-Planar Reconstruction (PPR) of the scene. The pipeline, named Piecewise-Planar StereoScan (PPSS), works as follows: the planes in the scene are detected for each stereo view using semi-dense depth estimation; the relative pose is computed by a new closed-form minimal algorithm that only uses point correspondences whenever plane detections do not fully constrain the motion; the camera motion and the PPR are jointly refined by alternating between discrete optimization and continuous bundle adjustment; and, finally, the detected 3D planes are segmented in images using a new framework that handles low texture and visibility issues. PPSS is extensively validated in indoor and outdoor datasets, and benchmarked against two popular point-based SfM pipelines. The experiments confirm that plane-based visual odometry is resilient to situations of small image overlap, poor texture, specularity, and perceptual aliasing where the fast LIBVISO2 pipeline fails. The comparison against VisualSfM+CMVS/PMVS shows that, for a similar computational complexity, PPSS is more accurate and provides much more compelling and visually pleasant 3D models. These results strongly suggest that plane primitives are an advantageous alternative to point correspondences for applications of SfM and 3D reconstruction in man-made environments.

Detection of visual events along the apparent motion trace in patients with paranoid schizophrenia.

PubMed

Sanders, Lia Lira Olivier; Muckli, Lars; de Millas, Walter; Lautenschlager, Marion; Heinz, Andreas; Kathmann, Norbert; Sterzer, Philipp

2012-07-30

Dysfunctional prediction in sensory processing has been suggested as a possible causal mechanism in the development of delusions in patients with schizophrenia. Previous studies in healthy subjects have shown that while the perception of apparent motion can mask visual events along the illusory motion trace, such motion masking is reduced when events are spatio-temporally compatible with the illusion, and, therefore, predictable. Here we tested the hypothesis that this specific detection advantage for predictable target stimuli on the apparent motion trace is reduced in patients with paranoid schizophrenia. Our data show that, although target detection along the illusory motion trace is generally impaired, both patients and healthy control participants detect predictable targets more often than unpredictable targets. Patients had a stronger motion masking effect when compared to controls. However, patients showed the same advantage in the detection of predictable targets as healthy control subjects. Our findings reveal stronger motion masking but intact prediction of visual events along the apparent motion trace in patients with paranoid schizophrenia and suggest that the sensory prediction mechanism underlying apparent motion is not impaired in paranoid schizophrenia. Copyright © 2012. Published by Elsevier Ireland Ltd.

Towards Wearable A-Mode Ultrasound Sensing for Real-Time Finger Motion Recognition.

PubMed

Yang, Xingchen; Sun, Xueli; Zhou, Dalin; Li, Yuefeng; Liu, Honghai

2018-06-01

It is evident that surface electromyography (sEMG) based human-machine interfaces (HMI) have inherent difficulty in predicting dexterous musculoskeletal movements such as finger motions. This paper is an attempt to investigate a plausible alternative to sEMG, ultrasound-driven HMI, for dexterous motion recognition due to its characteristic of detecting morphological changes of deep muscles and tendons. A multi-channel A-mode ultrasound lightweight device is adopted to evaluate the performance of finger motion recognition; an experiment is designed for both widely acceptable offline and online algorithms with eight able-bodied subjects employed. The experiment result presents that the offline recognition accuracy is up to 98.83% ± 0.79%. The real-time motion completion rate is 95.4% ± 8.7% and online motion selection time is 0.243 ± 0.127 s. The outcomes confirm the feasibility of A-mode ultrasound based wearable HMI and its prosperous applications in prosthetic devices, virtual reality, and remote manipulation.

New Astrometric Limits on the Stochastic Gravitational Wave Background

NASA Astrophysics Data System (ADS)

Darling, Jeremiah K.; Truebenbach, Alexandra; Paine, Jennie

2018-06-01

We present new limits on the low frequency (f < 10-8 Hz) stochastic gravitational wave background using correlated extragalactic proper motions. The familiar methods for gravitational wave detection are ground- and space-based laser interferometry, pulsar timing, and polarization of the cosmic microwave background. Astrometry offers an additional path to gravitational wave detection because gravitational waves deflect the light rays of extragalactic objects, creating apparent proper motions in a quadrupolar (and higher order modes) pattern. Astrometry is sensitive to gravitational waves with frequencies between roughly 10-18 Hz and 10-8 Hz (between H0 and 1/3 yr-1), which overlaps and bridges the pulsar timing and CMB polarization regimes. We present the methods and results of two complementary approaches to astrometric gravitational wave detection: (1) a small ~500-object radio interferometric sample with low per-source proper motion uncertainty but large intrinsic proper motions caused by radio jets, and (2) a thousand-fold larger sample with large per-source uncertainties that has small intrinsic proper motions (Gaia active galactic nuclei). Both approaches produce limits on ΩGW, the energy density of gravitational waves as a fraction of the cosmological critical energy density.The authors acknowledge support from the NSF grant AST-1411605 and the NASA grant 14-ATP14-0086.

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.

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.

Spatiotemporal motion boundary detection and motion boundary velocity estimation for tracking moving objects with a moving camera: a level sets PDEs approach with concurrent camera motion compensation.

PubMed

Feghali, Rosario; Mitiche, Amar

2004-11-01

The purpose of this study is to investigate a method of tracking moving objects with a moving camera. This method estimates simultaneously the motion induced by camera movement. The problem is formulated as a Bayesian motion-based partitioning problem in the spatiotemporal domain of the image quence. An energy functional is derived from the Bayesian formulation. The Euler-Lagrange descent equations determine imultaneously an estimate of the image motion field induced by camera motion and an estimate of the spatiotemporal motion undary surface. The Euler-Lagrange equation corresponding to the surface is expressed as a level-set partial differential equation for topology independence and numerically stable implementation. The method can be initialized simply and can track multiple objects with nonsimultaneous motions. Velocities on motion boundaries can be estimated from geometrical properties of the motion boundary. Several examples of experimental verification are given using synthetic and real-image sequences.

A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring

PubMed Central

Yang, Che-Chang; Hsu, Yeh-Liang

2010-01-01

Characteristics of physical activity are indicative of one’s mobility level, latent chronic diseases and aging process. Accelerometers have been widely accepted as useful and practical sensors for wearable devices to measure and assess physical activity. This paper reviews the development of wearable accelerometry-based motion detectors. The principle of accelerometry measurement, sensor properties and sensor placements are first introduced. Various research using accelerometry-based wearable motion detectors for physical activity monitoring and assessment, including posture and movement classification, estimation of energy expenditure, fall detection and balance control evaluation, are also reviewed. Finally this paper reviews and compares existing commercial products to provide a comprehensive outlook of current development status and possible emerging technologies. PMID:22163626

Real-time intra-fraction-motion tracking using the treatment couch: a feasibility study

NASA Astrophysics Data System (ADS)

D'Souza, Warren D.; Naqvi, Shahid A.; Yu, Cedric X.

2005-09-01

Significant differences between planned and delivered treatments may occur due to respiration-induced tumour motion, leading to underdosing of parts of the tumour and overdosing of parts of the surrounding critical structures. Existing methods proposed to counter tumour motion include breath-holds, gating and MLC-based tracking. Breath-holds and gating techniques increase treatment time considerably, whereas MLC-based tracking is limited to two dimensions. We present an alternative solution in which a robotic couch moves in real time in response to organ motion. To demonstrate proof-of-principle, we constructed a miniature adaptive couch model consisting of two movable platforms that simulate tumour motion and couch motion, respectively. These platforms were connected via an electronic feedback loop so that the bottom platform responded to the motion of the top platform. We tested our model with a seven-field step-and-shoot delivery case in which we performed three film-based experiments: (1) static geometry, (2) phantom-only motion and (3) phantom motion with simulated couch motion. Our measurements demonstrate that the miniature couch was able to compensate for phantom motion to the extent that the dose distributions were practically indistinguishable from those in static geometry. Motivated by this initial success, we investigated a real-time couch compensation system consisting of a stereoscopic infra-red camera system interfaced to a robotic couch known as the Hexapod™, which responds in real time to any change in position detected by the cameras. Optical reflectors placed on a solid water phantom were used as surrogates for motion. We tested the effectiveness of couch-based motion compensation for fixed fields and a dynamic arc delivery cases. Due to hardware limitations, we performed film-based experiments (1), (2) and (3), with the robotic couch at a phantom motion period and dose rate of 16 s and 100 MU min-1, respectively. Analysis of film measurements showed near-equivalent dose distributions (<=2 mm agreement of corresponding isodose lines) for static geometry and motion-synchronized real-time robotic couch tracking-based radiation delivery.

Stereomotion is processed by the third-order motion system: reply to comment on Three-systems theory of human visual motion perception: review and update

NASA Astrophysics Data System (ADS)

Lu, Zhong-Lin; Sperling, George

2002-10-01

Two theories are considered to account for the perception of motion of depth-defined objects in random-dot stereograms (stereomotion). In the LuSperling three-motion-systems theory J. Opt. Soc. Am. A 18 , 2331 (2001), stereomotion is perceived by the third-order motion system, which detects the motion of areas defined as figure (versus ground) in a salience map. Alternatively, in his comment J. Opt. Soc. Am. A 19 , 2142 (2002), Patterson proposes a low-level motion-energy system dedicated to stereo depth. The critical difference between these theories is the preprocessing (figureground based on depth and other cues versus simply stereo depth) rather than the motion-detection algorithm itself (because the motion-extraction algorithm for third-order motion is undetermined). Furthermore, the ability of observers to perceive motion in alternating feature displays in which stereo depth alternates with other features such as texture orientation indicates that the third-order motion system can perceive stereomotion. This reduces the stereomotion question to Is it third-order alone or third-order plus dedicated depth-motion processing? Two new experiments intended to support the dedicated depth-motion processing theory are shown here to be perfectly accounted for by third-order motion, as are many older experiments that have previously been shown to be consistent with third-order motion. Cyclopean and rivalry images are shown to be a likely confound in stereomotion studies, rivalry motion being as strong as stereomotion. The phase dependence of superimposed same-direction stereomotion stimuli, rivalry stimuli, and isoluminant color stimuli indicates that these stimuli are processed in the same (third-order) motion system. The phase-dependence paradigm Lu and Sperling, Vision Res. 35 , 2697 (1995) ultimately can resolve the question of which types of signals share a single motion detector. All the evidence accumulated so far is consistent with the three-motion-systems theory. 2002 Optical Society of America

Localized Harmonic Motion Imaging for Focused Ultrasound Surgery Targeting

PubMed Central

Curiel, Laura; Hynynen, Kullervo

2011-01-01

Recently, an in vivo real-time ultrasound-based monitoring technique that uses localized harmonic motion (LHM) to detect changes in tissues during focused ultrasound surgery (FUS) has been proposed to control the exposure. This technique can potentially be used as well for targeting imaging. In the present study we evaluated the potential of using LHM to detect changes in stiffness and the feasibility of using it for imaging purposes in phantoms and in vivo tumor detection. A single-element FUS transducer (80 mm focal length, 100 mm diameter, 1.485 MHz) was used for inducing a localized harmonic motion and a separate ultrasound diagnostic transducer excited by a pulser/receiver (5 kHz PRF, 5 MHz) was used to track motion. The motion was estimated using cross-correlation techniques on the acquired RF signal. Silicon phantom studies were performed in order to determine the size of inclusion that was possible to detect using this technique. Inclusions were discerned from the surroundings as a reduction on LHM amplitude and it was possible to depict inclusions as small as 4 mm. The amplitude of the induced LHM was always lower at the inclusions as compared with the one obtained at the surroundings. Ten New Zealand rabbits had VX2 tumors implanted on their thighs and LHM was induced and measured at the tumor region. Tumors (as small as 10 mm in length and 4 mm in width) were discerned from the surroundings as a reduction on LHM amplitude. PMID:21683514

Simultaneous Detection of Displacement, Rotation Angle, and Contact Pressure Using Sandpaper Molded Elastomer Based Triple Electrode Sensor

PubMed Central

Sul, Onejae; Lee, Seung-Beck

2017-01-01

In this article, we report on a flexible sensor based on a sandpaper molded elastomer that simultaneously detects planar displacement, rotation angle, and vertical contact pressure. When displacement, rotation, and contact pressure are applied, the contact area between the translating top elastomer electrode and the stationary three bottom electrodes change characteristically depending on the movement, making it possible to distinguish between them. The sandpaper molded undulating surface of the elastomer reduces friction at the contact allowing the sensor not to affect the movement during measurement. The sensor showed a 0.25 mm−1 displacement sensitivity with a ±33 μm accuracy, a 0.027 degree−1 of rotation sensitivity with ~0.95 degree accuracy, and a 4.96 kP−1 of pressure sensitivity. For possible application to joint movement detection, we demonstrated that our sensor effectively detected the up-and-down motion of a human forefinger and the bending and straightening motion of a human arm. PMID:28878166

Simultaneous Detection of Displacement, Rotation Angle, and Contact Pressure Using Sandpaper Molded Elastomer Based Triple Electrode Sensor.

PubMed

Choi, Eunsuk; Sul, Onejae; Lee, Seung-Beck

2017-09-06

In this article, we report on a flexible sensor based on a sandpaper molded elastomer that simultaneously detects planar displacement, rotation angle, and vertical contact pressure. When displacement, rotation, and contact pressure are applied, the contact area between the translating top elastomer electrode and the stationary three bottom electrodes change characteristically depending on the movement, making it possible to distinguish between them. The sandpaper molded undulating surface of the elastomer reduces friction at the contact allowing the sensor not to affect the movement during measurement. The sensor showed a 0.25 mm −1 displacement sensitivity with a ±33 μm accuracy, a 0.027 degree −1 of rotation sensitivity with ~0.95 degree accuracy, and a 4.96 kP −1 of pressure sensitivity. For possible application to joint movement detection, we demonstrated that our sensor effectively detected the up-and-down motion of a human forefinger and the bending and straightening motion of a human arm.

Graphene as a Platform for Hybrid Optomechanical Devices

NASA Astrophysics Data System (ADS)

Bouchiat, Vincent; Reserbat-Plantey, Antoine; Kalita, Dipankar; Marty, Laetitia; Arcizet, Olivier; Bendiab, Nedjma

2013-03-01

Graphene is known for providing a flat 2D material with outstanding optical, electrical and mechanical properties. We propose to take advantage of all three features by developing an optomechanical platform based on cantilevers made of freestanding multilayer graphene connected to an electrode. In this talk I will present several examples of a simple optomechanical systems involving a multilayer graphene suspended cantilevers that can act as a mirror closing an optical cavity. By varying the gate voltage applied on the mirror, its angle can be adjusted on a wide range (exceeding the wavelength of the incoming light) and its motion can be actuated and followed in real time from DC up to the tens of MHz range. Detection of elastic and inelastic scattered light can be performed. It allows simultaneous detection of motion, local stress and temperature of the membrane. A fully spectral detection of NEMS resonance is presented (1) and allows a novel optomechanical scheme based on coupling between motion and light through the dynamic mechanical stress. Further applications are presented as well such as a gate tunable enhancement of the Raman signal of molecular species adsorbed on the graphene platform. (1) Reserbat-Plantey, A., et al, Nature Nanotechnology, vol. 7, 151-155. (2012).

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.

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.

Detection of acoustic waves by NMR using a radiofrequency field gradient

NASA Astrophysics Data System (ADS)

Madelin, Guillaume; Baril, Nathalie; Lewa, Czeslaw J.; Franconi, Jean-Michel; Canioni, Paul; Thiaudiére, Eric; de Certaines, Jacques D.

2003-03-01

A B1 field gradient-based method previously described for the detection of mechanical vibrations has been applied to detect oscillatory motions in condensed matter originated from acoustic waves. A ladder-shaped coil generating a quasi-constant RF-field gradient was associated with a motion-encoding NMR sequence consisting in a repetitive binomial 1 3¯3 1¯ RF pulse train (stroboscopic acquisition). The NMR response of a gel phantom subject to acoustic wave excitation in the 20-200 Hz range was investigated. Results showed a linear relationship between the NMR signal and the wave amplitude and a spectroscopic selectivity of the NMR sequence with respect to the input acoustic frequency. Spin displacements as short as a few tens of nanometers were able to be detected with this method.

Detection of acoustic waves by NMR using a radiofrequency field gradient.

PubMed

Madelin, Guillaume; Baril, Nathalie; Lewa, Czeslaw J; Franconi, Jean Michel; Canioni, Paul; Thiaudiére, Eric; de Certaines, Jacques D

2003-03-01

A B(1) field gradient-based method previously described for the detection of mechanical vibrations has been applied to detect oscillatory motions in condensed matter originated from acoustic waves. A ladder-shaped coil generating a quasi-constant RF-field gradient was associated with a motion-encoding NMR sequence consisting in a repetitive binomial 13;31; RF pulse train (stroboscopic acquisition). The NMR response of a gel phantom subject to acoustic wave excitation in the 20-200 Hz range was investigated. Results showed a linear relationship between the NMR signal and the wave amplitude and a spectroscopic selectivity of the NMR sequence with respect to the input acoustic frequency. Spin displacements as short as a few tens of nanometers were able to be detected with this method.

Real-Time Detection of Rupture Development: Earthquake Early Warning Using P Waves From Growing Ruptures

NASA Astrophysics Data System (ADS)

Kodera, Yuki

2018-01-01

Large earthquakes with long rupture durations emit P wave energy throughout the rupture period. Incorporating late-onset P waves into earthquake early warning (EEW) algorithms could contribute to robust predictions of strong ground motion. Here I describe a technique to detect in real time P waves from growing ruptures to improve the timeliness of an EEW algorithm based on seismic wavefield estimation. The proposed P wave detector, which employs a simple polarization analysis, successfully detected P waves from strong motion generation areas of the 2011 Mw 9.0 Tohoku-oki earthquake rupture. An analysis using 23 large (M ≥ 7) events from Japan confirmed that seismic intensity predictions based on the P wave detector significantly increased lead times without appreciably decreasing the prediction accuracy. P waves from growing ruptures, being one of the fastest carriers of information on ongoing rupture development, have the potential to improve the performance of EEW systems.

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.

Preliminary investigation of motion requirements for the simulation of helicopter hover tasks

NASA Technical Reports Server (NTRS)

Parrish, R. V.

1980-01-01

Data from a preliminary experiment are presented which attempted to define a helicopter hover task that would allow the detection of objectively-measured differences in fixed base/moving base simulator performance. The addition of heave, pitch, and roll movement of a ship at sea to the hover task, by means of an adaption of a simulator g-seat, potentially fulfills the desired definition. The feasibility of g-seat substitution for platform motion can be investigated utilizing this task.

Photoplethysmograph signal reconstruction based on a novel hybrid motion artifact detection-reduction approach. Part I: Motion and noise artifact detection.

PubMed

Chong, Jo Woon; Dao, Duy K; Salehizadeh, S M A; McManus, David D; Darling, Chad E; Chon, Ki H; Mendelson, Yitzhak

2014-11-01

Motion and noise artifacts (MNA) are a serious obstacle in utilizing photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a MNA detection method which can provide a clean vs. corrupted decision on each successive PPG segment. For motion artifact detection, we compute four time-domain parameters: (1) standard deviation of peak-to-peak intervals (2) standard deviation of peak-to-peak amplitudes (3) standard deviation of systolic and diastolic interval ratios, and (4) mean standard deviation of pulse shape. We have adopted a support vector machine (SVM) which takes these parameters from clean and corrupted PPG signals and builds a decision boundary to classify them. We apply several distinct features of the PPG data to enhance classification performance. The algorithm we developed was verified on PPG data segments recorded by simulation, laboratory-controlled and walking/stair-climbing experiments, respectively, and we compared several well-established MNA detection methods to our proposed algorithm. All compared detection algorithms were evaluated in terms of motion artifact detection accuracy, heart rate (HR) error, and oxygen saturation (SpO2) error. For laboratory controlled finger, forehead recorded PPG data and daily-activity movement data, our proposed algorithm gives 94.4, 93.4, and 93.7% accuracies, respectively. Significant reductions in HR and SpO2 errors (2.3 bpm and 2.7%) were noted when the artifacts that were identified by SVM-MNA were removed from the original signal than without (17.3 bpm and 5.4%). The accuracy and error values of our proposed method were significantly higher and lower, respectively, than all other detection methods. Another advantage of our method is its ability to provide highly accurate onset and offset detection times of MNAs. This capability is important for an automated approach to signal reconstruction of only those data points that need to be reconstructed, which is the subject of the companion paper to this article. Finally, our MNA detection algorithm is real-time realizable as the computational speed on the 7-s PPG data segment was found to be only 7 ms with a Matlab code.

A Study on the Model of Detecting the Variation of Geomagnetic Intensity Based on an Adapted Motion Strategy.

PubMed

Li, Hong; Liu, Mingyong; Liu, Kun; Zhang, Feihu

2017-12-25

By simulating the geomagnetic fields and analyzing thevariation of intensities, this paper presents a model for calculating the objective function ofan Autonomous Underwater Vehicle (AUV)geomagnetic navigation task. By investigating the biologically inspired strategies, the AUV successfullyreachesthe destination duringgeomagnetic navigation without using the priori geomagnetic map. Similar to the pattern of a flatworm, the proposed algorithm relies on a motion pattern to trigger a local searching strategy by detecting the real-time geomagnetic intensity. An adapted strategy is then implemented, which is biased on the specific target. The results show thereliabilityandeffectivenessofthe proposed algorithm.

Toward an affordable and user-friendly visual motion capture system.

PubMed

Bonnet, V; Sylla, N; Cherubini, A; Gonzáles, A; Azevedo Coste, C; Fraisse, P; Venture, G

2014-01-01

The present study aims at designing and evaluating a low-cost, simple and portable system for arm joint angle estimation during grasping-like motions. The system is based on a single RGB-D camera and three customized markers. The automatically detected and tracked marker positions were used as inputs to an offline inverse kinematic process based on bio-mechanical constraints to reduce noise effect and handle marker occlusion. The method was validated on 4 subjects with different motions. The joint angles were estimated both with the proposed low-cost system and, a stereophotogrammetric system. Comparative analysis shows good accuracy with high correlation coefficient (r= 0.92) and low average RMS error (3.8 deg).

A stretchable strain sensor based on a metal nanoparticle thin film for human motion detection

NASA Astrophysics Data System (ADS)

Lee, Jaehwan; Kim, Sanghyeok; Lee, Jinjae; Yang, Daejong; Park, Byong Chon; Ryu, Seunghwa; Park, Inkyu

2014-09-01

Wearable strain sensors for human motion detection are being highlighted in various fields such as medical, entertainment and sports industry. In this paper, we propose a new type of stretchable strain sensor that can detect both tensile and compressive strains and can be fabricated by a very simple process. A silver nanoparticle (Ag NP) thin film patterned on the polydimethylsiloxane (PDMS) stamp by a single-step direct transfer process is used as the strain sensing material. The working principle is the change in the electrical resistance caused by the opening/closure of micro-cracks under mechanical deformation. The fabricated stretchable strain sensor shows highly sensitive and durable sensing performances in various tensile/compressive strains, long-term cyclic loading and relaxation tests. We demonstrate the applications of our stretchable strain sensors such as flexible pressure sensors and wearable human motion detection devices with high sensitivity, response speed and mechanical robustness.Wearable strain sensors for human motion detection are being highlighted in various fields such as medical, entertainment and sports industry. In this paper, we propose a new type of stretchable strain sensor that can detect both tensile and compressive strains and can be fabricated by a very simple process. A silver nanoparticle (Ag NP) thin film patterned on the polydimethylsiloxane (PDMS) stamp by a single-step direct transfer process is used as the strain sensing material. The working principle is the change in the electrical resistance caused by the opening/closure of micro-cracks under mechanical deformation. The fabricated stretchable strain sensor shows highly sensitive and durable sensing performances in various tensile/compressive strains, long-term cyclic loading and relaxation tests. We demonstrate the applications of our stretchable strain sensors such as flexible pressure sensors and wearable human motion detection devices with high sensitivity, response speed and mechanical robustness. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr03295k

Research and development of a control system for multi axis cooperative motion based on PMAC

NASA Astrophysics Data System (ADS)

Guo, Xiao-xiao; Dong, Deng-feng; Zhou, Wei-hu

2017-10-01

Based on Programmable Multi-axes Controller (PMAC), a design of a multi axis motion control system for the simulator of spatial targets' dynamic optical properties is proposed. According to analysis the properties of spatial targets' simulator motion control system, using IPC as the main control layer, TurboPMAC2 as the control layer to meet coordinated motion control, data acquisition and analog output. A simulator using 5 servomotors which is connected with speed reducers to drive the output axis was implemented to simulate the motion of both the sun and the space target. Based on PMAC using PID and a notch filter algorithm, negative feedback, the speed and acceleration feed forward algorithm to satisfy the axis' requirements of the good stability and high precision at low speeds. In the actual system, it shows that the velocity precision is higher than 0.04 s ° and the precision of repetitive positioning is better than 0.006° when each axis is at a low-speed. Besides, the system achieves the control function of multi axis coordinated motion. The design provides an important technical support for detecting spatial targets, also promoting the theoretical research.

Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

DTIC Science & Technology

2010-11-01

pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

Simulation and visualization of face seal motion stability by means of computer generated movies

NASA Technical Reports Server (NTRS)

Etsion, I.; Auer, B. M.

1980-01-01

A computer aided design method for mechanical face seals is described. Based on computer simulation, the actual motion of the flexibly mounted element of the seal can be visualized. This is achieved by solving the equations of motion of this element, calculating the displacements in its various degrees of freedom vs. time, and displaying the transient behavior in the form of a motion picture. Incorporating such a method in the design phase allows one to detect instabilities and to correct undesirable behavior of the seal. A theoretical background is presented. Details of the motion display technique are described, and the usefulness of the method is demonstrated by an example of a noncontacting conical face seal.

Simulation and visualization of face seal motion stability by means of computer generated movies

NASA Technical Reports Server (NTRS)

Etsion, I.; Auer, B. M.

1981-01-01

A computer aided design method for mechanical face seals is described. Based on computer simulation, the actual motion of the flexibly mounted element of the seal can be visualized. This is achieved by solving the equations of motion of this element, calculating the displacements in its various degrees of freedom vs. time, and displaying the transient behavior in the form of a motion picture. Incorporating such a method in the design phase allows one to detect instabilities and to correct undesirable behavior of the seal. A theoretical background is presented. Details of the motion display technique are described, and the usefulness of the method is demonstrated by an example of a noncontacting conical face seal.

Description and detection of burst events in turbulent flows

NASA Astrophysics Data System (ADS)

Schmid, P. J.; García-Gutierrez, A.; Jiménez, J.

2018-04-01

A mathematical and computational framework is developed for the detection and identification of coherent structures in turbulent wall-bounded shear flows. In a first step, this data-based technique will use an embedding methodology to formulate the fluid motion as a phase-space trajectory, from which state-transition probabilities can be computed. Within this formalism, a second step then applies repeated clustering and graph-community techniques to determine a hierarchy of coherent structures ranked by their persistencies. This latter information will be used to detect highly transitory states that act as precursors to violent and intermittent events in turbulent fluid motion (e.g., bursts). Used as an analysis tool, this technique allows the objective identification of intermittent (but important) events in turbulent fluid motion; however, it also lays the foundation for advanced control strategies for their manipulation. The techniques are applied to low-dimensional model equations for turbulent transport, such as the self-sustaining process (SSP), for varying levels of complexity.

Quantification of vocal fold motion using echography: application to recurrent nerve paralysis detection

NASA Astrophysics Data System (ADS)

Cohen, Mike-Ely; Lefort, Muriel; Bergeret-Cassagne, Héloïse; Hachi, Siham; Li, Ang; Russ, Gilles; Lazard, Diane; Menegaux, Fabrice; Leenhardt, Laurence; Trésallet, Christophe; Frouin, Frédérique

2015-03-01

Recurrent nerve paralysis (RP) is one of the most frequent complications of thyroid surgery. It reduces vocal fold mobility. Nasal endoscopy, a mini-invasive procedure, is the conventional way to detect RP. We suggest a new approach based on laryngeal ultrasound and a specific data analysis was designed to help with the automated detection of RP. Ten subjects were enrolled for this feasibility study: four controls, three patients with RP and three patients without RP according to nasal endoscopy. The ultrasound protocol was based on a ten seconds B-mode acquisition in a coronal plane during normal breathing. Image processing included three steps: 1) automated detection of two consecutive closing and opening images, corresponding to extreme positions of vocal folds in the sequence of B-mode images, using principal component analysis of the image sequence; 2) positioning of three landmarks and robust tracking of these points using a multi-pyramidal refined optical flow approach; 3) estimation of quantitative parameters indicating left and right fractions of mobility, and motion symmetry. Results provided by automated image processing were compared to those obtained by an expert. Detection of extreme images was accurate; tracking of landmarks was reliable in 80% of cases. Motion symmetry indices showed similar values for controls and patients without RP. Fraction of mobility was reduced in cases of RP. Thus, our CAD system helped in the detection of RP. Laryngeal ultrasound combined with appropriate image processing helped in the diagnosis of recurrent nerve paralysis and could be proposed as a first-line method.

Visual-Vestibular Conflict Detection Depends on Fixation.

PubMed

Garzorz, Isabelle T; MacNeilage, Paul R

2017-09-25

Visual and vestibular signals are the primary sources of sensory information for self-motion. Conflict among these signals can be seriously debilitating, resulting in vertigo [1], inappropriate postural responses [2], and motion, simulator, or cyber sickness [3-8]. Despite this significance, the mechanisms mediating conflict detection are poorly understood. Here we model conflict detection simply as crossmodal discrimination with benchmark performance limited by variabilities of the signals being compared. In a series of psychophysical experiments conducted in a virtual reality motion simulator, we measure these variabilities and assess conflict detection relative to this benchmark. We also examine the impact of eye movements on visual-vestibular conflict detection. In one condition, observers fixate a point that is stationary in the simulated visual environment by rotating the eyes opposite head rotation, thereby nulling retinal image motion. In another condition, eye movement is artificially minimized via fixation of a head-fixed fixation point, thereby maximizing retinal image motion. Visual-vestibular integration performance is also measured, similar to previous studies [9-12]. We observe that there is a tradeoff between integration and conflict detection that is mediated by eye movements. Minimizing eye movements by fixating a head-fixed target leads to optimal integration but highly impaired conflict detection. Minimizing retinal motion by fixating a scene-fixed target improves conflict detection at the cost of impaired integration performance. The common tendency to fixate scene-fixed targets during self-motion [13] may indicate that conflict detection is typically a higher priority than the increase in precision of self-motion estimation that is obtained through integration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Vision-Based Autonomous Sensor-Tasking in Uncertain Adversarial Environments

DTIC Science & Technology

2015-01-02

motion segmentation and change detection in crowd behavior. In particular we investigated Finite Time Lyapunov Exponents, Perron Frobenius Operator and...deformation tensor [11]. On the other hand, eigenfunctions of, the Perron Frobenius operator can be used to detect Almost Invariant Sets (AIS) which are... Perron Frobenius operator. Finally, Figure 1.12d shows the ergodic partitions (EP) obtained based on the eigenfunctions of the Koopman operator

Collaborative Point Paper on Border Surveillance Technology

DTIC Science & Technology

2007-06-01

Systems PLC LORHIS (Long Range Hyperspectral Imaging System ) can be configured for either manned or unmanned aircraft to automatically detect and...Airships, and/or Aerostats, (RF, Electro-Optical, Infrared, Video) • Land- based Sensor Systems (Attended/Mobile and Unattended: e.g., CCD, Motion, Acoustic...electronic surveillance technologies for intrusion detection and warning. These ground- based systems are primarily short-range, up to around 500 meters

Radar fall detection using principal component analysis

NASA Astrophysics Data System (ADS)

Jokanovic, Branka; Amin, Moeness; Ahmad, Fauzia; Boashash, Boualem

2016-05-01

Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant parameter tuning in order to provide successful detections. In this paper, we employ principal component analysis for fall detection, wherein eigen images of observed motions are employed for classification. Using real data, we demonstrate that the PCA based technique provides performance improvement over the conventional feature extraction methods.

Impaired visual recognition of biological motion in schizophrenia.

PubMed

Kim, Jejoong; Doop, Mikisha L; Blake, Randolph; Park, Sohee

2005-09-15

Motion perception deficits have been suggested to be an important feature of schizophrenia but the behavioral consequences of such deficits are unknown. Biological motion refers to the movements generated by living beings. The human visual system rapidly and effortlessly detects and extracts socially relevant information from biological motion. A deficit in biological motion perception may have significant consequences for detecting and interpreting social information. Schizophrenia patients and matched healthy controls were tested on two visual tasks: recognition of human activity portrayed in point-light animations (biological motion task) and a perceptual control task involving detection of a grouped figure against the background noise (global-form task). Both tasks required detection of a global form against background noise but only the biological motion task required the extraction of motion-related information. Schizophrenia patients performed as well as the controls in the global-form task, but were significantly impaired on the biological motion task. In addition, deficits in biological motion perception correlated with impaired social functioning as measured by the Zigler social competence scale [Zigler, E., Levine, J. (1981). Premorbid competence in schizophrenia: what is being measured? Journal of Consulting and Clinical Psychology, 49, 96-105.]. The deficit in biological motion processing, which may be related to the previously documented deficit in global motion processing, could contribute to abnormal social functioning in schizophrenia.

Early Improper Motion Detection in Golf Swings Using Wearable Motion Sensors: The First Approach

PubMed Central

Stančin, Sara; Tomažič, Sašo

2013-01-01

This paper presents an analysis of a golf swing to detect improper motion in the early phase of the swing. Led by the desire to achieve a consistent shot outcome, a particular golfer would (in multiple trials) prefer to perform completely identical golf swings. In reality, some deviations from the desired motion are always present due to the comprehensive nature of the swing motion. Swing motion deviations that are not detrimental to performance are acceptable. This analysis is conducted using a golfer's leading arm kinematic data, which are obtained from a golfer wearing a motion sensor that is comprised of gyroscopes and accelerometers. Applying the principal component analysis (PCA) to the reference observations of properly performed swings, the PCA components of acceptable swing motion deviations are established. Using these components, the motion deviations in the observations of other swings are examined. Any unacceptable deviations that are detected indicate an improper swing motion. Arbitrarily long observations of an individual player's swing sequences can be included in the analysis. The results obtained for the considered example show an improper swing motion in early phase of the swing, i.e., the first part of the backswing. An early detection method for improper swing motions that is conducted on an individual basis provides assistance for performance improvement. PMID:23752563

Early improper motion detection in golf swings using wearable motion sensors: the first approach.

PubMed

Stančin, Sara; Tomažič, Sašo

2013-06-10

This paper presents an analysis of a golf swing to detect improper motion in the early phase of the swing. Led by the desire to achieve a consistent shot outcome, a particular golfer would (in multiple trials) prefer to perform completely identical golf swings. In reality, some deviations from the desired motion are always present due to the comprehensive nature of the swing motion. Swing motion deviations that are not detrimental to performance are acceptable. This analysis is conducted using a golfer's leading arm kinematic data, which are obtained from a golfer wearing a motion sensor that is comprised of gyroscopes and accelerometers. Applying the principal component analysis (PCA) to the reference observations of properly performed swings, the PCA components of acceptable swing motion deviations are established. Using these components, the motion deviations in the observations of other swings are examined. Any unacceptable deviations that are detected indicate an improper swing motion. Arbitrarily long observations of an individual player's swing sequences can be included in the analysis. The results obtained for the considered example show an improper swing motion in early phase of the swing, i.e., the first part of the backswing. An early detection method for improper swing motions that is conducted on an individual basis provides assistance for performance improvement.

High-Speed Incoming Infrared Target Detection by Fusion of Spatial and Temporal Detectors

PubMed Central

Kim, Sungho

2015-01-01

This paper presents a method for detecting high-speed incoming targets by the fusion of spatial and temporal detectors to achieve a high detection rate for an active protection system (APS). The incoming targets have different image velocities according to the target-camera geometry. Therefore, single-target detector-based approaches, such as a 1D temporal filter, 2D spatial filter and 3D matched filter, cannot provide a high detection rate with moderate false alarms. The target speed variation was analyzed according to the incoming angle and target velocity. The speed of the distant target at the firing time is almost stationary and increases slowly. The speed varying targets are detected stably by fusing the spatial and temporal filters. The stationary target detector is activated by an almost zero temporal contrast filter (TCF) and identifies targets using a spatial filter called the modified mean subtraction filter (M-MSF). A small motion (sub-pixel velocity) target detector is activated by a small TCF value and finds targets using the same spatial filter. A large motion (pixel-velocity) target detector works when the TCF value is high. The final target detection is terminated by fusing the three detectors based on the threat priority. The experimental results of the various target sequences show that the proposed fusion-based target detector produces the highest detection rate with an acceptable false alarm rate. PMID:25815448

Comparison of two Simon tasks: neuronal correlates of conflict resolution based on coherent motion perception.

PubMed

Wittfoth, Matthias; Buck, Daniela; Fahle, Manfred; Herrmann, Manfred

2006-08-15

The present study aimed at characterizing the neural correlates of conflict resolution in two variations of the Simon effect. We introduced two different Simon tasks where subjects had to identify shapes on the basis of form-from-motion perception (FFMo) within a randomly moving dot field, while (1) motion direction (motion-based Simon task) or (2) stimulus location (location-based Simon task) had to be ignored. Behavioral data revealed that both types of Simon tasks induced highly significant interference effects. Using event-related fMRI, we could demonstrate that both tasks share a common cluster of activated brain regions during conflict resolution (pre-supplementary motor area (pre-SMA), superior parietal lobule (SPL), and cuneus) but also show task-specific activation patterns (left superior temporal cortex in the motion-based, and the left fusiform gyrus in the location-based Simon task). Although motion-based and location-based Simon tasks are conceptually very similar (Type 3 stimulus-response ensembles according to the taxonomy of [Kornblum, S., Stevens, G. (2002). Sequential effects of dimensional overlap: findings and issues. In: Prinz, W., Hommel., B. (Eds.), Common mechanism in perception and action. Oxford University Press, Oxford, pp. 9-54]) conflict resolution in both tasks results in the activation of different task-specific regions probably related to the different sources of task-irrelevant information. Furthermore, the present data give evidence those task-specific regions are most likely to detect the relationship between task-relevant and task-irrelevant information.

INS integrated motion analysis for autonomous vehicle navigation

NASA Technical Reports Server (NTRS)

Roberts, Barry; Bazakos, Mike

1991-01-01

The use of inertial navigation system (INS) measurements to enhance the quality and robustness of motion analysis techniques used for obstacle detection is discussed with particular reference to autonomous vehicle navigation. The approach to obstacle detection used here employs motion analysis of imagery generated by a passive sensor. Motion analysis of imagery obtained during vehicle travel is used to generate range measurements to points within the field of view of the sensor, which can then be used to provide obstacle detection. Results obtained with an INS integrated motion analysis approach are reviewed.

Motion-based prediction is sufficient to solve the aperture problem

PubMed Central

Perrinet, Laurent U; Masson, Guillaume S

2012-01-01

In low-level sensory systems, it is still unclear how the noisy information collected locally by neurons may give rise to a coherent global percept. This is well demonstrated for the detection of motion in the aperture problem: as luminance of an elongated line is symmetrical along its axis, tangential velocity is ambiguous when measured locally. Here, we develop the hypothesis that motion-based predictive coding is sufficient to infer global motion. Our implementation is based on a context-dependent diffusion of a probabilistic representation of motion. We observe in simulations a progressive solution to the aperture problem similar to physiology and behavior. We demonstrate that this solution is the result of two underlying mechanisms. First, we demonstrate the formation of a tracking behavior favoring temporally coherent features independently of their texture. Second, we observe that incoherent features are explained away while coherent information diffuses progressively to the global scale. Most previous models included ad-hoc mechanisms such as end-stopped cells or a selection layer to track specific luminance-based features as necessary conditions to solve the aperture problem. Here, we have proved that motion-based predictive coding, as it is implemented in this functional model, is sufficient to solve the aperture problem. This solution may give insights in the role of prediction underlying a large class of sensory computations. PMID:22734489

A Comprehensive Assessment of Regional Variation in the Impact of Head Micromovements on Functional Connectomics

PubMed Central

Yan, Chao-Gan; Cheung, Brian; Kelly, Clare; Colcombe, Stan; Craddock, R. Cameron; Di Martino, Adriana; Li, Qingyang; Zuo, Xi-Nian; Castellanos, F. Xavier; Milham, Michael P.

2014-01-01

Functional connectomics is one of the most rapidly expanding areas of neuroimaging research. Yet, concerns remain regarding the use of resting-state fMRI (R-fMRI) to characterize inter-individual variation in the functional connectome. In particular, recent findings that “micro” head movements can introduce artifactual inter-individual and group-related differences in R-fMRI metrics have raised concerns. Here, we first build on prior demonstrations of regional variation in the magnitude of framewise displacements associated with a given head movement, by providing a comprehensive voxel-based examination of the impact of motion on the BOLD signal (i.e., motion-BOLD relationships). Positive motion-BOLD relationships were detected in primary and supplementary motor areas, particularly in low motion datasets. Negative motion-BOLD relationships were most prominent in prefrontal regions, and expanded throughout the brain in high motion datasets (e.g., children). Scrubbing of volumes with FD > 0.2 effectively removed negative but not positive correlations; these findings suggest that positive relationships may reflect neural origins of motion while negative relationships are likely to originate from motion artifact. We also examined the ability of motion correction strategies to eliminate artifactual differences related to motion among individuals and between groups for a broad array of voxel-wise R-fMRI metrics. Residual relationships between motion and the examined R-fMRI metrics remained for all correction approaches, underscoring the need to covary motion effects at the group-level. Notably, global signal regression reduced relationships between motion and inter-individual differences in correlation-based R-fMRI metrics; Z-standardization (mean-centering and variance normalization) of subject-level maps for R-fMRI metrics prior to group-level analyses demonstrated similar advantages. Finally, our test-retest (TRT) analyses revealed significant motion effects on TRT reliability for R-fMRI metrics. Generally, motion compromised reliability of R-fMRI metrics, with the exception of those based on frequency characteristics – particularly, amplitude of low frequency fluctuations (ALFF). The implications of our findings for decision-making regarding the assessment and correction of motion are discussed, as are insights into potential differences among volume-based metrics of motion. PMID:23499792

Dendro-dendritic interactions between motion-sensitive large-field neurons in the fly.

PubMed

Haag, Juergen; Borst, Alexander

2002-04-15

For visual course control, flies rely on a set of motion-sensitive neurons called lobula plate tangential cells (LPTCs). Among these cells, the so-called CH (centrifugal horizontal) cells shape by their inhibitory action the receptive field properties of other LPTCs called FD (figure detection) cells specialized for figure-ground discrimination based on relative motion. Studying the ipsilateral input circuitry of CH cells by means of dual-electrode and combined electrical-optical recordings, we find that CH cells receive graded input from HS (large-field horizontal system) cells via dendro-dendritic electrical synapses. This particular wiring scheme leads to a spatial blur of the motion image on the CH cell dendrite, and, after inhibiting FD cells, to an enhancement of motion contrast. This could be crucial for enabling FD cells to discriminate object from self motion.

Acoustic facilitation of object movement detection during self-motion

PubMed Central

Calabro, F. J.; Soto-Faraco, S.; Vaina, L. M.

2011-01-01

In humans, as well as most animal species, perception of object motion is critical to successful interaction with the surrounding environment. Yet, as the observer also moves, the retinal projections of the various motion components add to each other and extracting accurate object motion becomes computationally challenging. Recent psychophysical studies have demonstrated that observers use a flow-parsing mechanism to estimate and subtract self-motion from the optic flow field. We investigated whether concurrent acoustic cues for motion can facilitate visual flow parsing, thereby enhancing the detection of moving objects during simulated self-motion. Participants identified an object (the target) that moved either forward or backward within a visual scene containing nine identical textured objects simulating forward observer translation. We found that spatially co-localized, directionally congruent, moving auditory stimuli enhanced object motion detection. Interestingly, subjects who performed poorly on the visual-only task benefited more from the addition of moving auditory stimuli. When auditory stimuli were not co-localized to the visual target, improvements in detection rates were weak. Taken together, these results suggest that parsing object motion from self-motion-induced optic flow can operate on multisensory object representations. PMID:21307050

Equivalent background speed in recovery from motion adaptation.

PubMed

Simpson, W A; Newman, A; Aasland, W

1997-01-01

We measured, in the same observers, (1) the detectability, d, of a small rotational jump following adaptation to rotational motion and (2) the detectability of the same jump when superimposed on one of several background rotation speeds. Following 90 s of motion adaptation the detectability of the jump was impaired, and sensitivity slowly recovered over the course of 60 s. The detectability of the jump was also impaired by the background speed in a way consistent with a quadratic form of Weber's law. We propose that motion adaptation impairs the detectability of the small jump because it is as if an equivalent background speed has been superimposed on the display. We measured the equivalent background by finding the real background speed that produced the same d' at each instant in the recovery from motion adaptation. The equivalent background started at approximately one to two thirds the speed of the adapting motion, declined rapidly, rose to a small peak at 30 s, then disappeared by 60 s. Since the equivalent background speed corresponds to the speed of the motion aftereffect, we have measured the time course of the motion aftereffect with objective psychophysics.

Fire detection system using random forest classification for image sequences of complex background

NASA Astrophysics Data System (ADS)

Kim, Onecue; Kang, Dong-Joong

2013-06-01

We present a fire alarm system based on image processing that detects fire accidents in various environments. To reduce false alarms that frequently appeared in earlier systems, we combined image features including color, motion, and blinking information. We specifically define the color conditions of fires in hue, saturation and value, and RGB color space. Fire features are represented as intensity variation, color mean and variance, motion, and image differences. Moreover, blinking fire features are modeled by using crossing patches. We propose an algorithm that classifies patches into fire or nonfire areas by using random forest supervised learning. We design an embedded surveillance device made with acrylonitrile butadiene styrene housing for stable fire detection in outdoor environments. The experimental results show that our algorithm works robustly in complex environments and is able to detect fires in real time.

Validation of vision-based obstacle detection algorithms for low-altitude helicopter flight

NASA Technical Reports Server (NTRS)

Suorsa, Raymond; Sridhar, Banavar

1991-01-01

A validation facility being used at the NASA Ames Research Center is described which is aimed at testing vision based obstacle detection and range estimation algorithms suitable for low level helicopter flight. The facility is capable of processing hundreds of frames of calibrated multicamera 6 degree-of-freedom motion image sequencies, generating calibrated multicamera laboratory images using convenient window-based software, and viewing range estimation results from different algorithms along with truth data using powerful window-based visualization software.

Measuring nanoparticle diffusion in an ABELtrap

NASA Astrophysics Data System (ADS)

Dienerowitz, M.; Dienerowitz, F.; Börsch, M.

2018-03-01

Monitoring the Brownian motion of individual nanoscopic objects is key to investigate their transport properties and interactions with their close environment. Most techniques rely on transient diffusion through a detection volume or immobilisation, which restrict observation times or motility. We measure the diffusion coefficient and surface charge of individual nanoparticles and DNA molecules in an anti-Brownian electrokinetic trap (ABELtrap). This instrument is an active feedback trap confining the Brownian motion of a nanoparticle to the detection site by applying an electric field based on the particle’s current position. We simulate the Brownian motion of nanospheres in our sample geometry, including wall effects, due to partial confinement in the third dimension. The theoretically predicted values are in excellent agreement with our diffusion measurements in the ABELtrap. We also demonstrate the ABELtrap’s ability to measure varying sizes of DNA origami structures during denaturation.

Imaging of optically diffusive media by use of opto-elastography

NASA Astrophysics Data System (ADS)

Bossy, Emmanuel; Funke, Arik R.; Daoudi, Khalid; Tanter, Mickael; Fink, Mathias; Boccara, Claude

2007-02-01

We present a camera-based optical detection scheme designed to detect the transient motion created by the acoustic radiation force in elastic media. An optically diffusive tissue mimicking phantom was illuminated with coherent laser light, and a high speed camera (2 kHz frame rate) was used to acquire and cross-correlate consecutive speckle patterns. Time-resolved transient decorrelations of the optical speckle were measured as the results of localised motion induced in the medium by the radiation force and subsequent propagating shear waves. As opposed to classical acousto-optic techniques which are sensitive to vibrations induced by compressional waves at ultrasonic frequencies, the proposed technique is sensitive only to the low frequency transient motion induced in the medium by the radiation force. It therefore provides a way to assess both optical and shear mechanical properties.

Hand motion modeling for psychology analysis in job interview using optical flow-history motion image: OF-HMI

NASA Astrophysics Data System (ADS)

Khalifa, Intissar; Ejbali, Ridha; Zaied, Mourad

2018-04-01

To survive the competition, companies always think about having the best employees. The selection is depended on the answers to the questions of the interviewer and the behavior of the candidate during the interview session. The study of this behavior is always based on a psychological analysis of the movements accompanying the answers and discussions. Few techniques are proposed until today to analyze automatically candidate's non verbal behavior. This paper is a part of a work psychology recognition system; it concentrates in spontaneous hand gesture which is very significant in interviews according to psychologists. We propose motion history representation of hand based on an hybrid approach that merges optical flow and history motion images. The optical flow technique is used firstly to detect hand motions in each frame of a video sequence. Secondly, we use the history motion images (HMI) to accumulate the output of the optical flow in order to have finally a good representation of the hand`s local movement in a global temporal template.

Quantitative Analysis of Transnasal Anterior Skull Base Approach: Report of Technology for Intraoperative Assessment of Instrument Motion.

PubMed

Berens, Angelique M; Harbison, Richard Alex; Li, Yangming; Bly, Randall A; Aghdasi, Nava; Ferreira, Manuel; Hannaford, Blake; Moe, Kris S

2017-08-01

To develop a method to measure intraoperative surgical instrument motion. This model will be applicable to the study of surgical instrument kinematics including surgical training, skill verification, and the development of surgical warning systems that detect aberrant instrument motion that may result in patient injury. We developed an algorithm to automate derivation of surgical instrument kinematics in an endoscopic endonasal skull base surgery model. Surgical instrument motion was recorded during a cadaveric endoscopic transnasal approach to the pituitary using a navigation system modified to record intraoperative time-stamped Euclidian coordinates and Euler angles. Microdebrider tip coordinates and angles were referenced to the cadaver's preoperative computed tomography scan allowing us to assess surgical instrument kinematics over time. A representative cadaveric endoscopic endonasal approach to the pituitary was performed to demonstrate feasibility of our algorithm for deriving surgical instrument kinematics. Technical feasibility of automatically measuring intraoperative surgical instrument motion and deriving kinematics measurements was demonstrated using standard navigation equipment.

Harmonic motion detection in a vibrating scattering medium.

PubMed

Urban, Matthew W; Chen, Shigao; Greenleaf, James

2008-09-01

Elasticity imaging is an emerging medical imaging modality that seeks to map the spatial distribution of tissue stiffness. Ultrasound radiation force excitation and motion tracking using pulse-echo ultrasound have been used in numerous methods. Dynamic radiation force is used in vibrometry to cause an object or tissue to vibrate, and the vibration amplitude and phase can be measured with exceptional accuracy. This paper presents a model that simulates harmonic motion detection in a vibrating scattering medium incorporating 3-D beam shapes for radiation force excitation and motion tracking. A parameterized analysis using this model provides a platform to optimize motion detection for vibrometry applications in tissue. An experimental method that produces a multifrequency radiation force is also presented. Experimental harmonic motion detection of simultaneous multifrequency vibration is demonstrated using a single transducer. This method can accurately detect motion with displacement amplitude as low as 100 to 200 nm in bovine muscle. Vibration phase can be measured within 10 degrees or less. The experimental results validate the conclusions observed from the model and show multifrequency vibration induction and measurements can be performed simultaneously.

Harmonic Motion Detection in a Vibrating Scattering Medium

PubMed Central

Urban, Matthew W.; Chen, Shigao; Greenleaf, James F.

2008-01-01

Elasticity imaging is an emerging medical imaging modality that seeks to map the spatial distribution of tissue stiffness. Ultrasound radiation force excitation and motion tracking using pulse-echo ultrasound have been used in numerous methods. Dynamic radiation force is used in vibrometry to cause an object or tissue to vibrate, and the vibration amplitude and phase can be measured with exceptional accuracy. This paper presents a model that simulates harmonic motion detection in a vibrating scattering medium incorporating 3-D beam shapes for radiation force excitation and motion tracking. A parameterized analysis using this model provides a platform to optimize motion detection for vibrometry applications in tissue. An experimental method that produces a multifrequency radiation force is also presented. Experimental harmonic motion detection of simultaneous multifrequency vibration is demonstrated using a single transducer. This method can accurately detect motion with displacement amplitude as low as 100 to 200 nm in bovine muscle. Vibration phase can be measured within 10° or less. The experimental results validate the conclusions observed from the model and show multifrequency vibration induction and measurements can be performed simultaneously. PMID:18986892

Pedestrian detection based on redundant wavelet transform

NASA Astrophysics Data System (ADS)

Huang, Lin; Ji, Liping; Hu, Ping; Yang, Tiejun

2016-10-01

Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.

Estimation of slipping organ motion by registration with direction-dependent regularization.

PubMed

Schmidt-Richberg, Alexander; Werner, René; Handels, Heinz; Ehrhardt, Jan

2012-01-01

Accurate estimation of respiratory motion is essential for many applications in medical 4D imaging, for example for radiotherapy of thoracic and abdominal tumors. It is usually done by non-linear registration of image scans at different states of the breathing cycle but without further modeling of specific physiological motion properties. In this context, the accurate computation of respiration-driven lung motion is especially challenging because this organ is sliding along the surrounding tissue during the breathing cycle, leading to discontinuities in the motion field. Without considering this property in the registration model, common intensity-based algorithms cause incorrect estimation along the object boundaries. In this paper, we present a model for incorporating slipping motion in image registration. Extending the common diffusion registration by distinguishing between normal- and tangential-directed motion, we are able to estimate slipping motion at the organ boundaries while preventing gaps and ensuring smooth motion fields inside and outside. We further present an algorithm for a fully automatic detection of discontinuities in the motion field, which does not rely on a prior segmentation of the organ. We evaluate the approach for the estimation of lung motion based on 23 inspiration/expiration pairs of thoracic CT images. The results show a visually more plausible motion estimation. Moreover, the target registration error is quantified using manually defined landmarks and a significant improvement over the standard diffusion regularization is shown. Copyright © 2011 Elsevier B.V. All rights reserved.

Dynamic Metasurface Aperture as Smart Around-the-Corner Motion Detector.

PubMed

Del Hougne, Philipp; F Imani, Mohammadreza; Sleasman, Timothy; Gollub, Jonah N; Fink, Mathias; Lerosey, Geoffroy; Smith, David R

2018-04-25

Detecting and analysing motion is a key feature of Smart Homes and the connected sensor vision they embrace. At present, most motion sensors operate in line-of-sight Doppler shift schemes. Here, we propose an alternative approach suitable for indoor environments, which effectively constitute disordered cavities for radio frequency (RF) waves; we exploit the fundamental sensitivity of modes of such cavities to perturbations, caused here by moving objects. We establish experimentally three key features of our proposed system: (i) ability to capture the temporal variations of motion and discern information such as periodicity ("smart"), (ii) non line-of-sight motion detection, and (iii) single-frequency operation. Moreover, we explain theoretically and demonstrate experimentally that the use of dynamic metasurface apertures can substantially enhance the performance of RF motion detection. Potential applications include accurately detecting human presence and monitoring inhabitants' vital signs.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: The case of domain motions

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-01

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: the case of domain motions.

PubMed

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-14

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Highly sensitive strain sensors based on fragmentized carbon nanotube/polydimethylsiloxane composites

NASA Astrophysics Data System (ADS)

Gao, Yang; Fang, Xiaoliang; Tan, Jianping; Lu, Ting; Pan, Likun; Xuan, Fuzhen

2018-06-01

Wearable strain sensors based on nanomaterial/elastomer composites have potential applications in flexible electronic skin, human motion detection, human–machine interfaces, etc. In this research, a type of high performance strain sensors has been developed using fragmentized carbon nanotube/polydimethylsiloxane (CNT/PDMS) composites. The CNT/PDMS composites were ground into fragments, and a liquid-induced densification method was used to fabricate the strain sensors. The strain sensors showed high sensitivity with gauge factors (GFs) larger than 200 and a broad strain detection range up to 80%, much higher than those strain sensors based on unfragmentized CNT/PDMS composites (GF < 1). The enhanced sensitivity of the strain sensors is ascribed to the sliding of individual fragmentized-CNT/PDMS-composite particles during mechanical deformation, which causes significant resistance change in the strain sensors. The strain sensors can differentiate mechanical stimuli and monitor various human body motions, such as bending of the fingers, human breathing, and blood pulsing.

Highly sensitive strain sensors based on fragmentized carbon nanotube/polydimethylsiloxane composites.

PubMed

Gao, Yang; Fang, Xiaoliang; Tan, Jianping; Lu, Ting; Pan, Likun; Xuan, Fuzhen

2018-06-08

Wearable strain sensors based on nanomaterial/elastomer composites have potential applications in flexible electronic skin, human motion detection, human-machine interfaces, etc. In this research, a type of high performance strain sensors has been developed using fragmentized carbon nanotube/polydimethylsiloxane (CNT/PDMS) composites. The CNT/PDMS composites were ground into fragments, and a liquid-induced densification method was used to fabricate the strain sensors. The strain sensors showed high sensitivity with gauge factors (GFs) larger than 200 and a broad strain detection range up to 80%, much higher than those strain sensors based on unfragmentized CNT/PDMS composites (GF < 1). The enhanced sensitivity of the strain sensors is ascribed to the sliding of individual fragmentized-CNT/PDMS-composite particles during mechanical deformation, which causes significant resistance change in the strain sensors. The strain sensors can differentiate mechanical stimuli and monitor various human body motions, such as bending of the fingers, human breathing, and blood pulsing.

Motion Estimation Utilizing Range Detection-Enhanced Visual Odometry

NASA Technical Reports Server (NTRS)

Morris, Daniel Dale (Inventor); Chang, Hong (Inventor); Friend, Paul Russell (Inventor); Chen, Qi (Inventor); Graf, Jodi Seaborn (Inventor)

2016-01-01

A motion determination system is disclosed. The system may receive a first and a second camera image from a camera, the first camera image received earlier than the second camera image. The system may identify corresponding features in the first and second camera images. The system may receive range data comprising at least one of a first and a second range data from a range detection unit, corresponding to the first and second camera images, respectively. The system may determine first positions and the second positions of the corresponding features using the first camera image and the second camera image. The first positions or the second positions may be determined by also using the range data. The system may determine a change in position of the machine based on differences between the first and second positions, and a VO-based velocity of the machine based on the determined change in position.

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 detection and compensation in infrared retinal image sequences.

PubMed

Scharcanski, J; Schardosim, L R; Santos, D; Stuchi, A

2013-01-01

Infrared image data captured by non-mydriatic digital retinography systems often are used in the diagnosis and treatment of the diabetic macular edema (DME). Infrared illumination is less aggressive to the patient retina, and retinal studies can be carried out without pupil dilation. However, sequences of infrared eye fundus images of static scenes, tend to present pixel intensity fluctuations in time, and noisy and background illumination changes pose a challenge to most motion detection methods proposed in the literature. In this paper, we present a retinal motion detection method that is adaptive to background noise and illumination changes. Our experimental results indicate that this method is suitable for detecting retinal motion in infrared image sequences, and compensate the detected motion, which is relevant in retinal laser treatment systems for DME. Copyright © 2013 Elsevier Ltd. All rights reserved.

An Individual Finger Gesture Recognition System Based on Motion-Intent Analysis Using Mechanomyogram Signal

PubMed Central

Ding, Huijun; He, Qing; Zhou, Yongjin; Dan, Guo; Cui, Song

2017-01-01

Motion-intent-based finger gesture recognition systems are crucial for many applications such as prosthesis control, sign language recognition, wearable rehabilitation system, and human–computer interaction. In this article, a motion-intent-based finger gesture recognition system is designed to correctly identify the tapping of every finger for the first time. Two auto-event annotation algorithms are firstly applied and evaluated for detecting the finger tapping frame. Based on the truncated signals, the Wavelet packet transform (WPT) coefficients are calculated and compressed as the features, followed by a feature selection method that is able to improve the performance by optimizing the feature set. Finally, three popular classifiers including naive Bayes (NBC), K-nearest neighbor (KNN), and support vector machine (SVM) are applied and evaluated. The recognition accuracy can be achieved up to 94%. The design and the architecture of the system are presented with full system characterization results. PMID:29167655

Dipolar filtered magic-sandwich-echoes as a tool for probing molecular motions using time domain NMR

NASA Astrophysics Data System (ADS)

Filgueiras, Jefferson G.; da Silva, Uilson B.; Paro, Giovanni; d'Eurydice, Marcel N.; Cobo, Márcio F.; deAzevedo, Eduardo R.

2017-12-01

We present a simple 1 H NMR approach for characterizing intermediate to fast regime molecular motions using 1 H time-domain NMR at low magnetic field. The method is based on a Goldmann Shen dipolar filter (DF) followed by a Mixed Magic Sandwich Echo (MSE). The dipolar filter suppresses the signals arising from molecular segments presenting sub kHz mobility, so only signals from mobile segments are detected. Thus, the temperature dependence of the signal intensities directly evidences the onset of molecular motions with rates higher than kHz. The DF-MSE signal intensity is described by an analytical function based on the Anderson Weiss theory, from where parameters related to the molecular motion (e.g. correlation times and activation energy) can be estimated when performing experiments as function of the temperature. Furthermore, we propose the use of the Tikhonov regularization for estimating the width of the distribution of correlation times.

PSD Camera Based Position and Posture Control of Redundant Robot Considering Contact Motion

NASA Astrophysics Data System (ADS)

Oda, Naoki; Kotani, Kentaro

The paper describes a position and posture controller design based on the absolute position by external PSD vision sensor for redundant robot manipulator. The redundancy enables a potential capability to avoid obstacle while continuing given end-effector jobs under contact with middle link of manipulator. Under contact motion, the deformation due to joint torsion obtained by comparing internal and external position sensor, is actively suppressed by internal/external position hybrid controller. The selection matrix of hybrid loop is given by the function of the deformation. And the detected deformation is also utilized in the compliant motion controller for passive obstacle avoidance. The validity of the proposed method is verified by several experimental results of 3link planar redundant manipulator.

Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology

PubMed Central

Brinkworth, Russell S. A.; O'Carroll, David C.

2009-01-01

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors. PMID:19893631

Direct Detection of the Helical Magnetic Field Geometry from 3D Reconstruction of Prominence Knot Trajectories

NASA Astrophysics Data System (ADS)

Zapiór, Maciej; Martínez-Gómez, David

2016-02-01

Based on the data collected by the Vacuum Tower Telescope located in the Teide Observatory in the Canary Islands, we analyzed the three-dimensional (3D) motion of so-called knots in a solar prominence of 2014 June 9. Trajectories of seven knots were reconstructed, giving information of the 3D geometry of the magnetic field. Helical motion was detected. From the equipartition principle, we estimated the lower limit of the magnetic field in the prominence to ≈1-3 G and from the Ampère’s law the lower limit of the electric current to ≈1.2 × 109 A.

Shaking video stabilization with content completion

NASA Astrophysics Data System (ADS)

Peng, Yi; Ye, Qixiang; Liu, Yanmei; Jiao, Jianbin

2009-01-01

A new stabilization algorithm to counterbalance the shaking motion in a video based on classical Kandade-Lucas- Tomasi (KLT) method is presented in this paper. Feature points are evaluated with law of large numbers and clustering algorithm to reduce the side effect of moving foreground. Analysis on the change of motion direction is also carried out to detect the existence of shaking. For video clips with detected shaking, an affine transformation is performed to warp the current frame to the reference one. In addition, the missing content of a frame during the stabilization is completed with optical flow analysis and mosaicking operation. Experiments on video clips demonstrate the effectiveness of the proposed algorithm.

First Steps Toward Ultrasound-Based Motion Compensation for Imaging and Therapy: Calibration with an Optical System and 4D PET Imaging

PubMed Central

Schwaab, Julia; Kurz, Christopher; Sarti, Cristina; Bongers, André; Schoenahl, Frédéric; Bert, Christoph; Debus, Jürgen; Parodi, Katia; Jenne, Jürgen Walter

2015-01-01

Target motion, particularly in the abdomen, due to respiration or patient movement is still a challenge in many diagnostic and therapeutic processes. Hence, methods to detect and compensate this motion are required. Diagnostic ultrasound (US) represents a non-invasive and dose-free alternative to fluoroscopy, providing more information about internal target motion than respiration belt or optical tracking. The goal of this project is to develop an US-based motion tracking for real-time motion correction in radiation therapy and diagnostic imaging, notably in 4D positron emission tomography (PET). In this work, a workflow is established to enable the transformation of US tracking data to the coordinates of the treatment delivery or imaging system – even if the US probe is moving due to respiration. It is shown that the US tracking signal is equally adequate for 4D PET image reconstruction as the clinically used respiration belt and provides additional opportunities in this concern. Furthermore, it is demonstrated that the US probe being within the PET field of view generally has no relevant influence on the image quality. The accuracy and precision of all the steps in the calibration workflow for US tracking-based 4D PET imaging are found to be in an acceptable range for clinical implementation. Eventually, we show in vitro that an US-based motion tracking in absolute room coordinates with a moving US transducer is feasible. PMID:26649277

Feasibility of Using Low-Cost Motion Capture for Automated Screening of Shoulder Motion Limitation after Breast Cancer Surgery.

PubMed

Gritsenko, Valeriya; Dailey, Eric; Kyle, Nicholas; Taylor, Matt; Whittacre, Sean; Swisher, Anne K

2015-01-01

To determine if a low-cost, automated motion analysis system using Microsoft Kinect could accurately measure shoulder motion and detect motion impairments in women following breast cancer surgery. Descriptive study of motion measured via 2 methods. Academic cancer center oncology clinic. 20 women (mean age = 60 yrs) were assessed for active and passive shoulder motions during a routine post-operative clinic visit (mean = 18 days after surgery) following mastectomy (n = 4) or lumpectomy (n = 16) for breast cancer. Participants performed 3 repetitions of active and passive shoulder motions on the side of the breast surgery. Arm motion was recorded using motion capture by Kinect for Windows sensor and on video. Goniometric values were determined from video recordings, while motion capture data were transformed to joint angles using 2 methods (body angle and projection angle). Correlation of motion capture with goniometry and detection of motion limitation. Active shoulder motion measured with low-cost motion capture agreed well with goniometry (r = 0.70-0.80), while passive shoulder motion measurements did not correlate well. Using motion capture, it was possible to reliably identify participants whose range of shoulder motion was reduced by 40% or more. Low-cost, automated motion analysis may be acceptable to screen for moderate to severe motion impairments in active shoulder motion. Automatic detection of motion limitation may allow quick screening to be performed in an oncologist's office and trigger timely referrals for rehabilitation.

4D numerical observer for lesion detection in respiratory-gated PET

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

Lorsakul, Auranuch; Li, Quanzheng; Ouyang, Jinsong

2014-10-15

Purpose: Respiratory-gated positron emission tomography (PET)/computed tomography protocols reduce lesion smearing and improve lesion detection through a synchronized acquisition of emission data. However, an objective assessment of image quality of the improvement gained from respiratory-gated PET is mainly limited to a three-dimensional (3D) approach. This work proposes a 4D numerical observer that incorporates both spatial and temporal informations for detection tasks in pulmonary oncology. Methods: The authors propose a 4D numerical observer constructed with a 3D channelized Hotelling observer for the spatial domain followed by a Hotelling observer for the temporal domain. Realistic {sup 18}F-fluorodeoxyglucose activity distributions were simulated usingmore » a 4D extended cardiac torso anthropomorphic phantom including 12 spherical lesions at different anatomical locations (lower, upper, anterior, and posterior) within the lungs. Simulated data based on Monte Carlo simulation were obtained using GEANT4 application for tomographic emission (GATE). Fifty noise realizations of six respiratory-gated PET frames were simulated by GATE using a model of the Siemens Biograph mMR scanner geometry. PET sinograms of the thorax background and pulmonary lesions that were simulated separately were merged to generate different conditions of the lesions to the background (e.g., lesion contrast and motion). A conventional ordered subset expectation maximization (OSEM) reconstruction (5 iterations and 6 subsets) was used to obtain: (1) gated, (2) nongated, and (3) motion-corrected image volumes (a total of 3200 subimage volumes: 2400 gated, 400 nongated, and 400 motion-corrected). Lesion-detection signal-to-noise ratios (SNRs) were measured in different lesion-to-background contrast levels (3.5, 8.0, 9.0, and 20.0), lesion diameters (10.0, 13.0, and 16.0 mm), and respiratory motion displacements (17.6–31.3 mm). The proposed 4D numerical observer applied on multiple-gated images was compared to the conventional 3D approach applied on the nongated and motion-corrected images. Results: On average, the proposed 4D numerical observer improved the detection SNR by 48.6% (p < 0.005), whereas the 3D methods on motion-corrected images improved by 31.0% (p < 0.005) as compared to the nongated method. For all different conditions of the lesions, the relative SNR measurement (Gain = SNR{sub Observed}/SNR{sub Nongated}) of the 4D method was significantly higher than one from the motion-corrected 3D method by 13.8% (p < 0.02), where Gain{sub 4D} was 1.49 ± 0.21 and Gain{sub 3D} was 1.31 ± 0.15. For the lesion with the highest amplitude of motion, the 4D numerical observer yielded the highest observer-performance improvement (176%). For the lesion undergoing the smallest motion amplitude, the 4D method provided superior lesion detectability compared with the 3D method, which provided a detection SNR close to the nongated method. The investigation on a structure of the 4D numerical observer showed that a Laguerre–Gaussian channel matrix with a volumetric 3D function yielded higher lesion-detection performance than one with a 2D-stack-channelized function, whereas a different kind of channels that have the ability to mimic the human visual system, i.e., difference-of-Gaussian, showed similar performance in detecting uniform and spherical lesions. The investigation of the detection performance when increasing noise levels yielded decreasing detection SNR by 27.6% and 41.5% for the nongated and gated methods, respectively. The investigation of lesion contrast and diameter showed that the proposed 4D observer preserved the linearity property of an optimal-linear observer while the motion was present. Furthermore, the investigation of the iteration and subset numbers of the OSEM algorithm demonstrated that these parameters had impact on the lesion detectability and the selection of the optimal parameters could provide the maximum lesion-detection performance. The proposed 4D numerical observer outperformed the other observers for the lesion-detection task in various lesion conditions and motions. Conclusions: The 4D numerical observer shows substantial improvement in lesion detectability over the 3D observer method. The proposed 4D approach could potentially provide a more reliable objective assessment of the impact of respiratory-gated PET improvement for lesion-detection tasks. On the other hand, the 4D approach may be used as an upper bound to investigate the performance of the motion correction method. In future work, the authors will validate the proposed 4D approach on clinical data for detection tasks in pulmonary oncology.« less

Self-sensing paper-based actuators employing ferromagnetic nanoparticles and graphite

NASA Astrophysics Data System (ADS)

Phan, Hoang-Phuong; Dinh, Toan; Nguyen, Tuan-Khoa; Vatani, Ashkan; Md Foisal, Abu Riduan; Qamar, Afzaal; Kermany, Atieh Ranjbar; Dao, Dzung Viet; Nguyen, Nam-Trung

2017-04-01

Paper-based microfluidics and sensors have attracted great attention. Although a large number of paper-based devices have been developed, surprisingly there are only a few studies investigating paper actuators. To fulfill the requirements for the integration of both sensors and actuators into paper, this work presents an unprecedented platform which utilizes ferromagnetic particles for actuation and graphite for motion monitoring. The use of the integrated mechanical sensing element eliminates the reliance on image processing for motion detection and also allows real-time measurements of the dynamic response in paper-based actuators. The proposed platform can also be quickly fabricated using a simple process, indicating its potential for controllable paper-based lab on chip.

Measurement of motion detection of wireless capsule endoscope inside large intestine.

PubMed

Zhou, Mingda; Bao, Guanqun; Pahlavan, Kaveh

2014-01-01

Wireless Capsule Endoscope (WCE) provides a noninvasive way to inspect the entire Gastrointestinal (GI) tract, including large intestine, where intestinal diseases most likely occur. As a critical component of capsule endoscopic examination, physicians need to know the precise position of the endoscopic capsule in order to identify the position of detected intestinal diseases. Knowing how the capsule moves inside the large intestine would greatly complement the existing wireless localization systems by providing the motion information. Since the most recently released WCE can take up to 6 frames per second, it's possible to estimate the movement of the capsule by processing the successive image sequence. In this paper, a computer vision based approach without utilizing any external device is proposed to estimate the motion of WCE inside the large intestine. The proposed approach estimate the displacement and rotation of the capsule by calculating entropy and mutual information between frames using Fibonacci method. The obtained results of this approach show its stability and better performance over other existing approaches of motion measurements. Meanwhile, findings of this paper lay a foundation for motion pattern of WCEs inside the large intestine, which will benefit other medical applications.

Assessing the performance of a motion tracking system based on optical joint transform correlation

NASA Astrophysics Data System (ADS)

Elbouz, M.; Alfalou, A.; Brosseau, C.; Ben Haj Yahia, N.; Alam, M. S.

2015-08-01

We present an optimized system specially designed for the tracking and recognition of moving subjects in a confined environment (such as an elderly remaining at home). In the first step of our study, we use a VanderLugt correlator (VLC) with an adapted pre-processing treatment of the input plane and a postprocessing of the correlation plane via a nonlinear function allowing us to make a robust decision. The second step is based on an optical joint transform correlation (JTC)-based system (NZ-NL-correlation JTC) for achieving improved detection and tracking of moving persons in a confined space. The proposed system has been found to have significantly superior discrimination and robustness capabilities allowing to detect an unknown target in an input scene and to determine the target's trajectory when this target is in motion. This system offers robust tracking performance of a moving target in several scenarios, such as rotational variation of input faces. Test results obtained using various real life video sequences show that the proposed system is particularly suitable for real-time detection and tracking of moving objects.

Motion artifact detection in four-dimensional computed tomography images

NASA Astrophysics Data System (ADS)

Bouilhol, G.; Ayadi, M.; Pinho, R.; Rit, S.; Sarrut, D.

2014-03-01

Motion artifacts appear in four-dimensional computed tomography (4DCT) images because of suboptimal acquisition parameters or patient breathing irregularities. Frequency of motion artifacts is high and they may introduce errors in radiation therapy treatment planning. Motion artifact detection can be useful for image quality assessment and 4D reconstruction improvement but manual detection in many images is a tedious process. We propose a novel method to evaluate the quality of 4DCT images by automatic detection of motion artifacts. The method was used to evaluate the impact of the optimization of acquisition parameters on image quality at our institute. 4DCT images of 114 lung cancer patients were analyzed. Acquisitions were performed with a rotation period of 0.5 seconds and a pitch of 0.1 (74 patients) or 0.081 (40 patients). A sensitivity of 0.70 and a specificity of 0.97 were observed. End-exhale phases were less prone to motion artifacts. In phases where motion speed is high, the number of detected artifacts was systematically reduced with a pitch of 0.081 instead of 0.1 and the mean reduction was 0.79. The increase of the number of patients with no artifact detected was statistically significant for the 10%, 70% and 80% respiratory phases, indicating a substantial image quality improvement.

Application of a net-based baseline correction scheme to strong-motion records of the 2011 Mw 9.0 Tohoku earthquake

NASA Astrophysics Data System (ADS)

Tu, Rui; Wang, Rongjiang; Zhang, Yong; Walter, Thomas R.

2014-06-01

The description of static displacements associated with earthquakes is traditionally achieved using GPS, EDM or InSAR data. In addition, displacement histories can be derived from strong-motion records, allowing an improvement of geodetic networks at a high sampling rate and a better physical understanding of earthquake processes. Strong-motion records require a correction procedure appropriate for baseline shifts that may be caused by rotational motion, tilting and other instrumental effects. Common methods use an empirical bilinear correction on the velocity seismograms integrated from the strong-motion records. In this study, we overcome the weaknesses of an empirically based bilinear baseline correction scheme by using a net-based criterion to select the timing parameters. This idea is based on the physical principle that low-frequency seismic waveforms at neighbouring stations are coherent if the interstation distance is much smaller than the distance to the seismic source. For a dense strong-motion network, it is plausible to select the timing parameters so that the correlation coefficient between the velocity seismograms of two neighbouring stations is maximized after the baseline correction. We applied this new concept to the KiK-Net and K-Net strong-motion data available for the 2011 Mw 9.0 Tohoku earthquake. We compared the derived coseismic static displacement with high-quality GPS data, and with the results obtained using empirical methods. The results show that the proposed net-based approach is feasible and more robust than the individual empirical approaches. The outliers caused by unknown problems in the measurement system can be easily detected and quantified.

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.

Image deblurring in smartphone devices using built-in inertial measurement sensors

NASA Astrophysics Data System (ADS)

Šindelář, Ondřej; Šroubek, Filip

2013-01-01

Long-exposure handheld photography is degraded with blur, which is difficult to remove without prior information about the camera motion. In this work, we utilize inertial sensors (accelerometers and gyroscopes) in modern smartphones to detect exact motion trajectory of the smartphone camera during exposure and remove blur from the resulting photography based on the recorded motion data. The whole system is implemented on the Android platform and embedded in the smartphone device, resulting in a close-to-real-time deblurring algorithm. The performance of the proposed system is demonstrated in real-life scenarios.

Harmonic Motion Imaging for Abdominal Tumor Detection and High-intensity Focused Ultrasound Ablation Monitoring: A Feasibility Study in a Transgenic Mouse Model of Pancreatic Cancer

PubMed Central

Chen, Hong; Hou, Gary Y.; Han, Yang; Payen, Thomas; Palermo, Carmine F.; Olive, Kenneth P.; Konofagou, Elisa E.

2015-01-01

Harmonic motion imaging (HMI) is a radiation force-based elasticity imaging technique that tracks oscillatory tissue displacements induced by sinusoidal ultrasonic radiation force to assess relative tissue stiffness. The objective of this study was to evaluate the feasibility of HMI in pancreatic tumor detection and high-intensity focused ultrasound (HIFU) treatment monitoring. The HMI system consisted of a focused ultrasound transducer, which generated sinusoidal radiation force to induce oscillatory tissue motion at 50 Hz, and a diagnostic ultrasound transducer, which detected the axial tissue displacements based on acquired radiofrequency signals using a 1D cross-correlation algorithm. For pancreatic tumor detection, HMI images were generated for pancreatic tumors in transgenic mice and normal pancreases in wild-type mice. The obtained HMI images showed a high contrast between normal and malignant pancreases with an average peak-to-peak HMI displacement ratio of 3.2. Histological analysis showed that no tissue damage was associated with HMI when it was used for the sole purpose of elasticity imaging. For pancreatic tumor ablation monitoring, the focused ultrasound transducer was operated with a higher acoustic power and longer pulse length than that used in tumor detection to simultaneously induce HIFU thermal ablation and oscillatory tissue displacements, allowing HMI monitoring without interrupting tumor ablation. HMI monitoring of HIFU ablation found significant decreases in the peak-to-peak HMI displacements before and after HIFU ablation with a reduction rate ranging from 15.8% to 57.0%. The formation of thermal lesions after HIFU exposure was confirmed by histological analysis. This study demonstrated the feasibility of HMI in abdominal tumor detection and HIFU ablation monitoring. PMID:26415128

Harmonic motion imaging for abdominal tumor detection and high-intensity focused ultrasound ablation monitoring: an in vivo feasibility study in a transgenic mouse model of pancreatic cancer.

PubMed

Chen, Hong; Hou, Gary Y; Han, Yang; Payen, Thomas; Palermo, Carmine F; Olive, Kenneth P; Konofagou, Elisa E

2015-09-01

Harmonic motion imaging (HMI) is a radiationforce- based elasticity imaging technique that tracks oscillatory tissue displacements induced by sinusoidal ultrasonic radiation force to assess the resulting oscillatory displacement denoting the underlying tissue stiffness. The objective of this study was to evaluate the feasibility of HMI in pancreatic tumor detection and high-intensity focused ultrasound (HIFU) treatment monitoring. The HMI system consisted of a focused ultrasound transducer, which generated sinusoidal radiation force to induce oscillatory tissue motion at 50 Hz, and a diagnostic ultrasound transducer, which detected the axial tissue displacements based on acquired radio-frequency signals using a 1-D cross-correlation algorithm. For pancreatic tumor detection, HMI images were generated for pancreatic tumors in transgenic mice and normal pancreases in wild-type mice. The obtained HMI images showed a high contrast between normal and malignant pancreases with an average peak-to-peak HMI displacement ratio of 3.2. Histological analysis showed that no tissue damage was associated with HMI when it was used for the sole purpose of elasticity imaging. For pancreatic tumor ablation monitoring, the focused ultrasound transducer was operated at a higher acoustic power and longer pulse length than that used in tumor detection to simultaneously induce HIFU thermal ablation and oscillatory tissue displacements, allowing HMI monitoring without interrupting tumor ablation. HMI monitoring of HIFU ablation found significant decreases in the peak-to-peak HMI displacements before and after HIFU ablation with a reduction rate ranging from 15.8% to 57.0%. The formation of thermal lesions after HIFU exposure was confirmed by histological analysis. This study demonstrated the feasibility of HMI in abdominal tumor detection and HIFU ablation monitoring.

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.

Detecting chaos, determining the dimensions of tori and predicting slow diffusion in Fermi-Pasta-Ulam lattices by the Generalized Alignment Index method

NASA Astrophysics Data System (ADS)

Skokos, C.; Bountis, T.; Antonopoulos, C.

2008-12-01

The recently introduced GALI method is used for rapidly detecting chaos, determining the dimensionality of regular motion and predicting slow diffusion in multi-dimensional Hamiltonian systems. We propose an efficient computation of the GALIk indices, which represent volume elements of k randomly chosen deviation vectors from a given orbit, based on the Singular Value Decomposition (SVD) algorithm. We obtain theoretically and verify numerically asymptotic estimates of GALIs long-time behavior in the case of regular orbits lying on low-dimensional tori. The GALIk indices are applied to rapidly detect chaotic oscillations, identify low-dimensional tori of Fermi-Pasta-Ulam (FPU) lattices at low energies and predict weak diffusion away from quasiperiodic motion, long before it is actually observed in the oscillations.

Remote monitoring and security alert based on motion detection using mobile

NASA Astrophysics Data System (ADS)

Suganya Devi, K.; Srinivasan, P.

2016-03-01

Background model does not have any robust solution and constitutes one of the main problems in surveillance systems. The aim of the paper is to provide a mobile based security to a remote monitoring system through a WAP using GSM modem. It is most designed to provide durability and versatility for a wide variety of indoor and outdoor applications. It is compatible with both narrow and band networks and provides simultaneous image detection. The communicator provides remote control, event driven recording, including pre-alarm and post-alarm and image motion detection. The web cam allowing them to be mounted either to a ceiling or wall without requiring bracket, with the use of web cam. We could continuously monitoring status in the client system through the web. If any intruder arrives in the client system, server will provide an alert to the mobile (what we are set in the message that message send to the authorized person) and the client can view the image using WAP.

The relationship of global form and motion detection to reading fluency.

PubMed

Englund, Julia A; Palomares, Melanie

2012-08-15

Visual motion processing in typical and atypical readers has suggested aspects of reading and motion processing share a common cortical network rooted in dorsal visual areas. Few studies have examined the relationship between reading performance and visual form processing, which is mediated by ventral cortical areas. We investigated whether reading fluency correlates with coherent motion detection thresholds in typically developing children using random dot kinematograms. As a comparison, we also evaluated the correlation between reading fluency and static form detection thresholds. Results show that both dorsal and ventral visual functions correlated with components of reading fluency, but that they have different developmental characteristics. Motion coherence thresholds correlated with reading rate and accuracy, which both improved with chronological age. Interestingly, when controlling for non-verbal abilities and age, reading accuracy significantly correlated with thresholds for coherent form detection but not coherent motion detection in typically developing children. Dorsal visual functions that mediate motion coherence seem to be related maturation of broad cognitive functions including non-verbal abilities and reading fluency. However, ventral visual functions that mediate form coherence seem to be specifically related to accurate reading in typically developing children. Copyright © 2012 Elsevier Ltd. All rights reserved.

Clearance detector and method for motion and distance

DOEpatents

Xavier, Patrick G [Albuquerque, NM

2011-08-09

A method for correct and efficient detection of clearances between three-dimensional bodies in computer-based simulations, where one or both of the volumes is subject to translation and/or rotations. The method conservatively determines of the size of such clearances and whether there is a collision between the bodies. Given two bodies, each of which is undergoing separate motions, the method utilizes bounding-volume hierarchy representations for the two bodies and, mappings and inverse mappings for the motions of the two bodies. The method uses the representations, mappings and direction vectors to determine the directionally furthest locations of points on the convex hulls of the volumes virtually swept by the bodies and hence the clearance between the bodies, without having to calculate the convex hulls of the bodies. The method includes clearance detection for bodies comprising convex geometrical primitives and more specific techniques for bodies comprising convex polyhedra.

A rain pixel recovery algorithm for videos with highly dynamic scenes.

PubMed

Jie Chen; Lap-Pui Chau

2014-03-01

Rain removal is a very useful and important technique in applications such as security surveillance and movie editing. Several rain removal algorithms have been proposed these years, where photometric, chromatic, and probabilistic properties of the rain have been exploited to detect and remove the rainy effect. Current methods generally work well with light rain and relatively static scenes, when dealing with heavier rainfall in dynamic scenes, these methods give very poor visual results. The proposed algorithm is based on motion segmentation of dynamic scene. After applying photometric and chromatic constraints for rain detection, rain removal filters are applied on pixels such that their dynamic property as well as motion occlusion clue are considered; both spatial and temporal informations are then adaptively exploited during rain pixel recovery. Results show that the proposed algorithm has a much better performance for rainy scenes with large motion than existing algorithms.

Initial clinical evaluation of PET-based ion beam therapy monitoring under consideration of organ motion

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

Kurz, Christopher, E-mail: christopher.kurz@physik.uni-muenchen.de; Bauer, Julia; Unholtz, Daniel

2016-02-15

Purpose: Intrafractional organ motion imposes considerable challenges to scanned ion beam therapy and demands for a thorough verification of the applied treatment. At the Heidelberg Ion-Beam Therapy Center (HIT), the scanned ion beam delivery is verified by means of postirradiation positron-emission-tomography (PET) imaging. This work presents a first clinical evaluation of PET-based treatment monitoring in ion beam therapy under consideration of target motion. Methods: Three patients with mobile liver lesions underwent scanned carbon ion irradiation at HIT and postirradiation PET/CT (x-ray-computed-tomography) imaging with a commercial scanner. Respiratory motion was recorded during irradiation and subsequent image acquisition. This enabled a time-resolvedmore » (4D) calculation of the expected irradiation-induced activity pattern and, for one patient where an additional 4D CT was acquired at the PET/CT scanner after treatment, a motion-compensated PET image reconstruction. For the other patients, PET data were reconstructed statically. To verify the treatment, calculated prediction and reconstructed measurement were compared with a focus on the ion beam range. Results: Results in the current three patients suggest that for motion amplitudes in the order of 2 mm there is no benefit from incorporating respiratory motion information into PET-based treatment monitoring. For a target motion in the order of 10 mm, motion-related effects become more severe and a time-resolved modeling of the expected activity distribution can lead to an improved data interpretation if a sufficient number of true coincidences is detected. Benefits from motion-compensated PET image reconstruction could not be shown conclusively at the current stage. Conclusions: The feasibility of clinical PET-based treatment verification under consideration of organ motion has been shown for the first time. Improvements in noise-robust 4D PET image reconstruction are deemed necessary to enhance the clinical potential.« less

SU-E-J-193: Application of Surface Mapping in Detecting Swallowing for Head-&-Neck Cancer

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

Cao, D; Xie, X; Mehta, V

2015-06-15

Purpose: Recent evidence is emerging that long term swallowing function may be improved after radiotherapy for head-&-neck cancer if doses are limited to certain swallowing structures. Immobilization of patients with head-&-neck cancer is typically done with a mask. This mask, however, doesn’t limit patient swallowing. Patient voluntary or involuntary swallowing may introduce significant tumor motion, which can lead to suboptimal delivery. In this study, we have examined the feasibility of using surface mapping technology to detect patient swallowing during treatment and evaluated its magnitude. Methods: The C-RAD Catalyst system was used to detect the patient surface map. A volunteer lyingmore » on the couch was used to simulate the patient under treatment. A virtual marker was placed near the throat and was used to monitor the swallowing action. The target motion calculated by the Catalyst system through deformable registration was also collected. Two treatment isocenters, one placed close to the throat and the other placed posterior to the base-of-tongue, were used to check the sensitivity of surface mapping technique. Results: When the patient’s throat is not in the shadow of the patient’s chest, the Catalyst system can clearly identify the swallowing motion. In our tests, the vertical motion of the skin can reach to about 5mm. The calculated target motion can reach up to 1 cm. The magnitude of this calculated target motion is more dramatic when the plan isocenter is closer to the skin surface, which suggests that the Catalyst motion tracking technique is more sensitive to the swallowing motion with a shallower isocenter. Conclusion: Surface mapping can clearly identify patient swallowing during radiation treatment. This information can be used to evaluate the dosimetric impact of the involuntary swallowing. It may also be used to potentially gate head-&-neck radiation treatments. A prospective IRB approved study is currently enrolling patients in our institution. Research was funded through an Elekta grant.« less

Development of a video-guided real-time patient motion monitoring system.

PubMed

Ju, Sang Gyu; Huh, Woong; Hong, Chae-Seon; Kim, Jin Sung; Shin, Jung Suk; Shin, Eunhyuk; Han, Youngyih; Ahn, Yong Chan; Park, Hee Chul; Choi, Doo Ho

2012-05-01

The authors developed a video image-guided real-time patient motion monitoring (VGRPM) system using PC-cams, and its clinical utility was evaluated using a motion phantom. The VGRPM system has three components: (1) an image acquisition device consisting of two PC-cams, (2) a main control computer with a radiation signal controller and warning system, and (3) patient motion analysis software developed in-house. The intelligent patient motion monitoring system was designed for synchronization with a beam on/off trigger signal in order to limit operation to during treatment time only and to enable system automation. During each treatment session, an initial image of the patient is acquired as soon as radiation starts and is compared with subsequent live images, which can be acquired at up to 30 fps by the real-time frame difference-based analysis software. When the error range exceeds the set criteria (δ(movement)) due to patient movement, a warning message is generated in the form of light and sound. The described procedure repeats automatically for each patient. A motion phantom, which operates by moving a distance of 0.1, 0.2, 0.3, 0.5, and 1.0 cm for 1 and 2 s, respectively, was used to evaluate the system performance. The authors measured optimal δ(movement) for clinical use, the minimum distance that can be detected with this system, and the response time of the whole system using a video analysis technique. The stability of the system in a linear accelerator unit was evaluated for a period of 6 months. As a result of the moving phantom test, the δ(movement) for detection of all simulated phantom motion except the 0.1 cm movement was determined to be 0.2% of total number of pixels in the initial image. The system can detect phantom motion as small as 0.2 cm. The measured response time from the detection of phantom movement to generation of the warning signal was 0.1 s. No significant functional disorder of the system was observed during the testing period. The VGRPM system has a convenient design, which synchronizes initiation of the analysis with a beam on/off signal from the treatment machine and may contribute to a reduction in treatment error due to patient motion and increase the accuracy of treatment dose delivery.

Harmonic Motion Imaging (HMI) for Tumor Imaging and Treatment Monitoring.

PubMed

Konofagou, Elisa E; Maleke, Caroline; Vappou, Jonathan

2012-01-01

Palpation is an established screening procedure for the detection of several superficial cancers including breast, thyroid, prostate, and liver tumors through both self and clinical examinations. This is because solid masses typically have distinct stiffnesses compared to the surrounding normal tissue. In this paper, the application of Harmonic Motion Imaging (HMI) for tumor detection based on its stiffness as well as its relevance in thermal treatment is reviewed. HMI uses a focused ultrasound (FUS) beam to generate an oscillatory acoustic radiation force for an internal, non-contact palpation to internally estimate relative tissue hardness. HMI studies have dealt with the measurement of the tissue dynamic motion in response to an oscillatory acoustic force at the same frequency, and have been shown feasible in simulations, phantoms, ex vivo human and bovine tissues as well as animals in vivo. Using an FUS beam, HMI can also be used in an ideal integration setting with thermal ablation using high-intensity focused ultrasound (HIFU), which also leads to an alteration in the tumor stiffness. In this paper, a short review of HMI is provided that encompasses the findings in all the aforementioned areas. The findings presented herein demonstrate that the HMI displacement can accurately depict the underlying tissue stiffness, and the HMI image of the relative stiffness could accurately detect and characterize the tumor or thermal lesion based on its distinct properties. HMI may thus constitute a non-ionizing, cost-efficient and reliable complementary method for noninvasive tumor detection, localization, diagnosis and treatment monitoring.

Harmonic Motion Imaging (HMI) for Tumor Imaging and Treatment Monitoring

PubMed Central

Maleke, Caroline; Vappou, Jonathan

2014-01-01

Palpation is an established screening procedure for the detection of several superficial cancers including breast, thyroid, prostate, and liver tumors through both self and clinical examinations. This is because solid masses typically have distinct stiffnesses compared to the surrounding normal tissue. In this paper, the application of Harmonic Motion Imaging (HMI) for tumor detection based on its stiffness as well as its relevance in thermal treatment is reviewed. HMI uses a focused ultrasound (FUS) beam to generate an oscillatory acoustic radiation force for an internal, non-contact palpation to internally estimate relative tissue hardness. HMI studies have dealt with the measurement of the tissue dynamic motion in response to an oscillatory acoustic force at the same frequency, and have been shown feasible in simulations, phantoms, ex vivo human and bovine tissues as well as animals in vivo. Using an FUS beam, HMI can also be used in an ideal integration setting with thermal ablation using high-intensity focused ultrasound (HIFU), which also leads to an alteration in the tumor stiffness. In this paper, a short review of HMI is provided that encompasses the findings in all the aforementioned areas. The findings presented herein demonstrate that the HMI displacement can accurately depict the underlying tissue stiffness, and the HMI image of the relative stiffness could accurately detect and characterize the tumor or thermal lesion based on its distinct properties. HMI may thus constitute a non-ionizing, cost-efficient and reliable complementary method for noninvasive tumor detection, localization, diagnosis and treatment monitoring. PMID:25364321

DDDAMS-based Urban Surveillance and Crowd Control via UAVs and UGVs

DTIC Science & Technology

2015-12-04

for crowd dynamics modeling by incorporating multi-resolution data, where a grid-based method is used to model crowd motion with UAVs’ low -resolution...information and more computational intensive (and time-consuming). Given that the deployment of fidelity selection results in simulation faces computational... low fidelity information FOV y (A) DR x (A) DR y (A) Not detected high fidelity information Table 1: Parameters for UAV and UGV for their detection

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.

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.

Motion-mode energy method for vehicle dynamics analysis and control

NASA Astrophysics Data System (ADS)

Zhang, Nong; Wang, Lifu; Du, Haiping

2014-01-01

Vehicle motion and vibration control is a fundamental motivation for the development of advanced vehicle suspension systems. In a vehicle-fixed coordinate system, the relative motions of the vehicle between body and wheel can be classified into several dynamic stages based on energy intensity, and can be decomposed into sets of uncoupled motion-modes according to modal parameters. Vehicle motions are coupled, but motion-modes are orthogonal. By detecting and controlling the predominating vehicle motion-mode, the system cost and energy consumption of active suspensions could be reduced. A motion-mode energy method (MEM) is presented in this paper to quantify the energy contribution of each motion-mode to vehicle dynamics in real time. The control of motion-modes is prioritised according to the level of motion-mode energy. Simulation results on a 10 degree-of-freedom nonlinear full-car model with the magic-formula tyre model illustrate the effectiveness of the proposed MEM. The contribution of each motion-mode to the vehicle's dynamic behaviour is analysed under different excitation inputs from road irregularities, directional manoeuvres and braking. With the identified dominant motion-mode, novel cost-effective suspension systems, such as active reconfigurable hydraulically interconnected suspension, can possibly be used to control full-car motions with reduced energy consumption. Finally, discussion, conclusions and suggestions for future work are provided.

Application of side-oblique image-motion blur correction to Kuaizhou-1 agile optical images.

PubMed

Sun, Tao; Long, Hui; Liu, Bao-Cheng; Li, Ying

2016-03-21

Given the recent development of agile optical satellites for rapid-response land observation, side-oblique image-motion (SOIM) detection and blur correction have become increasingly essential for improving the radiometric quality of side-oblique images. The Chinese small-scale agile mapping satellite Kuaizhou-1 (KZ-1) was developed by the Harbin Institute of Technology and launched for multiple emergency applications. Like other agile satellites, KZ-1 suffers from SOIM blur, particularly in captured images with large side-oblique angles. SOIM detection and blur correction are critical for improving the image radiometric accuracy. This study proposes a SOIM restoration method based on segmental point spread function detection. The segment region width is determined by satellite parameters such as speed, height, integration time, and side-oblique angle. The corresponding algorithms and a matrix form are proposed for SOIM blur correction. Radiometric objective evaluation indices are used to assess the restoration quality. Beijing regional images from KZ-1 are used as experimental data. The radiometric quality is found to increase greatly after SOIM correction. Thus, the proposed method effectively corrects image motion for KZ-1 agile optical satellites.

A habituation based approach for detection of visual changes in surveillance camera

NASA Astrophysics Data System (ADS)

Sha'abani, M. N. A. H.; Adan, N. F.; Sabani, M. S. M.; Abdullah, F.; Nadira, J. H. S.; Yasin, M. S. M.

2017-09-01

This paper investigates a habituation based approach in detecting visual changes using video surveillance systems in a passive environment. Various techniques have been introduced for dynamic environment such as motion detection, object classification and behaviour analysis. However, in a passive environment, most of the scenes recorded by the surveillance system are normal. Therefore, implementing a complex analysis all the time in the passive environment resulting on computationally expensive, especially when using a high video resolution. Thus, a mechanism of attention is required, where the system only responds to an abnormal event. This paper proposed a novelty detection mechanism in detecting visual changes and a habituation based approach to measure the level of novelty. The objective of the paper is to investigate the feasibility of the habituation based approach in detecting visual changes. Experiment results show that the approach are able to accurately detect the presence of novelty as deviations from the learned knowledge.

Relative Orientation and Position Detections Based on an RGB-D Sensor and Dynamic Cooperation Strategies for Jumping Sensor Nodes Recycling

PubMed Central

Zhang, Jun; Yang, Xi; Song, Guang-Ming; Chen, Tian-Yuan; Zhang, Yong

2015-01-01

This paper presents relative orientation and position detection methods for jumping sensor nodes (JSNs) recycling. The methods are based on motion captures of the JSNs by an RGB-D sensor mounted on a carrier robot and the dynamic cooperation between the carrier and the JSNs. A disc-like label with two different colored sides is mounted on the top of the JSNs. The RGB-D sensor can detect the motion of the label to calculate the orientations and positions of the JSNs and the carrier relative to each other. After the orientations and positions have been detected, the JSNs jump into a cabin mounted on the carrier in dynamic cooperation with the carrier for recycling. The performances of the proposed methods are tested with a prototype system. The results show that the carrier can detect a JSN from up to 2 m away and sense its relative orientation and position successfully. The errors of the JSN’s orientation and position detections relative to the carrier could be reduced to the values smaller than 1° and 1 cm, respectively, by using the dynamic cooperation strategies. The proposed methods in this paper could also be used for other kinds of mobile sensor nodes and multi-robot systems. PMID:26393589

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units

PubMed Central

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-01-01

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions. PMID:28208684

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units.

PubMed

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-02-12

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions.

Visual motion detection and habitat preference in Anolis lizards.

PubMed

Steinberg, David S; Leal, Manuel

2016-11-01

The perception of visual stimuli has been a major area of inquiry in sensory ecology, and much of this work has focused on coloration. However, for visually oriented organisms, the process of visual motion detection is often equally crucial to survival and reproduction. Despite the importance of motion detection to many organisms' daily activities, the degree of interspecific variation in the perception of visual motion remains largely unexplored. Furthermore, the factors driving this potential variation (e.g., ecology or evolutionary history) along with the effects of such variation on behavior are unknown. We used a behavioral assay under laboratory conditions to quantify the visual motion detection systems of three species of Puerto Rican Anolis lizard that prefer distinct structural habitat types. We then compared our results to data previously collected for anoles from Cuba, Puerto Rico, and Central America. Our findings indicate that general visual motion detection parameters are similar across species, regardless of habitat preference or evolutionary history. We argue that these conserved sensory properties may drive the evolution of visual communication behavior in this clade.

Development of 4D mathematical observer models for the task-based evaluation of gated myocardial perfusion SPECT

NASA Astrophysics Data System (ADS)

Lee, Taek-Soo; Frey, Eric C.; Tsui, Benjamin M. W.

2015-04-01

This paper presents two 4D mathematical observer models for the detection of motion defects in 4D gated medical images. Their performance was compared with results from human observers in detecting a regional motion abnormality in simulated 4D gated myocardial perfusion (MP) SPECT images. The first 4D mathematical observer model extends the conventional channelized Hotelling observer (CHO) based on a set of 2D spatial channels and the second is a proposed model that uses a set of 4D space-time channels. Simulated projection data were generated using the 4D NURBS-based cardiac-torso (NCAT) phantom with 16 gates/cardiac cycle. The activity distribution modelled uptake of 99mTc MIBI with normal perfusion and a regional wall motion defect. An analytical projector was used in the simulation and the filtered backprojection (FBP) algorithm was used in image reconstruction followed by spatial and temporal low-pass filtering with various cut-off frequencies. Then, we extracted 2D image slices from each time frame and reorganized them into a set of cine images. For the first model, we applied 2D spatial channels to the cine images and generated a set of feature vectors that were stacked for the images from different slices of the heart. The process was repeated for each of the 1,024 noise realizations, and CHO and receiver operating characteristics (ROC) analysis methodologies were applied to the ensemble of the feature vectors to compute areas under the ROC curves (AUCs). For the second model, a set of 4D space-time channels was developed and applied to the sets of cine images to produce space-time feature vectors to which the CHO methodology was applied. The AUC values of the second model showed better agreement (Spearman’s rank correlation (SRC) coefficient = 0.8) to human observer results than those from the first model (SRC coefficient = 0.4). The agreement with human observers indicates the proposed 4D mathematical observer model provides a good predictor of the performance of human observers in detecting regional motion defects in 4D gated MP SPECT images. The result supports the use of the observer model in the optimization and evaluation of 4D image reconstruction and compensation methods for improving the detection of motion abnormalities in 4D gated MP SPECT images.

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

Robust real-time extraction of respiratory signals from PET list-mode data

NASA Astrophysics Data System (ADS)

Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-06-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware.

Motion-seeded object-based attention for dynamic visual imagery

NASA Astrophysics Data System (ADS)

Huber, David J.; Khosla, Deepak; Kim, Kyungnam

2017-05-01

This paper† describes a novel system that finds and segments "objects of interest" from dynamic imagery (video) that (1) processes each frame using an advanced motion algorithm that pulls out regions that exhibit anomalous motion, and (2) extracts the boundary of each object of interest using a biologically-inspired segmentation algorithm based on feature contours. The system uses a series of modular, parallel algorithms, which allows many complicated operations to be carried out by the system in a very short time, and can be used as a front-end to a larger system that includes object recognition and scene understanding modules. Using this method, we show 90% accuracy with fewer than 0.1 false positives per frame of video, which represents a significant improvement over detection using a baseline attention algorithm.

Posture-based processing in visual short-term memory for actions.

PubMed

Vicary, Staci A; Stevens, Catherine J

2014-01-01

Visual perception of human action involves both form and motion processing, which may rely on partially dissociable neural networks. If form and motion are dissociable during visual perception, then they may also be dissociable during their retention in visual short-term memory (VSTM). To elicit form-plus-motion and form-only processing of dance-like actions, individual action frames can be presented in the correct or incorrect order. The former appears coherent and should elicit action perception, engaging both form and motion pathways, whereas the latter appears incoherent and should elicit posture perception, engaging form pathways alone. It was hypothesized that, if form and motion are dissociable in VSTM, then recognition of static body posture should be better after viewing incoherent than after viewing coherent actions. However, as VSTM is capacity limited, posture-based encoding of actions may be ineffective with increased number of items or frames. Using a behavioural change detection task, recognition of a single test posture was significantly more likely after studying incoherent than after studying coherent stimuli. However, this effect only occurred for spans of two (but not three) items and for stimuli with five (but not nine) frames. As in perception, posture and motion are dissociable in VSTM.

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

Video noise reduction

NASA Astrophysics Data System (ADS)

Drewery, J. O.; Storey, R.; Tanton, N. E.

1984-07-01

A video noise and film grain reducer is described which is based on a first-order recursive temporal filter. Filtering of moving detail is avoided by inhibiting recursion in response to the amount of motion in a picture. Motion detection is based on the point-by-point power of the picture difference signal coupled with a knowledge of the noise statistics. A control system measures the noise power and adjusts the working point of the motion detector accordingly. A field trial of a manual version of the equipment at Television Center indicated that a worthwhile improvement in the quality of noisy or grainy pictures received by the viewer could be obtained. Subsequent trials of the automated version confirmed that the improvement could be maintained. Commercial equipment based on the design is being manufactured and marketed by Pye T.V.T. under license. It is in regular use on both the BBC1 and BBC2 networks.

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

An active-optics image-motion compensation technology application for high-speed searching and infrared detection system

NASA Astrophysics Data System (ADS)

Wu, Jianping; Lu, Fei; Zou, Kai; Yan, Hong; Wan, Min; Kuang, Yan; Zhou, Yanqing

2018-03-01

An ultra-high angular velocity and minor-caliber high-precision stably control technology application for active-optics image-motion compensation, is put forward innovatively in this paper. The image blur problem due to several 100°/s high-velocity relative motion between imaging system and target is theoretically analyzed. The velocity match model of detection system and active optics compensation system is built, and active optics image motion compensation platform experiment parameters are designed. Several 100°/s high-velocity high-precision control optics compensation technology is studied and implemented. The relative motion velocity is up to 250°/s, and image motion amplitude is more than 20 pixel. After the active optics compensation, motion blur is less than one pixel. The bottleneck technology of ultra-high angular velocity and long exposure time in searching and infrared detection system is successfully broke through.

Multi-modal intelligent seizure acquisition (MISA) system--a new approach towards seizure detection based on full body motion measures.

PubMed

Conradsen, Isa; Beniczky, Sandor; Wolf, Peter; Terney, Daniella; Sams, Thomas; Sorensen, Helge B D

2009-01-01

Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG) and audio and video recording. The results showed that a non-subject specific MISA system developed on data from the modalities: accelerometer (ACM), gyroscope and EMG is able to detect 98% of the simulated seizures and at the same time mistakes only 4 of the normal movements for seizures. If the system is individualized (subject specific) it is able to detect all simulated seizures with a maximum of 1 false positive. Based on the results from the simulated seizures and normal movements the MISA system seems to be a promising approach to seizure detection.

An unbiased measure of the contributions of chroma and luminance to saccadic suppression of displacement.

PubMed

Anand, Sulekha; Bridgeman, Bruce

2002-02-01

Perception of image displacement is suppressed during saccadic eye movements. We probed the source of saccadic suppression of displacement by testing whether it selectively affects chromatic- or luminance-based motion information. Human subjects viewed a stimulus in which chromatic and luminance cues provided conflicting information about displacement direction. Apparent motion occurred during either fixation or a 19.5 degree saccade. Subjects detected motion and discriminated displacement direction in each trial. They reported motion in over 90% of fixation trials and over 70% of saccade trials. During fixation, the probability of perceiving the direction carried by chromatic cues decreased as luminance contrast increased. During saccades, subjects tended to perceive the direction indicated by luminance cues when luminance contrast was high. However, when luminance contrast was low, subjects showed no preference for the chromatic- or luminance-based direction. Thus magnocellular channels are suppressed, while stimulation of parvocellular channels is below threshold, so that neither channel drives motion perception during saccades. These results confirm that magnocellular inhibition is the source of saccadic suppression.

Motion-adaptive model-assisted compatible coding with spatiotemporal scalability

NASA Astrophysics Data System (ADS)

Lee, JaeBeom; Eleftheriadis, Alexandros

1997-01-01

We introduce the concept of motion adaptive spatio-temporal model-assisted compatible (MA-STMAC) coding, a technique to selectively encode areas of different importance to the human eye in terms of space and time in moving images with the consideration of object motion. PRevious STMAC was proposed base don the fact that human 'eye contact' and 'lip synchronization' are very important in person-to-person communication. Several areas including the eyes and lips need different types of quality, since different areas have different perceptual significance to human observers. The approach provides a better rate-distortion tradeoff than conventional image coding techniques base don MPEG-1, MPEG- 2, H.261, as well as H.263. STMAC coding is applied on top of an encoder, taking full advantage of its core design. Model motion tracking in our previous STMAC approach was not automatic. The proposed MA-STMAC coding considers the motion of the human face within the STMAC concept using automatic area detection. Experimental results are given using ITU-T H.263, addressing very low bit-rate compression.

Contributions of the 12 neuron classes in the fly lamina to motion vision

PubMed Central

Tuthill, John C.; Nern, Aljoscha; Holtz, Stephen L.; Rubin, Gerald M.; Reiser, Michael B.

2013-01-01

SUMMARY Motion detection is a fundamental neural computation performed by many sensory systems. In the fly, local motion computation is thought to occur within the first two layers of the visual system, the lamina and medulla. We constructed specific genetic driver lines for each of the 12 neuron classes in the lamina. We then depolarized and hyperpolarized each neuron type, and quantified fly behavioral responses to a diverse set of motion stimuli. We found that only a small number of lamina output neurons are essential for motion detection, while most neurons serve to sculpt and enhance these feedforward pathways. Two classes of feedback neurons (C2 and C3), and lamina output neurons (L2 and L4), are required for normal detection of directional motion stimuli. Our results reveal a prominent role for feedback and lateral interactions in motion processing, and demonstrate that motion-dependent behaviors rely on contributions from nearly all lamina neuron classes. PMID:23849200

Contributions of the 12 neuron classes in the fly lamina to motion vision.

PubMed

Tuthill, John C; Nern, Aljoscha; Holtz, Stephen L; Rubin, Gerald M; Reiser, Michael B

2013-07-10

Motion detection is a fundamental neural computation performed by many sensory systems. In the fly, local motion computation is thought to occur within the first two layers of the visual system, the lamina and medulla. We constructed specific genetic driver lines for each of the 12 neuron classes in the lamina. We then depolarized and hyperpolarized each neuron type and quantified fly behavioral responses to a diverse set of motion stimuli. We found that only a small number of lamina output neurons are essential for motion detection, while most neurons serve to sculpt and enhance these feedforward pathways. Two classes of feedback neurons (C2 and C3), and lamina output neurons (L2 and L4), are required for normal detection of directional motion stimuli. Our results reveal a prominent role for feedback and lateral interactions in motion processing and demonstrate that motion-dependent behaviors rely on contributions from nearly all lamina neuron classes. Copyright © 2013 Elsevier Inc. All rights reserved.

An algorithm to diagnose ball bearing faults in servomotors running arbitrary motion profiles

NASA Astrophysics Data System (ADS)

Cocconcelli, Marco; Bassi, Luca; Secchi, Cristian; Fantuzzi, Cesare; Rubini, Riccardo

2012-02-01

This paper describes a procedure to extend the scope of classical methods to detect ball bearing faults (based on envelope analysis and fault frequencies identification) beyond their usual area of application. The objective of this procedure is to allow condition-based monitoring of such bearings in servomotor applications, where typically the motor in its normal mode of operation has to follow a non-constant angular velocity profile that may contain motion inversions. After describing and analyzing the algorithm from a theoretical point of view, experimental results obtained on a real industrial application are presented and commented.

TH-EF-BRB-08: Robotic Motion Compensation for Radiation Therapy: A 6DOF Phantom Study

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

Belcher, AH; Liu, X; Wiersma, R

Purpose: The high accuracy of frame-based stereotactic radiosurgery (SRS), which uses a rigid frame fixed to the patient’s skull, is offset by potential drawbacks of poor patient compliance and clinical workflow restrictions. Recent research into frameless SRS has so far resulted in reduced accuracy. In this study, we investigate the use of a novel 6 degree-of-freedom (6DOF) robotic head motion cancellation system that continuously detects and compensates for patient head motions during a SRS delivery. This approach has the potential to reduce invasiveness while still achieving accuracies better or equal to traditional frame-based SRS. Methods: A 6DOF parallel kinematics roboticsmore » stage was constructed, and controlled using an inverse kinematics-based motion compensation algorithm. A 6DOF stereoscopic infrared (IR) marker tracking system was used to monitor real-time motions at sub-millimeter and sub-degree levels. A novel 6DOF calibration technique was first applied to properly orient the camera coordinate frame to match that of the LINAC and robotic control frames. Simulated head motions were measured by the system, and the robotic stage responded to these 6DOF motions automatically, returning the reflective marker coordinate frame to its original position. Results: After the motions were introduced to the system in the phantom-based study, the robotic stage automatically and rapidly returned the phantom to LINAC isocenter. When errors exceeded the compensation lower threshold of 0.25 mm or 0.25 degrees, the system registered the 6DOF error and generated a cancellation trajectory. The system responded in less than 0.5 seconds and returned all axes to less than 0.1 mm and 0.1 degree after the 6DOF compensation was performed. Conclusion: The 6DOF real-time motion cancellation system was found to be effective at compensating for translational and rotational motions to current SRS requirements. This system can improve frameless SRS by automatically returning patients to isocenter with high 6DOF accuracy.« less

[Image processing applying in analysis of motion features of cultured cardiac myocyte in rat].

PubMed

Teng, Qizhi; He, Xiaohai; Luo, Daisheng; Wang, Zhengrong; Zhou, Beiyi; Yuan, Zhirun; Tao, Dachang

2007-02-01

Study of mechanism of medicine actions, by quantitative analysis of cultured cardiac myocyte, is one of the cutting edge researches in myocyte dynamics and molecular biology. The characteristics of cardiac myocyte auto-beating without external stimulation make the research sense. Research of the morphology and cardiac myocyte motion using image analysis can reveal the fundamental mechanism of medical actions, increase the accuracy of medicine filtering, and design the optimal formula of medicine for best medical treatments. A system of hardware and software has been built with complete sets of functions including living cardiac myocyte image acquisition, image processing, motion image analysis, and image recognition. In this paper, theories and approaches are introduced for analysis of living cardiac myocyte motion images and implementing quantitative analysis of cardiac myocyte features. A motion estimation algorithm is used for motion vector detection of particular points and amplitude and frequency detection of a cardiac myocyte. Beatings of cardiac myocytes are sometimes very small. In such case, it is difficult to detect the motion vectors from the particular points in a time sequence of images. For this reason, an image correlation theory is employed to detect the beating frequencies. Active contour algorithm in terms of energy function is proposed to approximate the boundary and detect the changes of edge of myocyte.

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.

Slow dynamics of a protein backbone in molecular dynamics simulation revealed by time-structure based independent component analysis

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2013-12-01

We recently proposed the method of time-structure based independent component analysis (tICA) to examine the slow dynamics involved in conformational fluctuations of a protein as estimated by molecular dynamics (MD) simulation [Y. Naritomi and S. Fuchigami, J. Chem. Phys. 134, 065101 (2011)]. Our previous study focused on domain motions of the protein and examined its dynamics by using rigid-body domain analysis and tICA. However, the protein changes its conformation not only through domain motions but also by various types of motions involving its backbone and side chains. Some of these motions might occur on a slow time scale: we hypothesize that if so, we could effectively detect and characterize them using tICA. In the present study, we investigated slow dynamics of the protein backbone using MD simulation and tICA. The selected target protein was lysine-, arginine-, ornithine-binding protein (LAO), which comprises two domains and undergoes large domain motions. MD simulation of LAO in explicit water was performed for 1 μs, and the obtained trajectory of Cα atoms in the backbone was analyzed by tICA. This analysis successfully provided us with slow modes for LAO that represented either domain motions or local movements of the backbone. Further analysis elucidated the atomic details of the suggested local motions and confirmed that these motions truly occurred on the expected slow time scale.

Simulating patient-specific heart shape and motion using SPECT perfusion images with the MCAT phantom

NASA Astrophysics Data System (ADS)

Faber, Tracy L.; Garcia, Ernest V.; Lalush, David S.; Segars, W. Paul; Tsui, Benjamin M.

2001-05-01

The spline-based Mathematical Cardiac Torso (MCAT) phantom is a realistic software simulation designed to simulate single photon emission computed tomographic (SPECT) data. It incorporates a heart model of known size and shape; thus, it is invaluable for measuring accuracy of acquisition, reconstruction, and post-processing routines. New functionality has been added by replacing the standard heart model with left ventricular (LV) epicaridal and endocardial surface points detected from actual patient SPECT perfusion studies. LV surfaces detected from standard post-processing quantitation programs are converted through interpolation in space and time into new B-spline models. Perfusion abnormalities are added to the model based on results of standard perfusion quantification. The new LV is translated and rotated to fit within existing atria and right ventricular models, which are scaled based on the size of the LV. Simulations were created for five different patients with myocardial infractions who had undergone SPECT perfusion imaging. Shape, size, and motion of the resulting activity map were compared visually to the original SPECT images. In all cases, size, shape and motion of simulated LVs matched well with the original images. Thus, realistic simulations with known physiologic and functional parameters can be created for evaluating efficacy of processing algorithms.

Knowledge-Based Motion Control of AN Intelligent Mobile Autonomous System

NASA Astrophysics Data System (ADS)

Isik, Can

An Intelligent Mobile Autonomous System (IMAS), which is equipped with vision and low level sensors to cope with unknown obstacles, is modeled as a hierarchy of path planning and motion control. This dissertation concentrates on the lower level of this hierarchy (Pilot) with a knowledge-based controller. The basis of a theory of knowledge-based controllers is established, using the example of the Pilot level motion control of IMAS. In this context, the knowledge-based controller with a linguistic world concept is shown to be adequate for the minimum time control of an autonomous mobile robot motion. The Pilot level motion control of IMAS is approached in the framework of production systems. The three major components of the knowledge-based control that are included here are the hierarchies of the database, the rule base and the rule evaluator. The database, which is the representation of the state of the world, is organized as a semantic network, using a concept of minimal admissible vocabulary. The hierarchy of rule base is derived from the analytical formulation of minimum-time control of IMAS motion. The procedure introduced for rule derivation, which is called analytical model verbalization, utilizes the concept of causalities to describe the system behavior. A realistic analytical system model is developed and the minimum-time motion control in an obstacle strewn environment is decomposed to a hierarchy of motion planning and control. The conditions for the validity of the hierarchical problem decomposition are established, and the consistency of operation is maintained by detecting the long term conflicting decisions of the levels of the hierarchy. The imprecision in the world description is modeled using the theory of fuzzy sets. The method developed for the choice of the rule that prescribes the minimum-time motion control among the redundant set of applicable rules is explained and the usage of fuzzy set operators is justified. Also included in the dissertation are the description of the computer simulation of Pilot within the hierarchy of IMAS control and the simulated experiments that demonstrate the theoretical work.

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

Geo-Referenced Dynamic Pushbroom Stereo Mosaics for 3D and Moving Target Extraction - A New Geometric Approach

DTIC Science & Technology

2009-12-01

facilitating reliable stereo matching, occlusion handling, accurate 3D reconstruction and robust moving target detection . We use the fact that all the...a moving platform, we will have to naturally and effectively handle obvious motion parallax and object occlusions in order to be able to detect ...facilitating reliable stereo matching, occlusion handling, accurate 3D reconstruction and robust moving target detection . Based on the above two

Moving Object Detection on a Vehicle Mounted Back-Up Camera

PubMed Central

Kim, Dong-Sun; Kwon, Jinsan

2015-01-01

In the detection of moving objects from vision sources one usually assumes that the scene has been captured by stationary cameras. In case of backing up a vehicle, however, the camera mounted on the vehicle moves according to the vehicle’s movement, resulting in ego-motions on the background. This results in mixed motion in the scene, and makes it difficult to distinguish between the target objects and background motions. Without further treatments on the mixed motion, traditional fixed-viewpoint object detection methods will lead to many false-positive detection results. In this paper, we suggest a procedure to be used with the traditional moving object detection methods relaxing the stationary cameras restriction, by introducing additional steps before and after the detection. We also decribe the implementation as a FPGA platform along with the algorithm. The target application of this suggestion is use with a road vehicle’s rear-view camera systems. PMID:26712761

Analysis of Human's Motions Based on Local Mean Decomposition in Through-wall Radar Detection

NASA Astrophysics Data System (ADS)

Lu, Qi; Liu, Cai; Zeng, Zhaofa; Li, Jing; Zhang, Xuebing

2016-04-01

Observation of human motions through a wall is an important issue in security applications and search-and rescue. Radar has advantages in looking through walls where other sensors give low performance or cannot be used at all. Ultrawideband (UWB) radar has high spatial resolution as a result of employment of ultranarrow pulses. It has abilities to distinguish the closely positioned targets and provide time-lapse information of targets. Moreover, the UWB radar shows good performance in wall penetration when the inherently short pulses spread their energy over a broad frequency range. Human's motions show periodic features including respiration, swing arms and legs, fluctuations of the torso. Detection of human targets is based on the fact that there is always periodic motion due to breathing or other body movements like walking. The radar can gain the reflections from each human body parts and add the reflections at each time sample. The periodic movements will cause micro-Doppler modulation in the reflected radar signals. Time-frequency analysis methods are consider as the effective tools to analysis and extract micro-Doppler effects caused by the periodic movements in the reflected radar signal, such as short-time Fourier transform (STFT), wavelet transform (WT), and Hilbert-Huang transform (HHT).The local mean decomposition (LMD), initially developed by Smith (2005), is to decomposed amplitude and frequency modulated signals into a small set of product functions (PFs), each of which is the product of an envelope signal and a frequency modulated signal from which a time-vary instantaneous phase and instantaneous frequency can be derived. As bypassing the Hilbert transform, the LMD has no demodulation error coming from window effect and involves no negative frequency without physical sense. Also, the instantaneous attributes obtained by LMD are more stable and precise than those obtained by the empirical mode decomposition (EMD) because LMD uses smoothed local means and local magnitudes that facilitate a more natural decomposition than that using the cubic spline approach of EMD. In this paper, we apply the UWB radar system in through-wall human detections and present a method to characterize human's motions. We start with a walker's motion model and periodic motion features are given the analysis of the experimental data based on the combination of the LMT and fast Fourier Transform (FFT). The characteristics of human's motions including respiration, swing arms and legs, and fluctuations of the torso are extracted. At last, we calculate the actual distance between the human and the wall. This work was supported in part by National Natural Science Foundation of China under Grant 41574109 and 41430322.

Physical activity classification using time-frequency signatures of motion artifacts in multi-channel electrical impedance plethysmographs.

PubMed

Khan, Hassan Aqeel; Gore, Amit; Ashe, Jeff; Chakrabartty, Shantanu

2017-07-01

Physical activities are known to introduce motion artifacts in electrical impedance plethysmographic (EIP) sensors. Existing literature considers motion artifacts as a nuisance and generally discards the artifact containing portion of the sensor output. This paper examines the notion of exploiting motion artifacts for detecting the underlying physical activities which give rise to the artifacts in question. In particular, we investigate whether the artifact pattern associated with a physical activity is unique; and does it vary from one human-subject to another? Data was recorded from 19 adult human-subjects while conducting 5 distinct, artifact inducing, activities. A set of novel features based on the time-frequency signatures of the sensor outputs are then constructed. Our analysis demonstrates that these features enable high accuracy detection of the underlying physical activity. Using an SVM classifier we are able to differentiate between 5 distinct physical activities (coughing, reaching, walking, eating and rolling-on-bed) with an average accuracy of 85.46%. Classification is performed solely using features designed specifically to capture the time-frequency signatures of different physical activities. This enables us to measure both respiratory and motion information using only one type of sensor. This is in contrast to conventional approaches to physical activity monitoring; which rely on additional hardware such as accelerometers to capture activity information.

Thermal noise variance of a receive radiofrequency coil as a respiratory motion sensor.

PubMed

Andreychenko, A; Raaijmakers, A J E; Sbrizzi, A; Crijns, S P M; Lagendijk, J J W; Luijten, P R; van den Berg, C A T

2017-01-01

Development of a passive respiratory motion sensor based on the noise variance of the receive coil array. Respiratory motion alters the body resistance. The noise variance of an RF coil depends on the body resistance and, thus, is also modulated by respiration. For the noise variance monitoring, the noise samples were acquired without and with MR signal excitation on clinical 1.5/3 T MR scanners. The performance of the noise sensor was compared with the respiratory bellow and with the diaphragm displacement visible on MR images. Several breathing patterns were tested. The noise variance demonstrated a periodic, temporal modulation that was synchronized with the respiratory bellow signal. The modulation depth of the noise variance resulting from the respiration varied between the channels of the array and depended on the channel's location with respect to the body. The noise sensor combined with MR acquisition was able to detect the respiratory motion for every k-space read-out line. Within clinical MR systems, the respiratory motion can be detected by the noise in receive array. The noise sensor does not require careful positioning unlike the bellow, any additional hardware, and/or MR acquisition. Magn Reson Med 77:221-228, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Optical Flow Applied to Time-Lapse Image Series to Estimate Glacier Motion in the Southern Patagonia Ice Field

NASA Astrophysics Data System (ADS)

Lannutti, E.; Lenzano, M. G.; Toth, C.; Lenzano, L.; Rivera, A.

2016-06-01

In this work, we assessed the feasibility of using optical flow to obtain the motion estimation of a glacier. In general, former investigations used to detect glacier changes involve solutions that require repeated observations which are many times based on extensive field work. Taking into account glaciers are usually located in geographically complex and hard to access areas, deploying time-lapse imaging sensors, optical flow may provide an efficient solution at good spatial and temporal resolution to describe mass motion. Several studies in computer vision and image processing community have used this method to detect large displacements. Therefore, we carried out a test of the proposed Large Displacement Optical Flow method at the Viedma Glacier, located at South Patagonia Icefield, Argentina. We collected monoscopic terrestrial time-lapse imagery, acquired by a calibrated camera at every 24 hour from April 2014 until April 2015. A filter based on temporal correlation and RGB color discretization between the images was applied to minimize errors related to changes in lighting, shadows, clouds and snow. This selection allowed discarding images that do not follow a sequence of similarity. Our results show a flow field in the direction of the glacier movement with acceleration in the terminus. We analyzed the errors between image pairs, and the matching generally appears to be adequate, although some areas show random gross errors related to the presence of changes in lighting. The proposed technique allowed the determination of glacier motion during one year, providing accurate and reliable motion data for subsequent analysis.

Mechanisms of time-based figure-ground segregation.

PubMed

Kandil, Farid I; Fahle, Manfred

2003-11-01

Figure-ground segregation can rely on purely temporal information, that is, on short temporal delays between positional changes of elements in figure and ground (Kandil, F.I. & Fahle, M. (2001) Eur. J. Neurosci., 13, 2004-2008). Here, we investigate the underlying mechanisms by measuring temporal segregation thresholds for various kinds of motion cues. Segregation can rely on monocular first-order motion (based on luminance modulation) and second-order motion cues (contrast modulation) with a high temporal resolution of approximately 20 ms. The mechanism can also use isoluminant motion with a reduced temporal resolution of 60 ms. Figure-ground segregation can be achieved even at presentation frequencies too high for human subjects to inspect successive frames individually. In contrast, when stimuli are presented dichoptically, i.e. separately to both eyes, subjects are unable to perceive any segregation, irrespective of temporal frequency. We propose that segregation in these displays is detected by a mechanism consisting of at least two stages. On the first level, standard motion or flicker detectors signal local positional changes (flips). On the second level, a segregation mechanism combines the local activities of the low-level detectors with high temporal precision. Our findings suggest that the segregation mechanism can rely on monocular detectors but not on binocular mechanisms. Moreover, the results oppose the idea that segregation in these displays is achieved by motion detectors of a higher order (motion-from-motion), but favour mechanisms sensitive to short temporal delays even without activation of higher-order motion detectors.

Congestion detection of pedestrians using the velocity entropy: A case study of Love Parade 2010 disaster

NASA Astrophysics Data System (ADS)

Huang, Lida; Chen, Tao; Wang, Yan; Yuan, Hongyong

2015-12-01

Gatherings of large human crowds often result in crowd disasters such as the Love Parade Disaster in Duisburg, Germany on July 24, 2010. To avoid these tragedies, video surveillance and early warning are becoming more and more significant. In this paper, the velocity entropy is first defined as the criterion for congestion detection, which represents the motion magnitude distribution and the motion direction distribution simultaneously. Then the detection method is verified by the simulation data based on AnyLogic software. To test the generalization performance of this method, video recordings of a real-world case, the Love Parade disaster, are also used in the experiments. The velocity histograms of the foreground object in the videos are extracted by the Gaussian Mixture Model (GMM) and optical flow computation. With a sequential change-point detection algorithm, the velocity entropy can be applied to detect congestions of the Love Parade festival. It turned out that without recognizing and tracking individual pedestrian, our method can detect abnormal crowd behaviors in real-time.

Vision System Measures Motions of Robot and External Objects

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2008-01-01

A prototype of an advanced robotic vision system both (1) measures its own motion with respect to a stationary background and (2) detects other moving objects and estimates their motions, all by use of visual cues. Like some prior robotic and other optoelectronic vision systems, this system is based partly on concepts of optical flow and visual odometry. Whereas prior optoelectronic visual-odometry systems have been limited to frame rates of no more than 1 Hz, a visual-odometry subsystem that is part of this system operates at a frame rate of 60 to 200 Hz, given optical-flow estimates. The overall system operates at an effective frame rate of 12 Hz. Moreover, unlike prior machine-vision systems for detecting motions of external objects, this system need not remain stationary: it can detect such motions while it is moving (even vibrating). The system includes a stereoscopic pair of cameras mounted on a moving robot. The outputs of the cameras are digitized, then processed to extract positions and velocities. The initial image-data-processing functions of this system are the same as those of some prior systems: Stereoscopy is used to compute three-dimensional (3D) positions for all pixels in the camera images. For each pixel of each image, optical flow between successive image frames is used to compute the two-dimensional (2D) apparent relative translational motion of the point transverse to the line of sight of the camera. The challenge in designing this system was to provide for utilization of the 3D information from stereoscopy in conjunction with the 2D information from optical flow to distinguish between motion of the camera pair and motions of external objects, compute the motion of the camera pair in all six degrees of translational and rotational freedom, and robustly estimate the motions of external objects, all in real time. To meet this challenge, the system is designed to perform the following image-data-processing functions: The visual-odometry subsystem (the subsystem that estimates the motion of the camera pair relative to the stationary background) utilizes the 3D information from stereoscopy and the 2D information from optical flow. It computes the relationship between the 3D and 2D motions and uses a least-mean-squares technique to estimate motion parameters. The least-mean-squares technique is suitable for real-time implementation when the number of external-moving-object pixels is smaller than the number of stationary-background pixels.

Improved Hip-Based Individual Recognition Using Wearable Motion Recording Sensor

NASA Astrophysics Data System (ADS)

Gafurov, Davrondzhon; Bours, Patrick

In todays society the demand for reliable verification of a user identity is increasing. Although biometric technologies based on fingerprint or iris can provide accurate and reliable recognition performance, they are inconvenient for periodic or frequent re-verification. In this paper we propose a hip-based user recognition method which can be suitable for implicit and periodic re-verification of the identity. In our approach we use a wearable accelerometer sensor attached to the hip of the person, and then the measured hip motion signal is analysed for identity verification purposes. The main analyses steps consists of detecting gait cycles in the signal and matching two sets of detected gait cycles. Evaluating the approach on a hip data set consisting of 400 gait sequences (samples) from 100 subjects, we obtained equal error rate (EER) of 7.5% and identification rate at rank 1 was 81.4%. These numbers are improvements by 37.5% and 11.2% respectively of the previous study using the same data set.

Detecting dominant motion patterns in crowds of pedestrians

NASA Astrophysics Data System (ADS)

Saqib, Muhammad; Khan, Sultan Daud; Blumenstein, Michael

2017-02-01

As the population of the world increases, urbanization generates crowding situations which poses challenges to public safety and security. Manual analysis of crowded situations is a tedious job and usually prone to errors. In this paper, we propose a novel technique of crowd analysis, the aim of which is to detect different dominant motion patterns in real-time videos. A motion field is generated by computing the dense optical flow. The motion field is then divided into blocks. For each block, we adopt an Intra-clustering algorithm for detecting different flows within the block. Later on, we employ Inter-clustering for clustering the flow vectors among different blocks. We evaluate the performance of our approach on different real-time videos. The experimental results show that our proposed method is capable of detecting distinct motion patterns in crowded videos. Moreover, our algorithm outperforms state-of-the-art methods.

Monitoring eating habits using a piezoelectric sensor-based necklace.

PubMed

Kalantarian, Haik; Alshurafa, Nabil; Le, Tuan; Sarrafzadeh, Majid

2015-03-01

Maintaining appropriate levels of food intake and developing regularity in eating habits is crucial to weight loss and the preservation of a healthy lifestyle. Moreover, awareness of eating habits is an important step towards portion control and weight loss. In this paper, we introduce a novel food-intake monitoring system based around a wearable wireless-enabled necklace. The proposed necklace includes an embedded piezoelectric sensor, small Arduino-compatible microcontroller, Bluetooth LE transceiver, and Lithium-Polymer battery. Motion in the throat is captured and transmitted to a mobile application for processing and user guidance. Results from data collected from 30 subjects indicate that it is possible to detect solid and liquid foods, with an F-measure of 0.837 and 0.864, respectively, using a naive Bayes classifier. Furthermore, identification of extraneous motions such as head turns and walking are shown to significantly reduce the false positive rate of swallow detection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cyclotron Phase-Coherent Ion Spatial Dispersion in a Non-Quadratic Trapping Potential is Responsible for FT-ICR MS at the Cyclotron Frequency

NASA Astrophysics Data System (ADS)

Nagornov, Konstantin O.; Kozhinov, Anton N.; Tsybin, Yury O.

2018-01-01

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) at the cyclotron frequency instead of the reduced cyclotron frequency has been experimentally demonstrated using narrow aperture detection electrode (NADEL) ICR cells. Here, based on the results of SIMION simulations, we provide the initial mechanistic insights into the cyclotron frequency regime generation in FT-ICR MS. The reason for cyclotron frequency regime is found to be a new type of a collective motion of ions with a certain dispersion in the initial characteristics, such as pre-excitation ion velocities, in a highly non-quadratic trapping potential as realized in NADEL ICR cells. During ion detection, ions of the same m/z move in phase for cyclotron ion motion but out of phase for magnetron (drift) ion motion destroying signals at the fundamental and high order harmonics that comprise reduced cyclotron frequency components. After an initial magnetron motion period, ion clouds distribute into a novel type of structures - ion slabs, elliptical cylinders, or star-like structures. These structures rotate at the Larmor (half-cyclotron) frequency on a plane orthogonal to the magnetic field, inducing signals at the true cyclotron frequency on each of the narrow aperture detection electrodes. To eliminate the reduced cyclotron frequency peak upon dipolar ion detection, a number of slabs or elliptical cylinders organizing a star-like configuration are formed. In a NADEL ICR cell with quadrupolar ion detection, a single slab or an elliptical cylinder is sufficient to minimize the intensity of the reduced cyclotron frequency components, particularly the second harmonic. [Figure not available: see fulltext.

A Dual-Mode Human Computer Interface Combining Speech and Tongue Motion for People with Severe Disabilities

PubMed Central

Huo, Xueliang; Park, Hangue; Kim, Jeonghee; Ghovanloo, Maysam

2015-01-01

We are presenting a new wireless and wearable human computer interface called the dual-mode Tongue Drive System (dTDS), which is designed to allow people with severe disabilities to use computers more effectively with increased speed, flexibility, usability, and independence through their tongue motion and speech. The dTDS detects users’ tongue motion using a magnetic tracer and an array of magnetic sensors embedded in a compact and ergonomic wireless headset. It also captures the users’ voice wirelessly using a small microphone embedded in the same headset. Preliminary evaluation results based on 14 able-bodied subjects and three individuals with high level spinal cord injuries at level C3–C5 indicated that the dTDS headset, combined with a commercially available speech recognition (SR) software, can provide end users with significantly higher performance than either unimodal forms based on the tongue motion or speech alone, particularly in completing tasks that require both pointing and text entry. PMID:23475380

Robust myoelectric signal detection based on stochastic resonance using multiple-surface-electrode array made of carbon nanotube composite paper

NASA Astrophysics Data System (ADS)

Shirata, Kento; Inden, Yuki; Kasai, Seiya; Oya, Takahide; Hagiwara, Yosuke; Kaeriyama, Shunichi; Nakamura, Hideyuki

2016-04-01

We investigated the robust detection of surface electromyogram (EMG) signals based on the stochastic resonance (SR) phenomenon, in which the response to weak signals is optimized by adding noise, combined with multiple surface electrodes. Flexible carbon nanotube composite paper (CNT-cp) was applied to the surface electrode, which showed good performance that is comparable to that of conventional Ag/AgCl electrodes. The SR-based EMG signal system integrating an 8-Schmitt-trigger network and the multiple-CNT-cp-electrode array successfully detected weak EMG signals even when the subject’s body is in the motion, which was difficult to achieve using the conventional technique. The feasibility of the SR-based EMG detection technique was confirmed by demonstrating its applicability to robot hand control.

Dual gated PET/CT imaging of small targets of the heart: method description and testing with a dynamic heart phantom.

PubMed

Kokki, Tommi; Sipilä, Hannu T; Teräs, Mika; Noponen, Tommi; Durand-Schaefer, Nicolas; Klén, Riku; Knuuti, Juhani

2010-01-01

In PET imaging respiratory and cardiac contraction motions interfere the imaging of heart. The aim was to develop and evaluate dual gating method for improving the detection of small targets of the heart. The method utilizes two independent triggers which are sent periodically into list mode data based on respiratory and ECG cycles. An algorithm for generating dual gated segments from list mode data was developed. The test measurements showed that rotational and axial movements of point source can be separated spatially to different segments with well-defined borders. The effect of dual gating on detection of small moving targets was tested with a moving heart phantom. Dual gated images showed 51% elimination (3.6 mm out of 7.0 mm) of contraction motion of hot spot (diameter 3 mm) and 70% elimination (14 mm out of 20 mm) of respiratory motion. Averaged activity value of hot spot increases by 89% when comparing to non-gated images. Patient study of suspected cardiac sarcoidosis shows sharper spatial myocardial uptake profile and improved detection of small myocardial structures such as papillary muscles. The dual gating method improves detection of small moving targets in a phantom and it is feasible in clinical situations.

Extraction of advanced geospatial intelligence (AGI) from commercial synthetic aperture radar imagery

NASA Astrophysics Data System (ADS)

Kanberoglu, Berkay; Frakes, David

2017-04-01

The extraction of objects from advanced geospatial intelligence (AGI) products based on synthetic aperture radar (SAR) imagery is complicated by a number of factors. For example, accurate detection of temporal changes represented in two-color multiview (2CMV) AGI products can be challenging because of speckle noise susceptibility and false positives that result from small orientation differences between objects imaged at different times. These cases of apparent motion can result in 2CMV detection, but they obviously differ greatly in terms of significance. In investigating the state-of-the-art in SAR image processing, we have found that differentiating between these two general cases is a problem that has not been well addressed. We propose a framework of methods to address these problems. For the detection of the temporal changes while reducing the number of false positives, we propose using adaptive object intensity and area thresholding in conjunction with relaxed brightness optical flow algorithms that track the motion of objects across time in small regions of interest. The proposed framework for distinguishing between actual motion and misregistration can lead to more accurate and meaningful change detection and improve object extraction from a SAR AGI product. Results demonstrate the ability of our techniques to reduce false positives up to 60%.

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography

NASA Astrophysics Data System (ADS)

Allec, N.; Abbaszadeh, S.; Scott, C. C.; Lewin, J. M.; Karim, K. S.

2012-12-01

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography.

PubMed

Allec, N; Abbaszadeh, S; Scott, C C; Lewin, J M; Karim, K S

2012-12-21

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

The processing of social stimuli in early infancy: from faces to biological motion perception.

PubMed

Simion, Francesca; Di Giorgio, Elisa; Leo, Irene; Bardi, Lara

2011-01-01

There are several lines of evidence which suggests that, since birth, the human system detects social agents on the basis of at least two properties: the presence of a face and the way they move. This chapter reviews the infant research on the origin of brain specialization for social stimuli and on the role of innate mechanisms and perceptual experience in shaping the development of the social brain. Two lines of convergent evidence on face detection and biological motion detection will be presented to demonstrate the innate predispositions of the human system to detect social stimuli at birth. As for face detection, experiments will be presented to demonstrate that, by virtue of nonspecific attentional biases, a very coarse template of faces become active at birth. As for biological motion detection, studies will be presented to demonstrate that, since birth, the human system is able to detect social stimuli on the basis of their properties such as the presence of a semi-rigid motion named biological motion. Overall, the empirical evidence converges in supporting the notion that the human system begins life broadly tuned to detect social stimuli and that the progressive specialization will narrow the system for social stimuli as a function of experience. Copyright © 2011 Elsevier B.V. All rights reserved.

Temporal analysis of regional wall motion from cine cardiac MRI

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Didier, Dominique; Chretien, Anne; Rosset, Antoine; Magnin, Isabelle E.; Ligier, Yves

1996-04-01

The purpose of this work is to develop and to evaluate an automatic analysis technique for quantitative assessment of cardiac function from cine MRI and to identify regional alterations in synchronicity based on Fourier analysis of ventricular wall motion (WM). A temporal analysis technique of left ventricular wall displacement was developed for quantitative analysis of temporal delays in wall motion and applied to gated cine 'dark blood' cardiac MRI. This imaging technique allows the user to saturate the blood both above and below the imaging slice simultaneously by using a specially designed rf presaturation pulse. The acquisition parameters are: TR equals 25 - 60 msec, TE equals 5 - 7 msec, 0 equals 25 degrees, slice thickness equals 10 mm, 16 to 32 frames/cycle. Automatic edge detection was used to outline the ventricular cavities on all frames of a cardiac cycle. Two different segmentation techniques were applied to all studies and lead to similar results. Further improvement in edge detection accuracy was achieved by temporal interpolation of individual contours on each image of the cardiac cycle. Radial analysis of the ventricular wall motion was then performed along 64 radii drawn from the center of the ventricular cavity. The first harmonic of the Fourier transform of each radial motion curve is calculated. The phase of the fundamental Fourier component is used as an index of synchrony (delay) of regional wall motion. Results are displayed in color-coded maps of regional alterations in the amplitude and synchrony of wall motion. The temporal delays measured from individual segments are evaluated through a histogram of phase distribution, where the width of the main peak is used as an index of overall synchrony of wall motion. The variability of this technique was validated in 10 normal volunteers and was used to identify regions with asynchronous WM in 15 patients with documented CAD. The standard deviation (SD) of phase distribution measured in short axis views was calculated and used to identify regions with asynchronous wall motion in patients with coronary artery disease. Results suggest that this technique is more sensitive than global functional parameters such as ejection fraction for the detection of ventricular dysfunction. Color coded parametric display offers a more convenient way for the identification and localization of regional wall motion asynchrony. Data obtained from endocardial wall motion analysis were not significantly different from wall thickening measurements. The innovative approach of evaluating the temporal behavior of regional wall motion anomalies is expected to provide clinically relevant data about subtle alteration that cannot be detected through simple analysis of the extent (amplitude) of wall motion or myocardial thickening. Temporal analysis of regional WM abnormality from cine MRI offers an innovative and promising means for objective quantitative evaluation of subtle regional abnormalities. Color coded parametric maps allowed a better identification and localization of regional WM asynchrony.

Simultaneous Ionic Current and Potential Detection of Nanoparticles by a Multifunctional Nanopipette.

PubMed

Panday, Namuna; Qian, Gongming; Wang, Xuewen; Chang, Shuai; Pandey, Popular; He, Jin

2016-12-27

Nanopore sensing-based technologies have made significant progress for single molecule and single nanoparticle detection and analysis. In recent years, multimode sensing by multifunctional nanopores shows the potential to greatly improve the sensitivity and selectivity of traditional resistive-pulse sensing methods. In this paper, we showed that two label-free electric sensing modes could work cooperatively to detect the motion of 40 nm diameter spherical gold nanoparticles (GNPs) in solution by a multifunctional nanopipette. The multifunctional nanopipettes containing both nanopore and nanoelectrode (pyrolytic carbon) at the tip were fabricated quickly and cheaply. We demonstrated that the ionic current and local electrical potential changes could be detected simultaneously during the translocation of individual GNPs. We also showed that the nanopore/CNE tip geometry enabled the CNE not only to detect the translocation of single GNP but also to collectively detect several GNPs outside the nanopore entrance. The dynamic accumulation of GNPs near the nanopore entrance resulted in no detectable current changes, but was detected by the potential changes at the CNE. We revealed the motions of GNPs both outside and inside the nanopore, individually and collectively, with the combination of ionic current and potential measurements.

Needle detection in ultrasound using the spectral properties of the displacement field: a feasibility study

NASA Astrophysics Data System (ADS)

Beigi, Parmida; Salcudean, Tim; Rohling, Robert; Lessoway, Victoria A.; Ng, Gary C.

2015-03-01

This paper presents a new needle detection technique for ultrasound guided interventions based on the spectral properties of small displacements arising from hand tremour or intentional motion. In a block-based approach, the displacement map is computed for each block of interest versus a reference frame, using an optical flow technique. To compute the flow parameters, the Lucas-Kanade approach is used in a multiresolution and regularized form. A least-squares fit is used to estimate the flow parameters from the overdetermined system of spatial and temporal gradients. Lateral and axial components of the displacement are obtained for each block of interest at consecutive frames. Magnitude-squared spectral coherency is derived between the median displacements of the reference block and each block of interest, to determine the spectral correlation. In vivo images were obtained from the tissue near the abdominal aorta to capture the extreme intrinsic body motion and insertion images were captured from a tissue-mimicking agar phantom. According to the analysis, both the involuntary and intentional movement of the needle produces coherent displacement with respect to a reference window near the insertion site. Intrinsic body motion also produces coherent displacement with respect to a reference window in the tissue; however, the coherency spectra of intrinsic and needle motion are distinguishable spectrally. Blocks with high spectral coherency at high frequencies are selected, estimating a channel for needle trajectory. The needle trajectory is detected from locally thresholded absolute displacement map within the initial estimate. Experimental results show the RMS localization accuracy of 1:0 mm, 0:7 mm, and 0:5 mm for hand tremour, vibrational and rotational needle movements, respectively.

Small Moving Vehicle Detection in a Satellite Video of an Urban Area

PubMed Central

Yang, Tao; Wang, Xiwen; Yao, Bowei; Li, Jing; Zhang, Yanning; He, Zhannan; Duan, Wencheng

2016-01-01

Vehicle surveillance of a wide area allows us to learn much about the daily activities and traffic information. With the rapid development of remote sensing, satellite video has become an important data source for vehicle detection, which provides a broader field of surveillance. The achieved work generally focuses on aerial video with moderately-sized objects based on feature extraction. However, the moving vehicles in satellite video imagery range from just a few pixels to dozens of pixels and exhibit low contrast with respect to the background, which makes it hard to get available appearance or shape information. In this paper, we look into the problem of moving vehicle detection in satellite imagery. To the best of our knowledge, it is the first time to deal with moving vehicle detection from satellite videos. Our approach consists of two stages: first, through foreground motion segmentation and trajectory accumulation, the scene motion heat map is dynamically built. Following this, a novel saliency based background model which intensifies moving objects is presented to segment the vehicles in the hot regions. Qualitative and quantitative experiments on sequence from a recent Skybox satellite video dataset demonstrates that our approach achieves a high detection rate and low false alarm simultaneously. PMID:27657091

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

Beker, M. G., E-mail: M.Beker@Nikhef.nl; Bertolini, A.; Hennes, E.

There is a strong scientific case for the study of gravitational waves at or below the lower end of current detection bands. To take advantage of this scientific benefit, future generations of ground based gravitational wave detectors will need to expand the limit of their detection bands towards lower frequencies. Seismic motion presents a major challenge at these frequencies and vibration isolation systems will play a crucial role in achieving the desired low-frequency sensitivity. A compact vibration isolation system designed to isolate in-vacuum optical benches for Advanced Virgo will be introduced and measurements on this system are used to presentmore » its performance. All high performance isolation systems employ an active feedback control system to reduce the residual motion of their suspended payloads. The development of novel control schemes is needed to improve the performance beyond what is currently feasible. Here, we present a multi-channel feedback approach that is novel to the field. It utilizes a linear quadratic regulator in combination with a Kalman state observer and is shown to provide effective suppression of residual motion of the suspended payload. The application of state observer based feedback control for vibration isolation will be demonstrated with measurement results from the Advanced Virgo optical bench suspension system.« less

Drogue detection for vision-based autonomous aerial refueling via low rank and sparse decomposition with multiple features

NASA Astrophysics Data System (ADS)

Gao, Shibo; Cheng, Yongmei; Song, Chunhua

2013-09-01

The technology of vision-based probe-and-drogue autonomous aerial refueling is an amazing task in modern aviation for both manned and unmanned aircraft. A key issue is to determine the relative orientation and position of the drogue and the probe accurately for relative navigation system during the approach phase, which requires locating the drogue precisely. Drogue detection is a challenging task due to disorderly motion of drogue caused by both the tanker wake vortex and atmospheric turbulence. In this paper, the problem of drogue detection is considered as a problem of moving object detection. A drogue detection algorithm based on low rank and sparse decomposition with local multiple features is proposed. The global and local information of drogue is introduced into the detection model in a unified way. The experimental results on real autonomous aerial refueling videos show that the proposed drogue detection algorithm is effective.

Performance assessment of HIFU lesion detection by Harmonic Motion Imaging for Focused Ultrasound (HMIFU): A 3D finite-element-based framework with experimental validation

PubMed Central

Hou, Gary Y.; Luo, Jianwen; Marquet, Fabrice; Maleke, Caroline; Vappou, Jonathan; Konofagou, Elisa E.

2014-01-01

Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a novel high-intensity focused ultrasound (HIFU) therapy monitoring method with feasibilities demonstrated in vitro, ex vivo and in vivo. Its principle is based on Amplitude-modulated (AM) - Harmonic Motion Imaging (HMI), an oscillatory radiation force used for imaging the tissue mechanical response during thermal ablation. In this study, a theoretical framework of HMIFU is presented, comprising a customized nonlinear wave propagation model, a finite-element (FE) analysis module, and an image-formation model. The objective of this study is to develop such a framework in order to 1) assess the fundamental performance of HMIFU in detecting HIFU lesions based on the change in tissue apparent elasticity, i.e., the increasing Young's modulus, and the HIFU lesion size with respect to the HIFU exposure time and 2) validate the simulation findings ex vivo. The same HMI and HMIFU parameters as in the experimental studies were used, i.e., 4.5-MHz HIFU frequency and 25 Hz AM frequency. For a lesion-to-background Young's modulus ratio of 3, 6, and 9, the FE and estimated HMI displacement ratios were equal to 1.83, 3.69, 5.39 and 1.65, 3.19, 4.59, respectively. In experiments, the HMI displacement followed a similar increasing trend of 1.19, 1.28, and 1.78 at 10-s, 20-s, and 30-s HIFU exposure, respectively. In addition, moderate agreement in lesion size growth was also found in both simulations (16.2, 73.1 and 334.7 mm2) and experiments (26.2, 94.2 and 206.2 mm2). Therefore, the feasibility of HMIFU for HIFU lesion detection based on the underlying tissue elasticity changes was verified through the developed theoretical framework, i.e., validation of the fundamental performance of the HMIFU system for lesion detection, localization and quantification, was demonstrated both theoretically and ex vivo. PMID:22036637

Quantifying and correcting motion artifacts in MRI

NASA Astrophysics Data System (ADS)

Bones, Philip J.; Maclaren, Julian R.; Millane, Rick P.; Watts, Richard

2006-08-01

Patient motion during magnetic resonance imaging (MRI) can produce significant artifacts in a reconstructed image. Since measurements are made in the spatial frequency domain ('k-space'), rigid-body translational motion results in phase errors in the data samples while rotation causes location errors. A method is presented to detect and correct these errors via a modified sampling strategy, thereby achieving more accurate image reconstruction. The strategy involves sampling vertical and horizontal strips alternately in k-space and employs phase correlation within the overlapping segments to estimate translational motion. An extension, also based on correlation, is employed to estimate rotational motion. Results from simulations with computer-generated phantoms suggest that the algorithm is robust up to realistic noise levels. The work is being extended to physical phantoms. Provided that a reference image is available and the object is of limited extent, it is shown that a measure related to the amount of energy outside the support can be used to objectively compare the severity of motion-induced artifacts.

Quantification of organ motion based on an adaptive image-based scale invariant feature method

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

Paganelli, Chiara; Peroni, Marta; Baroni, Guido

2013-11-15

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application ofmore » contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT, providing a motion description comparable to expert manual identification, as confirmed by DIR.Conclusions: The application of the method to a 4D lung CT patient dataset demonstrated adaptive-SIFT potential as an automatic tool to detect landmarks for DIR regularization and internal motion quantification. Future works should include the optimization of the computational cost and the application of the method to other anatomical sites and image modalities.« less

EEG-based learning system for online motion sickness level estimation in a dynamic vehicle environment.

PubMed

Lin, Chin-Teng; Tsai, Shu-Fang; Ko, Li-Wei

2013-10-01

Motion sickness is a common experience for many people. Several previous researches indicated that motion sickness has a negative effect on driving performance and sometimes leads to serious traffic accidents because of a decline in a person's ability to maintain self-control. This safety issue has motivated us to find a way to prevent vehicle accidents. Our target was to determine a set of valid motion sickness indicators that would predict the occurrence of a person's motion sickness as soon as possible. A successful method for the early detection of motion sickness will help us to construct a cognitive monitoring system. Such a monitoring system can alert people before they become sick and prevent them from being distracted by various motion sickness symptoms while driving or riding in a car. In our past researches, we investigated the physiological changes that occur during the transition of a passenger's cognitive state using electroencephalography (EEG) power spectrum analysis, and we found that the EEG power responses in the left and right motors, parietal, lateral occipital, and occipital midline brain areas were more highly correlated to subjective sickness levels than other brain areas. In this paper, we propose the use of a self-organizing neural fuzzy inference network (SONFIN) to estimate a driver's/passenger's sickness level based on EEG features that have been extracted online from five motion sickness-related brain areas, while either in real or virtual vehicle environments. The results show that our proposed learning system is capable of extracting a set of valid motion sickness indicators that originated from EEG dynamics, and through SONFIN, a neuro-fuzzy prediction model, we successfully translated the set of motion sickness indicators into motion sickness levels. The overall performance of this proposed EEG-based learning system can achieve an average prediction accuracy of ~82%.

Highly stretchable strain sensor based on polyurethane substrate using hydrogen bond-assisted laminated structure for monitoring of tiny human motions

NASA Astrophysics Data System (ADS)

Huang, Ying; Zhao, Yunong; Wang, Yang; Guo, Xiaohui; Zhang, Yangyang; Liu, Ping; Liu, Caixia; Zhang, Yugang

2018-03-01

Strain sensors used as flexible and wearable electronic devices have improved prospects in the fields of artificial skin, robotics, human-machine interfaces, and healthcare. This work introduces a highly stretchable fiber-based strain sensor with a laminated structure made up of a graphene nanoplatelet layer and a carbon black/single-walled carbon nanotube synergetic conductive network layer. An ultrathin, flexible, and elastic two-layer polyurethane (PU) yarn substrate was successively deposited by a novel chemical bonding-based layered dip-coating process. These strain sensors demonstrated high stretchability (˜350%), little hysteresis, and long-term durability (over 2400 cycles) due to the favorable tensile properties of the PU substrate. The linearity of the strain sensor could reach an adjusted R-squared of 0.990 at 100% strain, which is better than most of the recently reported strain sensors. Meanwhile, the strain sensor exhibited good sensibility, rapid response, and a lower detection limit. The lower detection limit benefited from the hydrogen bond-assisted laminated structure and continuous conductive path. Finally, a series of experiments were carried out based on the special features of the PU strain sensor to show its capacity of detecting and monitoring tiny human motions.

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.

Parallel search for conjunctions with stimuli in apparent motion.

PubMed

Casco, C; Ganis, G

1999-01-01

A series of experiments was conducted to determine whether apparent motion tends to follow the similarity rule (i.e. is attribute-specific) and to investigate the underlying mechanism. Stimulus duration thresholds were measured during a two-alternative forced-choice task in which observers detected either the location or the motion direction of target groups defined by the conjunction of size and orientation. Target element positions were randomly chosen within a nominally defined rectangular subregion of the display (target region). The target region was presented either statically (followed by a 250 ms duration mask) or dynamically, displaced by a small distance (18 min of arc) from frame to frame. In the motion display, the position of both target and background elements was changed randomly from frame to frame within the respective areas to abolish spatial correspondence over time. Stimulus duration thresholds were lower in the motion than in the static task, indicating that target detection in the dynamic condition does not rely on the explicit identification of target elements in each static frame. Increasing the distractor-to-target ratio was found to reduce detectability in the static, but not in the motion task. This indicates that the perceptual segregation of the target is effortless and parallel with motion but not with static displays. The pattern of results holds regardless of the task or search paradigm employed. The detectability in the motion condition can be improved by increasing the number of frames and/or by reducing the width of the target area. Furthermore, parallel search in the dynamic condition can be conducted with both short-range and long-range motion stimuli. Finally, apparent motion of conjunctions is insufficient on its own to support location decision and is disrupted by random visual noise. Overall, these findings show that (i) the mechanism underlying apparent motion is attribute-specific; (ii) the motion system mediates temporal integration of feature conjunctions before they are identified by the static system; and (iii) target detectability in these stimuli relies upon a nonattentive, cooperative, directionally selective motion mechanism that responds to high-level attributes (conjunction of size and orientation).

Architectures and algorithms for digital image processing; Proceedings of the Meeting, Cannes, France, December 5, 6, 1985

NASA Technical Reports Server (NTRS)

Duff, Michael J. B. (Editor); Siegel, Howard J. (Editor); Corbett, Francis J. (Editor)

1986-01-01

The conference presents papers on the architectures, algorithms, and applications of image processing. Particular attention is given to a very large scale integration system for image reconstruction from projections, a prebuffer algorithm for instant display of volume data, and an adaptive image sequence filtering scheme based on motion detection. Papers are also presented on a simple, direct practical method of sensing local motion and analyzing local optical flow, image matching techniques, and an automated biological dosimetry system.

Motion Adaptation, its Role in Motion Detection Under Natural Image Conditions and Target Detection

DTIC Science & Technology

2005-06-02

Ibbotson, M.R. & Goodman, L.J. (1990) “Response characteristics of four wide-field motion sensitive descending interneurons in Apis mellifera ,” J. Exp...libraries (in particular a module, PyGame, original designed as an API for computer games applications). Andrew’s contribution to this effort was a

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.

Spatial detection of tv channel logos as outliers from the content

NASA Astrophysics Data System (ADS)

Ekin, Ahmet; Braspenning, Ralph

2006-01-01

This paper proposes a purely image-based TV channel logo detection algorithm that can detect logos independently from their motion and transparency features. The proposed algorithm can robustly detect any type of logos, such as transparent and animated, without requiring any temporal constraints whereas known methods have to wait for the occurrence of large motion in the scene and assume stationary logos. The algorithm models logo pixels as outliers from the actual scene content that is represented by multiple 3-D histograms in the YC BC R space. We use four scene histograms corresponding to each of the four corners because the content characteristics change from one image corner to another. A further novelty of the proposed algorithm is that we define image corners and the areas where we compute the scene histograms by a cinematic technique called Golden Section Rule that is used by professionals. The robustness of the proposed algorithm is demonstrated over a dataset of representative TV content.

Using Temporal Covariance of Motion and Geometric Features via Boosting for Human Fall Detection.

PubMed

Ali, Syed Farooq; Khan, Reamsha; Mahmood, Arif; Hassan, Malik Tahir; Jeon, And Moongu

2018-06-12

Fall induced damages are serious incidences for aged as well as young persons. A real-time automatic and accurate fall detection system can play a vital role in timely medication care which will ultimately help to decrease the damages and complications. In this paper, we propose a fast and more accurate real-time system which can detect people falling in videos captured by surveillance cameras. Novel temporal and spatial variance-based features are proposed which comprise the discriminatory motion, geometric orientation and location of the person. These features are used along with ensemble learning strategy of boosting with J48 and Adaboost classifiers. Experiments have been conducted on publicly available standard datasets including Multiple Cameras Fall ( with 2 classes and 3 classes ) and UR Fall Detection achieving percentage accuracies of 99.2, 99.25 and 99.0, respectively. Comparisons with nine state-of-the-art methods demonstrate the effectiveness of the proposed approach on both datasets.

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.

Statistical approach for the detection of motion/noise artifacts in Photoplethysmogram.

PubMed

Selvaraj, Nandakumar; Mendelson, Yitzhak; Shelley, Kirk H; Silverman, David G; Chon, Ki H

2011-01-01

Motion and noise artifacts (MNA) have been a serious obstacle in realizing the potential of Photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a statistical approach based on the computation of kurtosis and Shannon Entropy (SE) for the accurate detection of MNA in PPG data. The MNA detection algorithm was verified on multi-site PPG data collected from both laboratory and clinical settings. The accuracy of the fusion of kurtosis and SE metrics for the artifact detection was 99.0%, 94.8% and 93.3% in simultaneously recorded ear, finger and forehead PPGs obtained in a clinical setting, respectively. For laboratory PPG data recorded from a finger with contrived artifacts, the accuracy was 88.8%. It was identified that the measurements from the forehead PPG sensor contained the most artifacts followed by finger and ear. The proposed MNA algorithm can be implemented in real-time as the computation time was 0.14 seconds using Matlab®.

Restoration of non-uniform exposure motion blurred image

NASA Astrophysics Data System (ADS)

Luo, Yuanhong; Xu, Tingfa; Wang, Ningming; Liu, Feng

2014-11-01

Restoring motion-blurred image is the key technologies in the opto-electronic detection system. The imaging sensors such as CCD and infrared imaging sensor, which are mounted on the motion platforms, quickly move together with the platforms of high speed. As a result, the images become blur. The image degradation will cause great trouble for the succeeding jobs such as objects detection, target recognition and tracking. So the motion-blurred images must be restoration before detecting motion targets in the subsequent images. On the demand of the real weapon task, in order to deal with targets in the complex background, this dissertation uses the new theories in the field of image processing and computer vision to research the new technology of motion deblurring and motion detection. The principle content is as follows: 1) When the prior knowledge about degradation function is unknown, the uniform motion blurred images are restored. At first, the blur parameters, including the motion blur extent and direction of PSF(point spread function), are estimated individually in domain of logarithmic frequency. The direction of PSF is calculated by extracting the central light line of the spectrum, and the extent is computed by minimizing the correction between the fourier spectrum of the blurred image and a detecting function. Moreover, in order to remove the strip in the deblurred image, windows technique is employed in the algorithm, which makes the deblurred image clear. 2) According to the principle of infrared image non-uniform exposure, a new restoration model for infrared blurred images is developed. The fitting of infrared image non-uniform exposure curve is performed by experiment data. The blurred images are restored by the fitting curve.

Towards automated assistance for operating home medical devices.

PubMed

Gao, Zan; Detyniecki, Marcin; Chen, Ming-Yu; Wu, Wen; Hauptmann, Alexander G; Wactlar, Howard D

2010-01-01

To detect errors when subjects operate a home medical device, we observe them with multiple cameras. We then perform action recognition with a robust approach to recognize action information based on explicitly encoding motion information. This algorithm detects interest points and encodes not only their local appearance but also explicitly models local motion. Our goal is to recognize individual human actions in the operations of a home medical device to see if the patient has correctly performed the required actions in the prescribed sequence. Using a specific infusion pump as a test case, requiring 22 operation steps from 6 action classes, our best classifier selects high likelihood action estimates from 4 available cameras, to obtain an average class recognition rate of 69%.

Seismic Excitation of the Polar Motion, 1977-1993

NASA Technical Reports Server (NTRS)

Chao, Benjamin Fong; Gross, Richard S.; Han, Yan-Ben

1996-01-01

The mass redistribution in the earth as a result of an earthquake faulting changes the earth's inertia tensor, and hence its rotation. Using the complete formulae developed by CHAO and GROSS (1987) based on the normal mode theory, we calculated the earthquake-induced polar motion excitation for the largest 11,015 earthquakes that occurred during 1977.0-1993.6. The seismic excitations in this period are found to be two orders of magnitude below the detection threshold even with today's high precision earth rotation measurements. However, it was calculated that an earthquake of only one tenth the size of the great 1960 Chile event, if happened today, could be comfortably detected in polar motion observations. Furthermore, collectively these seismic excitations have a strong statistical tendency to nudge the pole towards approximately 140deg E, away from the actual observed polar drift direction. This non-random behavior, similarly found in other earthquake-induced changes in earth rotation and low-degree gravitational field by CHAO and GROSS (1987), manifests some geodynamic behavior yet to be explored.

Seismic Excitation of the Polar Motion

NASA Technical Reports Server (NTRS)

Chao, Benjamin Fong; Gross, Richard S.; Han, Yan-Ben

1996-01-01

The mass redistribution in the earth as a result of an earthquake faulting changes the earth's inertia tensor, and hence its rotation. Using the complete formulae developed by Chao and Gross (1987) based on the normal mode theory, we calculated the earthquake-induced polar motion excitation for the largest 11,015 earthquakes that occurred during 1977.0-1993.6. The seismic excitations in this period are found to be two orders of magnitude below the detection threshold even with today's high precision earth rotation measurements. However, it was calculated that an earthquake of only one tenth the size of the great 1960 Chile event, if happened today, could be comfortably detected in polar motion observations. Furthermore, collectively these seismic excitations have a strong statistical tendency to nudge the pole towards approx. 140 deg E, away from the actually observed polar drift direction. This non-random behavior, similarly found in other earthquake-induced changes in earth rotation and low-degree gravitational field by Chao and Gross (1987), manifests some geodynamic behavior yet to be explored.

Seismic excitation of the polar motion, 1977 1993

NASA Astrophysics Data System (ADS)

Chao, Benjamin Fong; Gross, Richard S.; Han, Yan-Ben

1996-09-01

The mass redistribution in the earth as a result of an earthquake faulting changes the earth's inertia tensor, and hence its rotation. Using the complete formulae developed by Chao and Gross (1987) based on the normal mode theory, we calculated the earthquake-induced polar motion excitation for the largest 11,015 earthquakes that occurred during 1977.0 1993.6. The seismic excitations in this period are found to be two orders of magnitude below the detection threshold even with today's high precision earth rotation measurements. However, it was calculated that an earthquake of only one tenth the size of the great 1960 Chile event, if happened today, could be comfortably detected in polar motion observations. Furthermore, collectively these seismic excitations have a strong statistical tendency to nudge the pole towards ˜140°E, away from the actually observed polar drift direction. This non-random behavior, similarly found in other earthquake-induced changes in earth rotation and low-degree gravitational field by Chao and Gross (1987), manifests some geodynamic behavior yet to be explored.

Nonrandom Intrafraction Target Motions and General Strategy for Correction of Spine Stereotactic Body Radiotherapy

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

Ma Lijun, E-mail: lijunma@radonc.ucsf.ed; Sahgal, Arjun; Hossain, Sabbir

2009-11-15

Purpose: To characterize nonrandom intrafraction target motions for spine stereotactic body radiotherapy and to develop a method of correction via image guidance. The dependence of target motions, as well as the effectiveness of the correction strategy for lesions of different locations within the spine, was analyzed. Methods and Materials: Intrafraction target motions for 64 targets in 64 patients treated with a total of 233 fractions were analyzed. Based on the target location, the cases were divided into three groups, i.e., cervical (n = 20 patients), thoracic (n = 20 patients), or lumbar-sacrum (n = 24 patients) lesions. For each case,more » time-lag autocorrelation analysis was performed for each degree of freedom of motion that included both translations (x, y, and z shifts) and rotations (roll, yaw, and pitch). A general correction strategy based on periodic interventions was derived to determine the time interval required between two adjacent interventions, to overcome the patient-specific target motions. Results: Nonrandom target motions were detected for 100% of cases regardless of target locations. Cervical spine targets were found to possess the highest incidence of nonrandom target motion compared with thoracic and lumbar-sacral lesions (p < 0.001). The average time needed to maintain the target motion to within 1 mm of translation or 1 deg. of rotational deviation was 5.5 min, 5.9 min, and 7.1 min for cervical, thoracic, and lumbar-sacrum locations, respectively (at 95% confidence level). Conclusions: A high incidence of nonrandom intrafraction target motions was found for spine stereotactic body radiotherapy treatments. Periodic interventions at approximately every 5 minutes or less were needed to overcome such motions.« less

Flexible and Compressible PEDOT:PSS@Melamine Conductive Sponge Prepared via One-Step Dip Coating as Piezoresistive Pressure Sensor for Human Motion Detection.

PubMed

Ding, Yichun; Yang, Jack; Tolle, Charles R; Zhu, Zhengtao

2018-05-09

Flexible and wearable pressure sensor may offer convenient, timely, and portable solutions to human motion detection, yet it is a challenge to develop cost-effective materials for pressure sensor with high compressibility and sensitivity. Herein, a cost-efficient and scalable approach is reported to prepare a highly flexible and compressible conductive sponge for piezoresistive pressure sensor. The conductive sponge, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)@melamine sponge (MS), is prepared by one-step dip coating the commercial melamine sponge (MS) in an aqueous dispersion of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). Due to the interconnected porous structure of MS, the conductive PEDOT:PSS@MS has a high compressibility and a stable piezoresistive response at the compressive strain up to 80%, as well as good reproducibility over 1000 cycles. Thereafter, versatile pressure sensors fabricated using the conductive PEDOT:PSS@MS sponges are attached to the different parts of human body; the capabilities of these devices to detect a variety of human motions including speaking, finger bending, elbow bending, and walking are evaluated. Furthermore, prototype tactile sensory array based on these pressure sensors is demonstrated.

Crossed beam roof target for motion tracking

NASA Technical Reports Server (NTRS)

Olczak, Eugene (Inventor)

2009-01-01

A system for detecting motion between a first body and a second body includes first and second detector-emitter pairs, disposed on the first body, and configured to transmit and receive first and second optical beams, respectively. At least a first optical rotator is disposed on the second body and configured to receive and reflect at least one of the first and second optical beams. First and second detectors of the detector-emitter pairs are configured to detect the first and second optical beams, respectively. Each of the first and second detectors is configured to detect motion between the first and second bodies in multiple degrees of freedom (DOFs). The first optical rotator includes a V-notch oriented to form an apex of an isosceles triangle with respect to a base of the isosceles triangle formed by the first and second detector-emitter pairs. The V-notch is configured to receive the first optical beam and reflect the first optical beam to both the first and second detectors. The V-notch is also configured to receive the second optical beam and reflect the second optical beam to both the first and second detectors.

Experimental evaluation of a system for human life detection under debris

NASA Astrophysics Data System (ADS)

Joju, Reshma; Konica, Pimplapure Ramya T.; Alex, Zachariah C.

2017-11-01

It is difficult to for the human beings to be found under debris or behind the walls in case of military applications. Due to which several rescue techniques such as robotic systems, optical devices, and acoustic devices were used. But if victim was unconscious then these rescue system failed. We conducted an experimental analysis on whether the microwaves could detect heart beat and breathing signals of human beings trapped under collapsed debris. For our analysis we used RADAR based on by Doppler shift effect. We calculated the minimum speed that the RADAR could detect. We checked the frequency variation by placing the RADAR at a fixed position and placing the object in motion at different distances. We checked the frequency variation by using objects of different materials as debris behind which the motion was made. The graphs of different analysis were plotted.

Omni-Purpose Stretchable Strain Sensor Based on a Highly Dense Nanocracking Structure for Whole-Body Motion Monitoring.

PubMed

Jeon, Hyungkook; Hong, Seong Kyung; Kim, Min Seo; Cho, Seong J; Lim, Geunbae

2017-12-06

Here, we report an omni-purpose stretchable strain sensor (OPSS sensor) based on a nanocracking structure for monitoring whole-body motions including both joint-level and skin-level motions. By controlling and optimizing the nanocracking structure, inspired by the spider sensory system, the OPSS sensor is endowed with both high sensitivity (gauge factor ≈ 30) and a wide working range (strain up to 150%) under great linearity (R 2 = 0.9814) and fast response time (<30 ms). Furthermore, the fabrication process of the OPSS sensor has advantages of being extremely simple, patternable, integrated circuit-compatible, and reliable in terms of reproducibility. Using the OPSS sensor, we detected various human body motions including both moving of joints and subtle deforming of skin such as pulsation. As specific medical applications of the sensor, we also successfully developed a glove-type hand motion detector and a real-time Morse code communication system for patients with general paralysis. Therefore, considering the outstanding sensing performances, great advantages of the fabrication process, and successful results from a variety of practical applications, we believe that the OPSS sensor is a highly suitable strain sensor for whole-body motion monitoring and has potential for a wide range of applications, such as medical robotics and wearable healthcare devices.

Workflow and intervention times of MR-guided focused ultrasound - Predicting the impact of new techniques.

PubMed

Loeve, Arjo J; Al-Issawi, Jumana; Fernandez-Gutiérrez, Fabiola; Langø, Thomas; Strehlow, Jan; Haase, Sabrina; Matzko, Matthias; Napoli, Alessandro; Melzer, Andreas; Dankelman, Jenny

2016-04-01

Magnetic resonance guided focused ultrasound surgery (MRgFUS) has become an attractive, non-invasive treatment for benign and malignant tumours, and offers specific benefits for poorly accessible locations in the liver. However, the presence of the ribcage and the occurrence of liver motion due to respiration limit the applicability MRgFUS. Several techniques are being developed to address these issues or to decrease treatment times in other ways. However, the potential benefit of such improvements has not been quantified. In this research, the detailed workflow of current MRgFUS procedures was determined qualitatively and quantitatively by using observation studies on uterine MRgFUS interventions, and the bottlenecks in MRgFUS were identified. A validated simulation model based on discrete events simulation was developed to quantitatively predict the effect of new technological developments on the intervention duration of MRgFUS on the liver. During the observation studies, the duration and occurrence frequencies of all actions and decisions in the MRgFUS workflow were registered, as were the occurrence frequencies of motion detections and intervention halts. The observation results show that current MRgFUS uterine interventions take on average 213min. Organ motion was detected on average 2.9 times per intervention, of which on average 1.0 actually caused a need for rework. Nevertheless, these motion occurrences and the actions required to continue after their detection consumed on average 11% and up to 29% of the total intervention duration. The simulation results suggest that, depending on the motion occurrence frequency, the addition of new technology to automate currently manual MRgFUS tasks and motion compensation could potentially reduce the intervention durations by 98.4% (from 256h 5min to 4h 4min) in the case of 90% motion occurrence, and with 24% (from 5h 19min to 4h 2min) in the case of no motion. In conclusion, new tools were developed to predict how intervention durations will be affected by future workflow changes and by the introduction of new technology. Copyright © 2016 Elsevier Inc. All rights reserved.

Magneto-motive detection of tissue-based macrophages by differential phase optical coherence tomography.

PubMed

Oh, Junghwan; Feldman, Marc D; Kim, Jihoon; Kang, Hyun Wook; Sanghi, Pramod; Milner, Thomas E

2007-03-01

A novel method to detect tissue-based macrophages using a combination of superparamagnetic iron oxide (SPIO) nanoparticles and differential phase optical coherence tomography (DP-OCT) with an external oscillating magnetic field is reported. Magnetic force acting on iron-laden tissue-based macrophages was varied by applying a sinusoidal current to a solenoid containing a conical iron core that substantially focused and increased magnetic flux density. Nanoparticle motion was detected with DP-OCT, which can detect tissue movement with nanometer resolution. Frequency response of iron-laden tissue movement was twice the modulation frequency since the magnetic force is proportional to the product of magnetic flux density and gradient. Results of our experiments indicate that DP-OCT can be used to identify tissue-based macrophage when excited by an external focused oscillating magnetic field. (c) 2007 Wiley-Liss, Inc

Biological Motion Preference in Humans at Birth: Role of Dynamic and Configural Properties

ERIC Educational Resources Information Center

Bardi, Lara; Regolin, Lucia; Simion, Francesca

2011-01-01

The present study addresses the hypothesis that detection of biological motion is an intrinsic capacity of the visual system guided by a non-species-specific predisposition for the pattern of vertebrate movement and investigates the role of global vs. local information in biological motion detection. Two-day-old babies exposed to a biological…

Validation of cardiac accelerometer sensor measurements.

PubMed

Remme, Espen W; Hoff, Lars; Halvorsen, Per Steinar; Naerum, Edvard; Skulstad, Helge; Fleischer, Lars A; Elle, Ole Jakob; Fosse, Erik

2009-12-01

In this study we have investigated the accuracy of an accelerometer sensor designed for the measurement of cardiac motion and automatic detection of motion abnormalities caused by myocardial ischaemia. The accelerometer, attached to the left ventricular wall, changed its orientation relative to the direction of gravity during the cardiac cycle. This caused a varying gravity component in the measured acceleration signal that introduced an error in the calculation of myocardial motion. Circumferential displacement, velocity and rotation of the left ventricular apical region were calculated from the measured acceleration signal. We developed a mathematical method to separate translational and gravitational acceleration components based on a priori assumptions of myocardial motion. The accuracy of the measured motion was investigated by comparison with known motion of a robot arm programmed to move like the heart wall. The accuracy was also investigated in an animal study. The sensor measurements were compared with simultaneously recorded motion from a robot arm attached next to the sensor on the heart and with measured motion by echocardiography and a video camera. The developed compensation method for the varying gravity component improved the accuracy of the calculated velocity and displacement traces, giving very good agreement with the reference methods.

Motion transparency: making models of motion perception transparent.

PubMed

Snowden; Verstraten

1999-10-01

In daily life our visual system is bombarded with motion information. We see cars driving by, flocks of birds flying in the sky, clouds passing behind trees that are dancing in the wind. Vision science has a good understanding of the first stage of visual motion processing, that is, the mechanism underlying the detection of local motions. Currently, research is focused on the processes that occur beyond the first stage. At this level, local motions have to be integrated to form objects, define the boundaries between them, construct surfaces and so on. An interesting, if complicated case is known as motion transparency: the situation in which two overlapping surfaces move transparently over each other. In that case two motions have to be assigned to the same retinal location. Several researchers have tried to solve this problem from a computational point of view, using physiological and psychophysical results as a guideline. We will discuss two models: one uses the traditional idea known as 'filter selection' and the other a relatively new approach based on Bayesian inference. Predictions from these models are compared with our own visual behaviour and that of the neural substrates that are presumed to underlie these perceptions.

Apnea Detection Method for Cheyne-Stokes Respiration Analysis on Newborn

NASA Astrophysics Data System (ADS)

Niimi, Taiga; Itoh, Yushi; Natori, Michiya; Aoki, Yoshimitsu

2013-04-01

Cheyne-Stokes respiration is especially prevalent in preterm newborns, but its severity may not be recognized. It is characterized by apnea and cyclical weakening and strengthening of the breathing. We developed a method for detecting apnea and this abnormal respiration and for estimating its malignancy. Apnea was detected based on a "difference" feature (calculated from wavelet coefficients) and a modified maximum displacement feature (related to the respiratory waveform shape). The waveform is calculated from vertical motion of the thoracic and abdominal region during respiration using a vision sensor. Our proposed detection method effectively detects apnea (sensitivity 88.4%, specificity 99.7%).

Automatic techniques for 3D reconstruction of critical workplace body postures from range imaging data

NASA Astrophysics Data System (ADS)

Westfeld, Patrick; Maas, Hans-Gerd; Bringmann, Oliver; Gröllich, Daniel; Schmauder, Martin

2013-11-01

The paper shows techniques for the determination of structured motion parameters from range camera image sequences. The core contribution of the work presented here is the development of an integrated least squares 3D tracking approach based on amplitude and range image sequences to calculate dense 3D motion vector fields. Geometric primitives of a human body model are fitted to time series of range camera point clouds using these vector fields as additional information. Body poses and motion information for individual body parts are derived from the model fit. On the basis of these pose and motion parameters, critical body postures are detected. The primary aim of the study is to automate ergonomic studies for risk assessments regulated by law, identifying harmful movements and awkward body postures in a workplace.

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

Pilat-Lohinger, E.; Bazsó, A.; Funk, B.

Gravitational perturbations in multi-planet systems caused by an accompanying star are the subject of this investigation. Our dynamical model is based on the binary star HD 41004 AB where a giant planet orbits HD 41004 A. We modify the orbital parameters of this system and analyze the motion of a hypothetical test planet surrounding HD 41004 A on an interior orbit to the detected giant planet. Our numerical computations indicate perturbations due to mean motion and secular resonances (SRs). The locations of these resonances are usually connected to high eccentricity and highly inclined motion depending strongly on the binary-planet architecture.more » As the positions of mean motion resonances can easily be determined, the main purpose of this study is to present a new semi-analytical method to determine the location of an SR without huge computational effort.« less

Motional studies of one and two laser-cooled trapped ions for electric-field sensing applications

NASA Astrophysics Data System (ADS)

Domínguez, F.; Gutiérrez, M. J.; Arrazola, I.; Berrocal, J.; Cornejo, J. M.; Del Pozo, J. J.; Rica, R. A.; Schmidt, S.; Solano, E.; Rodríguez, D.

2018-03-01

We have studied the dynamics of one and two laser-cooled trapped ?Ca? ions by applying electric fields of different nature along the axial direction of the trap, namely, driving the motion with a harmonic dipolar field, or with white noise. These two types of driving induce distinct motional states of the axial modes: a coherent oscillation with the dipolar field, or an enhanced Brownian motion due to an additional contribution to the heating rate from the electric noise. In both scenarios, the sensitivity of an isolated ion and a laser-cooled two-ion crystal has been evaluated and compared. The analysis and understanding of this dynamics is important towards the implementation of a novel Penning trap mass-spectroscopy technique based on optical detection, aiming at improving precision and sensitivity.

Extrapolation-Based References Improve Motion and Eddy-Current Correction of High B-Value DWI Data: Application in Parkinson's Disease Dementia.

PubMed

Nilsson, Markus; Szczepankiewicz, Filip; van Westen, Danielle; Hansson, Oskar

2015-01-01

Conventional motion and eddy-current correction, where each diffusion-weighted volume is registered to a non diffusion-weighted reference, suffers from poor accuracy for high b-value data. An alternative approach is to extrapolate reference volumes from low b-value data. We aim to compare the performance of conventional and extrapolation-based correction of diffusional kurtosis imaging (DKI) data, and to demonstrate the impact of the correction approach on group comparison studies. DKI was performed in patients with Parkinson's disease dementia (PDD), and healthy age-matched controls, using b-values of up to 2750 s/mm2. The accuracy of conventional and extrapolation-based correction methods was investigated. Parameters from DTI and DKI were compared between patients and controls in the cingulum and the anterior thalamic projection tract. Conventional correction resulted in systematic registration errors for high b-value data. The extrapolation-based methods did not exhibit such errors, yielding more accurate tractography and up to 50% lower standard deviation in DKI metrics. Statistically significant differences were found between patients and controls when using the extrapolation-based motion correction that were not detected when using the conventional method. We recommend that conventional motion and eddy-current correction should be abandoned for high b-value data in favour of more accurate methods using extrapolation-based references.

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.

Highly stretchable and wearable graphene strain sensors with controllable sensitivity for human motion monitoring.

PubMed

Park, Jung Jin; Hyun, Woo Jin; Mun, Sung Cik; Park, Yong Tae; Park, O Ok

2015-03-25

Because of their outstanding electrical and mechanical properties, graphene strain sensors have attracted extensive attention for electronic applications in virtual reality, robotics, medical diagnostics, and healthcare. Although several strain sensors based on graphene have been reported, the stretchability and sensitivity of these sensors remain limited, and also there is a pressing need to develop a practical fabrication process. This paper reports the fabrication and characterization of new types of graphene strain sensors based on stretchable yarns. Highly stretchable, sensitive, and wearable sensors are realized by a layer-by-layer assembly method that is simple, low-cost, scalable, and solution-processable. Because of the yarn structures, these sensors exhibit high stretchability (up to 150%) and versatility, and can detect both large- and small-scale human motions. For this study, wearable electronics are fabricated with implanted sensors that can monitor diverse human motions, including joint movement, phonation, swallowing, and breathing.

Fiber-based generator for wearable electronics and mobile medication.

PubMed

Zhong, Junwen; Zhang, Yan; Zhong, Qize; Hu, Qiyi; Hu, Bin; Wang, Zhong Lin; Zhou, Jun

2014-06-24

Smart garments for monitoring physiological and biomechanical signals of the human body are key sensors for personalized healthcare. However, they typically require bulky battery packs or have to be plugged into an electric plug in order to operate. Thus, a smart shirt that can extract energy from human body motions to run body-worn healthcare sensors is particularly desirable. Here, we demonstrated a metal-free fiber-based generator (FBG) via a simple, cost-effective method by using commodity cotton threads, a polytetrafluoroethylene aqueous suspension, and carbon nanotubes as source materials. The FBGs can convert biomechanical motions/vibration energy into electricity utilizing the electrostatic effect with an average output power density of ∼0.1 μW/cm(2) and have been identified as an effective building element for a power shirt to trigger a wireless body temperature sensor system. Furthermore, the FBG was demonstrated as a self-powered active sensor to quantitatively detect human motion.

Contrast based band selection for optimized weathered oil detection in hyperspectral images

NASA Astrophysics Data System (ADS)

Levaux, Florian; Bostater, Charles R., Jr.; Neyt, Xavier

2012-09-01

Hyperspectral imagery offers unique benefits for detection of land and water features due to the information contained in reflectance signatures such as the bi-directional reflectance distribution function or BRDF. The reflectance signature directly shows the relative absorption and backscattering features of targets. These features can be very useful in shoreline monitoring or surveillance applications, for example to detect weathered oil. In real-time detection applications, processing of hyperspectral data can be an important tool and Optimal band selection is thus important in real time applications in order to select the essential bands using the absorption and backscatter information. In the present paper, band selection is based upon the optimization of target detection using contrast algorithms. The common definition of the contrast (using only one band out of all possible combinations available within a hyperspectral image) is generalized in order to consider all the possible combinations of wavelength dependent contrasts using hyperspectral images. The inflection (defined here as an approximation of the second derivative) is also used in order to enhance the variations in the reflectance spectra as well as in the contrast spectrua in order to assist in optimal band selection. The results of the selection in term of target detection (false alarms and missed detection) are also compared with a previous method to perform feature detection, namely the matched filter. In this paper, imagery is acquired using a pushbroom hyperspectral sensor mounted at the bow of a small vessel. The sensor is mechanically rotated using an optical rotation stage. This opto-mechanical scanning system produces hyperspectral images with pixel sizes on the order of mm to cm scales, depending upon the distance between the sensor and the shoreline being monitored. The motion of the platform during the acquisition induces distortions in the collected HSI imagery. It is therefore necessary to apply a motion correction to the imagery. In this paper, imagery is corrected for the pitching motion of a vessel, which causes most of the deformation when the vessel is anchored at 2 points (bow and stern) during the acquisition of the hyperspectral imagry.

Canal–Otolith Interactions and Detection Thresholds of Linear and Angular Components During Curved-Path Self-Motion

PubMed Central

MacNeilage, Paul R.; Turner, Amanda H.

2010-01-01

Gravitational signals arising from the otolith organs and vertical plane rotational signals arising from the semicircular canals interact extensively for accurate estimation of tilt and inertial acceleration. Here we used a classical signal detection paradigm to examine perceptual interactions between otolith and horizontal semicircular canal signals during simultaneous rotation and translation on a curved path. In a rotation detection experiment, blindfolded subjects were asked to detect the presence of angular motion in blocks where half of the trials were pure nasooccipital translation and half were simultaneous translation and yaw rotation (curved-path motion). In separate, translation detection experiments, subjects were also asked to detect either the presence or the absence of nasooccipital linear motion in blocks, in which half of the trials were pure yaw rotation and half were curved path. Rotation thresholds increased slightly, but not significantly, with concurrent linear velocity magnitude. Yaw rotation detection threshold, averaged across all conditions, was 1.45 ± 0.81°/s (3.49 ± 1.95°/s2). Translation thresholds, on the other hand, increased significantly with increasing magnitude of concurrent angular velocity. Absolute nasooccipital translation detection threshold, averaged across all conditions, was 2.93 ± 2.10 cm/s (7.07 ± 5.05 cm/s2). These findings suggest that conscious perception might not have independent access to separate estimates of linear and angular movement parameters during curved-path motion. Estimates of linear (and perhaps angular) components might instead rely on integrated information from canals and otoliths. Such interaction may underlie previously reported perceptual errors during curved-path motion and may originate from mechanisms that are specialized for tilt-translation processing during vertical plane rotation. PMID:20554843

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.

Detecting chaos in particle accelerators through the frequency map analysis method.

PubMed

Papaphilippou, Yannis

2014-06-01

The motion of beams in particle accelerators is dominated by a plethora of non-linear effects, which can enhance chaotic motion and limit their performance. The application of advanced non-linear dynamics methods for detecting and correcting these effects and thereby increasing the region of beam stability plays an essential role during the accelerator design phase but also their operation. After describing the nature of non-linear effects and their impact on performance parameters of different particle accelerator categories, the theory of non-linear particle motion is outlined. The recent developments on the methods employed for the analysis of chaotic beam motion are detailed. In particular, the ability of the frequency map analysis method to detect chaotic motion and guide the correction of non-linear effects is demonstrated in particle tracking simulations but also experimental data.

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.

Detecting Motion from a Moving Platform; Phase 3: Unification of Control and Sensing for More Advanced Situational Awareness

DTIC Science & Technology

2011-11-01

RX-TY-TR-2011-0096-01) develops a novel computer vision sensor based upon the biological vision system of the common housefly , Musca domestica...01 summarizes the development of a novel computer vision sensor based upon the biological vision system of the common housefly , Musca domestica

Analysis of Nematode Motion Using an Improved Light-Scatter Based System

PubMed Central

Nutting, Chuck S.; Eversole, Rob R.; Blair, Kevin; Specht, Sabine; Nutman, Thomas B.; Klion, Amy D.; Wanji, Samuel; Boussinesq, Michel; Mackenzie, Charles D.

2015-01-01

Background The detailed assessment of nematode activity and viability still remains a relatively undeveloped area of biological and medical research. Computer-based approaches to assessing the motility of larger nematode stages have been developed, yet these lack the capability to detect and analyze the more subtle and important characteristics of the motion of nematodes. There is currently a need to improved methods of assessing the viability and health of parasitic worms. Methods We describe here a system that converts the motion of nematodes through a light-scattering system into an electrical waveform, and allows for reproducible, and wholly non-subjective, assessment of alterations in motion, as well as estimation of the number of nematode worms of different forms and sizes. Here we have used Brugia sp. microfilariae (L1), infective larvae (L3) and adults, together with the free-living nematode Caenorhabditis elegans. Results The motion of worms in a small (200ul) volume can be detected, with the presence of immotile worms not interfering with the readings at practical levels (up to at least 500 L1 /200ul). Alterations in the frequency of parasite movement following the application of the anti-parasitic drugs, (chloroquine and imatinib); the anti-filarial effect of the latter agent is the first demonstrated here for the first time. This system can also be used to estimate the number of parasites, and shortens the time required to estimate parasites numbers, and eliminates the need for microscopes and trained technicians to provide an estimate of microfilarial sample sizes up to 1000 parasites/ml. Alterations in the form of motion of the worms can also be depicted. Conclusions This new instrument, named a "WiggleTron", offers exciting opportunities to further study nematode biology and to aid drug discovery, as well as contributing to a rapid estimate of parasite numbers in various biological samples. PMID:25695776

Analysis of nematode motion using an improved light-scatter based system.

PubMed

Nutting, Chuck S; Eversole, Rob R; Blair, Kevin; Specht, Sabine; Nutman, Thomas B; Klion, Amy D; Wanji, Samuel; Boussinesq, Michel; Mackenzie, Charles D

2015-02-01

The detailed assessment of nematode activity and viability still remains a relatively undeveloped area of biological and medical research. Computer-based approaches to assessing the motility of larger nematode stages have been developed, yet these lack the capability to detect and analyze the more subtle and important characteristics of the motion of nematodes. There is currently a need to improved methods of assessing the viability and health of parasitic worms. We describe here a system that converts the motion of nematodes through a light-scattering system into an electrical waveform, and allows for reproducible, and wholly non-subjective, assessment of alterations in motion, as well as estimation of the number of nematode worms of different forms and sizes. Here we have used Brugia sp. microfilariae (L1), infective larvae (L3) and adults, together with the free-living nematode Caenorhabditis elegans. The motion of worms in a small (200 ul) volume can be detected, with the presence of immotile worms not interfering with the readings at practical levels (up to at least 500 L1 /200 ul). Alterations in the frequency of parasite movement following the application of the anti-parasitic drugs, (chloroquine and imatinib); the anti-filarial effect of the latter agent is the first demonstrated here for the first time. This system can also be used to estimate the number of parasites, and shortens the time required to estimate parasites numbers, and eliminates the need for microscopes and trained technicians to provide an estimate of microfilarial sample sizes up to 1000 parasites/ml. Alterations in the form of motion of the worms can also be depicted. This new instrument, named a "WiggleTron", offers exciting opportunities to further study nematode biology and to aid drug discovery, as well as contributing to a rapid estimate of parasite numbers in various biological samples.

A novel approach to simulate chest wall micro-motion for bio-radar life detection purpose

NASA Astrophysics Data System (ADS)

An, Qiang; Li, Zhao; Liang, Fulai; Chen, Fuming; Wang, Jianqi

2016-10-01

Volunteers are often recruited to serve as the detection targets during the research process of bio-radar life detection technology, in which the experiment results are highly susceptible to the physical status of different individuals (shape, posture, etc.). In order to objectively evaluate the radar system performance and life detection algorithms, a standard detection target is urgently needed. The paper first proposed a parameter quantitatively controllable system to simulate the chest wall micro-motion caused mainly by breathing and heart beating. Then, the paper continued to analyze the material and size selection of the scattering body mounted on the simulation system from the perspective of back scattering energy. The computational electromagnetic method was employed to determine the exact scattering body. Finally, on-site experiments were carried out to verify the reliability of the simulation platform utilizing an IR UWB bioradar. Experimental result shows that the proposed system can simulate a real human target from three aspects: respiration frequency, amplitude and body surface scattering energy. Thus, it can be utilized as a substitute for a human target in radar based non-contact life detection research in various scenarios.

Microarcsecond Astrometry As A Probe Of Circumstellar Structure

NASA Astrophysics Data System (ADS)

Velusamy, T.; Turyshev, S. G.

1999-12-01

The Space Interferometry Mission (SIM) is a space-based long-baseline optical interferometer for precision astrometry. This mission will open up many areas of astrophysics, via astrometry with unprecedented accuracy. Wide-angle measurements, which include annual parallax, will reach a design accuracy of 4 μ as. Over a narrow field of view the relative accuracy is better, and SIM is expected to achieve an accuracy of 1 μ as. In this mode, SIM will search for planetary companions to nearby stars, by detecting the astrometric `wobble' relative to a nearby (<= 1o) reference star. The expected proper motion accuracy is 2 μ as yr-1, corresponding to a transverse velocity of 10 m s-1 at a distance of 1 kpc. Such an accuracy of the future SIM instrument provides a very useful astrometric tool for probing the circumstellar structure. The motion of the photo center as detected by SIM is not necessarily that of the center of mass. It is expected that unmodelled dynamics of the stellar systems may be a potential source for systematic astrometric errors. In this paper we discuss the possibility of using SIM's precision astrometry not only to detect Keplerian signatures due to the planetary motion around nearby stars, but also to characterize the structure of the planetary and proto-planetary orbits, accretions disks, debris disks, circumstellar material, jets and other types of the mass transfer mechanisms. We evaluate possible astrometric signatures due to different types of dynamical processes (both gravitational, non-gravitational) and characterize the magnitude of the corresponding astrometric signal. We attempt to address the most natural scenario of non-Keplerian motion, caused by an extended structure and complex dynamics of the stellar systems that may produce a detectable wobble in the motion of the optical center of a target star. We examine the use of μ as astrometry, as complementary to high resolution imaging, to detect some of the structures present around stars. This work was performed by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Perception of Social Interactions for Spatially Scrambled Biological Motion

PubMed Central

Thurman, Steven M.; Lu, Hongjing

2014-01-01

It is vitally important for humans to detect living creatures in the environment and to analyze their behavior to facilitate action understanding and high-level social inference. The current study employed naturalistic point-light animations to examine the ability of human observers to spontaneously identify and discriminate socially interactive behaviors between two human agents. Specifically, we investigated the importance of global body form, intrinsic joint movements, extrinsic whole-body movements, and critically, the congruency between intrinsic and extrinsic motions. Motion congruency is hypothesized to be particularly important because of the constraint it imposes on naturalistic action due to the inherent causal relationship between limb movements and whole body motion. Using a free response paradigm in Experiment 1, we discovered that many naïve observers (55%) spontaneously attributed animate and/or social traits to spatially-scrambled displays of interpersonal interaction. Total stimulus motion energy was strongly correlated with the likelihood that an observer would attribute animate/social traits, as opposed to physical/mechanical traits, to the scrambled dot stimuli. In Experiment 2, we found that participants could identify interactions between spatially-scrambled displays of human dance as long as congruency was maintained between intrinsic/extrinsic movements. Violating the motion congruency constraint resulted in chance discrimination performance for the spatially-scrambled displays. Finally, Experiment 3 showed that scrambled point-light dancing animations violating this constraint were also rated as significantly less interactive than animations with congruent intrinsic/extrinsic motion. These results demonstrate the importance of intrinsic/extrinsic motion congruency for biological motion analysis, and support a theoretical framework in which early visual filters help to detect animate agents in the environment based on several fundamental constraints. Only after satisfying these basic constraints could stimuli be evaluated for high-level social content. In this way, we posit that perceptual animacy may serve as a gateway to higher-level processes that support action understanding and social inference. PMID:25406075

Auditory spatial processing in Alzheimer’s disease

PubMed Central

Golden, Hannah L.; Nicholas, Jennifer M.; Yong, Keir X. X.; Downey, Laura E.; Schott, Jonathan M.; Mummery, Catherine J.; Crutch, Sebastian J.

2015-01-01

The location and motion of sounds in space are important cues for encoding the auditory world. Spatial processing is a core component of auditory scene analysis, a cognitively demanding function that is vulnerable in Alzheimer’s disease. Here we designed a novel neuropsychological battery based on a virtual space paradigm to assess auditory spatial processing in patient cohorts with clinically typical Alzheimer’s disease (n = 20) and its major variant syndrome, posterior cortical atrophy (n = 12) in relation to healthy older controls (n = 26). We assessed three dimensions of auditory spatial function: externalized versus non-externalized sound discrimination, moving versus stationary sound discrimination and stationary auditory spatial position discrimination, together with non-spatial auditory and visual spatial control tasks. Neuroanatomical correlates of auditory spatial processing were assessed using voxel-based morphometry. Relative to healthy older controls, both patient groups exhibited impairments in detection of auditory motion, and stationary sound position discrimination. The posterior cortical atrophy group showed greater impairment for auditory motion processing and the processing of a non-spatial control complex auditory property (timbre) than the typical Alzheimer’s disease group. Voxel-based morphometry in the patient cohort revealed grey matter correlates of auditory motion detection and spatial position discrimination in right inferior parietal cortex and precuneus, respectively. These findings delineate auditory spatial processing deficits in typical and posterior Alzheimer’s disease phenotypes that are related to posterior cortical regions involved in both syndromic variants and modulated by the syndromic profile of brain degeneration. Auditory spatial deficits contribute to impaired spatial awareness in Alzheimer’s disease and may constitute a novel perceptual model for probing brain network disintegration across the Alzheimer’s disease syndromic spectrum. PMID:25468732

Measured Visual Motion Sensitivity at Fixed Contrast in the Periphery and Far Periphery

DTIC Science & Technology

2017-08-01

group Soldier performance. Soldier performance depends on visual detection of enemy personnel and materiel. Vision modeling in IWARS is neither...a highly time-critical and order- dependent activity, these unrealistic characterizations of target detection time and order severely limit the...recognize that MVTs should depend on target contrast, so we selected a target design different from that used in the Monaco et al. (2007) study. Based

A Comparative Survey of Methods for Remote Heart Rate Detection From Frontal Face Videos

PubMed Central

Wang, Chen; Pun, Thierry; Chanel, Guillaume

2018-01-01

Remotely measuring physiological activity can provide substantial benefits for both the medical and the affective computing applications. Recent research has proposed different methodologies for the unobtrusive detection of heart rate (HR) using human face recordings. These methods are based on subtle color changes or motions of the face due to cardiovascular activities, which are invisible to human eyes but can be captured by digital cameras. Several approaches have been proposed such as signal processing and machine learning. However, these methods are compared with different datasets, and there is consequently no consensus on method performance. In this article, we describe and evaluate several methods defined in literature, from 2008 until present day, for the remote detection of HR using human face recordings. The general HR processing pipeline is divided into three stages: face video processing, face blood volume pulse (BVP) signal extraction, and HR computation. Approaches presented in the paper are classified and grouped according to each stage. At each stage, algorithms are analyzed and compared based on their performance using the public database MAHNOB-HCI. Results found in this article are limited on MAHNOB-HCI dataset. Results show that extracted face skin area contains more BVP information. Blind source separation and peak detection methods are more robust with head motions for estimating HR. PMID:29765940

Constructing Carbon Fiber Motion-Detection Loops for Simultaneous EEG–fMRI

PubMed Central

Abbott, David F.; Masterton, Richard A. J.; Archer, John S.; Fleming, Steven W.; Warren, Aaron E. L.; Jackson, Graeme D.

2015-01-01

One of the most significant impediments to high-quality EEG recorded in an MRI scanner is subject motion. Availability of motion artifact sensors can substantially improve the quality of the recorded EEG. In the study of epilepsy, it can also dramatically increase the confidence that one has in discriminating true epileptiform activity from artifact. This is due both to the reduction in artifact and the ability to visually inspect the motion sensor signals when reading the EEG, revealing whether or not head motion is present. We have previously described the use of carbon fiber loops for detecting and correcting artifact in EEG acquired simultaneously with MRI. The loops, attached to the subject’s head, are electrically insulated from the scalp. They provide a simple and direct measure of specific artifact that is contaminating the EEG, including both subject motion and residual artifact arising from magnetic field gradients applied during MRI. Our previous implementation was used together with a custom-built EEG–fMRI system that differs substantially from current commercially available EEG–fMRI systems. The present technical note extends this work, describing in more detail how to construct the carbon fiber motion-detection loops, and how to interface them with a commercially available simultaneous EEG–fMRI system. We hope that the information provided may help those wishing to utilize a motion-detection/correction solution to improve the quality of EEG recorded within an MRI scanner. PMID:25601852

Measuring Relative Motions Across a Fault Using Seafloor Transponders Installed at Close Range to each Other Based on Differential GPS/Acoustic Technique

NASA Astrophysics Data System (ADS)

Kido, M.; Ashi, J.; Tsuji, T.; Tomita, F.

2016-12-01

Seafloor geodesy based on acoustic ranging technique is getting popular means to reveal crustal deformation beneath the ocean. GPS/acoustic technique can be applied to monitoring regional deformation or absolute position, while direct-path acoustic ranging can be applied to detecting localized strain or relative motion in a short distance ( 1-10 km). However the latter observation sometimes fails to keep the clearance of an acoustic path between the seafloor transponders because of topographic obstacle or of downward bending nature of the path due to vertical gradient of sound speed in deep-ocean. Especially at steep fault scarp, it is almost impossible to keep direct path between the top and bottom of the fault scarp. Even in such a situation, acoustic path to the sea surface might be always clear. Then we propose a new approach to monitor the relative motion of across a fault scarp using "differential" GPS/acoustic measurement, which account only for traveltime differences among the transponders. The advantages of this method are that: (1) uncertainty in sound speed in shallow water is almost canceled; (2) possible GPS error is also canceled; (3) picking error in traveltime detection is almost canceled; (4) only a pair of transponders can fully describe relative 3-dimensional motion. On the other hand the disadvantages are that: (5) data is not continuous but only campaign; (6) most advantages are only effective only for very short baseline (< 100-300 m). Our target being applied this method is a steep fault scarp near the Japan trench, which is expected as a surface expression of back thrust, in where time scale of fault activity is still controversial especially after the Tohoku earthquake. We have carefully installed three transponders across this scarp using a NSS system, which can remotely navigate instrument near the seafloor from a mother vessel based on video camera image. Baseline lengths among the transponders are 200-300 m at 3500 m depth. Initial campaign data shows that the detectable level of relative motion is sub-centimeter. So we expect that if the fault moves more than 1 cm within three years (battery life for pup-up recovery), it can be monitored in our system.

Violent Interaction Detection in Video Based on Deep Learning

NASA Astrophysics Data System (ADS)

Zhou, Peipei; Ding, Qinghai; Luo, Haibo; Hou, Xinglin

2017-06-01

Violent interaction detection is of vital importance in some video surveillance scenarios like railway stations, prisons or psychiatric centres. Existing vision-based methods are mainly based on hand-crafted features such as statistic features between motion regions, leading to a poor adaptability to another dataset. En lightened by the development of convolutional networks on common activity recognition, we construct a FightNet to represent the complicated visual violence interaction. In this paper, a new input modality, image acceleration field is proposed to better extract the motion attributes. Firstly, each video is framed as RGB images. Secondly, optical flow field is computed using the consecutive frames and acceleration field is obtained according to the optical flow field. Thirdly, the FightNet is trained with three kinds of input modalities, i.e., RGB images for spatial networks, optical flow images and acceleration images for temporal networks. By fusing results from different inputs, we conclude whether a video tells a violent event or not. To provide researchers a common ground for comparison, we have collected a violent interaction dataset (VID), containing 2314 videos with 1077 fight ones and 1237 no-fight ones. By comparison with other algorithms, experimental results demonstrate that the proposed model for violent interaction detection shows higher accuracy and better robustness.

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.

State observers and Kalman filtering for high performance vibration isolation systems.

PubMed

Beker, M G; Bertolini, A; van den Brand, J F J; Bulten, H J; Hennes, E; Rabeling, D S

2014-03-01

There is a strong scientific case for the study of gravitational waves at or below the lower end of current detection bands. To take advantage of this scientific benefit, future generations of ground based gravitational wave detectors will need to expand the limit of their detection bands towards lower frequencies. Seismic motion presents a major challenge at these frequencies and vibration isolation systems will play a crucial role in achieving the desired low-frequency sensitivity. A compact vibration isolation system designed to isolate in-vacuum optical benches for Advanced Virgo will be introduced and measurements on this system are used to present its performance. All high performance isolation systems employ an active feedback control system to reduce the residual motion of their suspended payloads. The development of novel control schemes is needed to improve the performance beyond what is currently feasible. Here, we present a multi-channel feedback approach that is novel to the field. It utilizes a linear quadratic regulator in combination with a Kalman state observer and is shown to provide effective suppression of residual motion of the suspended payload. The application of state observer based feedback control for vibration isolation will be demonstrated with measurement results from the Advanced Virgo optical bench suspension system.

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).

[Motion control of moving mirror based on fixed-mirror adjustment in FTIR spectrometer].

PubMed

Li, Zhong-bing; Xu, Xian-ze; Le, Yi; Xu, Feng-qiu; Li, Jun-wei

2012-08-01

The performance of the uniform motion of the moving mirror, which is the only constant motion part in FTIR spectrometer, and the performance of the alignment of the fixed mirror play a key role in FTIR spectrometer, and affect the interference effect and the quality of the spectrogram and may restrict the precision and resolution of the instrument directly. The present article focuses on the research on the uniform motion of the moving mirror and the alignment of the fixed mirror. In order to improve the FTIR spectrometer, the maglev support system was designed for the moving mirror and the phase detection technology was adopted to adjust the tilt angle between the moving mirror and the fixed mirror. This paper also introduces an improved fuzzy PID control algorithm to get the accurate speed of the moving mirror and realize the control strategy from both hardware design and algorithm. The results show that the development of the moving mirror motion control system gets sufficient accuracy and real-time, which can ensure the uniform motion of the moving mirror and the alignment of the fixed mirror.

Wearable carbon nanotube-based fabric sensors for monitoring human physiological performance

NASA Astrophysics Data System (ADS)

Wang, Long; Loh, Kenneth J.

2017-05-01

A target application of wearable sensors is to detect human motion and to monitor physical activity for improving athletic performance and for delivering better physical therapy. In addition, measuring human vital signals (e.g., respiration rate and body temperature) provides rich information that can be used to assess a subject’s physiological or psychological condition. This study aims to design a multifunctional, wearable, fabric-based sensing system. First, carbon nanotube (CNT)-based thin films were fabricated by spraying. Second, the thin films were integrated with stretchable fabrics to form the fabric sensors. Third, the strain and temperature sensing properties of sensors fabricated using different CNT concentrations were characterized. Furthermore, the sensors were demonstrated to detect human finger bending motions, so as to validate their practical strain sensing performance. Finally, to monitor human respiration, the fabric sensors were integrated with a chest band, which was directly worn by a human subject. Quantification of respiration rates were successfully achieved. Overall, the fabric sensors were characterized by advantages such as flexibility, ease of fabrication, lightweight, low-cost, noninvasiveness, and user comfort.

An information-based approach to change-point analysis with applications to biophysics and cell biology.

PubMed

Wiggins, Paul A

2015-07-21

This article describes the application of a change-point algorithm to the analysis of stochastic signals in biological systems whose underlying state dynamics consist of transitions between discrete states. Applications of this analysis include molecular-motor stepping, fluorophore bleaching, electrophysiology, particle and cell tracking, detection of copy number variation by sequencing, tethered-particle motion, etc. We present a unified approach to the analysis of processes whose noise can be modeled by Gaussian, Wiener, or Ornstein-Uhlenbeck processes. To fit the model, we exploit explicit, closed-form algebraic expressions for maximum-likelihood estimators of model parameters and estimated information loss of the generalized noise model, which can be computed extremely efficiently. We implement change-point detection using the frequentist information criterion (which, to our knowledge, is a new information criterion). The frequentist information criterion specifies a single, information-based statistical test that is free from ad hoc parameters and requires no prior probability distribution. We demonstrate this information-based approach in the analysis of simulated and experimental tethered-particle-motion data. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Image-based tracking: a new emerging standard

NASA Astrophysics Data System (ADS)

Antonisse, Jim; Randall, Scott

2012-06-01

Automated moving object detection and tracking are increasingly viewed as solutions to the enormous data volumes resulting from emerging wide-area persistent surveillance systems. In a previous paper we described a Motion Imagery Standards Board (MISB) initiative to help address this problem: the specification of a micro-architecture for the automatic extraction of motion indicators and tracks. This paper reports on the development of an extended specification of the plug-and-play tracking micro-architecture, on its status as an emerging standard across DoD, the Intelligence Community, and NATO.

Statistical data mining of streaming motion data for fall detection in assistive environments.

PubMed

Tasoulis, S K; Doukas, C N; Maglogiannis, I; Plagianakos, V P

2011-01-01

The analysis of human motion data is interesting for the purpose of activity recognition or emergency event detection, especially in the case of elderly or disabled people living independently in their homes. Several techniques have been proposed for identifying such distress situations using either motion, audio or video sensors on the monitored subject (wearable sensors) or the surrounding environment. The output of such sensors is data streams that require real time recognition, especially in emergency situations, thus traditional classification approaches may not be applicable for immediate alarm triggering or fall prevention. This paper presents a statistical mining methodology that may be used for the specific problem of real time fall detection. Visual data captured from the user's environment, using overhead cameras along with motion data are collected from accelerometers on the subject's body and are fed to the fall detection system. The paper includes the details of the stream data mining methodology incorporated in the system along with an initial evaluation of the achieved accuracy in detecting falls.

Sign determination methods for the respiratory signal in data-driven PET gating

NASA Astrophysics Data System (ADS)

Bertolli, Ottavia; Arridge, Simon; Wollenweber, Scott D.; Stearns, Charles W.; Hutton, Brian F.; Thielemans, Kris

2017-04-01

Patient respiratory motion during PET image acquisition leads to blurring in the reconstructed images and may cause significant artifacts, resulting in decreased lesion detectability, inaccurate standard uptake value calculation and incorrect treatment planning in radiation therapy. To reduce these effects data can be regrouped into (nearly) ‘motion-free’ gates prior to reconstruction by selecting the events with respect to the breathing phase. This gating procedure therefore needs a respiratory signal: on current scanners it is obtained from an external device, whereas with data driven (DD) methods it can be directly obtained from the raw PET data. DD methods thus eliminate the use of external equipment, which is often expensive, needs prior setup and can cause patient discomfort, and they could also potentially provide increased fidelity to the internal movement. DD methods have been recently applied on PET data showing promising results. However, many methods provide signals whose direction with respect to the physical motion is uncertain (i.e. their sign is arbitrary), therefore a maximum in the signal could refer either to the end-inspiration or end-expiration phase, possibly causing inaccurate motion correction. In this work we propose two novel methods, CorrWeights and CorrSino, to detect the correct direction of the motion represented by the DD signal, that is obtained by applying principal component analysis (PCA) on the acquired data. They only require the PET raw data, and they rely on the assumption that one of the major causes of change in the acquired data related to the chest is respiratory motion in the axial direction, that generates a cranio-caudal motion of the internal organs. We also implemented two versions of a published registration-based method, that require image reconstruction. The methods were first applied on XCAT simulations, and later evaluated on cancer patient datasets monitored by the Varian Real-time Position ManagementTM (RPM) device, selecting the lower chest bed positions. For each patient different time intervals were evaluated ranging from 50 to 300 s in duration. The novel methods proved to be generally more accurate than the registration-based ones in detecting the correct sign of the respiratory signal, and their failure rates are lower than 3% when the DD signal is highly correlated with the RPM. They also have the advantage of faster computation time, avoiding reconstruction. Moreover, CorrWeights is not specifically related to PCA and considering its simple implementation, it could easily be applied together with any DD method in clinical practice.

A motion detection system for AXAF X-ray ground testing

NASA Technical Reports Server (NTRS)

Arenberg, Jonathan W.; Texter, Scott C.

1993-01-01

The concept, implementation, and performance of the motion detection system (MDS) designed as a diagnostic for X-ray ground testing for AXAF are described. The purpose of the MDS is to measure the magnitude of a relative rigid body motion among the AXAF test optic, the X-ray source, and X-ray focal plane detector. The MDS consists of a point source, lens, centroid detector, transimpedance amplifier, and computer system. Measurement of the centroid position of the image of the optical point source provides a direct measure of the motions of the X-ray optical system. The outputs from the detector and filter/amplifier are digitized and processed using the calibration with a 50 Hz bandwidth to give the centroid's location on the detector. Resolution of 0.008 arcsec has been achieved by this system. Data illustrating the performance of the motion detection system are also presented.

Orientation selectivity sharpens motion detection in Drosophila

PubMed Central

Fisher, Yvette E.; Silies, Marion; Clandinin, Thomas R.

2015-01-01

SUMMARY Detecting the orientation and movement of edges in a scene is critical to visually guided behaviors of many animals. What are the circuit algorithms that allow the brain to extract such behaviorally vital visual cues? Using in vivo two-photon calcium imaging in Drosophila, we describe direction selective signals in the dendrites of T4 and T5 neurons, detectors of local motion. We demonstrate that this circuit performs selective amplification of local light inputs, an observation that constrains motion detection models and confirms a core prediction of the Hassenstein-Reichardt Correlator (HRC). These neurons are also orientation selective, responding strongly to static features that are orthogonal to their preferred axis of motion, a tuning property not predicted by the HRC. This coincident extraction of orientation and direction sharpens directional tuning through surround inhibition and reveals a striking parallel between visual processing in flies and vertebrate cortex, suggesting a universal strategy for motion processing. PMID:26456048

Visual communications and image processing '92; Proceedings of the Meeting, Boston, MA, Nov. 18-20, 1992

NASA Astrophysics Data System (ADS)

Maragos, Petros

The topics discussed at the conference include hierarchical image coding, motion analysis, feature extraction and image restoration, video coding, and morphological and related nonlinear filtering. Attention is also given to vector quantization, morphological image processing, fractals and wavelets, architectures for image and video processing, image segmentation, biomedical image processing, and model-based analysis. Papers are presented on affine models for motion and shape recovery, filters for directly detecting surface orientation in an image, tracking of unresolved targets in infrared imagery using a projection-based method, adaptive-neighborhood image processing, and regularized multichannel restoration of color images using cross-validation. (For individual items see A93-20945 to A93-20951)

Automated reference-free detection of motion artifacts in magnetic resonance images.

PubMed

Küstner, Thomas; Liebgott, Annika; Mauch, Lukas; Martirosian, Petros; Bamberg, Fabian; Nikolaou, Konstantin; Yang, Bin; Schick, Fritz; Gatidis, Sergios

2018-04-01

Our objectives were to provide an automated method for spatially resolved detection and quantification of motion artifacts in MR images of the head and abdomen as well as a quality control of the trained architecture. T1-weighted MR images of the head and the upper abdomen were acquired in 16 healthy volunteers under rest and under motion. Images were divided into overlapping patches of different sizes achieving spatial separation. Using these patches as input data, a convolutional neural network (CNN) was trained to derive probability maps for the presence of motion artifacts. A deep visualization offers a human-interpretable quality control of the trained CNN. Results were visually assessed on probability maps and as classification accuracy on a per-patch, per-slice and per-volunteer basis. On visual assessment, a clear difference of probability maps was observed between data sets with and without motion. The overall accuracy of motion detection on a per-patch/per-volunteer basis reached 97%/100% in the head and 75%/100% in the abdomen, respectively. Automated detection of motion artifacts in MRI is feasible with good accuracy in the head and abdomen. The proposed method provides quantification and localization of artifacts as well as a visualization of the learned content. It may be extended to other anatomic areas and used for quality assurance of MR images.

A Motion-Based Feature for Event-Based Pattern Recognition

PubMed Central

Clady, Xavier; Maro, Jean-Matthieu; Barré, Sébastien; Benosman, Ryad B.

2017-01-01

This paper introduces an event-based luminance-free feature from the output of asynchronous event-based neuromorphic retinas. The feature consists in mapping the distribution of the optical flow along the contours of the moving objects in the visual scene into a matrix. Asynchronous event-based neuromorphic retinas are composed of autonomous pixels, each of them asynchronously generating “spiking” events that encode relative changes in pixels' illumination at high temporal resolutions. The optical flow is computed at each event, and is integrated locally or globally in a speed and direction coordinate frame based grid, using speed-tuned temporal kernels. The latter ensures that the resulting feature equitably represents the distribution of the normal motion along the current moving edges, whatever their respective dynamics. The usefulness and the generality of the proposed feature are demonstrated in pattern recognition applications: local corner detection and global gesture recognition. PMID:28101001

Quasi-local action of curl-less vector potential on vortex dynamics in superconductors

NASA Astrophysics Data System (ADS)

Gulian, Armen M.; Nikoghosyan, Vahan R.; Gulian, Ellen D.; Melkonyan, Gurgen G.

2018-04-01

Studies of the Abrikosov vortex motion in superconductors based on time-dependent Ginzburg-Landau equations reveal an opportunity to detect the values of the Aharonov-Bohm type curl-less vector potentials without closed-loop electron trajectories encompassing the magnetic flux.

Decoding the origins of vertical land motions observed today at coasts

NASA Astrophysics Data System (ADS)

Pfeffer, J.; Spada, G.; Mémin, A.; Boy, J.-P.; Allemand, P.

2017-07-01

In recent decades, geodetic techniques have allowed detecting vertical land motions and sea-level changes of a few millimetres per year, based on measurements taken at the coast (tide gauges), on board of satellite platforms (satellite altimetry) or both (Global Navigation Satellite System). Here, contemporary vertical land motions are analysed from January 1993 to July 2013 at 849 globally distributed coastal sites. The vertical displacement of the coastal platform due to surface mass changes is modelled using elastic and viscoelastic Green's functions. Special attention is paid to the effects of glacial isostatic adjustment induced by past and present-day ice melting. Various rheological and loading parameters are explored to provide a set of scenarios that could explain the coastal observations of vertical land motions globally. In well-instrumented regions, predicted vertical land motions explain more than 80 per cent of the variance observed at scales larger than a few hundred kilometres. Residual vertical land motions show a strong local variability, especially in the vicinity of plate boundaries due to the earthquake cycle. Significant residual signals are also observed at scales of a few hundred kilometres over nine well-instrumented regions forming observation windows on unmodelled geophysical processes. This study highlights the potential of our multitechnique database to detect geodynamical processes, driven by anthropogenic influence, surface mass changes (surface loading and glacial isostatic adjustment) and tectonic activity (including the earthquake cycle, sediment and volcanic loading, as well as regional tectonic constraints). Future improvements should be aimed at densifying the instrumental network and at investigating more thoroughly the uncertainties associated with glacial isostatic adjustment models.

Detecting Abnormal Vehicular Dynamics at Intersections Based on an Unsupervised Learning Approach and a Stochastic Model

PubMed Central

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems. PMID:22163616

Detecting abnormal vehicular dynamics at intersections based on an unsupervised learning approach and a stochastic model.

PubMed

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems.

The relationship between stereoacuity and stereomotion thresholds.

PubMed

Cumming, B G

1995-01-01

There are in principle at least two binocular sources of information that could be used to determine the motion of an object towards or away from an observer; such motion produces changes in binocular disparities over time and also generates different image velocities in the two eyes. It has been argued in the past that stereomotion is detected by a mechanism that is independent of that which detects static disparities. More recently this conclusion has been questioned. If stereomotion detection in fact depends upon detecting disparities, there should be a clear correlation between static stereo-detection thresholds and stereomotion thresholds. If the systems are separate, there need be no such correlation. Four types of threshold measurement were performed by means of random-dot stereograms: (1) static stereo detection/discrimination; (2) stereomotion detection in random-dot stereograms (temporally uncorrelated); (3) stereomotion detection in temporally correlated random-dot stereograms; and (4) binocular detection of frontoparallel motion. Three normal subjects and five subjects with unusually high stereoacuities were studied. In addition, two manipulations were performed that altered stereomotion thresholds: changes in mean disparity, and image defocus produced by positive spectacle lenses. Across subjects and conditions, stereomotion thresholds were well correlated with stereo-discrimination thresholds. Stereomotion was poorly correlated with binocular frontoparallel-motion thresholds. These results suggest that stereomotion is detected by means of registering changes in the output of the same disparity detectors that are used to detect static disparities.

The perception of object versus objectless motion.

PubMed

Hock, Howard S; Nichols, David F

2013-05-01

Wertheimer, M. (Zeitschrift für Psychologie und Physiologie der Sinnesorgane, 61:161-265, 1912) classical distinction between beta (object) and phi (objectless) motion is elaborated here in a series of experiments concerning competition between two qualitatively different motion percepts, induced by sequential changes in luminance for two-dimensional geometric objects composed of rectangular surfaces. One of these percepts is of spreading-luminance motion that continuously sweeps across the entire object; it exhibits shape invariance and is perceived most strongly for fast speeds. Significantly for the characterization of phi as objectless motion, the spreading luminance does not involve surface boundaries or any other feature; the percept is driven solely by spatiotemporal changes in luminance. Alternatively, and for relatively slow speeds, a discrete series of edge motions can be perceived in the direction opposite to spreading-luminance motion. Akin to beta motion, the edges appear to move through intermediate positions within the object's changing surfaces. Significantly for the characterization of beta as object motion, edge motion exhibits shape dependence and is based on the detection of oppositely signed changes in contrast (i.e., counterchange) for features essential to the determination of an object's shape, the boundaries separating its surfaces. These results are consistent with area MT neurons that differ with respect to speed preference Newsome et al (Journal of Neurophysiology, 55:1340-1351, 1986) and shape dependence Zeki (Journal of Physiology, 236:549-573, 1974).

Gravity Cues Embedded in the Kinematics of Human Motion Are Detected in Form-from-Motion Areas of the Visual System and in Motor-Related Areas

PubMed Central

Cignetti, Fabien; Chabeauti, Pierre-Yves; Menant, Jasmine; Anton, Jean-Luc J. J.; Schmitz, Christina; Vaugoyeau, Marianne; Assaiante, Christine

2017-01-01

The present study investigated the cortical areas engaged in the perception of graviceptive information embedded in biological motion (BM). To this end, functional magnetic resonance imaging was used to assess the cortical areas active during the observation of human movements performed under normogravity and microgravity (parabolic flight). Movements were defined by motion cues alone using point-light displays. We found that gravity modulated the activation of a restricted set of regions of the network subtending BM perception, including form-from-motion areas of the visual system (kinetic occipital region, lingual gyrus, cuneus) and motor-related areas (primary motor and somatosensory cortices). These findings suggest that compliance of observed movements with normal gravity was carried out by mapping them onto the observer’s motor system and by extracting their overall form from local motion of the moving light points. We propose that judgment on graviceptive information embedded in BM can be established based on motor resonance and visual familiarity mechanisms and not necessarily by accessing the internal model of gravitational motion stored in the vestibular cortex. PMID:28861024

Three-dimensional computer graphic animations for studying social approach behaviour in medaka fish: Effects of systematic manipulation of morphological and motion cues.

PubMed

Nakayasu, Tomohiro; Yasugi, Masaki; Shiraishi, Soma; Uchida, Seiichi; Watanabe, Eiji

2017-01-01

We studied social approach behaviour in medaka fish using three-dimensional computer graphic (3DCG) animations based on the morphological features and motion characteristics obtained from real fish. This is the first study which used 3DCG animations and examined the relative effects of morphological and motion cues on social approach behaviour in medaka. Various visual stimuli, e.g., lack of motion, lack of colour, alternation in shape, lack of locomotion, lack of body motion, and normal virtual fish in which all four features (colour, shape, locomotion, and body motion) were reconstructed, were created and presented to fish using a computer display. Medaka fish presented with normal virtual fish spent a long time in proximity to the display, whereas time spent near the display was decreased in other groups when compared with normal virtual medaka group. The results suggested that the naturalness of visual cues contributes to the induction of social approach behaviour. Differential effects between body motion and locomotion were also detected. 3DCG animations can be a useful tool to study the mechanisms of visual processing and social behaviour in medaka.

Three-dimensional computer graphic animations for studying social approach behaviour in medaka fish: Effects of systematic manipulation of morphological and motion cues

PubMed Central

Nakayasu, Tomohiro; Yasugi, Masaki; Shiraishi, Soma; Uchida, Seiichi; Watanabe, Eiji

2017-01-01

We studied social approach behaviour in medaka fish using three-dimensional computer graphic (3DCG) animations based on the morphological features and motion characteristics obtained from real fish. This is the first study which used 3DCG animations and examined the relative effects of morphological and motion cues on social approach behaviour in medaka. Various visual stimuli, e.g., lack of motion, lack of colour, alternation in shape, lack of locomotion, lack of body motion, and normal virtual fish in which all four features (colour, shape, locomotion, and body motion) were reconstructed, were created and presented to fish using a computer display. Medaka fish presented with normal virtual fish spent a long time in proximity to the display, whereas time spent near the display was decreased in other groups when compared with normal virtual medaka group. The results suggested that the naturalness of visual cues contributes to the induction of social approach behaviour. Differential effects between body motion and locomotion were also detected. 3DCG animations can be a useful tool to study the mechanisms of visual processing and social behaviour in medaka. PMID:28399163

Correcting bulk in-plane motion artifacts in MRI using the point spread function.

PubMed

Lin, Wei; Wehrli, Felix W; Song, Hee Kwon

2005-09-01

A technique is proposed for correcting both translational and rotational motion artifacts in magnetic resonance imaging without the need to collect additional navigator data or to perform intensive postprocessing. The method is based on measuring the point spread function (PSF) by attaching one or two point-sized markers to the main imaging object. Following the isolation of a PSF marker from the acquired image, translational motion could be corrected directly from the modulation transfer function, without the need to determine the object's positions during the scan, although the shifts could be extracted if desired. Rotation is detected by analyzing the relative displacements of two such markers. The technique was evaluated with simulations, phantom and in vivo experiments.

Accurate band-to-band registration of AOTF imaging spectrometer using motion detection technology

NASA Astrophysics Data System (ADS)

Zhou, Pengwei; Zhao, Huijie; Jin, Shangzhong; Li, Ningchuan

2016-05-01

This paper concerns the problem of platform vibration induced band-to-band misregistration with acousto-optic imaging spectrometer in spaceborne application. Registrating images of different bands formed at different time or different position is difficult, especially for hyperspectral images form acousto-optic tunable filter (AOTF) imaging spectrometer. In this study, a motion detection method is presented using the polychromatic undiffracted beam of AOTF. The factors affecting motion detect accuracy are analyzed theoretically, and calculations show that optical distortion is an easily overlooked factor to achieve accurate band-to-band registration. Hence, a reflective dual-path optical system has been proposed for the first time, with reduction of distortion and chromatic aberration, indicating the potential of higher registration accuracy. Consequently, a spectra restoration experiment using additional motion detect channel is presented for the first time, which shows the accurate spectral image registration capability of this technique.

Neurons compute internal models of the physical laws of motion.

PubMed

Angelaki, Dora E; Shaikh, Aasef G; Green, Andrea M; Dickman, J David

2004-07-29

A critical step in self-motion perception and spatial awareness is the integration of motion cues from multiple sensory organs that individually do not provide an accurate representation of the physical world. One of the best-studied sensory ambiguities is found in visual processing, and arises because of the inherent uncertainty in detecting the motion direction of an untextured contour moving within a small aperture. A similar sensory ambiguity arises in identifying the actual motion associated with linear accelerations sensed by the otolith organs in the inner ear. These internal linear accelerometers respond identically during translational motion (for example, running forward) and gravitational accelerations experienced as we reorient the head relative to gravity (that is, head tilt). Using new stimulus combinations, we identify here cerebellar and brainstem motion-sensitive neurons that compute a solution to the inertial motion detection problem. We show that the firing rates of these populations of neurons reflect the computations necessary to construct an internal model representation of the physical equations of motion.

Optimal Stimulus Amplitude for Vestibular Stochastic Stimulation to Improve Sensorimotor Function

NASA Technical Reports Server (NTRS)

Goel, R.; Kofman, I.; DeDios, Y. E.; Jeevarajan, J.; Stepanyan, V.; Nair, M.; Congdon, S.; Fregia, M.; Cohen, H.; Bloomberg, J. J.;

Exercise Sensing and Pose Recovery Inference Tool (ESPRIT) - A Compact Stereo-based Motion Capture Solution For Exercise Monitoring

NASA Technical Reports Server (NTRS)

Lee, Mun Wai

2015-01-01

Crew exercise is important during long-duration space flight not only for maintaining health and fitness but also for preventing adverse health problems, such as losses in muscle strength and bone density. Monitoring crew exercise via motion capture and kinematic analysis aids understanding of the effects of microgravity on exercise and helps ensure that exercise prescriptions are effective. Intelligent Automation, Inc., has developed ESPRIT to monitor exercise activities, detect body markers, extract image features, and recover three-dimensional (3D) kinematic body poses. The system relies on prior knowledge and modeling of the human body and on advanced statistical inference techniques to achieve robust and accurate motion capture. In Phase I, the company demonstrated motion capture of several exercises, including walking, curling, and dead lifting. Phase II efforts focused on enhancing algorithms and delivering an ESPRIT prototype for testing and demonstration.

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

Plasticity Beyond V1: Reinforcement of Motion Perception upon Binocular Central Retinal Lesions in Adulthood.

PubMed

Burnat, Kalina; Hu, Tjing-Tjing; Kossut, Małgorzata; Eysel, Ulf T; Arckens, Lutgarde

2017-09-13

Induction of a central retinal lesion in both eyes of adult mammals is a model for macular degeneration and leads to retinotopic map reorganization in the primary visual cortex (V1). Here we characterized the spatiotemporal dynamics of molecular activity levels in the central and peripheral representation of five higher-order visual areas, V2/18, V3/19, V4/21a,V5/PMLS, area 7, and V1/17, in adult cats with central 10° retinal lesions (both sexes), by means of real-time PCR for the neuronal activity reporter gene zif268. The lesions elicited a similar, permanent reduction in activity in the center of the lesion projection zone of area V1/17, V2/18, V3/19, and V4/21a, but not in the motion-driven V5/PMLS, which instead displayed an increase in molecular activity at 3 months postlesion, independent of visual field coordinates. Also area 7 only displayed decreased activity in its LPZ in the first weeks postlesion and increased activities in its periphery from 1 month onward. Therefore we examined the impact of central vision loss on motion perception using random dot kinematograms to test the capacity for form from motion detection based on direction and velocity cues. We revealed that the central retinal lesions either do not impair motion detection or even result in better performance, specifically when motion discrimination was based on velocity discrimination. In conclusion, we propose that central retinal damage leads to enhanced peripheral vision by sensitizing the visual system for motion processing relying on feedback from V5/PMLS and area 7. SIGNIFICANCE STATEMENT Central retinal lesions, a model for macular degeneration, result in functional reorganization of the primary visual cortex. Examining the level of cortical reactivation with the molecular activity marker zif268 revealed reorganization in visual areas outside V1. Retinotopic lesion projection zones typically display an initial depression in zif268 expression, followed by partial recovery with postlesion time. Only the motion-sensitive area V5/PMLS shows no decrease, and even a significant activity increase at 3 months post-retinal lesion. Behavioral tests of motion perception found no impairment and even better sensitivity to higher random dot stimulus velocities. We demonstrate that the loss of central vision induces functional mobilization of motion-sensitive visual cortex, resulting in enhanced perception of moving stimuli. Copyright © 2017 the authors 0270-6474/17/378989-11$15.00/0.

Microwave and millimeter-wave Doppler radar heart sensing

NASA Astrophysics Data System (ADS)

Boric-Lubecke, Olga; Lin, Jenshan; Lubecke, Victor M.; Host-Madsen, Anders; Sizer, Tod

2007-04-01

Technology that can be used to unobtrusively detect and monitor the presence of human subjects from a distance and through barriers can be a powerful tool for meeting new security challenges, including asymmetric battlefield threats abroad and defense infrastructure needs back home. Our team is developing mobile remote sensing technology for battle-space awareness and warfighter protection, based on microwave and millimeter-wave Doppler radar motion sensing devices that detect human presence. This technology will help overcome a shortfall of current see-through-thewall (STTW) systems, which is, the poor detection of stationary personnel. By detecting the minute Doppler shifts induced by a subject's cardiopulmonary related chest motion, the technology will allow users to detect personnel that are completely stationary more effectively. This personnel detection technique can also have an extremely low probability of intercept since the signals used can be those from everyday communications. The software and hardware developments and challenges for personnel detection and count at a distance will be discussed, including a 2.4 GHz quadrature radar single-chip silicon CMOS implementation, a low-power double side-band Ka-band transmission radar, and phase demodulation and heart rate extraction algorithms. In addition, the application of MIMO techniques for determining the number of subjects will be discussed.

A comparison of line enhancement techniques: applications to guide-wire detection and respiratory motion tracking

NASA Astrophysics Data System (ADS)

Bismuth, Vincent; Vancamberg, Laurence; Gorges, Sébastien

2009-02-01

During interventional radiology procedures, guide-wires are usually inserted into the patients vascular tree for diagnosis or healing purpose. These procedures are monitored with an Xray interventional system providing images of the interventional devices navigating through the patient's body. The automatic detection of such tools by image processing means has gained maturity over the past years and enables applications ranging from image enhancement to multimodal image fusion. Sophisticated detection methods are emerging, which rely on a variety of device enhancement techniques. In this article we reviewed and classified these techniques into three families. We chose a state of the art approach in each of them and built a rigorous framework to compare their detection capability and their computational complexity. Through simulations and the intensive use of ROC curves we demonstrated that the Hessian based methods are the most robust to strong curvature of the devices and that the family of rotated filters technique is the most suited for detecting low CNR and low curvature devices. The steerable filter approach demonstrated less interesting detection capabilities and appears to be the most expensive one to compute. Finally we demonstrated the interest of automatic guide-wire detection on a clinical topic: the compensation of respiratory motion in multimodal image fusion.

Detection of motion and posture change using an IR-UWB radar.

PubMed

Van Nguyen; Javaid, Abdul Q; Weitnauer, Mary A

2016-08-01

Impulse radio ultra-wide band (IR-UWB) radar has recently emerged as a promising candidate for non-contact monitoring of respiration and heart rate. Different studies have reported various radar based algorithms for estimation of these physiological parameters. The radar can be placed under a subject's mattress as he lays stationary on his back or it can be attached to the ceiling directly above the subject's bed. However, advertent or inadvertent movement on part of the subject and different postures can affect the radar returned signal and also the accuracy of the estimated parameters from it. The detection and analysis of these postural changes can not only lead to improvement in estimation algorithms but also towards prevention of bed sores and ulcers in patients who require periodic posture changes. In this paper, we present an algorithm that detects and quantifies different types of motion events using an under-the-mattress IR-UWB radar. The algorithm also indicates a change in posture after a macro-movement event. Based on the findings of this paper, we anticipate that IR-UWB radar can be used for extracting posture related information in non-clinical enviroments for patients who are bed-ridden.

An intelligent surveillance platform for large metropolitan areas with dense sensor deployment.

PubMed

Fernández, Jorge; Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M; Carro, Belén; Sánchez-Esguevillas, Antonio; Alonso-López, Jesus A; Smilansky, Zeev

2013-06-07

This paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform's control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coverage.

Video Altimeter and Obstruction Detector for an Aircraft

NASA Technical Reports Server (NTRS)

Delgado, Frank J.; Abernathy, Michael F.; White, Janis; Dolson, William R.

2013-01-01

Video-based altimetric and obstruction detection systems for aircraft have been partially developed. The hardware of a system of this type includes a downward-looking video camera, a video digitizer, a Global Positioning System receiver or other means of measuring the aircraft velocity relative to the ground, a gyroscope based or other attitude-determination subsystem, and a computer running altimetric and/or obstruction-detection software. From the digitized video data, the altimetric software computes the pixel velocity in an appropriate part of the video image and the corresponding angular relative motion of the ground within the field of view of the camera. Then by use of trigonometric relationships among the aircraft velocity, the attitude of the camera, the angular relative motion, and the altitude, the software computes the altitude. The obstruction-detection software performs somewhat similar calculations as part of a larger task in which it uses the pixel velocity data from the entire video image to compute a depth map, which can be correlated with a terrain map, showing locations of potential obstructions. The depth map can be used as real-time hazard display and/or to update an obstruction database.

Model-Based Building Detection from Low-Cost Optical Sensors Onboard Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Karantzalos, K.; Koutsourakis, P.; Kalisperakis, I.; Grammatikopoulos, L.

2015-08-01

The automated and cost-effective building detection in ultra high spatial resolution is of major importance for various engineering and smart city applications. To this end, in this paper, a model-based building detection technique has been developed able to extract and reconstruct buildings from UAV aerial imagery and low-cost imaging sensors. In particular, the developed approach through advanced structure from motion, bundle adjustment and dense image matching computes a DSM and a true orthomosaic from the numerous GoPro images which are characterised by important geometric distortions and fish-eye effect. An unsupervised multi-region, graphcut segmentation and a rule-based classification is responsible for delivering the initial multi-class classification map. The DTM is then calculated based on inpaininting and mathematical morphology process. A data fusion process between the detected building from the DSM/DTM and the classification map feeds a grammar-based building reconstruction and scene building are extracted and reconstructed. Preliminary experimental results appear quite promising with the quantitative evaluation indicating detection rates at object level of 88% regarding the correctness and above 75% regarding the detection completeness.

Source detection at 100 meter standoff with a time-encoded imaging system

NASA Astrophysics Data System (ADS)

Brennan, J.; Brubaker, E.; Gerling, M.; Marleau, P.; Monterial, M.; Nowack, A.; Schuster, P.; Sturm, B.; Sweany, M.

2018-01-01

We present the design, characterization, and testing of a laboratory prototype radiological search and localization system. The system, based on time-encoded imaging, uses the attenuation signature of neutrons in time, induced by the geometrical layout and motion of the system. We have demonstrated the ability to detect a ∼ 1mCi252Cf radiological source at 100m standoff with 90% detection efficiency and 10% false positives against background in 12min. This same detection efficiency is met at 15s for a 40m standoff, and 1 . 2s for a 20m standoff.

Optical Measurement of In-plane Waves in Mechanical Metamaterials Through Digital Image Correlation

NASA Astrophysics Data System (ADS)

Schaeffer, Marshall; Trainiti, Giuseppe; Ruzzene, Massimo

2017-02-01

We report on a Digital Image Correlation-based technique for the detection of in-plane elastic waves propagating in structural lattices. The experimental characterization of wave motion in lattice structures is currently of great interest due its relevance to the design of novel mechanical metamaterials with unique/unusual properties such as strongly directional behaviour, negative refractive indexes and topologically protected wave motion. Assessment of these functionalities often requires the detection of highly spatially resolved in-plane wavefields, which for reticulated or porous structural assemblies is an open challenge. A Digital Image Correlation approach is implemented that tracks small displacements of the lattice nodes by centring image subsets about the lattice intersections. A high speed camera records the motion of the points by properly interleaving subse- quent frames thus artificially enhancing the available sampling rate. This, along with an imaging stitching procedure, enables the capturing of a field of view that is sufficiently large for subsequent processing. The transient response is recorded in the form of the full wavefields, which are processed to unveil features of wave motion in a hexagonal lattice. Time snapshots and frequency contours in the spatial Fourier domain are compared with numerical predictions to illustrate the accuracy of the recorded wavefields.

New Worlds Observer Formation Control Design Based on the Dynamics of Relative Motion

NASA Technical Reports Server (NTRS)

Luquette, Richard J.

2008-01-01

The New Worlds Observer (NWO) mission is designed for the direct detection and characterization of extrasolar planets. The NWO mission concept employs a two spacecraft leader-follower formation on a trajectory around the Earth/Moon-Sun L(sub 2) Libration Point. The leader spacecraft is baselined as a 4 meter optical telescope. The follower, Starshade spacecraft, is designed to suppress light from a central body star permitting direct detection of a surrounding exoplanetary system. The current design requires a nominal leader-follower separation range of 72 Megameters. NWO poses many challenges including formation control. NWO cycles between three principal control modes during the nominal mission timeline: science (fine pointing), realignment and transition. This paper examines formation control strategies in the context of dynamics of relative motion for two spacecraft operating in the vicinity of the Earth/Moon-Sun L(sub 2)libration point. The paper presents an overview of the equations of relative motion followed by a discussion of each of the control modes. Discussion and analysis characterize control strategies for each of the mission control modes, including requirements, implementation challenges and project fuel budgets.

EXOPLANETARY DETECTION BY MULTIFRACTAL SPECTRAL ANALYSIS

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

Agarwal, Sahil; Wettlaufer, John S.; Sordo, Fabio Del

2017-01-01

Owing to technological advances, the number of exoplanets discovered has risen dramatically in the last few years. However, when trying to observe Earth analogs, it is often difficult to test the veracity of detection. We have developed a new approach to the analysis of exoplanetary spectral observations based on temporal multifractality, which identifies timescales that characterize planetary orbital motion around the host star and those that arise from stellar features such as spots. Without fitting stellar models to spectral data, we show how the planetary signal can be robustly detected from noisy data using noise amplitude as a source ofmore » information. For observation of transiting planets, combining this method with simple geometry allows us to relate the timescales obtained to primary and secondary eclipse of the exoplanets. Making use of data obtained with ground-based and space-based observations we have tested our approach on HD 189733b. Moreover, we have investigated the use of this technique in measuring planetary orbital motion via Doppler shift detection. Finally, we have analyzed synthetic spectra obtained using the SOAP 2.0 tool, which simulates a stellar spectrum and the influence of the presence of a planet or a spot on that spectrum over one orbital period. We have demonstrated that, so long as the signal-to-noise-ratio ≥ 75, our approach reconstructs the planetary orbital period, as well as the rotation period of a spot on the stellar surface.« less

Compliant finger sensor for sensorimotor studies in MEG and MR environment

NASA Astrophysics Data System (ADS)

Li, Y.; Yong, X.; Cheung, T. P. L.; Menon, C.

2016-07-01

Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) are widely used for functional brain imaging. The correlations between the sensorimotor functions of the hand and brain activities have been investigated in MEG/fMRI studies. Currently, limited information can be drawn from these studies due to the limitations of existing motion sensors that are used to detect hand movements. One major challenge in designing these motion sensors is to limit the signal interference between the motion sensors and the MEG/fMRI. In this work, a novel finger motion sensor, which contains low-ferromagnetic and non-conductive materials, is introduced. The finger sensor consists of four air-filled chambers. When compressed by finger(s), the pressure change in the chambers can be detected by the electronics of the finger sensor. Our study has validated that the interference between the finger sensor and an MEG is negligible. Also, by applying a support vector machine algorithm to the data obtained from the finger sensor, at least 11 finger patterns can be discriminated. Comparing to the use of traditional electromyography (EMG) in detecting finger motion, our proposed finger motion sensor is not only MEG/fMRI compatible, it is also easy to use. As the signals acquired from the sensor have a higher SNR than that of the EMG, no complex algorithms are required to detect different finger movement patterns. Future studies can utilize this motion sensor to investigate brain activations during different finger motions and correlate the activations with the sensory and motor functions respectively.

Performance assessment of HIFU lesion detection by harmonic motion imaging for focused ultrasound (HMIFU): a 3-D finite-element-based framework with experimental validation.

PubMed

Hou, Gary Y; Luo, Jianwen; Marquet, Fabrice; Maleke, Caroline; Vappou, Jonathan; Konofagou, Elisa E

2011-12-01

Harmonic motion imaging for focused ultrasound (HMIFU) is a novel high-intensity focused ultrasound (HIFU) therapy monitoring method with feasibilities demonstrated in vitro, ex vivo and in vivo. Its principle is based on amplitude-modulated (AM) - harmonic motion imaging (HMI), an oscillatory radiation force used for imaging the tissue mechanical response during thermal ablation. In this study, a theoretical framework of HMIFU is presented, comprising a customized nonlinear wave propagation model, a finite-element (FE) analysis module and an image-formation model. The objective of this study is to develop such a framework to (1) assess the fundamental performance of HMIFU in detecting HIFU lesions based on the change in tissue apparent elasticity, i.e., the increasing Young's modulus, and the HIFU lesion size with respect to the HIFU exposure time and (2) validate the simulation findings ex vivo. The same HMI and HMIFU parameters as in the experimental studies were used, i.e., 4.5-MHz HIFU frequency and 25 Hz AM frequency. For a lesion-to-background Young's modulus ratio of 3, 6 and 9, the FE and estimated HMI displacement ratios were equal to 1.83, 3.69 and 5.39 and 1.65, 3.19 and 4.59, respectively. In experiments, the HMI displacement followed a similar increasing trend of 1.19, 1.28 and 1.78 at 10-s, 20-s and 30-s HIFU exposure, respectively. In addition, moderate agreement in lesion size growth was found in both simulations (16.2, 73.1 and 334.7 mm(2)) and experiments (26.2, 94.2 and 206.2 mm(2)). Therefore, the feasibility of HMIFU for HIFU lesion detection based on the underlying tissue elasticity changes was verified through the developed theoretical framework, i.e., validation of the fundamental performance of the HMIFU system for lesion detection, localization and quantification, was demonstrated both theoretically and ex vivo. Copyright © 2011 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Detecting target changes in multiple object tracking with peripheral vision: More pronounced eccentricity effects for changes in form than in motion.

PubMed

Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim

2017-05-01

In the current study, dual-task performance is examined with multiple-object tracking as a primary task and target-change detection as a secondary task. The to-be-detected target changes in conditions of either change type (form vs. motion; Experiment 1) or change salience (stop vs. slowdown; Experiment 2), with changes occurring at either near (5°-10°) or far (15°-20°) eccentricities (Experiments 1 and 2). The aim of the study was to test whether changes can be detected solely with peripheral vision. By controlling for saccades and computing gaze distances, we could show that participants used peripheral vision to monitor the targets and, additionally, to perceive changes at both near and far eccentricities. Noticeably, gaze behavior was not affected by the actual target change. Detection rates as well as response times generally varied as a function of change condition and eccentricity, with faster detections for motion changes and near changes. However, in contrast to the effects found for motion changes, sharp declines in detection rates and increased response times were observed for form changes as a function of the eccentricities. This result can be ascribed to properties of the visual system, namely to the limited spatial acuity in the periphery and the comparably receptive motion sensitivity of peripheral vision. These findings show that peripheral vision is functional for simultaneous target monitoring and target-change detection as saccadic information suppression can be avoided and covert attention can be optimally distributed to all targets. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Depth information in natural environments derived from optic flow by insect motion detection system: a model analysis

PubMed Central

Schwegmann, Alexander; Lindemann, Jens P.; Egelhaaf, Martin

2014-01-01

Knowing the depth structure of the environment is crucial for moving animals in many behavioral contexts, such as collision avoidance, targeting objects, or spatial navigation. An important source of depth information is motion parallax. This powerful cue is generated on the eyes during translatory self-motion with the retinal images of nearby objects moving faster than those of distant ones. To investigate how the visual motion pathway represents motion-based depth information we analyzed its responses to image sequences recorded in natural cluttered environments with a wide range of depth structures. The analysis was done on the basis of an experimentally validated model of the visual motion pathway of insects, with its core elements being correlation-type elementary motion detectors (EMDs). It is the key result of our analysis that the absolute EMD responses, i.e., the motion energy profile, represent the contrast-weighted nearness of environmental structures during translatory self-motion at a roughly constant velocity. In other words, the output of the EMD array highlights contours of nearby objects. This conclusion is largely independent of the scale over which EMDs are spatially pooled and was corroborated by scrutinizing the motion energy profile after eliminating the depth structure from the natural image sequences. Hence, the well-established dependence of correlation-type EMDs on both velocity and textural properties of motion stimuli appears to be advantageous for representing behaviorally relevant information about the environment in a computationally parsimonious way. PMID:25136314

StopWatch: The preliminary evaluation of a smartwatch-based system for passive detection of cigarette smoking.

PubMed

Skinner, Andrew L; Stone, Christopher J; Doughty, Hazel; Munafò, Marcus R

2018-01-24

Recent developments in smoking cessation support systems and interventions have highlighted the requirement for unobtrusive, passive ways to measure smoking behaviour. A number of systems have been developed for this that either use bespoke sensing technology, or expensive combinations of wearables and smartphones. Here we present StopWatch, a system for passive detection of cigarette smoking that runs on a low-cost smartwatch and does not require additional sensing or a connected smartphone. Our system uses motion data from the accelerometer and gyroscope in an Android smartwatch to detect the signature hand movements of cigarette smoking. It uses machine learning techniques to transform raw motion data into motion features, and in turn into individual drags and instances of smoking. These processes run on the smartwatch, and do not require a smartphone. We conducted preliminary validations of the system in daily smokers (n=13) in laboratory and free-living conditions running on an Android LG G-Watch. In free-living conditions, over a 24-hour period, the system achieved precision of 86% and recall of 71%. StopWatch is a system for passive measurement of cigarette smoking that runs entirely on a commercially available Android smartwatch. It requires no smartphone so the cost is low, and needs no bespoke sensing equipment so participant burden is also low. Performance is currently lower than other more expensive and complex systems, though adequate for some applications. Future developments will focus on enhancing performance, validation on a range of smartwatches, and detection of electronic cigarette use. We present a low-cost, smartwatch-based system for passive detection of cigarette smoking. It uses data from the motion sensors in the watch to identify the signature hand movements of cigarette smoking. The system will provide the detailed measures of individual smoking behaviour needed for context-triggered just-in-time smoking cessation support systems, and to enable just-in-time adaptive interventions. More broadly, the system will enable researchers to obtain detailed measures of individual smoking behaviour in free-living conditions that are free from the recall errors and reporting biases associated with self-report of smoking. © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.

People detection method using graphics processing units for a mobile robot with an omnidirectional camera

NASA Astrophysics Data System (ADS)

Kang, Sungil; Roh, Annah; Nam, Bodam; Hong, Hyunki

2011-12-01

This paper presents a novel vision system for people detection using an omnidirectional camera mounted on a mobile robot. In order to determine regions of interest (ROI), we compute a dense optical flow map using graphics processing units, which enable us to examine compliance with the ego-motion of the robot in a dynamic environment. Shape-based classification algorithms are employed to sort ROIs into human beings and nonhumans. The experimental results show that the proposed system detects people more precisely than previous methods.

SU-E-J-172: Development of a Video Guided Real-Time Patient Motion Monitoring System for Helical Tomotherpay.

PubMed

Ju, S; Hong, C; Yim, D; Kim, M; Kim, J; Han, Y; Shin, J; Shin, E; Ahn, S; Choi, D

2012-06-01

We developed a video image-guided real-time patient motion monitoring system for helical Tomotherapy (VGRPM-Tomo), and its clinical utility was evaluated using a motion phantom. The VGRPM-Tomo consisted of three components: an image acquisition device consisting of two PC-cams, a main control computer with a radiation signal controller and warning system, and patient motion analysis software, which was developed in house. The system was designed for synchronization with a beam on/off trigger signal to limit operation during treatment time only and to enable system automation. In order to detect the patient motion while the couch is moving into the gantry, a reference image, which continuously updated its background by exponential weighting filter (EWF), is compared with subsequent live images using the real-time frame difference-based analysis software. When the error range exceeds the set criteria (δ_movement) due to patient movement, a warning message is generated in the form of light and sound. The described procedure repeats automatically for each patient. A motion phantom, which operates by moving a distance of 0.1, 0.2, 0.5, and 1.0 cm for 1 and 2 sec, respectively, was used to evaluate the system performance at maximum couch speed (0.196 cm/sec) in a Helical Tomotherapy (HD, Hi-art, Tomotherapy, USA). We measured the optimal EWF factor (a) and δ_movement, which is the minimum distance that can be detected with this system, and the response time of the whole system. The optimal a for clinical use ranged from 0.85 to 0.9. The system was able to detect phantom motion as small as 0.2 cm with tight δ_movement, 0.1% total number of pixels in the reference image. The measured response time of the whole system was 0.1 sec. The VGRPM-tomo can contribute to reduction of treatment error caused by the motion of patients and increase the accuracy of treatment dose delivery in HD. This work was supported by the Technology Innovation Program, 10040362, Development of an integrated management solution for radiation therapy funded by the Ministry of Knowledge Economy (MKE, Korea). This idea is protected by a Korean patent (patent no. 10-1007367). © 2012 American Association of Physicists in Medicine.

An integrated framework for detecting suspicious behaviors in video surveillance

NASA Astrophysics Data System (ADS)

Zin, Thi Thi; Tin, Pyke; Hama, Hiromitsu; Toriu, Takashi

2014-03-01

In this paper, we propose an integrated framework for detecting suspicious behaviors in video surveillance systems which are established in public places such as railway stations, airports, shopping malls and etc. Especially, people loitering in suspicion, unattended objects left behind and exchanging suspicious objects between persons are common security concerns in airports and other transit scenarios. These involve understanding scene/event, analyzing human movements, recognizing controllable objects, and observing the effect of the human movement on those objects. In the proposed framework, multiple background modeling technique, high level motion feature extraction method and embedded Markov chain models are integrated for detecting suspicious behaviors in real time video surveillance systems. Specifically, the proposed framework employs probability based multiple backgrounds modeling technique to detect moving objects. Then the velocity and distance measures are computed as the high level motion features of the interests. By using an integration of the computed features and the first passage time probabilities of the embedded Markov chain, the suspicious behaviors in video surveillance are analyzed for detecting loitering persons, objects left behind and human interactions such as fighting. The proposed framework has been tested by using standard public datasets and our own video surveillance scenarios.

Coronary calcium visualization using dual energy chest radiography with sliding organ registration

NASA Astrophysics Data System (ADS)

Wen, Di; Nye, Katelyn; Zhou, Bo; Gilkeson, Robert C.; Wilson, David L.

2016-03-01

Coronary artery calcification (CAC) is the lead biomarker for atherosclerotic heart disease. We are developing a new technique to image CAC using ubiquitously ordered, low cost, low radiation dual energy (DE) chest radiography (using the two-shot GE Revolution XRd system). In this paper, we proposed a novel image processing method (CorCalDx) based on sliding organ registration to create a bone-image-like, coronary calcium image (CCI) that significantly reduces motion artifacts and improves CAC conspicuity. Experiments on images of a physical dynamic cardiac phantom showed that CorCalDx reduced 73% of the motion artifact area as compared to standard DE over a range of heart rates up to 90 bpm and varying x-ray radiation exposures. Residual motion artifact in the phantom CCI is greatly suppressed in gray level and area (0.88% of the heart area). In a Functional Measurement Test (FMT) with 20 clinical exams, image quality improvement of CorCalDx against standard DE (measured from -10 to +10) was significantly suggested (p<0.0001) by three radiologists for cardiac motion artifacts (7.2+/-2.1) and cardiac anatomy visibility (6.1+/-3.5). CorCalDx was always chosen best in every image tested. In preliminary assessments of 12 patients with 18 calcifications, 90% of motion artifact regions in standard DE results were removed in CorCalDx results, with 100% sensitivity of calcification detection, showing great potential of CorCalDx to improve CAC detection and grading in DE chest radiography.

Stereo-motion cooperation and the use of motion disparity in the visual perception of 3-D structure.

PubMed

Cornilleau-Pérès, V; Droulez, J

1993-08-01

When an observer views a moving scene binocularly, both motion parallax and binocular disparity provide depth information. In Experiments 1A-1C, we measured sensitivity to surface curvature when these depth cues were available either individually or simultaneously. When the depth cues yielded comparable sensitivity to surface curvature, we found that curvature detection was easier with the cues present simultaneously, rather than individually. For 2 of the 6 subjects, this effect was stronger when the component of frontal translation of the surface was vertical, rather than horizontal. No such anisotropy was found for the 4 other subjects. If a moving object is observed binocularly, the patterns of optic flow are different on the left and right retinae. We have suggested elsewhere (Cornilleau-Pérès & Droulez, in press) that this motion disparity might be used as a visual cue for the perception of a 3-D structure. Our model consisted in deriving binocular disparity from the left and right distributions of vertical velocities, rather than from luminous intensities, as has been done in classical studies on stereoscopic vision. The model led to some predictions concerning the detection of surface curvature from motion disparity in the presence or absence of intensity-based disparity (classically termed binocular disparity). In a second set of experiments, we attempted to test these predictions, and we failed to validate our theoretical scheme from a physiological point of view.

From Supercomputer Modeling to Highest Mass Resolution in FT-ICR.

PubMed

N Nikolaev, Evgene; N Vladimirov, Gleb; Jertz, Roland; Baykut, Gökhan

2013-01-01

Understanding of behavior of ion ensembles inside FT-ICR cell based on the computer simulation of ion motion gives rise to the new ideas of cell designs. The recently introduced novel FT-ICR cell based on a Penning ion trap with specially shaped excitation and detection electrodes prevents distortion of ion cyclotron motion phases (normally caused by non-ideal electric trapping fields) by averaging the trapping DC electric field during the ion motion in the ICR cell. Detection times of 5 min resulting in resolving power close to 40,000,000 have been reached for reserpine at m/z 609 at a magnetic field of only 7 Tesla. Fine structures of resolved 13Cn isotopic cluster groups could be measured for molecular masses up to 5.7 kDa (insulin) with resolving power of 4,000,000 at 7 Tesla. Based on resolved fine structure patterns atomic compositions can be directly determined using a new developed algorithm for fine structure processing. Mass spectra of proteins and multimers of proteins reaching masses up to 186 kDa (enolase tetramer) could be measured with isotopic resolution. For instance, at 7 Tesla resolving power of 800,000 was achieved for enolase dimer (96 kDa) and 500,000 for molecular masses above 100 kDa. Experimental data indicate that there is practically no limit for the resolving power of this ICR cell except by collisional damping in the ultrahigh vacuum chamber.

Small-scale heat detection using catalytic microengines irradiated by laser

NASA Astrophysics Data System (ADS)

Liu, Zhaoqian; Li, Jinxing; Wang, Jiao; Huang, Gaoshan; Liu, Ran; Mei, Yongfeng

2013-01-01

We demonstrate a novel approach to modulating the motion speed of catalytic microtubular engines via laser irradiation/heating with regard to small-scale heat detection. Laser irradiation on the engines leads to a thermal heating effect and thus enhances the engine speed. During a laser on/off period, the motion behaviour of a microengine can be repeatable and reversible, demonstrating a regulation of motion speeds triggered by laser illumination. Also, the engine velocity exhibits a linear dependence on laser power in various fuel concentrations, which implies an application potential as local heat sensors. Our work may hold great promise in applications such as lab on a chip, micro/nano factories, and environmental detection.We demonstrate a novel approach to modulating the motion speed of catalytic microtubular engines via laser irradiation/heating with regard to small-scale heat detection. Laser irradiation on the engines leads to a thermal heating effect and thus enhances the engine speed. During a laser on/off period, the motion behaviour of a microengine can be repeatable and reversible, demonstrating a regulation of motion speeds triggered by laser illumination. Also, the engine velocity exhibits a linear dependence on laser power in various fuel concentrations, which implies an application potential as local heat sensors. Our work may hold great promise in applications such as lab on a chip, micro/nano factories, and environmental detection. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr32494f

Vision-Based Finger Detection, Tracking, and Event Identification Techniques for Multi-Touch Sensing and Display Systems

PubMed Central

Chen, Yen-Lin; Liang, Wen-Yew; Chiang, Chuan-Yen; Hsieh, Tung-Ju; Lee, Da-Cheng; Yuan, Shyan-Ming; Chang, Yang-Lang

2011-01-01

This study presents efficient vision-based finger detection, tracking, and event identification techniques and a low-cost hardware framework for multi-touch sensing and display applications. The proposed approach uses a fast bright-blob segmentation process based on automatic multilevel histogram thresholding to extract the pixels of touch blobs obtained from scattered infrared lights captured by a video camera. The advantage of this automatic multilevel thresholding approach is its robustness and adaptability when dealing with various ambient lighting conditions and spurious infrared noises. To extract the connected components of these touch blobs, a connected-component analysis procedure is applied to the bright pixels acquired by the previous stage. After extracting the touch blobs from each of the captured image frames, a blob tracking and event recognition process analyzes the spatial and temporal information of these touch blobs from consecutive frames to determine the possible touch events and actions performed by users. This process also refines the detection results and corrects for errors and occlusions caused by noise and errors during the blob extraction process. The proposed blob tracking and touch event recognition process includes two phases. First, the phase of blob tracking associates the motion correspondence of blobs in succeeding frames by analyzing their spatial and temporal features. The touch event recognition process can identify meaningful touch events based on the motion information of touch blobs, such as finger moving, rotating, pressing, hovering, and clicking actions. Experimental results demonstrate that the proposed vision-based finger detection, tracking, and event identification system is feasible and effective for multi-touch sensing applications in various operational environments and conditions. PMID:22163990

Vocal fold motion outcome based on excellent prognosis with laryngeal electromyography.

PubMed

Smith, Libby J; Rosen, Clark A; Munin, Michael C

2016-10-01

As laryngeal electromyography (LEMG) becomes more refined, accurate predictions of vocal fold motion recovery are possible. Focus has been on outcomes for patients with poor prognosis for vocal fold motion recovery. Limited information is available regarding the expected rate of purposeful vocal fold motion recovery when there is good to normal motor recruitment, no signs of denervation, and no signs of synkinetic activity with LEMG, termed excellent prognosis. The objective of this study is to determine the rate of vocal fold motion recovery with excellent prognosis findings on LEMG after acute recurrent laryngeal nerve injury. Retrospective review. Patients undergoing a standardized LEMG protocol, consisting of qualitative (evaluation of motor recruitment, motor unit configuration, detection of fibrillations, presence of synkinesis) and quantitative (turns analysis) measurements were evaluated for purposeful vocal-fold motion recovery, calculated after at least 6 months since onset of injury. Twenty-three patients who underwent LEMG for acute vocal fold paralysis met the inclusion criteria of excellent prognosis. Eighteen patients (78.3%) recovered vocal fold motion, as determined by flexible laryngoscopy. Nearly 80% of patients determined to have excellent prognosis for vocal fold motion recovery experienced return of vocal fold motion. This information will help clinicians not only counsel their patients on expectations but will also help guide treatment. 4. Laryngoscope, 126:2310-2314, 2016. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Local collective motion analysis for multi-probe dynamic imaging and microrheology

NASA Astrophysics Data System (ADS)

Khan, Manas; Mason, Thomas G.

2016-08-01

Dynamical artifacts, such as mechanical drift, advection, and hydrodynamic flow, can adversely affect multi-probe dynamic imaging and passive particle-tracking microrheology experiments. Alternatively, active driving by molecular motors can cause interesting non-Brownian motion of probes in local regions. Existing drift-correction techniques, which require large ensembles of probes or fast temporal sampling, are inadequate for handling complex spatio-temporal drifts and non-Brownian motion of localized domains containing relatively few probes. Here, we report an analytical method based on local collective motion (LCM) analysis of as few as two probes for detecting the presence of non-Brownian motion and for accurately eliminating it to reveal the underlying Brownian motion. By calculating an ensemble-average, time-dependent, LCM mean square displacement (MSD) of two or more localized probes and comparing this MSD to constituent single-probe MSDs, we can identify temporal regimes during which either thermal or athermal motion dominates. Single-probe motion, when referenced relative to the moving frame attached to the multi-probe LCM trajectory, provides a true Brownian MSD after scaling by an appropriate correction factor that depends on the number of probes used in LCM analysis. We show that LCM analysis can be used to correct many different dynamical artifacts, including spatially varying drifts, gradient flows, cell motion, time-dependent drift, and temporally varying oscillatory advection, thereby offering a significant improvement over existing approaches.

Direction detection thresholds of passive self-motion in artistic gymnasts.

PubMed

Hartmann, Matthias; Haller, Katia; Moser, Ivan; Hossner, Ernst-Joachim; Mast, Fred W

2014-04-01

In this study, we compared direction detection thresholds of passive self-motion in the dark between artistic gymnasts and controls. Twenty-four professional female artistic gymnasts (ranging from 7 to 20 years) and age-matched controls were seated on a motion platform and asked to discriminate the direction of angular (yaw, pitch, roll) and linear (leftward-rightward) motion. Gymnasts showed lower thresholds for the linear leftward-rightward motion. Interestingly, there was no difference for the angular motions. These results show that the outstanding self-motion abilities in artistic gymnasts are not related to an overall higher sensitivity in self-motion perception. With respect to vestibular processing, our results suggest that gymnastic expertise is exclusively linked to superior interpretation of otolith signals when no change in canal signals is present. In addition, thresholds were overall lower for the older (14-20 years) than for the younger (7-13 years) participants, indicating the maturation of vestibular sensitivity from childhood to adolescence.

Optical coherence tomography speckle decorrelation for detecting cell death

NASA Astrophysics Data System (ADS)

Farhat, Golnaz; Mariampillai, Adrian; Yang, Victor X. D.; Czarnota, Gregory J.; Kolios, Michael C.

2011-03-01

We present a dynamic light scattering technique applied to optical coherence tomography (OCT) for detecting changes in intracellular motion caused by cellular reorganization during apoptosis. We have validated our method by measuring Brownian motion in microsphere suspensions and comparing the measured values to those derived based on particle diffusion calculated using the Einstein-Stokes equation. Autocorrelations of OCT signal intensities acquired from acute myeloid leukemia cells as a function of treatment time demonstrated a significant drop in the decorrelation time after 24 hours of cisplatin treatment. This corresponded with nuclear fragmentation and irregular cell shape observed in histological sections. A similar analysis conducted with multicellular tumor spheroids indicated a shorter decorrelation time in the spheroid core relative to its edges. The spheroid core corresponded to a region exhibiting signs of cell death in histological sections and increased backscatter intensity in OCT images.

A new full-field interferometry approach for counting and differentiating aquatic biotic nanoparticles (Conference Presentation)

NASA Astrophysics Data System (ADS)

Boccara, A. Claude; Fedala, Yasmina; Voronkoff, Justine; Paffoni, Nina; Boccara, Martine

2017-03-01

Due to the huge abundance and the major role that viruses and membrane vesicles play in the seas or rivers ecosystems it is necessary to develop simple, sensitive, compact and reliable methods for their detection and characterization. Our approach is based on the measurement of the weak light level scattered by the biotic nanoparticles. We describe a new full-field, incoherently illuminated, shot-noise limited, common-path interferometric detection method coupled with the analysis of Brownian motion to detect, quantify, and differentiate biotic nanoparticles. The last developments take advantage of a new fast (700 Hz) camera with 2 Me- full well capacity that improves the signal to noise ratio and increases the precision of the Brownian motion characterization. We validated the method with calibrated nanoparticles and homogeneous DNA or RNA.viruses. The smallest virus size that we characterized with a suitable signal-to-noise ratio was around 30 nm in diameter with a target towards the numerous 20 nm diameter viruses. We show for the first time anisotropic trajectories for myoviruses meaning that there is a memory of the initial direction of their Brownian motions. Significant improvements have been made in the handling of the sample as well as in the statistical analysis for differentiating the various families of vesicles and virus. We further applied the method for vesicles detection and for analysis of coastal and oligotrophic samples from Tara Oceans circumnavigation as well of various rivers.

SU-D-17A-07: Development and Evaluation of a Prototype Ultrasonography Respiratory Monitoring System for 4DCT Reconstruction

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

Yan, P; Cheng, S; Chao, C

Purpose: Respiratory motion artifacts are commonly seen in the abdominal and thoracic CT images. A Real-time Position Management (RPM) system is integrated with CT simulator using abdominal surface as a surrogate for tracking the patient respiratory motion. The respiratory-correlated four-dimensional computed tomography (4DCT) is then reconstructed by GE advantage software. However, there are still artifacts due to inaccurate respiratory motion detecting and sorting methods. We developed an Ultrasonography Respiration Monitoring (URM) system which can directly monitor diaphragm motion to detect respiratory cycles. We also developed a new 4DCT sorting and motion estimation method to reduce the respiratory motion artifacts. Themore » new 4DCT system was compared with RPM and the GE 4DCT system. Methods: Imaging from a GE CT scanner was simultaneously correlated with both the RPM and URM to detect respiratory motion. A radiation detector, Blackcat GM-10, recorded the X-ray on/off and synchronized with URM. The diaphragm images were acquired with Ultrasonix RP system. The respiratory wave was derived from diaphragm images and synchronized with CT scanner. A more precise peaks and valleys detection tool was developed and compared with RPM. The motion is estimated for the slices which are not in the predefined respiratory phases by using block matching and optical flow method. The CT slices were then sorted into different phases and reconstructed, compared with the images reconstructed from GE Advantage software using respiratory wave produced from RPM system. Results: The 4DCT images were reconstructed for eight patients. The discontinuity at the diaphragm level due to an inaccurate identification of phases by the RPM was significantly improved by URM system. Conclusion: Our URM 4DCT system was evaluated and compared with RPM and GE 4DCT system. The new system is user friendly and able to reduce motion artifacts. It also has the potential to monitor organ motion during therapy.« less

Non-Verbal IQ Is Correlated with Visual Field Advantages for Short Duration Coherent Motion Detection in Deaf Signers with Varied ASL Exposure and Etiologies of Deafness

ERIC Educational Resources Information Center

Samar, Vincent J.; Parasnis, Ila

2007-01-01

Studies have reported a right visual field (RVF) advantage for coherent motion detection by deaf and hearing signers but not non-signers. Yet two studies [Bosworth R. G., & Dobkins, K. R. (2002). Visual field asymmetries for motion processing in deaf and hearing signers. "Brain and Cognition," 49, 170-181; Samar, V. J., & Parasnis, I. (2005).…

Thermal effects on nonlinear vibration of a carbon nanotube-based mass sensor using finite element analysis

NASA Astrophysics Data System (ADS)

Kang, Dong-Keun; Kim, Chang-Wan; Yang, Hyun-Ik

2017-01-01

In the present study we carried out a dynamic analysis of a CNT-based mass sensor by using a finite element method (FEM)-based nonlinear analysis model of the CNT resonator to elucidate the combined effects of thermal effects and nonlinear oscillation behavior upon the overall mass detection sensitivity. Mass sensors using carbon nanotube (CNT) resonators provide very high sensing performance. Because CNT-based resonators can have high aspect ratios, they can easily exhibit nonlinear oscillation behavior due to large displacements. Also, CNT-based devices may experience high temperatures during their manufacture and operation. These geometrical nonlinearities and temperature changes affect the sensing performance of CNT-based mass sensors. However, it is very hard to find previous literature addressing the detection sensitivity of CNT-based mass sensors including considerations of both these nonlinear behaviors and thermal effects. We modeled the nonlinear equation of motion by using the von Karman nonlinear strain-displacement relation, taking into account the additional axial force associated with the thermal effect. The FEM was employed to solve the nonlinear equation of motion because it can effortlessly handle the more complex geometries and boundary conditions. A doubly clamped CNT resonator actuated by distributed electrostatic force was the configuration subjected to the numerical experiments. Thermal effects upon the fundamental resonance behavior and the shift of resonance frequency due to attached mass, i.e., the mass detection sensitivity, were examined in environments of both high and low (or room) temperature. The fundamental resonance frequency increased with decreasing temperature in the high temperature environment, and increased with increasing temperature in the low temperature environment. The magnitude of the shift in resonance frequency caused by an attached mass represents the sensing performance of a mass sensor, i.e., its mass detection sensitivity, and it can be seen that this shift is affected by the temperature change and the amount of electrostatic force. The thermal effects on the mass detection sensitivity are intensified in the linear oscillation regime and increase with increasing CNT length; this intensification can either improve or worsen the detection sensitivity.

An adaptive field detection method for bridge scour monitoring using motion-sensing radio transponders (RFIDs).

DOT National Transportation Integrated Search

2014-01-01

A comprehensive field detection method is proposed that is aimed at developing advanced capability for : reliable monitoring, inspection and life estimation of bridge infrastructure. The goal is to utilize Motion-Sensing Radio Transponders (RFIDS) on...

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.

Robust laser-based detection of Lamb waves using photo-EMF sensors

NASA Astrophysics Data System (ADS)

Klein, Marvin B.; Bacher, Gerald D.

1998-03-01

Lamb waves are easily generated and detected using laser techniques. It has been shown that both symmetric and antisymmetric modes can be produced, using single-spot and phased array generation. Detection has been demonstrated with Michelson interferometers, but these instruments can not function effectively on rough surfaces. By contrast, the confocal Fabry-Perot interferometer can interrogate rough surfaces, but generally is not practical for operation below 300 kHz. In this paper we will present Lamb wave data on a number of parts using a robust, adaptive receiver based on photo-emf detection. This receiver has useful sensitivity down to at least 100 kHz, can process speckled beams and can be easily configured to measure both out-of-plane and in- plane motion with a single probe beam.

Real-time myocardial perfusion imaging for pharmacologic stress testing: added value to single photon emission computed tomography.

PubMed

Korosoglou, Grigorios; Dubart, Alain-Eric; DaSilva, K Gaspar C; Labadze, Nino; Hardt, Stefan; Hansen, Alexander; Bekeredjian, Raffi; Zugck, Christian; Zehelein, Joerg; Katus, Hugo A; Kuecherer, Helmut

2006-01-01

Little is known about the incremental value of real-time myocardial contrast echocardiography (MCE) as an adjunct to pharmacologic stress testing. This study was performed to evaluate the diagnostic value of MCE to detect abnormal myocardial perfusion by technetium Tc 99m sestamibi-single photon emission computed tomography (SPECT) and anatomically significant coronary artery disease (CAD) by angiography. Myocardial contrast echocardiography was performed at rest and during vasodilator stress in consecutive patients (N = 120) undergoing SPECT imaging for known or suspected CAD. Myocardial opacification, wall motion, and tracer uptake were visually analyzed in 12 myocardial segments by 2 pairs of blinded observers. Concordance between the 2 methods was assessed using the kappa statistic. Of 1356 segments, 1025 (76%) were interpretable by MCE, wall motion, and SPECT. Sensitivity of wall motion was 75%, specificity 83%, and accuracy 81% for detecting abnormal myocardial perfusion by SPECT (kappa = 0.53). Myocardial contrast echocardiography and wall motion together yielded significantly higher sensitivity (85% vs 74%, P < .05), specificity of 83%, and accuracy of 85% (kappa = 0.64) for the detection of abnormal myocardial perfusion. In 89 patients who underwent coronary angiography, MCE and wall motion together yielded higher sensitivity (83% vs 64%, P < .05) and accuracy (77% vs 68%, P < .05) but similar specificity (72%) compared with SPECT for the detection of high-grade, stenotic (> or = 75%) coronary lesions. Assessment of myocardial perfusion adds value to conventional stress echocardiography by increasing its sensitivity for the detection of functionally abnormal myocardial perfusion. Myocardial contrast echocardiography and wall motion together provide higher sensitivity and accuracy for detection of CAD compared with SPECT.

Usefulness of free-breathing readout-segmented echo-planar imaging (RESOLVE) for detection of malignant liver tumors: comparison with single-shot echo-planar imaging (SS-EPI).

PubMed

Tokoro, Hirokazu; Fujinaga, Yasunari; Ohya, Ayumi; Ueda, Kazuhiko; Shiobara, Aya; Kitou, Yoshihiro; Ueda, Hitoshi; Kadoya, Masumi

2014-10-01

We aimed to clarify the usefulness of free-breathing readout-segmented echo-planar imaging (RESOLVE), which is multi-shot echo-planar imaging based on a 2D-navigator-based reacquisition technique, for detecting malignant liver tumor. In 77 patients with malignant liver tumors, free-breathing RESOLVE and respiratory-triggered single-shot echo-planar imaging (SS-EPI) at 3-T MR unit were performed. We set a scan time up to approximately 5 min (300s) before examination, measured actual scan time and assessed (1) susceptibility and (2) motion artifacts in the right and left liver lobes (3, no artifact; 1, marked), and (3) detectability of malignant liver tumors (3, good; 1, poor) using a 3-point scale. The median actual scan time of RESOLVE/SS-EPI was 365/423s. The median scores of each factor in RESOLVE/SS-EPI were as following in this order: (1) 3/2 (right lobe); 3/3 (left lobe), (2) 2/3 (right lobe); 1/2 (left lobe), and (3) 3/3, respectively. Significant differences were noted between RESOLVE and SS-EPI in all evaluated factors (P<0.05) except for susceptibility of left lobe and detectability of the lesions. Despite the effect of motion artifacts, RESOLVE provides a comparable detectability of the lesion and the advantage of reducing scanning time compared with SS-EPI. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Motion measurement of acoustically levitated object

NASA Technical Reports Server (NTRS)

Watkins, John L. (Inventor); Barmatz, Martin B. (Inventor)

1993-01-01

A system is described for determining motion of an object that is acoustically positioned in a standing wave field in a chamber. Sonic energy in the chamber is sensed, and variation in the amplitude of the sonic energy is detected, which is caused by linear motion, rotational motion, or drop shape oscillation of the object. Apparatus for detecting object motion can include a microphone coupled to the chamber and a low pass filter connected to the output of the microphone, which passes only frequencies below the frequency of sound produced by a transducer that maintains the acoustic standing wave field. Knowledge about object motion can be useful by itself, can be useful to determine surface tension, viscosity, and other information about the object, and can be useful to determine the pressure and other characteristics of the acoustic field.

Clock Synchronization Through Time-Variant Underwater Acoustic Channels

DTIC Science & Technology

2012-09-01

stage, we analyze a series of chirp responses to identify the least time -varying multipath present in the channel between the two nodes. Based on the... based on the detected arrivals and determines the most stable one based on the correlation coefficient of a model fit to the time -of-arrival estimates...short periods of time . Nevertheless, signal fluctuations can occur due to transceiver motion or inherent changes within the propagation medium

Content-based video retrieval by example video clip

NASA Astrophysics Data System (ADS)

Dimitrova, Nevenka; Abdel-Mottaleb, Mohamed

1997-01-01

This paper presents a novel approach for video retrieval from a large archive of MPEG or Motion JPEG compressed video clips. We introduce a retrieval algorithm that takes a video clip as a query and searches the database for clips with similar contents. Video clips are characterized by a sequence of representative frame signatures, which are constructed from DC coefficients and motion information (`DC+M' signatures). The similarity between two video clips is determined by using their respective signatures. This method facilitates retrieval of clips for the purpose of video editing, broadcast news retrieval, or copyright violation detection.

Comparing consistency of R2* and T2*-weighted BOLD analysis of resting state fetal fMRI

NASA Astrophysics Data System (ADS)

Seshamani, Sharmishtaa; Blazejewska, Anna I.; Gatenby, Christopher; Mckown, Susan; Caucutt, Jason; Dighe, Manjiri; Studholme, Colin

2015-03-01

Understanding when and how resting state brain functional activity begins in the human brain is an increasing area of interest in both basic neuroscience and in the clinical evaluation of the brain during pregnancy and after premature birth. Although fMRI studies have been carried out on pregnant women since the 1990's, reliable mapping of brain function in utero is an extremely challenging problem due to the unconstrained fetal head motion. Recent studies have employed scrubbing to exclude parts of the time series and whole subjects from studies in order to control the confounds of motion. Fundamentally, even after correction of the location of signals due to motion, signal intensity variations are a fundamental limitation, due to coil sensitivity and spin history effects. An alternative technique is to use a more parametric MRI signal derived from multiple echoes that provides a level of independence from basic MRI signal variation. Here we examine the use of R2* mapping combined with slice based multi echo geometric distortion correction for in-utero studies. The challenges for R2* mapping arise from the relatively low signal strength of in-utero data. In this paper we focus on comparing activation detection in-utero using T2W and R2* approaches. We make use a subset of studies with relatively limited motion to compare the activation patterns without the additional confound of significant motion. Results at different gestational ages indicate comparable agreement in many activation patterns when limited motion is present, and the detection of some additional networks in the R2* data, not seen in the T2W results.

Thermal bioaerosol cloud tracking with Bayesian classification

NASA Astrophysics Data System (ADS)

Smith, Christian W.; Dupuis, Julia R.; Schundler, Elizabeth C.; Marinelli, William J.

2017-05-01

The development of a wide area, bioaerosol early warning capability employing existing uncooled thermal imaging systems used for persistent perimeter surveillance is discussed. The capability exploits thermal imagers with other available data streams including meteorological data and employs a recursive Bayesian classifier to detect, track, and classify observed thermal objects with attributes consistent with a bioaerosol plume. Target detection is achieved based on similarity to a phenomenological model which predicts the scene-dependent thermal signature of bioaerosol plumes. Change detection in thermal sensor data is combined with local meteorological data to locate targets with the appropriate thermal characteristics. Target motion is tracked utilizing a Kalman filter and nearly constant velocity motion model for cloud state estimation. Track management is performed using a logic-based upkeep system, and data association is accomplished using a combinatorial optimization technique. Bioaerosol threat classification is determined using a recursive Bayesian classifier to quantify the threat probability of each tracked object. The classifier can accept additional inputs from visible imagers, acoustic sensors, and point biological sensors to improve classification confidence. This capability was successfully demonstrated for bioaerosol simulant releases during field testing at Dugway Proving Grounds. Standoff detection at a range of 700m was achieved for as little as 500g of anthrax simulant. Developmental test results will be reviewed for a range of simulant releases, and future development and transition plans for the bioaerosol early warning platform will be discussed.

Image-based fall detection and classification of a user with a walking support system

NASA Astrophysics Data System (ADS)

Taghvaei, Sajjad; Kosuge, Kazuhiro

2017-10-01

The classification of visual human action is important in the development of systems that interact with humans. This study investigates an image-based classification of the human state while using a walking support system to improve the safety and dependability of these systems.We categorize the possible human behavior while utilizing a walker robot into eight states (i.e., sitting, standing, walking, and five falling types), and propose two different methods, namely, normal distribution and hidden Markov models (HMMs), to detect and recognize these states. The visual feature for the state classification is the centroid position of the upper body, which is extracted from the user's depth images. The first method shows that the centroid position follows a normal distribution while walking, which can be adopted to detect any non-walking state. The second method implements HMMs to detect and recognize these states. We then measure and compare the performance of both methods. The classification results are employed to control the motion of a passive-type walker (called "RT Walker") by activating its brakes in non-walking states. Thus, the system can be used for sit/stand support and fall prevention. The experiments are performed with four subjects, including an experienced physiotherapist. Results show that the algorithm can be adapted to the new user's motion pattern within 40 s, with a fall detection rate of 96.25% and state classification rate of 81.0%. The proposed method can be implemented to other abnormality detection/classification applications that employ depth image-sensing devices.

Development and clinical evaluation of a simple optical method to detect and measure patient external motion.

PubMed

Barbés, Benigno; Azcona, Juan Diego; Prieto, Elena; de Foronda, José Manuel; García, Marina; Burguete, Javier

2015-09-08

A simple and independent system to detect and measure the position of a number of points in space was devised and implemented. Its application aimed to detect patient motion during radiotherapy treatments, alert of out-of-tolerances motion, and record the trajectories for subsequent studies. The system obtains the 3D position of points in space, through its projections in 2D images recorded by two cameras. It tracks black dots on a white sticker placed on the surface of the moving object. The system was tested with linear displacements of a phantom, circular trajectories of a rotating disk, oscillations of an in-house phantom, and oscillations of a 4D phantom. It was also used to track 461 trajectories of points on the surface of patients during their radiotherapy treatments. Trajectories of several points were reproduced with accuracy better than 0.3 mm in the three spatial directions. The system was able to follow periodic motion with amplitudes lower than 0.5 mm, to follow trajectories of rotating points at speeds up to 11.5 cm/s, and to track accurately the motion of a respiratory phantom. The technique has been used to track the motion of patients during radiotherapy and to analyze that motion. The method is flexible. Its installation and calibration are simple and quick. It is easy to use and can be implemented at a very affordable price. Data collection does not involve any discomfort to the patient and does not delay the treatment, so the system can be used routinely in all treatments. It has an accuracy similar to that of other, more sophisticated, commercially available systems. It is suitable to implement a gating system or any other application requiring motion detection, such as 4D CT, MRI or PET.

Four Types of Pulse Oximeters Accurately Detect Hypoxia during Low Perfusion and Motion.

PubMed

Louie, Aaron; Feiner, John R; Bickler, Philip E; Rhodes, Laura; Bernstein, Michael; Lucero, Jennifer

2018-03-01

Pulse oximeter performance is degraded by motion artifacts and low perfusion. Manufacturers developed algorithms to improve instrument performance during these challenges. There have been no independent comparisons of these devices. We evaluated the performance of four pulse oximeters (Masimo Radical-7, USA; Nihon Kohden OxyPal Neo, Japan; Nellcor N-600, USA; and Philips Intellivue MP5, USA) in 10 healthy adult volunteers. Three motions were evaluated: tapping, pseudorandom, and volunteer-generated rubbing, adjusted to produce photoplethsmogram disturbance similar to arterial pulsation amplitude. During motion, inspired gases were adjusted to achieve stable target plateaus of arterial oxygen saturation (SaO2) at 75%, 88%, and 100%. Pulse oximeter readings were compared with simultaneous arterial blood samples to calculate bias (oxygen saturation measured by pulse oximetry [SpO2] - SaO2), mean, SD, 95% limits of agreement, and root mean square error. Receiver operating characteristic curves were determined to detect mild (SaO2 < 90%) and severe (SaO2 < 80%) hypoxemia. Pulse oximeter readings corresponding to 190 blood samples were analyzed. All oximeters detected hypoxia but motion and low perfusion degraded performance. Three of four oximeters (Masimo, Nellcor, and Philips) had root mean square error greater than 3% for SaO2 70 to 100% during any motion, compared to a root mean square error of 1.8% for the stationary control. A low perfusion index increased error. All oximeters detected hypoxemia during motion and low-perfusion conditions, but motion impaired performance at all ranges, with less accuracy at lower SaO2. Lower perfusion degraded performance in all but the Nihon Kohden instrument. We conclude that different types of pulse oximeters can be similarly effective in preserving sensitivity to clinically relevant hypoxia.

A novel nano-sensor based on optomechanical crystal cavity

NASA Astrophysics Data System (ADS)

Zhang, Yeping; Ai, Jie; Ma, Jingfang

2017-10-01

Optical devices based on new sensing principle are widely used in biochemical and medical area. Nowadays, mass sensing based on monitoring the frequency shifts induced by added mass in oscillators is a well-known and widely used technique. It is interesting to note that for nanoscience and nanotechnology applications there is a strong demand for very sensitive mass sensors, being the target a sensor for single molecule detection. The desired mass resolution for very few or even single molecule detection, has to be below the femtogram range. Considering the strong interaction between high co-localized optical mode and mechanical mode in optomechanical crystal (OMC) cavities, we investigate OMC splitnanobeam cavities in silicon operating near at the 1550nm to achieve high optomechanical coupling rate and ultra-small motion mass. Theoretical investigations of the optical and mechanical characteristic for the proposed cavity are carried out. By adjusting the structural parameters, the cavity's effective motion mass below 10fg and mechanical frequency exceed 10GHz. The transmission spectrum of the cavity is sensitive to the sample which located on the center of the cavity. We conducted the fabrication and the characterization of this cavity sensor on the silicon-on-insulator (SOI) chip. By using vertical coupling between the tapered fiber and the SOI chip, we measured the transmission spectrum of the cavity, and verify this cavity is promising for ultimate precision mass sensing and detection.

Solid state nuclear magnetic resonance investigation of polymer backbone dynamics in poly(ethylene oxide) based lithium and sodium polyether-ester-sulfonate ionomers.

PubMed

Roach, David J; Dou, Shichen; Colby, Ralph H; Mueller, Karl T

2013-05-21

Polymer backbone dynamics of single ion conducting poly(ethylene oxide) (PEO)-based ionomer samples with low glass transition temperatures (T(g)) have been investigated using solid-state nuclear magnetic resonance. Experiments detecting (13)C with (1)H decoupling under magic angle spinning (MAS) conditions identified the different components of the polymer backbone (PEO spacer and isophthalate groups) and their relative mobilities for a suite of lithium- and sodium-containing ionomer samples with varying cation contents. Variable temperature (203-373 K) (1)H-(13)C cross-polarization MAS (CP-MAS) experiments also provided qualitative assessment of the differences in the motions of the polymer backbone components as a function of cation content and identity. Each of the main backbone components exhibit distinct motions, following the trends expected for motional characteristics based on earlier Quasi Elastic Neutron Scattering and (1)H spin-lattice relaxation rate measurements. Previous (1)H and (7)Li spin-lattice relaxation measurements focused on both the polymer backbone and cation motion on the nanosecond timescale. The studies presented here assess the slower timescale motion of the polymer backbone allowing for a more comprehensive understanding of the polymer dynamics. The temperature dependences of (13)C linewidths were used to both qualitatively and quantitatively examine the effects of cation content and identity on PEO spacer mobility. Variable contact time (1)H-(13)C CP-MAS experiments were used to further assess the motions of the polymer backbone on the microsecond timescale. The motion of the PEO spacer, reported via the rate of magnetization transfer from (1)H to (13)C nuclei, becomes similar for T≳1.1 T(g) in all ionic samples, indicating that at similar elevated reduced temperatures the motions of the polymer backbones on the microsecond timescale become insensitive to ion interactions. These results present an improved picture, beyond those of previous findings, for the dependence of backbone dynamics on cation density (and here, cation identity as well) in these amorphous PEO-based ionomer systems.

Blurred digital mammography images: an analysis of technical recall and observer detection performance.

PubMed

Ma, Wang Kei; Borgen, Rita; Kelly, Judith; Millington, Sara; Hilton, Beverley; Aspin, Rob; Lança, Carla; Hogg, Peter

2017-03-01

Blurred images in full-field digital mammography are a problem in the UK Breast Screening Programme. Technical recalls may be due to blurring not being seen on lower resolution monitors used for review. This study assesses the visual detection of blurring on a 2.3-MP monitor and a 5-MP report grade monitor and proposes an observer standard for the visual detection of blurring on a 5-MP reporting grade monitor. 28 observers assessed 120 images for blurring; 20 images had no blurring present, whereas 100 images had blurring imposed through mathematical simulation at 0.2, 0.4, 0.6, 0.8 and 1.0 mm levels of motion. Technical recall rate for both monitors and angular size at each level of motion were calculated. χ 2 tests were used to test whether significant differences in blurring detection existed between 2.3- and 5-MP monitors. The technical recall rate for 2.3- and 5-MP monitors are 20.3% and 9.1%, respectively. The angular size for 0.2- to 1-mm motion varied from 55 to 275 arc s. The minimum amount of motion for visual detection of blurring in this study is 0.4 mm. For 0.2-mm simulated motion, there was no significant difference [χ 2 (1, N = 1095) = 1.61, p = 0.20] in blurring detection between the 2.3- and 5-MP monitors. According to this study, monitors ≤2.3 MP are not suitable for technical review of full-field digital mammography images for the detection of blur. Advances in knowledge: This research proposes the first observer standard for the visual detection of blurring.

Blurred digital mammography images: an analysis of technical recall and observer detection performance

PubMed Central

Borgen, Rita; Kelly, Judith; Millington, Sara; Hilton, Beverley; Aspin, Rob; Lança, Carla; Hogg, Peter

2017-01-01

Objective: Blurred images in full-field digital mammography are a problem in the UK Breast Screening Programme. Technical recalls may be due to blurring not being seen on lower resolution monitors used for review. This study assesses the visual detection of blurring on a 2.3-MP monitor and a 5-MP report grade monitor and proposes an observer standard for the visual detection of blurring on a 5-MP reporting grade monitor. Methods: 28 observers assessed 120 images for blurring; 20 images had no blurring present, whereas 100 images had blurring imposed through mathematical simulation at 0.2, 0.4, 0.6, 0.8 and 1.0 mm levels of motion. Technical recall rate for both monitors and angular size at each level of motion were calculated. χ2 tests were used to test whether significant differences in blurring detection existed between 2.3- and 5-MP monitors. Results: The technical recall rate for 2.3- and 5-MP monitors are 20.3% and 9.1%, respectively. The angular size for 0.2- to 1-mm motion varied from 55 to 275 arc s. The minimum amount of motion for visual detection of blurring in this study is 0.4 mm. For 0.2-mm simulated motion, there was no significant difference [χ2 (1, N = 1095) = 1.61, p = 0.20] in blurring detection between the 2.3- and 5-MP monitors. Conclusion: According to this study, monitors ≤2.3 MP are not suitable for technical review of full-field digital mammography images for the detection of blur. Advances in knowledge: This research proposes the first observer standard for the visual detection of blurring. PMID:28134567

Detection of the Sleep Stages Throughout Non-Obtrusive Measures of Inter-Beat Fluctuations and Motion: Night and Day Sleep of Female Shift Workers

NASA Astrophysics Data System (ADS)

Mendez, Martin O.; Palacios-Hernandez, Elvia R.; Alba, Alfonso; Kortelainen, Juha M.; Tenhunen, Mirja L.; Bianchi, Anna M.

Automatic sleep staging based on inter-beat fluctuations and motion signals recorded through a pressure bed sensor during sleep is presented. The analysis of the sleep was based on the three major divisions of the sleep time: Wake, non-rapid eye movement (nREM) and rapid eye movement (REM) sleep stages. Twelve sleep recordings, from six females working alternate shift, with their respective annotations were used in the study. Six recordings were acquired during the night and six during the day after a night shift. A Time-Variant Autoregressive Model was used to extract features from inter-beat fluctuations which later were fed to a Support Vector Machine classifier. Accuracy, Kappa index, and percentage in wake, REM and nREM were used as performance measures. Comparison between the automatic sleep staging detection and the standard clinical annotations, shows mean values of 87% for accuracy 0.58 for kappa index, and mean errors of 5% for sleep stages. The performance measures were similar for night and day sleep recordings. In this sample of recordings, the results suggest that inter-beat fluctuations and motions acquired in non-obtrusive way carried valuable information related to the sleep macrostructure and could be used to support to the experts in extensive evaluation and monitoring of sleep.

A model describing vestibular detection of body sway motion.

NASA Technical Reports Server (NTRS)

Nashner, L. M.

1971-01-01

An experimental technique was developed which facilitated the formulation of a quantitative model describing vestibular detection of body sway motion in a postural response mode. All cues, except vestibular ones, which gave a subject an indication that he was beginning to sway, were eliminated using a specially designed two-degree-of-freedom platform; body sway was then induced and resulting compensatory responses at the ankle joints measured. Hybrid simulation compared the experimental results with models of the semicircular canals and utricular otolith receptors. Dynamic characteristics of the resulting canal model compared closely with characteristics of models which describe eye movement and subjective responses to body rotational motions. The average threshold level, in the postural response mode, however, was considerably lower. Analysis indicated that the otoliths probably play no role in the initial detection of body sway motion.

Perception of linear acceleration in weightlessness

NASA Technical Reports Server (NTRS)

Arrott, A. P.; Young, L. R.

1987-01-01

Eye movements and subjective detection of acceleration were measured on human experimental subjects during vestibular sled acceleration during the D1 Spacelab Mission. Methods and results are reported on the time to detection of small acceleration steps, the threshold for detection of linear acceleration, perceived motion path, and CLOAT. A consistently shorter time to detection of small acceleration steps is found. Subjective reports of perceived motion during sinusoidal oscillation in weightlessness were qualitatively similar to reports on earth.

Modeling and measuring the visual detection of ecologically relevant motion by an Anolis lizard.

PubMed

Pallus, Adam C; Fleishman, Leo J; Castonguay, Philip M

2010-01-01

Motion in the visual periphery of lizards, and other animals, often causes a shift of visual attention toward the moving object. This behavioral response must be more responsive to relevant motion (predators, prey, conspecifics) than to irrelevant motion (windblown vegetation). Early stages of visual motion detection rely on simple local circuits known as elementary motion detectors (EMDs). We presented a computer model consisting of a grid of correlation-type EMDs, with videos of natural motion patterns, including prey, predators and windblown vegetation. We systematically varied the model parameters and quantified the relative response to the different classes of motion. We carried out behavioral experiments with the lizard Anolis sagrei and determined that their visual response could be modeled with a grid of correlation-type EMDs with a spacing parameter of 0.3 degrees visual angle, and a time constant of 0.1 s. The model with these parameters gave substantially stronger responses to relevant motion patterns than to windblown vegetation under equivalent conditions. However, the model is sensitive to local contrast and viewer-object distance. Therefore, additional neural processing is probably required for the visual system to reliably distinguish relevant from irrelevant motion under a full range of natural conditions.

The UKIDSS-2MASS proper motion survey - I. Ultracool dwarfs from UKIDSS DR4

NASA Astrophysics Data System (ADS)

Deacon, N. R.; Hambly, N. C.; King, R. R.; McCaughrean, M. J.

2009-04-01

The UK Infrared Telescope Infrared Deep Sky Survey (UKIDSS) is the first of a new generation of infrared surveys. Here, we combine the data from two UKIDSS components, the Large Area Survey (LAS) and the Galactic Cluster Survey (GCS), with Two-Micron All-Sky Survey (2MASS) data to produce an infrared proper motion survey for low-mass stars and brown dwarfs. In total, we detect 267 low-mass stars and brown dwarfs with significant proper motions. We recover all 10 known single L dwarfs and the one known T dwarf above the 2MASS detection limit in our LAS survey area and identify eight additional new candidate L dwarfs. We also find one new candidate L dwarf in our GCS sample. Our sample also contains objects from 11 potential common proper motion binaries. Finally, we test our proper motions and find that while the LAS objects have proper motions consistent with absolute proper motions, the GCS stars may have proper motions which are significantly underestimated. This is possibly due to the bulk motion of some of the local astrometric reference stars used in the proper motion determination.

A Possible Role for End-Stopped V1 Neurons in the Perception of Motion: A Computational Model

PubMed Central

Zarei Eskikand, Parvin; Kameneva, Tatiana; Ibbotson, Michael R.; Burkitt, Anthony N.; Grayden, David B.

2016-01-01

We present a model of the early stages of processing in the visual cortex, in particular V1 and MT, to investigate the potential role of end-stopped V1 neurons in solving the aperture problem. A hierarchical network is used in which the incoming motion signals provided by complex V1 neurons and end-stopped V1 neurons proceed to MT neurons at the next stage. MT neurons are categorized into two types based on their function: integration and segmentation. The role of integration neurons is to propagate unambiguous motion signals arriving from those V1 neurons that emphasize object terminators (e.g. corners). Segmentation neurons detect the discontinuities in the input stimulus to control the activity of integration neurons. Although the activity of the complex V1 neurons at the terminators of the object accurately represents the direction of the motion, their level of activity is less than the activity of the neurons along the edges. Therefore, a model incorporating end-stopped neurons is essential to suppress ambiguous motion signals along the edges of the stimulus. It is shown that the unambiguous motion signals at terminators propagate over the rest of the object to achieve an accurate representation of motion. PMID:27741307

VizieR Online Data Catalog: OGLE high proper motion stars towards MC (Soszynski+, 2002)

NASA Astrophysics Data System (ADS)

Soszynski, I.; Zebrun, K.; Udalski, A.; Wozniak, P. R.; Szymanski, M.; Kubiak, M.; Pietrzynski, G.; Szewczyk, O.; Wyrzykowski, L.

2002-11-01

We present a catalog of high proper motion (HPM) stars detected in the foreground of central parts of the Magellanic Clouds. The Catalog contains 2161 objects in the 4.5 square degree area towards the LMC, and 892 HPM stars in the 2.4 square degree area towards the SMC. The Catalog is based on observations collected during four years of the OGLE-II microlensing survey. The Difference Image Analysis (DIA) of the images provided candidate HPM stars with proper motion as small as 4mas/yr. These appeared as pseudo-variables, and were all measured astrometrically on all CCD images, providing typically about 400 data points per star. The reference frame was defined by the majority of background stars, most of them members of the Magellanic Clouds. The reflex motion due to solar velocity with respect to the local standards of rest is clearly seen. The largest proper motion in our sample is 363mas/yr. Parallaxes were measured with errors smaller than 20% for several stars. (2 data files).

Source detection at 100 meter standoff with a time-encoded imaging system

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

Brennan, J.; Brubaker, E.; Gerling, M.

Here, we present the design, characterization, and testing of a laboratory prototype radiological search and localization system. The system, based on time-encoded imaging, uses the attenuation signature of neutrons in time, induced by the geometrical layout and motion of the system. We have demonstrated the ability to detect a ~1 mCi 252 Cf radiological source at 100 m standoff with 90% detection efficiency and 10% false positives against background in 12 min. As a result, this same detection efficiency is met at 15 s for a 40 m standoff, and 1.2 s for a 20 m standoff.

Source detection at 100 meter standoff with a time-encoded imaging system

DOE PAGES

Brennan, J.; Brubaker, E.; Gerling, M.; ...

2017-09-28

Here, we present the design, characterization, and testing of a laboratory prototype radiological search and localization system. The system, based on time-encoded imaging, uses the attenuation signature of neutrons in time, induced by the geometrical layout and motion of the system. We have demonstrated the ability to detect a ~1 mCi 252 Cf radiological source at 100 m standoff with 90% detection efficiency and 10% false positives against background in 12 min. As a result, this same detection efficiency is met at 15 s for a 40 m standoff, and 1.2 s for a 20 m standoff.

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

Cifter, G; Redler, G; Lee, C

Purpose: Compared to traditional radiotherapy techniques, stereotactic body radiation therapy (SBRT) provides more favorable outcomes during the treatment of certain lung tumors. Despite advancements in image guidance, accurate target localization still remains a challenge. In this work, we expand our knowledge of a novel scatter imaging modality in order to develop a real-time tumor localization method using scattered photons from the patient during treatment. Methods: Images of the QUASAR™ Respiratory Motion Phantom were taken by irradiating it on a Varian TrueBeam accelerator. The scattered radiation was detected using a flat panel-based pinhole camera detection system. Two motion settings were investigated:more » static and dynamic. In the former, the lung tumor was manually shifted between imaging. In the latter, the lung tumor was set to move at a certain frequency and amplitude while the images were acquired continuously for one minute. The accuracy of tumor localization and the irradiation time required to distinguish the lung tumor were studied. Results: The comparison of measured and expected location of the lung tumor during static motion was shown to be under standard deviation (STD) of 0.064 with a mean STD of 0.031cm. The dynamic motion was taken at a rate of 1400 MU/min for one minute and the measured location of the lung tumor was then compared with the QUASAR phantom’s sinusoidal motion pattern and the agreement found to be at an average STD of 0.275cm. The location of the lung tumor was investigated using aggregate images consisting of 1 or 2 frames/image and the change was below STD of 0.30cm. The lung tumor also appeared to be blurrier in images consisting of two frames. Conclusion: Based on our preliminary results real-time image guidance using the scatter imaging modality to localize and track tumors during lung SBRT has the potential to become clinical reality.« less

Motion-Based System Identification and Fault Detection and Isolation Technologies for Thruster Controlled Spacecraft

NASA Technical Reports Server (NTRS)

Wilson, Edward; Sutter, David W.; Berkovitz, Dustin; Betts, Bradley J.; Kong, Edmund; delMundo, Rommel; Lages, Christopher R.; Mah, Robert W.; Papasin, Richard

2003-01-01

By analyzing the motions of a thruster-controlled spacecraft, it is possible to provide on-line (1) thruster fault detection and isolation (FDI), and (2) vehicle mass- and thruster-property identification (ID). Technologies developed recently at NASA Ames have significantly improved the speed and accuracy of these ID and FDI capabilities, making them feasible for application to a broad class of spacecraft. Since these technologies use existing sensors, the improved system robustness and performance that comes with the thruster fault tolerance and system ID can be achieved through a software-only implementation. This contrasts with the added cost, mass, and hardware complexity commonly required by FDI. Originally developed in partnership with NASA - Johnson Space Center to provide thruster FDI capability for the X-38 during re-entry, these technologies are most recently being applied to the MIT SPHERES experimental spacecraft to fly on the International Space Station in 2004. The model-based FDI uses a maximum-likelihood calculation at its core, while the ID is based upon recursive least squares estimation. Flight test results from the SPHERES implementation, as flown aboard the NASA KC-1 35A 0-g simulator aircraft in November 2003 are presented.

Multi-Sensor Methods for Mobile Radar Motion Capture and Compensation

NASA Astrophysics Data System (ADS)

Nakata, Robert

Remote sensing has many applications, including surveying and mapping, geophysics exploration, military surveillance, search and rescue and counter-terrorism operations. Remote sensor systems typically use visible image, infrared or radar sensors. Camera based image sensors can provide high spatial resolution but are limited to line-of-sight capture during daylight. Infrared sensors have lower resolution but can operate during darkness. Radar sensors can provide high resolution motion measurements, even when obscured by weather, clouds and smoke and can penetrate walls and collapsed structures constructed with non-metallic materials up to 1 m to 2 m in depth depending on the wavelength and transmitter power level. However, any platform motion will degrade the target signal of interest. In this dissertation, we investigate alternative methodologies to capture platform motion, including a Body Area Network (BAN) that doesn't require external fixed location sensors, allowing full mobility of the user. We also investigated platform stabilization and motion compensation techniques to reduce and remove the signal distortion introduced by the platform motion. We evaluated secondary ultrasonic and radar sensors to stabilize the platform resulting in an average 5 dB of Signal to Interference Ratio (SIR) improvement. We also implemented a Digital Signal Processing (DSP) motion compensation algorithm that improved the SIR by 18 dB on average. These techniques could be deployed on a quadcopter platform and enable the detection of respiratory motion using an onboard radar sensor.

Mobile Motion Capture--MiMiC.

PubMed

Harbert, Simeon D; Jaiswal, Tushar; Harley, Linda R; Vaughn, Tyler W; Baranak, Andrew S

2013-01-01

The low cost, simple, robust, mobile, and easy to use Mobile Motion Capture (MiMiC) system is presented and the constraints which guided the design of MiMiC are discussed. The MiMiC Android application allows motion data to be captured from kinematic modules such as Shimmer 2r sensors over Bluetooth. MiMiC is cost effective and can be used for an entire day in a person's daily routine without being intrusive. MiMiC is a flexible motion capture system which can be used for many applications including fall detection, detection of fatigue in industry workers, and analysis of individuals' work patterns in various environments.

An Approach to Sensorless Detection of Human Input Torque and Its Application to Power Assist Motion in Electric Wheelchair

NASA Astrophysics Data System (ADS)

Kaida, Yukiko; Murakami, Toshiyuki

A wheelchair is an important apparatus of mobility for people with disability. Power-assist motion in an electric wheelchair is to expand the operator's field of activities. This paper describes force sensorless detection of human input torque. Reaction torque estimation observer calculates the total disturbance torque first. Then, the human input torque is extracted from the estimated disturbance. In power-assist motion, assist torque is synthesized according to the product of assist gain and the average torque of the right and left input torque. Finally, the proposed method is verified through the experiments of power-assist motion.

Motion dazzle and camouflage as distinct anti-predator defenses.

PubMed

Stevens, Martin; Searle, W Tom L; Seymour, Jenny E; Marshall, Kate L A; Ruxton, Graeme D

2011-11-25

Camouflage patterns that hinder detection and/or recognition by antagonists are widely studied in both human and animal contexts. Patterns of contrasting stripes that purportedly degrade an observer's ability to judge the speed and direction of moving prey ('motion dazzle') are, however, rarely investigated. This is despite motion dazzle having been fundamental to the appearance of warships in both world wars and often postulated as the selective agent leading to repeated patterns on many animals (such as zebra and many fish, snake, and invertebrate species). Such patterns often appear conspicuous, suggesting that protection while moving by motion dazzle might impair camouflage when stationary. However, the relationship between motion dazzle and camouflage is unclear because disruptive camouflage relies on high-contrast markings. In this study, we used a computer game with human subjects detecting and capturing either moving or stationary targets with different patterns, in order to provide the first empirical exploration of the interaction of these two protective coloration mechanisms. Moving targets with stripes were caught significantly less often and missed more often than targets with camouflage patterns. However, when stationary, targets with camouflage markings were captured less often and caused more false detections than those with striped patterns, which were readily detected. Our study provides the clearest evidence to date that some patterns inhibit the capture of moving targets, but that camouflage and motion dazzle are not complementary strategies. Therefore, the specific coloration that evolves in animals will depend on how the life history and ontogeny of each species influence the trade-off between the costs and benefits of motion dazzle and camouflage.

Defining the computational structure of the motion detector in Drosophila

PubMed Central

Clark, Damon A.; Bursztyn, Limor; Horowitz, Mark; Schnitzer, Mark J.; Clandinin, Thomas R.

2011-01-01

SUMMARY Many animals rely on visual motion detection for survival. Motion information is extracted from spatiotemporal intensity patterns on the retina, a paradigmatic neural computation. A phenomenological model, the Hassenstein-Reichardt Correlator (HRC), relates visual inputs to neural and behavioral responses to motion, but the circuits that implement this computation remain unknown. Using cell-type specific genetic silencing, minimal motion stimuli, and in vivo calcium imaging, we examine two critical HRC inputs. These two pathways respond preferentially to light and dark moving edges. We demonstrate that these pathways perform overlapping but complementary subsets of the computations underlying the HRC. A numerical model implementing differential weighting of these operations displays the observed edge preferences. Intriguingly, these pathways are distinguished by their sensitivities to a stimulus correlation that corresponds to an illusory percept, “reverse phi”, that affects many species. Thus, this computational architecture may be widely used to achieve edge selectivity in motion detection. PMID:21689602

Simultaneous detection of rotational and translational motion in optical tweezers by measurement of backscattered intensity.

PubMed

Roy, Basudev; Bera, Sudipta K; Banerjee, Ayan

2014-06-01

We describe a simple yet powerful technique of simultaneously measuring both translational and rotational motion of mesoscopic particles in optical tweezers by measuring the backscattered intensity on a quadrant photodiode (QPD). While the measurement of translational motion by taking the difference of the backscattered intensity incident on adjacent quadrants of a QPD is well known, we demonstrate that rotational motion can be measured very precisely by taking the difference between the diagonal quadrants. The latter measurement eliminates the translational component entirely and leads to a detection sensitivity of around 50 mdeg at S/N of 2 for angular motion of a driven microrod. The technique is also able to resolve the translational and rotational Brownian motion components of the microrod in an unperturbed trap and can be very useful in measuring translation-rotation coupling of micro-objects induced by hydrodynamic interactions.

Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection

PubMed Central

Giakoumis, Dimitris; Drosou, Anastasios; Cipresso, Pietro; Tzovaras, Dimitrios; Hassapis, George; Gaggioli, Andrea; Riva, Giuseppe

2012-01-01

This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing. PMID:23028461

MotorSense: Using Motion Tracking Technology to Support the Identification and Treatment of Gross-Motor Dysfunction.

PubMed

Arnedillo-Sánchez, Inmaculada; Boyle, Bryan; Bossavit, Benoît

2017-01-01

MotorSense is a motion detection and tracking technology that can be implemented across a range of environments to assist in detecting delays in gross-motor skills development. The system utilises the motion tracking functionality of Microsoft's Kinect™. It features games that require children to perform graded gross-motor tasks matched with their chronological and developmental ages. This paper describes the rationale for MotorSense, provides an overview of the functionality of the system and illustrates sample activities.

An automatic fall detection framework using data fusion of Doppler radar and motion sensor network.

PubMed

Liu, Liang; Popescu, Mihail; Skubic, Marjorie; Rantz, Marilyn

2014-01-01

This paper describes the ongoing work of detecting falls in independent living senior apartments. We have developed a fall detection system with Doppler radar sensor and implemented ceiling radar in real senior apartments. However, the detection accuracy on real world data is affected by false alarms inherent in the real living environment, such as motions from visitors. To solve this issue, this paper proposes an improved framework by fusing the Doppler radar sensor result with a motion sensor network. As a result, performance is significantly improved after the data fusion by discarding the false alarms generated by visitors. The improvement of this new method is tested on one week of continuous data from an actual elderly person who frequently falls while living in her senior home.

An Unobtrusive Fall Detection and Alerting System Based on Kalman Filter and Bayes Network Classifier.

PubMed

He, Jian; Bai, Shuang; Wang, Xiaoyi

2017-06-16

Falls are one of the main health risks among the elderly. A fall detection system based on inertial sensors can automatically detect fall event and alert a caregiver for immediate assistance, so as to reduce injuries causing by falls. Nevertheless, most inertial sensor-based fall detection technologies have focused on the accuracy of detection while neglecting quantization noise caused by inertial sensor. In this paper, an activity model based on tri-axial acceleration and gyroscope is proposed, and the difference between activities of daily living (ADLs) and falls is analyzed. Meanwhile, a Kalman filter is proposed to preprocess the raw data so as to reduce noise. A sliding window and Bayes network classifier are introduced to develop a wearable fall detection system, which is composed of a wearable motion sensor and a smart phone. The experiment shows that the proposed system distinguishes simulated falls from ADLs with a high accuracy of 95.67%, while sensitivity and specificity are 99.0% and 95.0%, respectively. Furthermore, the smart phone can issue an alarm to caregivers so as to provide timely and accurate help for the elderly, as soon as the system detects a fall.

Commissioning of an integrated platform for time-resolved treatment delivery in scanned ion beam therapy by means of optical motion monitoring.

PubMed

Fattori, G; Saito, N; Seregni, M; Kaderka, R; Pella, A; Constantinescu, A; Riboldi, M; Steidl, P; Cerveri, P; Bert, C; Durante, M; Baroni, G

2014-12-01

The integrated use of optical technologies for patient monitoring is addressed in the framework of time-resolved treatment delivery for scanned ion beam therapy. A software application has been designed to provide the therapy control system (TCS) with a continuous geometrical feedback by processing the external surrogates tridimensional data, detected in real-time via optical tracking. Conventional procedures for phase-based respiratory phase detection were implemented, as well as the interface to patient specific correlation models, in order to estimate internal tumor motion from surface markers. In this paper, particular attention is dedicated to the quantification of time delays resulting from system integration and its compensation by means of polynomial interpolation in the time domain. Dedicated tests to assess the separate delay contributions due to optical signal processing, digital data transfer to the TCS and passive beam energy modulation actuation have been performed. We report the system technological commissioning activities reporting dose distribution errors in a phantom study, where the treatment of a lung lesion was simulated, with both lateral and range beam position compensation. The zero-delay systems integration with a specific active scanning delivery machine was achieved by tuning the amount of time prediction applied to lateral (14.61 ± 0.98 ms) and depth (34.1 ± 6.29 ms) beam position correction signals, featuring sub-millimeter accuracy in forward estimation. Direct optical target observation and motion phase (MPh) based tumor motion discretization strategies were tested, resulting in 20.3(2.3)% and 21.2(9.3)% median (IQR) percentual relative dose difference with respect to static irradiation, respectively. Results confirm the technical feasibility of the implemented strategy towards 4D treatment delivery, with negligible percentual dose deviations with respect to static irradiation.

TH-AB-202-07: Radar Tracking of Respiratory Motion in Real Time

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

Fung, A; Li, C; Torres, C

Purpose: To propose a method of real time tracking of respiratory motion in patients undergoing radiation therapy. Radar technology can be employed to detection the movement of diaphragm and thoracic anatomy. Methods: A radar transceiver was specially designed. During experiment, the radar device was securely attached to a fixed frame. Respiratory motion was simulated with: 1) Varian RPM phantom, 2) Standard Imaging Respiratory Gating Platform. Signals recorded with radar equipment were compared with those measured with Varian RPM system as a reference. Results: Motion generated by Varian RPM phantom was recorded by the radar device, and compared to the signalsmore » recorded by RPM camera. The results showed exact agreement between the two monitoring equipments. Motion was also generated by Standard Imaging Respiratory Motion Platform. The results showed the radar device was capable of measuring motion of various amplitudes and periods. Conclusion: The proposed radar device is able to measure movements such as respiratory motion. Compared to state-of-the-art respiratory detection instrument, the radar device is shown to be equally precise and effective for monitoring respiration in radiation oncology patients.« less

Secular Extragalactic Parallax and Geometric Distances with Gaia Proper Motions

NASA Astrophysics Data System (ADS)

Paine, Jennie; Darling, Jeremiah K.

2018-06-01

The motion of the Solar System with respect to the cosmic microwave background (CMB) rest frame creates a well measured dipole in the CMB, which corresponds to a linear solar velocity of about 78 AU/yr. This motion causes relatively nearby extragalactic objects to appear to move compared to more distant objects, an effect that can be measured in the proper motions of nearby galaxies. An object at 1 Mpc and perpendicular to the CMB apex will exhibit a secular parallax, observed as a proper motion, of 78 µas/yr. The relatively large peculiar motions of galaxies make the detection of secular parallax challenging for individual objects. Instead, a statistical parallax measurement can be made for a sample of objects with proper motions, where the global parallax signal is modeled as an E-mode dipole that diminishes linearly with distance. We present preliminary results of applying this model to a sample of nearby galaxies with Gaia proper motions to detect the statistical secular parallax signal. The statistical measurement can be used to calibrate the canonical cosmological “distance ladder.”

An Intelligent Surveillance Platform for Large Metropolitan Areas with Dense Sensor Deployment

PubMed Central

Fernández, Jorge; Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M.; Carro, Belén; Sánchez-Esguevillas, Antonio; Alonso-López, Jesus A.; Smilansky, Zeev

2013-01-01

This paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform's control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coverage. PMID:23748169

Noise Reduction in Brainwaves by Using Both EEG Signals and Frontal Viewing Camera Images

PubMed Central

Bang, Jae Won; Choi, Jong-Suk; Park, Kang Ryoung

2013-01-01

Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) have been used in various applications, including human–computer interfaces, diagnosis of brain diseases, and measurement of cognitive status. However, EEG signals can be contaminated with noise caused by user's head movements. Therefore, we propose a new method that combines an EEG acquisition device and a frontal viewing camera to isolate and exclude the sections of EEG data containing these noises. This method is novel in the following three ways. First, we compare the accuracies of detecting head movements based on the features of EEG signals in the frequency and time domains and on the motion features of images captured by the frontal viewing camera. Second, the features of EEG signals in the frequency domain and the motion features captured by the frontal viewing camera are selected as optimal ones. The dimension reduction of the features and feature selection are performed using linear discriminant analysis. Third, the combined features are used as inputs to support vector machine (SVM), which improves the accuracy in detecting head movements. The experimental results show that the proposed method can detect head movements with an average error rate of approximately 3.22%, which is smaller than that of other methods. PMID:23669713

Bio-inspired optical rotation sensor

NASA Astrophysics Data System (ADS)

O'Carroll, David C.; Shoemaker, Patrick A.; Brinkworth, Russell S. A.

2007-01-01

Traditional approaches to calculating self-motion from visual information in artificial devices have generally relied on object identification and/or correlation of image sections between successive frames. Such calculations are computationally expensive and real-time digital implementation requires powerful processors. In contrast flies arrive at essentially the same outcome, the estimation of self-motion, in a much smaller package using vastly less power. Despite the potential advantages and a few notable successes, few neuromorphic analog VLSI devices based on biological vision have been employed in practical applications to date. This paper describes a hardware implementation in aVLSI of our recently developed adaptive model for motion detection. The chip integrates motion over a linear array of local motion processors to give a single voltage output. Although the device lacks on-chip photodetectors, it includes bias circuits to use currents from external photodiodes, and we have integrated it with a ring-array of 40 photodiodes to form a visual rotation sensor. The ring configuration reduces pattern noise and combined with the pixel-wise adaptive characteristic of the underlying circuitry, permits a robust output that is proportional to image rotational velocity over a large range of speeds, and is largely independent of either mean luminance or the spatial structure of the image viewed. In principle, such devices could be used as an element of a velocity-based servo to replace or augment inertial guidance systems in applications such as mUAVs.

Adaptive algorithm of magnetic heading detection

NASA Astrophysics Data System (ADS)

Liu, Gong-Xu; Shi, Ling-Feng

2017-11-01

Magnetic data obtained from a magnetic sensor usually fluctuate in a certain range, which makes it difficult to estimate the magnetic heading accurately. In fact, magnetic heading information is usually submerged in noise because of all kinds of electromagnetic interference and the diversity of the pedestrian’s motion states. In order to solve this problem, a new adaptive algorithm based on the (typically) right-angled corridors of a building or residential buildings is put forward to process heading information. First, a 3D indoor localization platform is set up based on MPU9250. Then, several groups of data are measured by changing the experimental environment and pedestrian’s motion pace. The raw data from the attached inertial measurement unit are calibrated and arranged into a time-stamped array and written to a data file. Later, the data file is imported into MATLAB for processing and analysis using the proposed adaptive algorithm. Finally, the algorithm is verified by comparison with the existing algorithm. The experimental results show that the algorithm has strong robustness and good fault tolerance, which can detect the heading information accurately and in real-time.

Probe Scanning Support System by a Parallel Mechanism for Robotic Echography

NASA Astrophysics Data System (ADS)

Aoki, Yusuke; Kaneko, Kenta; Oyamada, Masami; Takachi, Yuuki; Masuda, Kohji

We propose a probe scanning support system based on force/visual servoing control for robotic echography. First, we have designed and formulated its inverse kinematics the construction of mechanism. Next, we have developed a scanning method of the ultrasound probe on body surface to construct visual servo system based on acquired echogram by the standalone medical robot to move the ultrasound probe on patient abdomen in three-dimension. The visual servo system detects local change of brightness in time series echogram, which is stabilized the position of the probe by conventional force servo system in the robot, to compensate not only periodical respiration motion but also body motion. Then we integrated control method of the visual servo with the force servo as a hybrid control in both of position and force. To confirm the ability to apply for actual abdomen, we experimented the total system to follow the gallbladder as a moving target to keep its position in the echogram by minimizing variation of reaction force on abdomen. As the result, the system has a potential to be applied to automatic detection of human internal organ.

Three-Dimensional Graphene Structure for Healable Flexible Electronics Based on Diels-Alder Chemistry.

PubMed

Li, Jinhui; Liu, Qiang; Ho, Derek; Zhao, Songfang; Wu, Shuwen; Ling, Lei; Han, Fei; Wu, Xinxiu; Zhang, Guoping; Sun, Rong; Wong, Ching-Ping

2018-03-21

Wearable electronics with excellent stretchability and sensitivity have emerged as a very promising field with wide applications such as e-skin and human motion detection. Although three-dimensional (3D) graphene structures (GS) have been reported for high-performance strain sensors, challenges still remain such as the high cost of GS preparation, low stretchability, and the lack of ability to heal itself. In this paper, we reported a novel self-healing flexible electronics with 3D GS based on Diels-Alder (DA) chemistry. Furfurylamine (FA) was employed as a reducing as well as a modifying agent, forming GS by FA (FAGS)/DA bonds contained polyurethane with the "infiltrate-gel-dry" process. The as-prepared composite exhibited excellent stretchability (200%) and intrinsic conductivity with low incorporation of graphene (about 2 wt %), which could be directly employed for flexible electronics to detect human motions. Besides, the FAGS/DAPU composite exhibited lower temperature retro-DA response for the continuous graphene networks. Highly effective healing of the composites by heat and microwave has been demonstrated successfully.

Road-Aided Ground Slowly Moving Target 2D Motion Estimation for Single-Channel Synthetic Aperture Radar.

PubMed

Wang, Zhirui; Xu, Jia; Huang, Zuzhen; Zhang, Xudong; Xia, Xiang-Gen; Long, Teng; Bao, Qian

2016-03-16

To detect and estimate ground slowly moving targets in airborne single-channel synthetic aperture radar (SAR), a road-aided ground moving target indication (GMTI) algorithm is proposed in this paper. First, the road area is extracted from a focused SAR image based on radar vision. Second, after stationary clutter suppression in the range-Doppler domain, a moving target is detected and located in the image domain via the watershed method. The target's position on the road as well as its radial velocity can be determined according to the target's offset distance and traffic rules. Furthermore, the target's azimuth velocity is estimated based on the road slope obtained via polynomial fitting. Compared with the traditional algorithms, the proposed method can effectively cope with slowly moving targets partly submerged in a stationary clutter spectrum. In addition, the proposed method can be easily extended to a multi-channel system to further improve the performance of clutter suppression and motion estimation. Finally, the results of numerical experiments are provided to demonstrate the effectiveness of the proposed algorithm.

A 1500 deg2 near infrared proper motion catalogue from the UKIDSS Large Area Survey

NASA Astrophysics Data System (ADS)

Smith, Leigh; Lucas, P. W.; Burningham, B.; Jones, H. R. A.; Smart, R. L.; Andrei, A. H.; Catalán, S.; Pinfield, D. J.

2014-02-01

The United Kingdom Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS) began in 2005, with the start of the UKIDSS programme as a 7 year effort to survey roughly 4000 deg2 at high Galactic latitudes in Y, J, H and K bands. The survey also included a significant quantity of two epoch J band observations, with an epoch baseline greater than 2 years to calculate proper motions. We present a near-infrared proper motion catalogue for the 1500 deg2 of the two epoch LAS data, which includes 135 625 stellar sources and a further 88 324 with ambiguous morphological classifications, all with motions detected above the 5σ level. We developed a custom proper motion pipeline which we describe here. Our catalogue agrees well with the proper motion data supplied for a 300 deg2 subset in the current Wide Field Camera Science Archive (WSA) 10th data release (DR10) catalogue, and in various optical catalogues, but it benefits from a larger matching radius and hence a larger upper proper motion detection limit. We provide absolute proper motions, using LAS galaxies for the relative to absolute correction. By using local second-order polynomial transformations, as opposed to linear transformations in the WSA, we correct better for any local distortions in the focal plane, not including the radial distortion that is removed by the UKIDSS pipeline. We present the results of proper motion searches for new brown dwarfs and white dwarfs. We discuss 41 sources in the WSA DR10 overlap with our catalogue with proper motions >300 mas yr-1, several of which are new detections. We present 15 new candidate ultracool dwarf binary systems.

Atom-atom entanglement by single-photon detection.

PubMed

Slodička, L; Hétet, G; Röck, N; Schindler, P; Hennrich, M; Blatt, R

2013-02-22

A scheme for entangling distant atoms is realized, as proposed in the seminal paper by [C. Cabrillo et al., Phys. Rev. A 59, 1025 (1999)]. The protocol is based on quantum interference and detection of a single photon scattered from two effectively one meter distant laser cooled and trapped atomic ions. The detection of a single photon heralds entanglement of two internal states of the trapped ions with high rate and with a fidelity limited mostly by atomic motion. Control of the entangled state phase is demonstrated by changing the path length of the single-photon interferometer.

Optic flow detection is not influenced by visual-vestibular congruency.

PubMed

Holten, Vivian; MacNeilage, Paul R

2018-01-01

Optic flow patterns generated by self-motion relative to the stationary environment result in congruent visual-vestibular self-motion signals. Incongruent signals can arise due to object motion, vestibular dysfunction, or artificial stimulation, which are less common. Hence, we are predominantly exposed to congruent rather than incongruent visual-vestibular stimulation. If the brain takes advantage of this probabilistic association, we expect observers to be more sensitive to visual optic flow that is congruent with ongoing vestibular stimulation. We tested this expectation by measuring the motion coherence threshold, which is the percentage of signal versus noise dots, necessary to detect an optic flow pattern. Observers seated on a hexapod motion platform in front of a screen experienced two sequential intervals. One interval contained optic flow with a given motion coherence and the other contained noise dots only. Observers had to indicate which interval contained the optic flow pattern. The motion coherence threshold was measured for detection of laminar and radial optic flow during leftward/rightward and fore/aft linear self-motion, respectively. We observed no dependence of coherence thresholds on vestibular congruency for either radial or laminar optic flow. Prior studies using similar methods reported both decreases and increases in coherence thresholds in response to congruent vestibular stimulation; our results do not confirm either of these prior reports. While methodological differences may explain the diversity of results, another possibility is that motion coherence thresholds are mediated by neural populations that are either not modulated by vestibular stimulation or that are modulated in a manner that does not depend on congruency.

The Population of Small Comets: Optimum Techniques for Detection

NASA Technical Reports Server (NTRS)

Brandt, John C.

1997-01-01

The goals of this project were: (1) to present evidence to the scientific community for the importance of the small comet population and (2) to develop techniques for optimum detection in order to characterize the population. Our work on techniques has been to develop algorithms for searching images for SCs based on the distinctive properties of comets; (1) motion with respect to background stars; (2) extended source with most light coming from the coma rather than the nucleus; and characteristic spectral signature.

Kernelized correlation tracking with long-term motion cues

NASA Astrophysics Data System (ADS)

Lv, Yunqiu; Liu, Kai; Cheng, Fei

2018-04-01

Robust object tracking is a challenging task in computer vision due to interruptions such as deformation, fast motion and especially, occlusion of tracked object. When occlusions occur, image data will be unreliable and is insufficient for the tracker to depict the object of interest. Therefore, most trackers are prone to fail under occlusion. In this paper, an occlusion judgement and handling method based on segmentation of the target is proposed. If the target is occluded, the speed and direction of it must be different from the objects occluding it. Hence, the value of motion features are emphasized. Considering the efficiency and robustness of Kernelized Correlation Filter Tracking (KCF), it is adopted as a pre-tracker to obtain a predicted position of the target. By analyzing long-term motion cues of objects around this position, the tracked object is labelled. Hence, occlusion could be detected easily. Experimental results suggest that our tracker achieves a favorable performance and effectively handles occlusion and drifting problems.

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.

Feasibility evaluation of a motion detection system with face images for stereotactic radiosurgery.

PubMed

Yamakawa, Takuya; Ogawa, Koichi; Iyatomi, Hitoshi; Kunieda, Etsuo

2011-01-01

In stereotactic radiosurgery we can irradiate a targeted volume precisely with a narrow high-energy x-ray beam, and thus the motion of a targeted area may cause side effects to normal organs. This paper describes our motion detection system with three USB cameras. To reduce the effect of change in illuminance in a tracking area we used an infrared light and USB cameras that were sensitive to the infrared light. The motion detection of a patient was performed by tracking his/her ears and nose with three USB cameras, where pattern matching between a predefined template image for each view and acquired images was done by an exhaustive search method with a general-purpose computing on a graphics processing unit (GPGPU). The results of the experiments showed that the measurement accuracy of our system was less than 0.7 mm, amounting to less than half of that of our previous system.

The Optical Gravitational Lensing Experiment. Gaia South Ecliptic Pole Field as Seen by OGLE-IV

NASA Astrophysics Data System (ADS)

Soszyński, I.; Udalski, A.; Poleski, R.; Kozłowski, S.; Wyrzykowski, Ł.; Pietrukowicz, P.; Szymański, M. K.; Kubiak, M.; Pietrzyński, G.; Ulaczyk, K.; Skowron, J.

2012-09-01

We present a comprehensive analysis of the Gaia South Ecliptic Pole (GSEP) field, 5.3 square degrees area around the South Ecliptic Pole on the outskirts of the LMC, based on the data collected during the fourth phase of the Optical Gravitational Lensing Experiment, OGLE-IV. The GSEP field will be observed during the commissioning phase of the ESA Gaia space mission for testing and calibrating the Gaia instruments. We provide the photometric maps of the GSEP region containing the mean VI photometry of all detected stellar objects and their equatorial coordinates. We show the quality and completeness of the OGLE-IV photometry and color-magnitude diagrams of this region. We conducted an extensive search for variable stars in the GSEP field leading to the discovery of 6789 variable stars. In this sample we found 132 classical Cepheids, 686 RR Lyr type stars, 2819 long-period, and 1377 eclipsing variables. Several objects deserving special attention were also selected, including a new classical Cepheid in a binary eclipsing system. To provide empirical data for the Gaia Science Alert system we also conducted a search for optical transients. We discovered two firm type Ia supernovae and nine additional supernova candidates. To facilitate future Gaia supernovae detections we prepared a list of more than 1900 galaxies to redshift about 0.1 located in the GSEP field. Finally, we present the results of astrometric study of the GSEP field. With the 26 months time base of the presented here OGLE-IV data, proper motions of stars could be detected with the accuracy reaching 2 mas/yr. Astrometry allowed to distinguish galactic foreground variable stars detected in the GSEP field from LMC objects and to discover about 50 high proper motion stars (proper motion ≥ 100 mas/yr). Among them three new nearby white dwarfs were found. All data presented in this paper are available to the astronomical community from the OGLE Internet archive.

Effects of Piecewise Spatial Smoothing in 4-D SPECT Reconstruction

NASA Astrophysics Data System (ADS)

Qi, Wenyuan; Yang, Yongyi; King, Michael A.

2014-02-01

In nuclear medicine, cardiac gated SPECT images are known to suffer from significantly increased noise owing to limited data counts. Consequently, spatial (and temporal) smoothing has been indispensable for suppressing the noise artifacts in SPECT reconstruction. However, recently we demonstrated that the benefit of spatial processing in motion-compensated reconstruction of gated SPECT (aka 4-D) could be outweighed by its adverse effects on the myocardium, which included degraded wall motion and perfusion defect detectability. In this work, we investigate whether we can alleviate these adverse effects by exploiting an alternative spatial smoothing prior in 4-D based on image total variation (TV). TV based prior is known to induce piecewise smoothing which can preserve edge features (such as boundaries of the heart wall) in reconstruction. However, it is not clear whether such a property would necessarily be beneficial for improving the accuracy of the myocardium in 4-D reconstruction. In particular, it is unknown whether it would adversely affect the detectability of perfusion defects that are small in size or low in contrast. In our evaluation study, we first use Monte Carlo simulated imaging with 4-D NURBS-based cardiac-torso (NCAT) phantom wherein the ground truth is known for quantitative comparison. We evaluated the accuracy of the reconstructed myocardium using a number of metrics, including regional and overall accuracy of the myocardium, accuracy of the phase activity curve (PAC) of the LV wall for wall motion, uniformity and spatial resolution of the LV wall, and detectability of perfusion defects using a channelized Hotelling observer (CHO). For lesion detection, we simulated perfusion defects with different sizes and contrast levels with the focus being on perfusion defects that are subtle. As a preliminary demonstration, we also tested on three sets of clinical acquisitions. From the quantitative results, it was demonstrated that TV smoothing could further reduce the error level in the myocardium in 4-D reconstruction along with motion-compensated temporal smoothing. In contrast to quadratic spatial smoothing, TV smoothing could reduce the noise level in the LV at a faster pace than the increase in the bias level, thereby achieving a net decrease in the error level. In particular, at the same noise level, TV smoothing could reduce the bias by about 30% compared to quadratic smoothing. Moreover, the CHO results indicate that TV could also improve the lesion detectability even when the lesion is small. The PAC results show that, at the same noise level, TV smoothing achieved lower temporal bias, which is also consistent with the improved spatial resolution of the LV in reconstruction. The improvement in blurring effects by TV was also observed in the clinical images.

Comparison of Hyperemic Impedance Echocardiography with Dobutamine Stress Echocardiography to Detect Inducible Myocardial Ischemia: A Pilot Study.

PubMed

Patel, Jijibhoy J; Gupta, Ankur; Nanda, Navin C

2016-03-01

Stress echocardiography using exercise or pharmacological stressors is either contraindicated or associated with significant side effects in some patients. This pilot study was designed to evaluate a new technique, hyperemic impedance echocardiography (HIE). It is based on reactive coronary hyperemia when transient limb ischemia is induced by tourniquet inflation. We hypothesized that this physiologic coronary hyperemia can identify inducible myocardial ischemia by assessment of regional wall motion abnormalities on echocardiography when compared with dobutamine stress echocardiography (DSE). Twenty consecutive outpatients with suspected stable coronary artery disease (CAD) who underwent clinically indicated DSE were recruited for performance of HIE after informed consent was obtained. Standard graded dobutamine infusion protocol from 5 to 40 μg/kg per min was used for DSE. HIE was performed by inflating tourniquets at a pressure of 10 mmHg below the systolic blood pressure for 1 minute in three of four extremities at a time for total of four cycles. Echocardiography was performed immediately after the last rotating tourniquet deflation. DSE and HIE were classified as abnormal for development of new or worsening wall motion abnormality in at least one myocardial segment. Test characteristics were also determined for a subset of these patients (n = 12) who underwent clinically indicated coronary angiography. Hyperemic impedance echocardiography showed 86% sensitivity, 67% specificity, 86% positive predictive value, and 67% negative predictive value with a test accuracy of 80% to detect inducible myocardial wall motion abnormalities when compared with DSE. HIE also showed 83% sensitivity, 75% negative predictive value with a test accuracy of 66.7% for detection of significant (≥50% diameter stenosis) CAD on coronary angiography. In this pilot study, HIE was a feasible, safe, and promising method for detection of inducible myocardial ischemia by assessment of regional wall motion abnormalities when compared to DSE and coronary angiography. Larger studies are needed to confirm these findings. © 2016, Wiley Periodicals, Inc.

Implementation of accelerometer sensor module and fall detection monitoring system based on wireless sensor network.

PubMed

Lee, Youngbum; Kim, Jinkwon; Son, Muntak; Lee, Myoungho

2007-01-01

This research implements wireless accelerometer sensor module and algorithm to determine wearer's posture, activity and fall. Wireless accelerometer sensor module uses ADXL202, 2-axis accelerometer sensor (Analog Device). And using wireless RF module, this module measures accelerometer signal and shows the signal at ;Acceloger' viewer program in PC. ADL algorithm determines posture, activity and fall that activity is determined by AC component of accelerometer signal and posture is determined by DC component of accelerometer signal. Those activity and posture include standing, sitting, lying, walking, running, etc. By the experiment for 30 subjects, the performance of implemented algorithm was assessed, and detection rate for postures, motions and subjects was calculated. Lastly, using wireless sensor network in experimental space, subject's postures, motions and fall monitoring system was implemented. By the simulation experiment for 30 subjects, 4 kinds of activity, 3 times, fall detection rate was calculated. In conclusion, this system can be application to patients and elders for activity monitoring and fall detection and also sports athletes' exercise measurement and pattern analysis. And it can be expected to common person's exercise training and just plaything for entertainment.

A feasibility study of damage detection in beams using high-speed camera (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wan, Chao; Yuan, Fuh-Gwo

2017-04-01

In this paper a method for damage detection in beam structures using high-speed camera is presented. Traditional methods of damage detection in structures typically involve contact (i.e., piezoelectric sensor or accelerometer) or non-contact sensors (i.e., laser vibrometer) which can be costly and time consuming to inspect an entire structure. With the popularity of the digital camera and the development of computer vision technology, video cameras offer a viable capability of measurement including higher spatial resolution, remote sensing and low-cost. In the study, a damage detection method based on the high-speed camera was proposed. The system setup comprises a high-speed camera and a line-laser which can capture the out-of-plane displacement of a cantilever beam. The cantilever beam with an artificial crack was excited and the vibration process was recorded by the camera. A methodology called motion magnification, which can amplify subtle motions in a video is used for modal identification of the beam. A finite element model was used for validation of the proposed method. Suggestions for applications of this methodology and challenges in future work will be discussed.

Automated eye blink detection and correction method for clinical MR eye imaging.

PubMed

Wezel, Joep; Garpebring, Anders; Webb, Andrew G; van Osch, Matthias J P; Beenakker, Jan-Willem M

2017-07-01

To implement an on-line monitoring system to detect eye blinks during ocular MRI using field probes, and to reacquire corrupted k-space lines by means of an automatic feedback system integrated with the MR scanner. Six healthy subjects were scanned on a 7 Tesla MRI whole-body system using a custom-built receive coil. Subjects were asked to blink multiple times during the MR-scan. The local magnetic field changes were detected with an external fluorine-based field probe which was positioned close to the eye. The eye blink produces a field shift greater than a threshold level, this was communicated in real-time to the MR system which immediately reacquired the motion-corrupted k-space lines. The uncorrected images, using the original motion-corrupted data, showed severe artifacts, whereas the corrected images, using the reacquired data, provided an image quality similar to images acquired without blinks. Field probes can successfully detect eye blinks during MRI scans. By automatically reacquiring the eye blink-corrupted data, high quality MR-images of the eye can be acquired. Magn Reson Med 78:165-171, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

A research on the postural stability of a person wearing the lower limb exoskeletal robot by the HAT model.

PubMed

Chang, Minsu; Kim, Yeongmin; Lee, Yoseph; Jeon, Doyoung

2017-07-01

This paper proposes a method of detecting the postural stability of a person wearing the lower limb exoskeletal robot with the HAT(Head-Arm-Trunk) model. Previous studies have shown that the human posture is stable when the CoM(Center of Mass) of the human body is placed on the BoS(Base of Support). In the case of the lower limb exoskeletal robot, the motion data, which are used for the CoM estimation, are acquired by sensors in the robot. The upper body, however, does not have sensors in each segment so that it may cause the error of the CoM estimation. In this paper, the HAT(Head-Arm-Trunk) model which combines head, arms, and torso into a single segment is considered because the motion of head and arms are unknown due to the lack of sensors. To verify the feasibility of HAT model, the reflecting markers are attached to each segment of the whole human body and the exact motion data are acquired by the VICON to compare the COM of the full body model and HAT model. The difference between the CoM with full body and that with HAT model is within 20mm for the various motions of head and arms. Based on the HAT model, the XCoM(Extrapolated Center of Mass) which includes the velocity of the CoM is used for prediction of the postural stability. The experiment of making unstable posture shows that the XCoM of the whole body based on the HAT model is feasible to detect the instance of postural instability earlier than the CoM by 20-250 msec. This result may be used for the lower limb exoskeletal robot to prepare for any action to prevent the falling down.

Poaching Detection Technologies—A Survey

PubMed Central

Meratnia, Nirvana; Havinga, Paul

2018-01-01

Between 1960 and 1990, 95% of the black rhino population in the world was killed. In South Africa, a rhino was killed every 8 h for its horn throughout 2016. Wild animals, rhinos and elephants, in particular, are facing an ever increasing poaching crisis. In this paper, we review poaching detection technologies that aim to save endangered species from extinction. We present requirements for effective poacher detection and identify research challenges through the survey. We describe poaching detection technologies in four domains: perimeter based, ground based, aerial based, and animal tagging based technologies. Moreover, we discuss the different types of sensor technologies that are used in intruder detection systems such as: radar, magnetic, acoustic, optic, infrared and thermal, radio frequency, motion, seismic, chemical, and animal sentinels. The ultimate long-term solution for the poaching crisis is to remove the drivers of demand by educating people in demanding countries and raising awareness of the poaching crisis. Until prevention of poaching takes effect, there will be a continuous urgent need for new (combined) approaches that take up the research challenges and provide better protection against poaching in wildlife areas. PMID:29738501

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

DOEpatents

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

2015-07-28

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

DNAzymes in DNA Nanomachines and DNA Analysis

NASA Astrophysics Data System (ADS)

He, Yu; Tian, Ye; Chen, Yi; Mao, Chengde

This chapter discusses our efforts in using DNAzymes in DNA nano-machines and DNA analysis systems. 10-23 DNAzymes can cleave specific phos-phodiester bonds in RNA. We use them to construct an autonomous DNA-RNA chimera nanomotor, which constantly extracts chemical energy from RNA substrates and transduces the energy into a mechanical motion: cycles of contraction and extension. The motor's motion can be reversibly turned on and off by a DNA analogue (brake) of the RNA substrate. Addition and removal of the brake stops and restarts, respectively, the motor's motion. Furthermore, when the RNA substrates are preorganized into a one-dimensional track, a DNAzyme can continuously move along the track so long as there are substrates available ahead. Based on a similar mechanism, a novel DNA detection system has been developed. A target DNA activates a DNAzyme to cleave RNA-containing molecular beacons (MB), which generates an enhanced fluorescence signal. A following work integrates two steps of signal amplifications: a rolling-circle amplification (RCA) to synthesize multiple copies of DNAzymes, and the DNAzymes catalyze a chemical reaction to generate a colorimetric signal. This method allows detection of DNA analytes whose concentration is as low as 1 pM.