Camera pose estimation for augmented reality in a small indoor dynamic scene

NASA Astrophysics Data System (ADS)

Frikha, Rawia; Ejbali, Ridha; Zaied, Mourad

2017-09-01

Camera pose estimation remains a challenging task for augmented reality (AR) applications. Simultaneous localization and mapping (SLAM)-based methods are able to estimate the six degrees of freedom camera motion while constructing a map of an unknown environment. However, these methods do not provide any reference for where to insert virtual objects since they do not have any information about scene structure and may fail in cases of occlusion of three-dimensional (3-D) map points or dynamic objects. This paper presents a real-time monocular piece wise planar SLAM method using the planar scene assumption. Using planar structures in the mapping process allows rendering virtual objects in a meaningful way on the one hand and improving the precision of the camera pose and the quality of 3-D reconstruction of the environment by adding constraints on 3-D points and poses in the optimization process on the other hand. We proposed to benefit from the 3-D planes rigidity motion in the tracking process to enhance the system robustness in the case of dynamic scenes. Experimental results show that using a constrained planar scene improves our system accuracy and robustness compared with the classical SLAM systems.

Incorporating structure from motion uncertainty into image-based pose estimation

NASA Astrophysics Data System (ADS)

Ludington, Ben T.; Brown, Andrew P.; Sheffler, Michael J.; Taylor, Clark N.; Berardi, Stephen

2015-05-01

A method for generating and utilizing structure from motion (SfM) uncertainty estimates within image-based pose estimation is presented. The method is applied to a class of problems in which SfM algorithms are utilized to form a geo-registered reference model of a particular ground area using imagery gathered during flight by a small unmanned aircraft. The model is then used to form camera pose estimates in near real-time from imagery gathered later. The resulting pose estimates can be utilized by any of the other onboard systems (e.g. as a replacement for GPS data) or downstream exploitation systems, e.g., image-based object trackers. However, many of the consumers of pose estimates require an assessment of the pose accuracy. The method for generating the accuracy assessment is presented. First, the uncertainty in the reference model is estimated. Bundle Adjustment (BA) is utilized for model generation. While the high-level approach for generating a covariance matrix of the BA parameters is straightforward, typical computing hardware is not able to support the required operations due to the scale of the optimization problem within BA. Therefore, a series of sparse matrix operations is utilized to form an exact covariance matrix for only the parameters that are needed at a particular moment. Once the uncertainty in the model has been determined, it is used to augment Perspective-n-Point pose estimation algorithms to improve the pose accuracy and to estimate the resulting pose uncertainty. The implementation of the described method is presented along with results including results gathered from flight test data.

Monocular-Based 6-Degree of Freedom Pose Estimation Technology for Robotic Intelligent Grasping Systems

PubMed Central

Liu, Tao; Guo, Yin; Yang, Shourui; Yin, Shibin; Zhu, Jigui

2017-01-01

Industrial robots are expected to undertake ever more advanced tasks in the modern manufacturing industry, such as intelligent grasping, in which robots should be capable of recognizing the position and orientation of a part before grasping it. In this paper, a monocular-based 6-degree of freedom (DOF) pose estimation technology to enable robots to grasp large-size parts at informal poses is proposed. A camera was mounted on the robot end-flange and oriented to measure several featured points on the part before the robot moved to grasp it. In order to estimate the part pose, a nonlinear optimization model based on the camera object space collinearity error in different poses is established, and the initial iteration value is estimated with the differential transformation. Measuring poses of the camera are optimized based on uncertainty analysis. Also, the principle of the robotic intelligent grasping system was developed, with which the robot could adjust its pose to grasp the part. In experimental tests, the part poses estimated with the method described in this paper were compared with those produced by a laser tracker, and results show the RMS angle and position error are about 0.0228° and 0.4603 mm. Robotic intelligent grasping tests were also successfully performed in the experiments. PMID:28216555

Monocular-Based 6-Degree of Freedom Pose Estimation Technology for Robotic Intelligent Grasping Systems.

PubMed

Liu, Tao; Guo, Yin; Yang, Shourui; Yin, Shibin; Zhu, Jigui

2017-02-14

Industrial robots are expected to undertake ever more advanced tasks in the modern manufacturing industry, such as intelligent grasping, in which robots should be capable of recognizing the position and orientation of a part before grasping it. In this paper, a monocular-based 6-degree of freedom (DOF) pose estimation technology to enable robots to grasp large-size parts at informal poses is proposed. A camera was mounted on the robot end-flange and oriented to measure several featured points on the part before the robot moved to grasp it. In order to estimate the part pose, a nonlinear optimization model based on the camera object space collinearity error in different poses is established, and the initial iteration value is estimated with the differential transformation. Measuring poses of the camera are optimized based on uncertainty analysis. Also, the principle of the robotic intelligent grasping system was developed, with which the robot could adjust its pose to grasp the part. In experimental tests, the part poses estimated with the method described in this paper were compared with those produced by a laser tracker, and results show the RMS angle and position error are about 0.0228° and 0.4603 mm. Robotic intelligent grasping tests were also successfully performed in the experiments.

A Nonrigid Kernel-Based Framework for 2D-3D Pose Estimation and 2D Image Segmentation

PubMed Central

Sandhu, Romeil; Dambreville, Samuel; Yezzi, Anthony; Tannenbaum, Allen

2013-01-01

In this work, we present a nonrigid approach to jointly solving the tasks of 2D-3D pose estimation and 2D image segmentation. In general, most frameworks that couple both pose estimation and segmentation assume that one has exact knowledge of the 3D object. However, under nonideal conditions, this assumption may be violated if only a general class to which a given shape belongs is given (e.g., cars, boats, or planes). Thus, we propose to solve the 2D-3D pose estimation and 2D image segmentation via nonlinear manifold learning of 3D embedded shapes for a general class of objects or deformations for which one may not be able to associate a skeleton model. Thus, the novelty of our method is threefold: First, we present and derive a gradient flow for the task of nonrigid pose estimation and segmentation. Second, due to the possible nonlinear structures of one’s training set, we evolve the preimage obtained through kernel PCA for the task of shape analysis. Third, we show that the derivation for shape weights is general. This allows us to use various kernels, as well as other statistical learning methodologies, with only minimal changes needing to be made to the overall shape evolution scheme. In contrast with other techniques, we approach the nonrigid problem, which is an infinite-dimensional task, with a finite-dimensional optimization scheme. More importantly, we do not explicitly need to know the interaction between various shapes such as that needed for skeleton models as this is done implicitly through shape learning. We provide experimental results on several challenging pose estimation and segmentation scenarios. PMID:20733218

Recovering the 3d Pose and Shape of Vehicles from Stereo Images

NASA Astrophysics Data System (ADS)

Coenen, M.; Rottensteiner, F.; Heipke, C.

2018-05-01

The precise reconstruction and pose estimation of vehicles plays an important role, e.g. for autonomous driving. We tackle this problem on the basis of street level stereo images obtained from a moving vehicle. Starting from initial vehicle detections, we use a deformable vehicle shape prior learned from CAD vehicle data to fully reconstruct the vehicles in 3D and to recover their 3D pose and shape. To fit a deformable vehicle model to each detection by inferring the optimal parameters for pose and shape, we define an energy function leveraging reconstructed 3D data, image information, the vehicle model and derived scene knowledge. To minimise the energy function, we apply a robust model fitting procedure based on iterative Monte Carlo model particle sampling. We evaluate our approach using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012). Our approach can deal with very coarse pose initialisations and we achieve encouraging results with up to 82 % correct pose estimations. Moreover, we are able to deliver very precise orientation estimation results with an average absolute error smaller than 4°.

Object recognition and localization from 3D point clouds by maximum-likelihood estimation

NASA Astrophysics Data System (ADS)

Dantanarayana, Harshana G.; Huntley, Jonathan M.

2017-08-01

We present an algorithm based on maximum-likelihood analysis for the automated recognition of objects, and estimation of their pose, from 3D point clouds. Surfaces segmented from depth images are used as the features, unlike `interest point'-based algorithms which normally discard such data. Compared to the 6D Hough transform, it has negligible memory requirements, and is computationally efficient compared to iterative closest point algorithms. The same method is applicable to both the initial recognition/pose estimation problem as well as subsequent pose refinement through appropriate choice of the dispersion of the probability density functions. This single unified approach therefore avoids the usual requirement for different algorithms for these two tasks. In addition to the theoretical description, a simple 2 degrees of freedom (d.f.) example is given, followed by a full 6 d.f. analysis of 3D point cloud data from a cluttered scene acquired by a projected fringe-based scanner, which demonstrated an RMS alignment error as low as 0.3 mm.

Vision based object pose estimation for mobile robots

NASA Technical Reports Server (NTRS)

Wu, Annie; Bidlack, Clint; Katkere, Arun; Feague, Roy; Weymouth, Terry

1994-01-01

Mobile robot navigation using visual sensors requires that a robot be able to detect landmarks and obtain pose information from a camera image. This paper presents a vision system for finding man-made markers of known size and calculating the pose of these markers. The algorithm detects and identifies the markers using a weighted pattern matching template. Geometric constraints are then used to calculate the position of the markers relative to the robot. The selection of geometric constraints comes from the typical pose of most man-made signs, such as the sign standing vertical and the dimensions of known size. This system has been tested successfully on a wide range of real images. Marker detection is reliable, even in cluttered environments, and under certain marker orientations, estimation of the orientation has proven accurate to within 2 degrees, and distance estimation to within 0.3 meters.

3-D rigid body tracking using vision and depth sensors.

PubMed

Gedik, O Serdar; Alatan, A Aydn

2013-10-01

In robotics and augmented reality applications, model-based 3-D tracking of rigid objects is generally required. With the help of accurate pose estimates, it is required to increase reliability and decrease jitter in total. Among many solutions of pose estimation in the literature, pure vision-based 3-D trackers require either manual initializations or offline training stages. On the other hand, trackers relying on pure depth sensors are not suitable for AR applications. An automated 3-D tracking algorithm, which is based on fusion of vision and depth sensors via extended Kalman filter, is proposed in this paper. A novel measurement-tracking scheme, which is based on estimation of optical flow using intensity and shape index map data of 3-D point cloud, increases 2-D, as well as 3-D, tracking performance significantly. The proposed method requires neither manual initialization of pose nor offline training, while enabling highly accurate 3-D tracking. The accuracy of the proposed method is tested against a number of conventional techniques, and a superior performance is clearly observed in terms of both objectively via error metrics and subjectively for the rendered scenes.

Rhythmic Extended Kalman Filter for Gait Rehabilitation Motion Estimation and Segmentation.

PubMed

Joukov, Vladimir; Bonnet, Vincent; Karg, Michelle; Venture, Gentiane; Kulic, Dana

2018-02-01

This paper proposes a method to enable the use of non-intrusive, small, wearable, and wireless sensors to estimate the pose of the lower body during gait and other periodic motions and to extract objective performance measures useful for physiotherapy. The Rhythmic Extended Kalman Filter (Rhythmic-EKF) algorithm is developed to estimate the pose, learn an individualized model of periodic movement over time, and use the learned model to improve pose estimation. The proposed approach learns a canonical dynamical system model of the movement during online observation, which is used to accurately model the acceleration during pose estimation. The canonical dynamical system models the motion as a periodic signal. The estimated phase and frequency of the motion also allow the proposed approach to segment the motion into repetitions and extract useful features, such as gait symmetry, step length, and mean joint movement and variance. The algorithm is shown to outperform the extended Kalman filter in simulation, on healthy participant data, and stroke patient data. For the healthy participant marching dataset, the Rhythmic-EKF improves joint acceleration and velocity estimates over regular EKF by 40% and 37%, respectively, estimates joint angles with 2.4° root mean squared error, and segments the motion into repetitions with 96% accuracy.

Curve Set Feature-Based Robust and Fast Pose Estimation Algorithm

PubMed Central

Hashimoto, Koichi

2017-01-01

Bin picking refers to picking the randomly-piled objects from a bin for industrial production purposes, and robotic bin picking is always used in automated assembly lines. In order to achieve a higher productivity, a fast and robust pose estimation algorithm is necessary to recognize and localize the randomly-piled parts. This paper proposes a pose estimation algorithm for bin picking tasks using point cloud data. A novel descriptor Curve Set Feature (CSF) is proposed to describe a point by the surface fluctuation around this point and is also capable of evaluating poses. The Rotation Match Feature (RMF) is proposed to match CSF efficiently. The matching process combines the idea of the matching in 2D space of origin Point Pair Feature (PPF) algorithm with nearest neighbor search. A voxel-based pose verification method is introduced to evaluate the poses and proved to be more than 30-times faster than the kd-tree-based verification method. Our algorithm is evaluated against a large number of synthetic and real scenes and proven to be robust to noise, able to detect metal parts, more accurately and more than 10-times faster than PPF and Oriented, Unique and Repeatable (OUR)-Clustered Viewpoint Feature Histogram (CVFH). PMID:28771216

Detailed 3D representations for object recognition and modeling.

PubMed

Zia, M Zeeshan; Stark, Michael; Schiele, Bernt; Schindler, Konrad

2013-11-01

Geometric 3D reasoning at the level of objects has received renewed attention recently in the context of visual scene understanding. The level of geometric detail, however, is typically limited to qualitative representations or coarse boxes. This is linked to the fact that today's object class detectors are tuned toward robust 2D matching rather than accurate 3D geometry, encouraged by bounding-box-based benchmarks such as Pascal VOC. In this paper, we revisit ideas from the early days of computer vision, namely, detailed, 3D geometric object class representations for recognition. These representations can recover geometrically far more accurate object hypotheses than just bounding boxes, including continuous estimates of object pose and 3D wireframes with relative 3D positions of object parts. In combination with robust techniques for shape description and inference, we outperform state-of-the-art results in monocular 3D pose estimation. In a series of experiments, we analyze our approach in detail and demonstrate novel applications enabled by such an object class representation, such as fine-grained categorization of cars and bicycles, according to their 3D geometry, and ultrawide baseline matching.

A review of cooperative and uncooperative spacecraft pose determination techniques for close-proximity operations

NASA Astrophysics Data System (ADS)

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2017-08-01

The capability of an active spacecraft to accurately estimate its relative position and attitude (pose) with respect to an active/inactive, artificial/natural space object (target) orbiting in close-proximity is required to carry out various activities like formation flying, on-orbit servicing, active debris removal, and space exploration. According to the specific mission scenario, the pose determination task involves both theoretical and technological challenges related to the search for the most suitable algorithmic solution and sensor architecture, respectively. As regards the latter aspect, electro-optical sensors represent the best option as their use is compatible with mass and power limitation of micro and small satellites, and their measurements can be processed to estimate all the pose parameters. Overall, the degree of complexity of the challenges related to pose determination largely varies depending on the nature of the targets, which may be actively/passively cooperative, uncooperative but known, or uncooperative and unknown space objects. In this respect, while cooperative pose determination has been successfully demonstrated in orbit, the uncooperative case is still under study by universities, research centers, space agencies and private companies. However, in both the cases, the demand for space applications involving relative navigation maneuvers, also in close-proximity, for which pose determination capabilities are mandatory, is significantly increasing. In this framework, a review of state-of-the-art techniques and algorithms developed in the last decades for cooperative and uncooperative pose determination by processing data provided by electro-optical sensors is herein presented. Specifically, their main advantages and drawbacks in terms of achieved performance, computational complexity, and sensitivity to variability of pose and target geometry, are highlighted.

Marginal space learning for efficient detection of 2D/3D anatomical structures in medical images.

PubMed

Zheng, Yefeng; Georgescu, Bogdan; Comaniciu, Dorin

2009-01-01

Recently, marginal space learning (MSL) was proposed as a generic approach for automatic detection of 3D anatomical structures in many medical imaging modalities [1]. To accurately localize a 3D object, we need to estimate nine pose parameters (three for position, three for orientation, and three for anisotropic scaling). Instead of exhaustively searching the original nine-dimensional pose parameter space, only low-dimensional marginal spaces are searched in MSL to improve the detection speed. In this paper, we apply MSL to 2D object detection and perform a thorough comparison between MSL and the alternative full space learning (FSL) approach. Experiments on left ventricle detection in 2D MRI images show MSL outperforms FSL in both speed and accuracy. In addition, we propose two novel techniques, constrained MSL and nonrigid MSL, to further improve the efficiency and accuracy. In many real applications, a strong correlation may exist among pose parameters in the same marginal spaces. For example, a large object may have large scaling values along all directions. Constrained MSL exploits this correlation for further speed-up. The original MSL only estimates the rigid transformation of an object in the image, therefore cannot accurately localize a nonrigid object under a large deformation. The proposed nonrigid MSL directly estimates the nonrigid deformation parameters to improve the localization accuracy. The comparison experiments on liver detection in 226 abdominal CT volumes demonstrate the effectiveness of the proposed methods. Our system takes less than a second to accurately detect the liver in a volume.

An Improved Method of Pose Estimation for Lighthouse Base Station Extension.

PubMed

Yang, Yi; Weng, Dongdong; Li, Dong; Xun, Hang

2017-10-22

In 2015, HTC and Valve launched a virtual reality headset empowered with Lighthouse, the cutting-edge space positioning technology. Although Lighthouse is superior in terms of accuracy, latency and refresh rate, its algorithms do not support base station expansion, and is flawed concerning occlusion in moving targets, that is, it is unable to calculate their poses with a small set of sensors, resulting in the loss of optical tracking data. In view of these problems, this paper proposes an improved pose estimation algorithm for cases where occlusion is involved. Our algorithm calculates the pose of a given object with a unified dataset comprising of inputs from sensors recognized by all base stations, as long as three or more sensors detect a signal in total, no matter from which base station. To verify our algorithm, HTC official base stations and autonomous developed receivers are used for prototyping. The experiment result shows that our pose calculation algorithm can achieve precise positioning when a few sensors detect the signal.

An Improved Method of Pose Estimation for Lighthouse Base Station Extension

PubMed Central

Yang, Yi; Weng, Dongdong; Li, Dong; Xun, Hang

2017-01-01

In 2015, HTC and Valve launched a virtual reality headset empowered with Lighthouse, the cutting-edge space positioning technology. Although Lighthouse is superior in terms of accuracy, latency and refresh rate, its algorithms do not support base station expansion, and is flawed concerning occlusion in moving targets, that is, it is unable to calculate their poses with a small set of sensors, resulting in the loss of optical tracking data. In view of these problems, this paper proposes an improved pose estimation algorithm for cases where occlusion is involved. Our algorithm calculates the pose of a given object with a unified dataset comprising of inputs from sensors recognized by all base stations, as long as three or more sensors detect a signal in total, no matter from which base station. To verify our algorithm, HTC official base stations and autonomous developed receivers are used for prototyping. The experiment result shows that our pose calculation algorithm can achieve precise positioning when a few sensors detect the signal. PMID:29065509

A deep learning approach for pose estimation from volumetric OCT data.

PubMed

Gessert, Nils; Schlüter, Matthias; Schlaefer, Alexander

2018-05-01

Tracking the pose of instruments is a central problem in image-guided surgery. For microscopic scenarios, optical coherence tomography (OCT) is increasingly used as an imaging modality. OCT is suitable for accurate pose estimation due to its micrometer range resolution and volumetric field of view. However, OCT image processing is challenging due to speckle noise and reflection artifacts in addition to the images' 3D nature. We address pose estimation from OCT volume data with a new deep learning-based tracking framework. For this purpose, we design a new 3D convolutional neural network (CNN) architecture to directly predict the 6D pose of a small marker geometry from OCT volumes. We use a hexapod robot to automatically acquire labeled data points which we use to train 3D CNN architectures for multi-output regression. We use this setup to provide an in-depth analysis on deep learning-based pose estimation from volumes. Specifically, we demonstrate that exploiting volume information for pose estimation yields higher accuracy than relying on 2D representations with depth information. Supporting this observation, we provide quantitative and qualitative results that 3D CNNs effectively exploit the depth structure of marker objects. Regarding the deep learning aspect, we present efficient design principles for 3D CNNs, making use of insights from the 2D deep learning community. In particular, we present Inception3D as a new architecture which performs best for our application. We show that our deep learning approach reaches errors at our ground-truth label's resolution. We achieve a mean average error of 14.89 ± 9.3 µm and 0.096 ± 0.072° for position and orientation learning, respectively. Copyright © 2018 Elsevier B.V. All rights reserved.

A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating.

PubMed

Knips, Guido; Zibner, Stephan K U; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp.

A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating

PubMed Central

Knips, Guido; Zibner, Stephan K. U.; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp. PMID:28303100

Detection and 3d Modelling of Vehicles from Terrestrial Stereo Image Pairs

NASA Astrophysics Data System (ADS)

Coenen, M.; Rottensteiner, F.; Heipke, C.

2017-05-01

The detection and pose estimation of vehicles plays an important role for automated and autonomous moving objects e.g. in autonomous driving environments. We tackle that problem on the basis of street level stereo images, obtained from a moving vehicle. Processing every stereo pair individually, our approach is divided into two subsequent steps: the vehicle detection and the modelling step. For the detection, we make use of the 3D stereo information and incorporate geometric assumptions on vehicle inherent properties in a firstly applied generic 3D object detection. By combining our generic detection approach with a state of the art vehicle detector, we are able to achieve satisfying detection results with values for completeness and correctness up to more than 86%. By fitting an object specific vehicle model into the vehicle detections, we are able to reconstruct the vehicles in 3D and to derive pose estimations as well as shape parameters for each vehicle. To deal with the intra-class variability of vehicles, we make use of a deformable 3D active shape model learned from 3D CAD vehicle data in our model fitting approach. While we achieve encouraging values up to 67.2% for correct position estimations, we are facing larger problems concerning the orientation estimation. The evaluation is done by using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012).

Segmentation, classification, and pose estimation of military vehicles in low resolution laser radar images

NASA Astrophysics Data System (ADS)

Neulist, Joerg; Armbruster, Walter

2005-05-01

Model-based object recognition in range imagery typically involves matching the image data to the expected model data for each feasible model and pose hypothesis. Since the matching procedure is computationally expensive, the key to efficient object recognition is the reduction of the set of feasible hypotheses. This is particularly important for military vehicles, which may consist of several large moving parts such as the hull, turret, and gun of a tank, and hence require an eight or higher dimensional pose space to be searched. The presented paper outlines techniques for reducing the set of feasible hypotheses based on an estimation of target dimensions and orientation. Furthermore, the presence of a turret and a main gun and their orientations are determined. The vehicle parts dimensions as well as their error estimates restrict the number of model hypotheses whereas the position and orientation estimates and their error bounds reduce the number of pose hypotheses needing to be verified. The techniques are applied to several hundred laser radar images of eight different military vehicles with various part classifications and orientations. On-target resolution in azimuth, elevation and range is about 30 cm. The range images contain up to 20% dropouts due to atmospheric absorption. Additionally some target retro-reflectors produce outliers due to signal crosstalk. The presented algorithms are extremely robust with respect to these and other error sources. The hypothesis space for hull orientation is reduced to about 5 degrees as is the error for turret rotation and gun elevation, provided the main gun is visible.

A model-based 3D template matching technique for pose acquisition of an uncooperative space object.

PubMed

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2015-03-16

This paper presents a customized three-dimensional template matching technique for autonomous pose determination of uncooperative targets. This topic is relevant to advanced space applications, like active debris removal and on-orbit servicing. The proposed technique is model-based and produces estimates of the target pose without any prior pose information, by processing three-dimensional point clouds provided by a LIDAR. These estimates are then used to initialize a pose tracking algorithm. Peculiar features of the proposed approach are the use of a reduced number of templates and the idea of building the database of templates on-line, thus significantly reducing the amount of on-board stored data with respect to traditional techniques. An algorithm variant is also introduced aimed at further accelerating the pose acquisition time and reducing the computational cost. Technique performance is investigated within a realistic numerical simulation environment comprising a target model, LIDAR operation and various target-chaser relative dynamics scenarios, relevant to close-proximity flight operations. Specifically, the capability of the proposed techniques to provide a pose solution suitable to initialize the tracking algorithm is demonstrated, as well as their robustness against highly variable pose conditions determined by the relative dynamics. Finally, a criterion for autonomous failure detection of the presented techniques is presented.

The relative pose estimation of aircraft based on contour model

NASA Astrophysics Data System (ADS)

Fu, Tai; Sun, Xiangyi

2017-02-01

This paper proposes a relative pose estimation approach based on object contour model. The first step is to obtain a two-dimensional (2D) projection of three-dimensional (3D)-model-based target, which will be divided into 40 forms by clustering and LDA analysis. Then we proceed by extracting the target contour in each image and computing their Pseudo-Zernike Moments (PZM), thus a model library is constructed in an offline mode. Next, we spot a projection contour that resembles the target silhouette most in the present image from the model library with reference of PZM; then similarity transformation parameters are generated as the shape context is applied to match the silhouette sampling location, from which the identification parameters of target can be further derived. Identification parameters are converted to relative pose parameters, in the premise that these values are the initial result calculated via iterative refinement algorithm, as the relative pose parameter is in the neighborhood of actual ones. At last, Distance Image Iterative Least Squares (DI-ILS) is employed to acquire the ultimate relative pose parameters.

Reentry survivability modeling

NASA Astrophysics Data System (ADS)

Fudge, Michael L.; Maher, Robert L.

1997-10-01

Statistical methods for expressing the impact risk posed to space systems in general [and the International Space Station (ISS) in particular] by other resident space objects have been examined. One of the findings of this investigation is that there are legitimate physical modeling reasons for the common statistical expression of the collision risk. A combination of statistical methods and physical modeling is also used to express the impact risk posed by re-entering space systems to objects of interest (e.g., people and property) on Earth. One of the largest uncertainties in the expressing of this risk is the estimation of survivable material which survives reentry to impact Earth's surface. This point was recently demonstrated in dramatic fashion by the impact of an intact expendable launch vehicle (ELV) upper stage near a private residence in the continental United States. Since approximately half of the missions supporting ISS will utilize ELVs, it is appropriate to examine the methods used to estimate the amount and physical characteristics of ELV debris surviving reentry to impact Earth's surface. This paper examines reentry survivability estimation methodology, including the specific methodology used by Caiman Sciences' 'Survive' model. Comparison between empirical results (observations of objects which have been recovered on Earth after surviving reentry) and Survive estimates are presented for selected upper stage or spacecraft components and a Delta launch vehicle second stage.

Fuzzy Set Methods for Object Recognition in Space Applications

NASA Technical Reports Server (NTRS)

Keller, James M. (Editor)

1992-01-01

Progress on the following four tasks is described: (1) fuzzy set based decision methodologies; (2) membership calculation; (3) clustering methods (including derivation of pose estimation parameters), and (4) acquisition of images and testing of algorithms.

Machine Vision for Relative Spacecraft Navigation During Approach to Docking

NASA Technical Reports Server (NTRS)

Chien, Chiun-Hong; Baker, Kenneth

2011-01-01

This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

Assimilating data into open ocean tidal models

NASA Astrophysics Data System (ADS)

Kivman, Gennady A.

The problem of deriving tidal fields from observations by reason of incompleteness and imperfectness of every data set practically available has an infinitely large number of allowable solutions fitting the data within measurement errors and hence can be treated as ill-posed. Therefore, interpolating the data always relies on some a priori assumptions concerning the tides, which provide a rule of sampling or, in other words, a regularization of the ill-posed problem. Data assimilation procedures used in large scale tide modeling are viewed in a common mathematical framework as such regularizations. It is shown that they all (basis functions expansion, parameter estimation, nudging, objective analysis, general inversion, and extended general inversion), including those (objective analysis and general inversion) originally formulated in stochastic terms, may be considered as utilizations of one of the three general methods suggested by the theory of ill-posed problems. The problem of grid refinement critical for inverse methods and nudging is discussed.

Maximal likelihood correspondence estimation for face recognition across pose.

PubMed

Li, Shaoxin; Liu, Xin; Chai, Xiujuan; Zhang, Haihong; Lao, Shihong; Shan, Shiguang

2014-10-01

Due to the misalignment of image features, the performance of many conventional face recognition methods degrades considerably in across pose scenario. To address this problem, many image matching-based methods are proposed to estimate semantic correspondence between faces in different poses. In this paper, we aim to solve two critical problems in previous image matching-based correspondence learning methods: 1) fail to fully exploit face specific structure information in correspondence estimation and 2) fail to learn personalized correspondence for each probe image. To this end, we first build a model, termed as morphable displacement field (MDF), to encode face specific structure information of semantic correspondence from a set of real samples of correspondences calculated from 3D face models. Then, we propose a maximal likelihood correspondence estimation (MLCE) method to learn personalized correspondence based on maximal likelihood frontal face assumption. After obtaining the semantic correspondence encoded in the learned displacement, we can synthesize virtual frontal images of the profile faces for subsequent recognition. Using linear discriminant analysis method with pixel-intensity features, state-of-the-art performance is achieved on three multipose benchmarks, i.e., CMU-PIE, FERET, and MultiPIE databases. Owe to the rational MDF regularization and the usage of novel maximal likelihood objective, the proposed MLCE method can reliably learn correspondence between faces in different poses even in complex wild environment, i.e., labeled face in the wild database.

Grasping objects autonomously in simulated KC-135 zero-g

NASA Technical Reports Server (NTRS)

Norsworthy, Robert S.

1994-01-01

The KC-135 aircraft was chosen for simulated zero gravity testing of the Extravehicular Activity Helper/retriever (EVAHR). A software simulation of the EVAHR hardware, KC-135 flight dynamics, collision detection and grasp inpact dynamics has been developed to integrate and test the EVAHR software prior to flight testing on the KC-135. The EVAHR software will perform target pose estimation, tracking, and motion estimation for rigid, freely rotating, polyhedral objects. Manipulator grasp planning and trajectory control software has also been developed to grasp targets while avoiding collisions.

Stereovision-based pose and inertia estimation of unknown and uncooperative space objects

NASA Astrophysics Data System (ADS)

Pesce, Vincenzo; Lavagna, Michèle; Bevilacqua, Riccardo

2017-01-01

Autonomous close proximity operations are an arduous and attractive problem in space mission design. In particular, the estimation of pose, motion and inertia properties of an uncooperative object is a challenging task because of the lack of available a priori information. This paper develops a novel method to estimate the relative position, velocity, angular velocity, attitude and the ratios of the components of the inertia matrix of an uncooperative space object using only stereo-vision measurements. The classical Extended Kalman Filter (EKF) and an Iterated Extended Kalman Filter (IEKF) are used and compared for the estimation procedure. In addition, in order to compute the inertia properties, the ratios of the inertia components are added to the state and a pseudo-measurement equation is considered in the observation model. The relative simplicity of the proposed algorithm could be suitable for an online implementation for real applications. The developed algorithm is validated by numerical simulations in MATLAB using different initial conditions and uncertainty levels. The goal of the simulations is to verify the accuracy and robustness of the proposed estimation algorithm. The obtained results show satisfactory convergence of estimation errors for all the considered quantities. The obtained results, in several simulations, shows some improvements with respect to similar works, which deal with the same problem, present in literature. In addition, a video processing procedure is presented to reconstruct the geometrical properties of a body using cameras. This inertia reconstruction algorithm has been experimentally validated at the ADAMUS (ADvanced Autonomous MUltiple Spacecraft) Lab at the University of Florida. In the future, this different method could be integrated to the inertia ratios estimator to have a complete tool for mass properties recognition.

Algorithm for pose estimation based on objective function with uncertainty-weighted measuring error of feature point cling to the curved surface.

PubMed

Huo, Ju; Zhang, Guiyang; Yang, Ming

2018-04-20

This paper is concerned with the anisotropic and non-identical gray distribution of feature points clinging to the curved surface, upon which a high precision and uncertainty-resistance algorithm for pose estimation is proposed. Weighted contribution of uncertainty to the objective function of feature points measuring error is analyzed. Then a novel error objective function based on the spatial collinear error is constructed by transforming the uncertainty into a covariance-weighted matrix, which is suitable for the practical applications. Further, the optimized generalized orthogonal iterative (GOI) algorithm is utilized for iterative solutions such that it avoids the poor convergence and significantly resists the uncertainty. Hence, the optimized GOI algorithm extends the field-of-view applications and improves the accuracy and robustness of the measuring results by the redundant information. Finally, simulation and practical experiments show that the maximum error of re-projection image coordinates of the target is less than 0.110 pixels. Within the space 3000  mm×3000  mm×4000  mm, the maximum estimation errors of static and dynamic measurement for rocket nozzle motion are superior to 0.065° and 0.128°, respectively. Results verify the high accuracy and uncertainty attenuation performance of the proposed approach and should therefore have potential for engineering applications.

Local sensory control of a dexterous end effector

NASA Technical Reports Server (NTRS)

Pinto, Victor H.; Everett, Louis J.; Driels, Morris

1990-01-01

A numerical scheme was developed to solve the inverse kinematics for a user-defined manipulator. The scheme was based on a nonlinear least-squares technique which determines the joint variables by minimizing the difference between the target end effector pose and the actual end effector pose. The scheme was adapted to a dexterous hand in which the joints are either prismatic or revolute and the fingers are considered open kinematic chains. Feasible solutions were obtained using a three-fingered dexterous hand. An algorithm to estimate the position and orientation of a pre-grasped object was also developed. The algorithm was based on triangulation using an ideal sensor and a spherical object model. By choosing the object to be a sphere, only the position of the object frame was important. Based on these simplifications, a minimum of three sensors are needed to find the position of a sphere. A two dimensional example to determine the position of a circle coordinate frame using a two-fingered dexterous hand was presented.

On three dimensional object recognition and pose-determination: An abstraction based approach. Ph.D. Thesis - Michigan Univ. Final Report

NASA Technical Reports Server (NTRS)

Quek, Kok How Francis

1990-01-01

A method of computing reliable Gaussian and mean curvature sign-map descriptors from the polynomial approximation of surfaces was demonstrated. Such descriptors which are invariant under perspective variation are suitable for hypothesis generation. A means for determining the pose of constructed geometric forms whose algebraic surface descriptors are nonlinear in terms of their orienting parameters was developed. This was done by means of linear functions which are capable of approximating nonlinear forms and determining their parameters. It was shown that biquadratic surfaces are suitable companion linear forms for cylindrical approximation and parameter estimation. The estimates provided the initial parametric approximations necessary for a nonlinear regression stage to fine tune the estimates by fitting the actual nonlinear form to the data. A hypothesis-based split-merge algorithm for extraction and pose determination of cylinders and planes which merge smoothly into other surfaces was developed. It was shown that all split-merge algorithms are hypothesis-based. A finite-state algorithm for the extraction of the boundaries of run-length regions was developed. The computation takes advantage of the run list topology and boundary direction constraints implicit in the run-length encoding.

Image-based aircraft pose estimation: a comparison of simulations and real-world data

NASA Astrophysics Data System (ADS)

Breuers, Marcel G. J.; de Reus, Nico

2001-10-01

The problem of estimating aircraft pose information from mono-ocular image data is considered using a Fourier descriptor based algorithm. The dependence of pose estimation accuracy on image resolution and aspect angle is investigated through simulations using sets of synthetic aircraft images. Further evaluation shows that god pose estimation accuracy can be obtained in real world image sequences.

Volumetric segmentation of range images for printed circuit board inspection

NASA Astrophysics Data System (ADS)

Van Dop, Erik R.; Regtien, Paul P. L.

1996-10-01

Conventional computer vision approaches towards object recognition and pose estimation employ 2D grey-value or color imaging. As a consequence these images contain information about projections of a 3D scene only. The subsequent image processing will then be difficult, because the object coordinates are represented with just image coordinates. Only complicated low-level vision modules like depth from stereo or depth from shading can recover some of the surface geometry of the scene. Recent advances in fast range imaging have however paved the way towards 3D computer vision, since range data of the scene can now be obtained with sufficient accuracy and speed for object recognition and pose estimation purposes. This article proposes the coded-light range-imaging method together with superquadric segmentation to approach this task. Superquadric segments are volumetric primitives that describe global object properties with 5 parameters, which provide the main features for object recognition. Besides, the principle axes of a superquadric segment determine the phase of an object in the scene. The volumetric segmentation of a range image can be used to detect missing, false or badly placed components on assembled printed circuit boards. Furthermore, this approach will be useful to recognize and extract valuable or toxic electronic components on printed circuit boards scrap that currently burden the environment during electronic waste processing. Results on synthetic range images with errors constructed according to a verified noise model illustrate the capabilities of this approach.

Viewpoint Invariant Gesture Recognition and 3D Hand Pose Estimation Using RGB-D

ERIC Educational Resources Information Center

Doliotis, Paul

2013-01-01

The broad application domain of the work presented in this thesis is pattern classification with a focus on gesture recognition and 3D hand pose estimation. One of the main contributions of the proposed thesis is a novel method for 3D hand pose estimation using RGB-D. Hand pose estimation is formulated as a database retrieval problem. The proposed…

Point Cloud Based Relative Pose Estimation of a Satellite in Close Range

PubMed Central

Liu, Lujiang; Zhao, Gaopeng; Bo, Yuming

2016-01-01

Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estimation. This paper aims to estimate the pose of a target satellite in close range on the basis of its known model by using point cloud data generated by a flash LIDAR sensor. A novel model based pose estimation method is proposed; it includes a fast and reliable pose initial acquisition method based on global optimal searching by processing the dense point cloud data directly, and a pose tracking method based on Iterative Closest Point algorithm. Also, a simulation system is presented in this paper in order to evaluate the performance of the sensor and generate simulated sensor point cloud data. It also provides truth pose of the test target so that the pose estimation error can be quantified. To investigate the effectiveness of the proposed approach and achievable pose accuracy, numerical simulation experiments are performed; results demonstrate algorithm capability of operating with point cloud directly and large pose variations. Also, a field testing experiment is conducted and results show that the proposed method is effective. PMID:27271633

Estimating satellite pose and motion parameters using a novelty filter and neural net tracker

NASA Technical Reports Server (NTRS)

Lee, Andrew J.; Casasent, David; Vermeulen, Pieter; Barnard, Etienne

1989-01-01

A system for determining the position, orientation and motion of a satellite with respect to a robotic spacecraft using video data is advanced. This system utilizes two levels of pose and motion estimation: an initial system which provides coarse estimates of pose and motion, and a second system which uses the coarse estimates and further processing to provide finer pose and motion estimates. The present paper emphasizes the initial coarse pose and motion estimation sybsystem. This subsystem utilizes novelty detection and filtering for locating novel parts and a neural net tracker to track these parts over time. Results of using this system on a sequence of images of a spin stabilized satellite are presented.

Progressive 3D shape abstraction via hierarchical CSG tree

NASA Astrophysics Data System (ADS)

Chen, Xingyou; Tang, Jin; Li, Chenglong

2017-06-01

A constructive solid geometry(CSG) tree model is proposed to progressively abstract 3D geometric shape of general object from 2D image. Unlike conventional ones, our method applies to general object without the need for massive CAD models, and represents the object shapes in a coarse-to-fine manner that allows users to view temporal shape representations at any time. It stands in a transitional position between 2D image feature and CAD model, benefits from state-of-the-art object detection approaches and better initializes CAD model for finer fitting, estimates 3D shape and pose parameters of object at different levels according to visual perception objective, in a coarse-to-fine manner. Two main contributions are the application of CSG building up procedure into visual perception, and the ability of extending object estimation result into a more flexible and expressive model than 2D/3D primitive shapes. Experimental results demonstrate the feasibility and effectiveness of the proposed approach.

Projector-Based Augmented Reality for Quality Inspection of Scanned Objects

NASA Astrophysics Data System (ADS)

Kern, J.; Weinmann, M.; Wursthorn, S.

2017-09-01

After scanning or reconstructing the geometry of objects, we need to inspect the result of our work. Are there any parts missing? Is every detail covered in the desired quality? We typically do this by looking at the resulting point clouds or meshes of our objects on-screen. What, if we could see the information directly visualized on the object itself? Augmented reality is the generic term for bringing virtual information into our real environment. In our paper, we show how we can project any 3D information like thematic visualizations or specific monitoring information with reference to our object onto the object's surface itself, thus augmenting it with additional information. For small objects that could for instance be scanned in a laboratory, we propose a low-cost method involving a projector-camera system to solve this task. The user only needs a calibration board with coded fiducial markers to calibrate the system and to estimate the projector's pose later on for projecting textures with information onto the object's surface. Changes within the projected 3D information or of the projector's pose will be applied in real-time. Our results clearly reveal that such a simple setup will deliver a good quality of the augmented information.

Localizing intracavitary brachytherapy applicators from cone-beam CT x-ray projections via a novel iterative forward projection matching algorithm.

PubMed

Pokhrel, Damodar; Murphy, Martin J; Todor, Dorin A; Weiss, Elisabeth; Williamson, Jeffrey F

2011-02-01

To present a novel method for reconstructing the 3D pose (position and orientation) of radio-opaque applicators of known but arbitrary shape from a small set of 2D x-ray projections in support of intraoperative brachytherapy planning. The generalized iterative forward projection matching (gIFPM) algorithm finds the six degree-of-freedom pose of an arbitrary rigid object by minimizing the sum-of-squared-intensity differences (SSQD) between the computed and experimentally acquired autosegmented projection of the objects. Starting with an initial estimate of the object's pose, gIFPM iteratively refines the pose parameters (3D position and three Euler angles) until the SSQD converges. The object, here specialized to a Fletcher-Weeks intracavitary brachytherapy (ICB) applicator, is represented by a fine mesh of discrete points derived from complex combinatorial geometric models of the actual applicators. Three pairs of computed and measured projection images with known imaging geometry are used. Projection images of an intrauterine tandem and colpostats were acquired from an ACUITY cone-beam CT digital simulator. An image postprocessing step was performed to create blurred binary applicators only images. To quantify gIFPM accuracy, the reconstructed 3D pose of the applicator model was forward projected and overlaid with the measured images and empirically calculated the nearest-neighbor applicator positional difference for each image pair. In the numerical simulations, the tandem and colpostats positions (x,y,z) and orientations (alpha, beta, gamma) were estimated with accuracies of 0.6 mm and 2 degrees, respectively. For experimentally acquired images of actual applicators, the residual 2D registration error was less than 1.8 mm for each image pair, corresponding to about 1 mm positioning accuracy at isocenter, with a total computation time of less than 1.5 min on a 1 GHz processor. This work describes a novel, accurate, fast, and completely automatic method to localize radio-opaque applicators of arbitrary shape from measured 2D x-ray projections. The results demonstrate approximately 1 mm accuracy while compared against the measured applicator projections. No lateral film is needed. By localizing the applicator internal structure as well as radioactive sources, the effect of intra-applicator and interapplicator attenuation can be included in the resultant dose calculations. Further validation tests using clinically acquired tandem and colpostats images will be performed for the accurate and robust applicator/sources localization in ICB patients.

Localizing intracavitary brachytherapy applicators from cone-beam CT x-ray projections via a novel iterative forward projection matching algorithm

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

Pokhrel, Damodar; Murphy, Martin J.; Todor, Dorin A.

2011-02-15

Purpose: To present a novel method for reconstructing the 3D pose (position and orientation) of radio-opaque applicators of known but arbitrary shape from a small set of 2D x-ray projections in support of intraoperative brachytherapy planning. Methods: The generalized iterative forward projection matching (gIFPM) algorithm finds the six degree-of-freedom pose of an arbitrary rigid object by minimizing the sum-of-squared-intensity differences (SSQD) between the computed and experimentally acquired autosegmented projection of the objects. Starting with an initial estimate of the object's pose, gIFPM iteratively refines the pose parameters (3D position and three Euler angles) until the SSQD converges. The object, heremore » specialized to a Fletcher-Weeks intracavitary brachytherapy (ICB) applicator, is represented by a fine mesh of discrete points derived from complex combinatorial geometric models of the actual applicators. Three pairs of computed and measured projection images with known imaging geometry are used. Projection images of an intrauterine tandem and colpostats were acquired from an ACUITY cone-beam CT digital simulator. An image postprocessing step was performed to create blurred binary applicators only images. To quantify gIFPM accuracy, the reconstructed 3D pose of the applicator model was forward projected and overlaid with the measured images and empirically calculated the nearest-neighbor applicator positional difference for each image pair. Results: In the numerical simulations, the tandem and colpostats positions (x,y,z) and orientations ({alpha},{beta},{gamma}) were estimated with accuracies of 0.6 mm and 2 deg., respectively. For experimentally acquired images of actual applicators, the residual 2D registration error was less than 1.8 mm for each image pair, corresponding to about 1 mm positioning accuracy at isocenter, with a total computation time of less than 1.5 min on a 1 GHz processor. Conclusions: This work describes a novel, accurate, fast, and completely automatic method to localize radio-opaque applicators of arbitrary shape from measured 2D x-ray projections. The results demonstrate {approx}1 mm accuracy while compared against the measured applicator projections. No lateral film is needed. By localizing the applicator internal structure as well as radioactive sources, the effect of intra-applicator and interapplicator attenuation can be included in the resultant dose calculations. Further validation tests using clinically acquired tandem and colpostats images will be performed for the accurate and robust applicator/sources localization in ICB patients.« less

Nonlinear dynamic model for visual object tracking on Grassmann manifolds with partial occlusion handling.

PubMed

Khan, Zulfiqar Hasan; Gu, Irene Yu-Hua

2013-12-01

This paper proposes a novel Bayesian online learning and tracking scheme for video objects on Grassmann manifolds. Although manifold visual object tracking is promising, large and fast nonplanar (or out-of-plane) pose changes and long-term partial occlusions of deformable objects in video remain a challenge that limits the tracking performance. The proposed method tackles these problems with the main novelties on: 1) online estimation of object appearances on Grassmann manifolds; 2) optimal criterion-based occlusion handling for online updating of object appearances; 3) a nonlinear dynamic model for both the appearance basis matrix and its velocity; and 4) Bayesian formulations, separately for the tracking process and the online learning process, that are realized by employing two particle filters: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in an alternating fashion to mitigate the tracking drift. Experiments using the proposed tracker on videos captured by a single dynamic/static camera have shown robust tracking performance, particularly for scenarios when target objects contain significant nonplanar pose changes and long-term partial occlusions. Comparisons with eight existing state-of-the-art/most relevant manifold/nonmanifold trackers with evaluations have provided further support to the proposed scheme.

A pose estimation method for unmanned ground vehicles in GPS denied environments

NASA Astrophysics Data System (ADS)

Tamjidi, Amirhossein; Ye, Cang

2012-06-01

This paper presents a pose estimation method based on the 1-Point RANSAC EKF (Extended Kalman Filter) framework. The method fuses the depth data from a LIDAR and the visual data from a monocular camera to estimate the pose of a Unmanned Ground Vehicle (UGV) in a GPS denied environment. Its estimation framework continuy updates the vehicle's 6D pose state and temporary estimates of the extracted visual features' 3D positions. In contrast to the conventional EKF-SLAM (Simultaneous Localization And Mapping) frameworks, the proposed method discards feature estimates from the extended state vector once they are no longer observed for several steps. As a result, the extended state vector always maintains a reasonable size that is suitable for online calculation. The fusion of laser and visual data is performed both in the feature initialization part of the EKF-SLAM process and in the motion prediction stage. A RANSAC pose calculation procedure is devised to produce pose estimate for the motion model. The proposed method has been successfully tested on the Ford campus's LIDAR-Vision dataset. The results are compared with the ground truth data of the dataset and the estimation error is ~1.9% of the path length.

Head pose estimation in computer vision: a survey.

PubMed

Murphy-Chutorian, Erik; Trivedi, Mohan Manubhai

2009-04-01

The capacity to estimate the head pose of another person is a common human ability that presents a unique challenge for computer vision systems. Compared to face detection and recognition, which have been the primary foci of face-related vision research, identity-invariant head pose estimation has fewer rigorously evaluated systems or generic solutions. In this paper, we discuss the inherent difficulties in head pose estimation and present an organized survey describing the evolution of the field. Our discussion focuses on the advantages and disadvantages of each approach and spans 90 of the most innovative and characteristic papers that have been published on this topic. We compare these systems by focusing on their ability to estimate coarse and fine head pose, highlighting approaches that are well suited for unconstrained environments.

Art critic: Multisignal vision and speech interaction system in a gaming context.

PubMed

Reale, Michael J; Liu, Peng; Yin, Lijun; Canavan, Shaun

2013-12-01

True immersion of a player within a game can only occur when the world simulated looks and behaves as close to reality as possible. This implies that the game must correctly read and understand, among other things, the player's focus, attitude toward the objects/persons in focus, gestures, and speech. In this paper, we proposed a novel system that integrates eye gaze estimation, head pose estimation, facial expression recognition, speech recognition, and text-to-speech components for use in real-time games. Both the eye gaze and head pose components utilize underlying 3-D models, and our novel head pose estimation algorithm uniquely combines scene flow with a generic head model. The facial expression recognition module uses the local binary patterns with three orthogonal planes approach on the 2-D shape index domain rather than the pixel domain, resulting in improved classification. Our system has also been extended to use a pan-tilt-zoom camera driven by the Kinect, allowing us to track a moving player. A test game, Art Critic, is also presented, which not only demonstrates the utility of our system but also provides a template for player/non-player character (NPC) interaction in a gaming context. The player alters his/her view of the 3-D world using head pose, looks at paintings/NPCs using eye gaze, and makes an evaluation based on the player's expression and speech. The NPC artist will respond with facial expression and synthetic speech based on its personality. Both qualitative and quantitative evaluations of the system are performed to illustrate the system's effectiveness.

Stable image acquisition for mobile image processing applications

NASA Astrophysics Data System (ADS)

Henning, Kai-Fabian; Fritze, Alexander; Gillich, Eugen; Mönks, Uwe; Lohweg, Volker

2015-02-01

Today, mobile devices (smartphones, tablets, etc.) are widespread and of high importance for their users. Their performance as well as versatility increases over time. This leads to the opportunity to use such devices for more specific tasks like image processing in an industrial context. For the analysis of images requirements like image quality (blur, illumination, etc.) as well as a defined relative position of the object to be inspected are crucial. Since mobile devices are handheld and used in constantly changing environments the challenge is to fulfill these requirements. We present an approach to overcome the obstacles and stabilize the image capturing process such that image analysis becomes significantly improved on mobile devices. Therefore, image processing methods are combined with sensor fusion concepts. The approach consists of three main parts. First, pose estimation methods are used to guide a user moving the device to a defined position. Second, the sensors data and the pose information are combined for relative motion estimation. Finally, the image capturing process is automated. It is triggered depending on the alignment of the device and the object as well as the image quality that can be achieved under consideration of motion and environmental effects.

Optimal accelerometer placement on a robot arm for pose estimation

NASA Astrophysics Data System (ADS)

Wijayasinghe, Indika B.; Sanford, Joseph D.; Abubakar, Shamsudeen; Saadatzi, Mohammad Nasser; Das, Sumit K.; Popa, Dan O.

2017-05-01

The performance of robots to carry out tasks depends in part on the sensor information they can utilize. Usually, robots are fitted with angle joint encoders that are used to estimate the position and orientation (or the pose) of its end-effector. However, there are numerous situations, such as in legged locomotion, mobile manipulation, or prosthetics, where such joint sensors may not be present at every, or any joint. In this paper we study the use of inertial sensors, in particular accelerometers, placed on the robot that can be used to estimate the robot pose. Studying accelerometer placement on a robot involves many parameters that affect the performance of the intended positioning task. Parameters such as the number of accelerometers, their size, geometric placement and Signal-to-Noise Ratio (SNR) are included in our study of their effects for robot pose estimation. Due to the ubiquitous availability of inexpensive accelerometers, we investigated pose estimation gains resulting from using increasingly large numbers of sensors. Monte-Carlo simulations are performed with a two-link robot arm to obtain the expected value of an estimation error metric for different accelerometer configurations, which are then compared for optimization. Results show that, with a fixed SNR model, the pose estimation error decreases with increasing number of accelerometers, whereas for a SNR model that scales inversely to the accelerometer footprint, the pose estimation error increases with the number of accelerometers. It is also shown that the optimal placement of the accelerometers depends on the method used for pose estimation. The findings suggest that an integration-based method favors placement of accelerometers at the extremities of the robot links, whereas a kinematic-constraints-based method favors a more uniformly distributed placement along the robot links.

Space Vehicle Pose Estimation via Optical Correlation and Nonlinear Estimation

NASA Technical Reports Server (NTRS)

Rakoczy, John M.; Herren, Kenneth A.

2008-01-01

A technique for 6-degree-of-freedom (6DOF) pose estimation of space vehicles is being developed. This technique draws upon recent developments in implementing optical correlation measurements in a nonlinear estimator, which relates the optical correlation measurements to the pose states (orientation and position). For the optical correlator, the use of both conjugate filters and binary, phase-only filters in the design of synthetic discriminant function (SDF) filters is explored. A static neural network is trained a priori and used as the nonlinear estimator. New commercial animation and image rendering software is exploited to design the SDF filters and to generate a large filter set with which to train the neural network. The technique is applied to pose estimation for rendezvous and docking of free-flying spacecraft and to terrestrial surface mobility systems for NASA's Vision for Space Exploration. Quantitative pose estimation performance will be reported. Advantages and disadvantages of the implementation of this technique are discussed.

Space Vehicle Pose Estimation via Optical Correlation and Nonlinear Estimation

NASA Technical Reports Server (NTRS)

Rakoczy, John; Herren, Kenneth

2007-01-01

A technique for 6-degree-of-freedom (6DOF) pose estimation of space vehicles is being developed. This technique draws upon recent developments in implementing optical correlation measurements in a nonlinear estimator, which relates the optical correlation measurements to the pose states (orientation and position). For the optical correlator, the use of both conjugate filters and binary, phase-only filters in the design of synthetic discriminant function (SDF) filters is explored. A static neural network is trained a priori and used as the nonlinear estimator. New commercial animation and image rendering software is exploited to design the SDF filters and to generate a large filter set with which to train the neural network. The technique is applied to pose estimation for rendezvous and docking of free-flying spacecraft and to terrestrial surface mobility systems for NASA's Vision for Space Exploration. Quantitative pose estimation performance will be reported. Advantages and disadvantages of the implementation of this technique are discussed.

Satellite markers: a simple method for ground truth car pose on stereo video

NASA Astrophysics Data System (ADS)

Gil, Gustavo; Savino, Giovanni; Piantini, Simone; Pierini, Marco

2018-04-01

Artificial prediction of future location of other cars in the context of advanced safety systems is a must. The remote estimation of car pose and particularly its heading angle is key to predict its future location. Stereo vision systems allow to get the 3D information of a scene. Ground truth in this specific context is associated with referential information about the depth, shape and orientation of the objects present in the traffic scene. Creating 3D ground truth is a measurement and data fusion task associated with the combination of different kinds of sensors. The novelty of this paper is the method to generate ground truth car pose only from video data. When the method is applied to stereo video, it also provides the extrinsic camera parameters for each camera at frame level which are key to quantify the performance of a stereo vision system when it is moving because the system is subjected to undesired vibrations and/or leaning. We developed a video post-processing technique which employs a common camera calibration tool for the 3D ground truth generation. In our case study, we focus in accurate car heading angle estimation of a moving car under realistic imagery. As outcomes, our satellite marker method provides accurate car pose at frame level, and the instantaneous spatial orientation for each camera at frame level.

Head Pose Estimation on Eyeglasses Using Line Detection and Classification Approach

NASA Astrophysics Data System (ADS)

Setthawong, Pisal; Vannija, Vajirasak

This paper proposes a unique approach for head pose estimation of subjects with eyeglasses by using a combination of line detection and classification approaches. Head pose estimation is considered as an important non-verbal form of communication and could also be used in the area of Human-Computer Interface. A major improvement of the proposed approach is that it allows estimation of head poses at a high yaw/pitch angle when compared with existing geometric approaches, does not require expensive data preparation and training, and is generally fast when compared with other approaches.

Fast human pose estimation using 3D Zernike descriptors

NASA Astrophysics Data System (ADS)

Berjón, Daniel; Morán, Francisco

2012-03-01

Markerless video-based human pose estimation algorithms face a high-dimensional problem that is frequently broken down into several lower-dimensional ones by estimating the pose of each limb separately. However, in order to do so they need to reliably locate the torso, for which they typically rely on time coherence and tracking algorithms. Their losing track usually results in catastrophic failure of the process, requiring human intervention and thus precluding their usage in real-time applications. We propose a very fast rough pose estimation scheme based on global shape descriptors built on 3D Zernike moments. Using an articulated model that we configure in many poses, a large database of descriptor/pose pairs can be computed off-line. Thus, the only steps that must be done on-line are the extraction of the descriptors for each input volume and a search against the database to get the most likely poses. While the result of such process is not a fine pose estimation, it can be useful to help more sophisticated algorithms to regain track or make more educated guesses when creating new particles in particle-filter-based tracking schemes. We have achieved a performance of about ten fps on a single computer using a database of about one million entries.

Head Pose Estimation Using Multilinear Subspace Analysis for Robot Human Awareness

NASA Technical Reports Server (NTRS)

Ivanov, Tonislav; Matthies, Larry; Vasilescu, M. Alex O.

2009-01-01

Mobile robots, operating in unconstrained indoor and outdoor environments, would benefit in many ways from perception of the human awareness around them. Knowledge of people's head pose and gaze directions would enable the robot to deduce which people are aware of the its presence, and to predict future motions of the people for better path planning. To make such inferences, requires estimating head pose on facial images that are combination of multiple varying factors, such as identity, appearance, head pose, and illumination. By applying multilinear algebra, the algebra of higher-order tensors, we can separate these factors and estimate head pose regardless of subject's identity or image conditions. Furthermore, we can automatically handle uncertainty in the size of the face and its location. We demonstrate a pipeline of on-the-move detection of pedestrians with a robot stereo vision system, segmentation of the head, and head pose estimation in cluttered urban street scenes.

Optical correlation based pose estimation using bipolar phase grayscale amplitude spatial light modulators

NASA Astrophysics Data System (ADS)

Outerbridge, Gregory John, II

Pose estimation techniques have been developed on both optical and digital correlator platforms to aid in the autonomous rendezvous and docking of spacecraft. This research has focused on the optical architecture, which utilizes high-speed bipolar-phase grayscale-amplitude spatial light modulators as the image and correlation filter devices. The optical approach has the primary advantage of optical parallel processing: an extremely fast and efficient way of performing complex correlation calculations. However, the constraints imposed on optically implementable filters makes optical correlator based posed estimation technically incompatible with the popular weighted composite filter designs successfully used on the digital platform. This research employs a much simpler "bank of filters" approach to optical pose estimation that exploits the inherent efficiency of optical correlation devices. A novel logarithmically mapped optically implementable matched filter combined with a pose search algorithm resulted in sub-degree standard deviations in angular pose estimation error. These filters were extremely simple to generate, requiring no complicated training sets and resulted in excellent performance even in the presence of significant background noise. Common edge detection and scaling of the input image was the only image pre-processing necessary for accurate pose detection at all alignment distances of interest.

Robot Acting on Moving Bodies (RAMBO): Interaction with tumbling objects

NASA Technical Reports Server (NTRS)

Davis, Larry S.; Dementhon, Daniel; Bestul, Thor; Ziavras, Sotirios; Srinivasan, H. V.; Siddalingaiah, Madhu; Harwood, David

1989-01-01

Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Constructing a Database from Multiple 2D Images for Camera Pose Estimation and Robot Localization

NASA Technical Reports Server (NTRS)

Wolf, Michael; Ansar, Adnan I.; Brennan, Shane; Clouse, Daniel S.; Padgett, Curtis W.

2012-01-01

The LMDB (Landmark Database) Builder software identifies persistent image features (landmarks) in a scene viewed multiple times and precisely estimates the landmarks 3D world positions. The software receives as input multiple 2D images of approximately the same scene, along with an initial guess of the camera poses for each image, and a table of features matched pair-wise in each frame. LMDB Builder aggregates landmarks across an arbitrarily large collection of frames with matched features. Range data from stereo vision processing can also be passed to improve the initial guess of the 3D point estimates. The LMDB Builder aggregates feature lists across all frames, manages the process to promote selected features to landmarks, and iteratively calculates the 3D landmark positions using the current camera pose estimations (via an optimal ray projection method), and then improves the camera pose estimates using the 3D landmark positions. Finally, it extracts image patches for each landmark from auto-selected key frames and constructs the landmark database. The landmark database can then be used to estimate future camera poses (and therefore localize a robotic vehicle that may be carrying the cameras) by matching current imagery to landmark database image patches and using the known 3D landmark positions to estimate the current pose.

Robust head pose estimation via supervised manifold learning.

PubMed

Wang, Chao; Song, Xubo

2014-05-01

Head poses can be automatically estimated using manifold learning algorithms, with the assumption that with the pose being the only variable, the face images should lie in a smooth and low-dimensional manifold. However, this estimation approach is challenging due to other appearance variations related to identity, head location in image, background clutter, facial expression, and illumination. To address the problem, we propose to incorporate supervised information (pose angles of training samples) into the process of manifold learning. The process has three stages: neighborhood construction, graph weight computation and projection learning. For the first two stages, we redefine inter-point distance for neighborhood construction as well as graph weight by constraining them with the pose angle information. For Stage 3, we present a supervised neighborhood-based linear feature transformation algorithm to keep the data points with similar pose angles close together but the data points with dissimilar pose angles far apart. The experimental results show that our method has higher estimation accuracy than the other state-of-art algorithms and is robust to identity and illumination variations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Near-Earth Object Astrometric Interferometry

NASA Technical Reports Server (NTRS)

Werner, Martin R.

2005-01-01

Using astrometric interferometry on near-Earth objects (NEOs) poses many interesting and difficult challenges. Poor reflectance properties and potentially no significant active emissions lead to NEOs having intrinsically low visual magnitudes. Using worst case estimates for signal reflection properties leads to NEOs having visual magnitudes of 27 and higher. Today the most sensitive interferometers in operation have limiting magnitudes of 20 or less. The main reason for this limit is due to the atmosphere, where turbulence affects the light coming from the target, limiting the sensitivity of the interferometer. In this analysis, the interferometer designs assume no atmosphere, meaning they would be placed at a location somewhere in space. Interferometer configurations and operational uncertainties are looked at in order to parameterize the requirements necessary to achieve measurements of low visual magnitude NEOs. This analysis provides a preliminary estimate of what will be required in order to take high resolution measurements of these objects using interferometry techniques.

Exemplar-based human action pose correction.

PubMed

Shen, Wei; Deng, Ke; Bai, Xiang; Leyvand, Tommer; Guo, Baining; Tu, Zhuowen

2014-07-01

The launch of Xbox Kinect has built a very successful computer vision product and made a big impact on the gaming industry. This sheds lights onto a wide variety of potential applications related to action recognition. The accurate estimation of human poses from the depth image is universally a critical step. However, existing pose estimation systems exhibit failures when facing severe occlusion. In this paper, we propose an exemplar-based method to learn to correct the initially estimated poses. We learn an inhomogeneous systematic bias by leveraging the exemplar information within a specific human action domain. Furthermore, as an extension, we learn a conditional model by incorporation of pose tags to further increase the accuracy of pose correction. In the experiments, significant improvements on both joint-based skeleton correction and tag prediction are observed over the contemporary approaches, including what is delivered by the current Kinect system. Our experiments for the facial landmark correction also illustrate that our algorithm can improve the accuracy of other detection/estimation systems.

Robot acting on moving bodies (RAMBO): Preliminary results

NASA Technical Reports Server (NTRS)

Davis, Larry S.; Dementhon, Daniel; Bestul, Thor; Ziavras, Sotirios; Srinivasan, H. V.; Siddalingaiah, Madju; Harwood, David

1989-01-01

A robot system called RAMBO is being developed. It is equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a moving object. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations nearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enchancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows the use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using parametric cubic splines between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

The ART of representation: Memory reduction and noise tolerance in a neural network vision system

NASA Astrophysics Data System (ADS)

Langley, Christopher S.

The Feature Cerebellar Model Arithmetic Computer (FCMAC) is a multiple-input-single-output neural network that can provide three-degree-of-freedom (3-DOF) pose estimation for a robotic vision system. The FCMAC provides sufficient accuracy to enable a manipulator to grasp an object from an arbitrary pose within its workspace. The network learns an appearance-based representation of an object by storing coarsely quantized feature patterns. As all unique patterns are encoded, the network size grows uncontrollably. A new architecture is introduced herein, which combines the FCMAC with an Adaptive Resonance Theory (ART) network. The ART module categorizes patterns observed during training into a set of prototypes that are used to build the FCMAC. As a result, the network no longer grows without bound, but constrains itself to a user-specified size. Pose estimates remain accurate since the ART layer tends to discard the least relevant information first. The smaller network performs recall faster, and in some cases is better for generalization, resulting in a reduction of error at recall time. The ART-Under-Constraint (ART-C) algorithm is extended to include initial filling with randomly selected patterns (referred to as ART-F). In experiments using a real-world data set, the new network performed equally well using less than one tenth the number of coarse patterns as a regular FCMAC. The FCMAC is also extended to include real-valued input activations. As a result, the network can be tuned to reject a variety of types of noise in the image feature detection. A quantitative analysis of noise tolerance was performed using four synthetic noise algorithms, and a qualitative investigation was made using noisy real-world image data. In validation experiments, the FCMAC system outperformed Radial Basis Function (RBF) networks for the 3-DOF problem, and had accuracy comparable to that of Principal Component Analysis (PCA) and superior to that of Shape Context Matching (SCM), both of which estimate orientation only.

Feature Extraction for Pose Estimation. A Comparison Between Synthetic and Real IR Imagery

DTIC Science & Technology

1991-12-01

determine the orientation of the sensor relative to the target ....... ........................ 33 4. Effects of changing sensor and target parameters...Reference object is a T-62 tank facing the viewer (sensor/target parameters set equal to zero). NOTE: Changing the target parameters produces...anomalous results. For these images, the field of view (FOV) was not changed .......................... 35 5. Image anomalies from changing the target

Real-Time 3D Tracking and Reconstruction on Mobile Phones.

PubMed

Prisacariu, Victor Adrian; Kähler, Olaf; Murray, David W; Reid, Ian D

2015-05-01

We present a novel framework for jointly tracking a camera in 3D and reconstructing the 3D model of an observed object. Due to the region based approach, our formulation can handle untextured objects, partial occlusions, motion blur, dynamic backgrounds and imperfect lighting. Our formulation also allows for a very efficient implementation which achieves real-time performance on a mobile phone, by running the pose estimation and the shape optimisation in parallel. We use a level set based pose estimation but completely avoid the, typically required, explicit computation of a global distance. This leads to tracking rates of more than 100 Hz on a desktop PC and 30 Hz on a mobile phone. Further, we incorporate additional orientation information from the phone's inertial sensor which helps us resolve the tracking ambiguities inherent to region based formulations. The reconstruction step first probabilistically integrates 2D image statistics from selected keyframes into a 3D volume, and then imposes coherency and compactness using a total variational regularisation term. The global optimum of the overall energy function is found using a continuous max-flow algorithm and we show that, similar to tracking, the integration of per voxel posteriors instead of likelihoods improves the precision and accuracy of the reconstruction.

Automatic C-arm pose estimation via 2D/3D hybrid registration of a radiographic fiducial

NASA Astrophysics Data System (ADS)

Moult, E.; Burdette, E. C.; Song, D. Y.; Abolmaesumi, P.; Fichtinger, G.; Fallavollita, P.

2011-03-01

Motivation: In prostate brachytherapy, real-time dosimetry would be ideal to allow for rapid evaluation of the implant quality intra-operatively. However, such a mechanism requires an imaging system that is both real-time and which provides, via multiple C-arm fluoroscopy images, clear information describing the three-dimensional position of the seeds deposited within the prostate. Thus, accurate tracking of the C-arm poses proves to be of critical importance to the process. Methodology: We compute the pose of the C-arm relative to a stationary radiographic fiducial of known geometry by employing a hybrid registration framework. Firstly, by means of an ellipse segmentation algorithm and a 2D/3D feature based registration, we exploit known FTRAC geometry to recover an initial estimate of the C-arm pose. Using this estimate, we then initialize the intensity-based registration which serves to recover a refined and accurate estimation of the C-arm pose. Results: Ground-truth pose was established for each C-arm image through a published and clinically tested segmentation-based method. Using 169 clinical C-arm images and a +/-10° and +/-10 mm random perturbation of the ground-truth pose, the average rotation and translation errors were 0.68° (std = 0.06°) and 0.64 mm (std = 0.24 mm). Conclusion: Fully automated C-arm pose estimation using a 2D/3D hybrid registration scheme was found to be clinically robust based on human patient data.

Bone Pose Estimation in the Presence of Soft Tissue Artifact Using Triangular Cosserat Point Elements.

PubMed

Solav, Dana; Rubin, M B; Cereatti, Andrea; Camomilla, Valentina; Wolf, Alon

2016-04-01

Accurate estimation of the position and orientation (pose) of a bone from a cluster of skin markers is limited mostly by the relative motion between the bone and the markers, which is known as the soft tissue artifact (STA). This work presents a method, based on continuum mechanics, to describe the kinematics of a cluster affected by STA. The cluster is characterized by triangular cosserat point elements (TCPEs) defined by all combinations of three markers. The effects of the STA on the TCPEs are quantified using three parameters describing the strain in each TCPE and the relative rotation and translation between TCPEs. The method was evaluated using previously collected ex vivo kinematic data. Femur pose was estimated from 12 skin markers on the thigh, while its reference pose was measured using bone pins. Analysis revealed that instantaneous subsets of TCPEs exist which estimate bone position and orientation more accurately than the Procrustes Superimposition applied to the cluster of all markers. It has been shown that some of these parameters correlate well with femur pose errors, which suggests that they can be used to select, at each instant, subsets of TCPEs leading an improved estimation of the underlying bone pose.

Coupled multiview autoencoders with locality sensitivity for three-dimensional human pose estimation

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng; Luo, Shasha; Duan, Bichao

2017-09-01

Estimating three-dimensional (3D) human poses from a single camera is usually implemented by searching pose candidates with image descriptors. Existing methods usually suppose that the mapping from feature space to pose space is linear, but in fact, their mapping relationship is highly nonlinear, which heavily degrades the performance of 3D pose estimation. We propose a method to recover 3D pose from a silhouette image. It is based on the multiview feature embedding (MFE) and the locality-sensitive autoencoders (LSAEs). On the one hand, we first depict the manifold regularized sparse low-rank approximation for MFE and then the input image is characterized by a fused feature descriptor. On the other hand, both the fused feature and its corresponding 3D pose are separately encoded by LSAEs. A two-layer back-propagation neural network is trained by parameter fine-tuning and then used to map the encoded 2D features to encoded 3D poses. Our LSAE ensures a good preservation of the local topology of data points. Experimental results demonstrate the effectiveness of our proposed method.

Empirical mode decomposition-based facial pose estimation inside video sequences

NASA Astrophysics Data System (ADS)

Qing, Chunmei; Jiang, Jianmin; Yang, Zhijing

2010-03-01

We describe a new pose-estimation algorithm via integration of the strength in both empirical mode decomposition (EMD) and mutual information. While mutual information is exploited to measure the similarity between facial images to estimate poses, EMD is exploited to decompose input facial images into a number of intrinsic mode function (IMF) components, which redistribute the effect of noise, expression changes, and illumination variations as such that, when the input facial image is described by the selected IMF components, all the negative effects can be minimized. Extensive experiments were carried out in comparisons to existing representative techniques, and the results show that the proposed algorithm achieves better pose-estimation performances with robustness to noise corruption, illumination variation, and facial expressions.

Learning toward practical head pose estimation

NASA Astrophysics Data System (ADS)

Sang, Gaoli; He, Feixiang; Zhu, Rong; Xuan, Shibin

2017-08-01

Head pose is useful information for many face-related tasks, such as face recognition, behavior analysis, human-computer interfaces, etc. Existing head pose estimation methods usually assume that the face images have been well aligned or that sufficient and precise training data are available. In practical applications, however, these assumptions are very likely to be invalid. This paper first investigates the impact of the failure of these assumptions, i.e., misalignment of face images, uncertainty and undersampling of training data, on head pose estimation accuracy of state-of-the-art methods. A learning-based approach is then designed to enhance the robustness of head pose estimation to these factors. To cope with misalignment, instead of using hand-crafted features, it seeks suitable features by learning from a set of training data with a deep convolutional neural network (DCNN), such that the training data can be best classified into the correct head pose categories. To handle uncertainty and undersampling, it employs multivariate labeling distributions (MLDs) with dense sampling intervals to represent the head pose attributes of face images. The correlation between the features and the dense MLD representations of face images is approximated by a maximum entropy model, whose parameters are optimized on the given training data. To estimate the head pose of a face image, its MLD representation is first computed according to the model based on the features extracted from the image by the trained DCNN, and its head pose is then assumed to be the one corresponding to the peak in its MLD. Evaluation experiments on the Pointing'04, FacePix, Multi-PIE, and CASIA-PEAL databases prove the effectiveness and efficiency of the proposed method.

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait.

PubMed

Solav, Dana; Camomilla, Valentina; Cereatti, Andrea; Barré, Arnaud; Aminian, Kamiar; Wolf, Alon

2017-09-06

The aim of this study was to analyze the accuracy of bone pose estimation based on sub-clusters of three skin-markers characterized by triangular Cosserat point elements (TCPEs) and to evaluate the capability of four instantaneous physical parameters, which can be measured non-invasively in vivo, to identify the most accurate TCPEs. Moreover, TCPE pose estimations were compared with the estimations of two least squares minimization methods applied to the cluster of all markers, using rigid body (RBLS) and homogeneous deformation (HDLS) assumptions. Analysis was performed on previously collected in vivo treadmill gait data composed of simultaneous measurements of the gold-standard bone pose by bi-plane fluoroscopy tracking the subjects' knee prosthesis and a stereophotogrammetric system tracking skin-markers affected by soft tissue artifact. Femur orientation and position errors estimated from skin-marker clusters were computed for 18 subjects using clusters of up to 35 markers. Results based on gold-standard data revealed that instantaneous subsets of TCPEs exist which estimate the femur pose with reasonable accuracy (median root mean square error during stance/swing: 1.4/2.8deg for orientation, 1.5/4.2mm for position). A non-invasive and instantaneous criteria to select accurate TCPEs for pose estimation (4.8/7.3deg, 5.8/12.3mm), was compared with RBLS (4.3/6.6deg, 6.9/16.6mm) and HDLS (4.6/7.6deg, 6.7/12.5mm). Accounting for homogeneous deformation, using HDLS or selected TCPEs, yielded more accurate position estimations than RBLS method, which, conversely, yielded more accurate orientation estimations. Further investigation is required to devise effective criteria for cluster selection that could represent a significant improvement in bone pose estimation accuracy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating the burden of foodborne diseases in Japan

PubMed Central

Kumagai, Yuko; Gilmour, Stuart; Ota, Erika; Momose, Yoshika; Onishi, Toshiro; Bilano, Ver Luanni Feliciano; Kasuga, Fumiko; Sekizaki, Tsutomu

2015-01-01

Abstract Objective To assess the burden posed by foodborne diseases in Japan using methods developed by the World Health Organization’s Foodborne Disease Burden Epidemiology Reference Group (FERG). Methods Expert consultation and statistics on food poisoning during 2011 were used to identify three common causes of foodborne disease in Japan: Campylobacter and Salmonella species and enterohaemorrhagic Escherichia coli (EHEC). We conducted systematic reviews of English and Japanese literature on the complications caused by these pathogens, by searching Embase, the Japan medical society abstract database and Medline. We estimated the annual incidence of acute gastroenteritis from reported surveillance data, based on estimated probabilities that an affected person would visit a physician and have gastroenteritis confirmed. We then calculated disability-adjusted life-years (DALYs) lost in 2011, using the incidence estimates along with disability weights derived from published studies. Findings In 2011, foodborne disease caused by Campylobacter species, Salmonella species and EHEC led to an estimated loss of 6099, 3145 and 463 DALYs in Japan, respectively. These estimated burdens are based on the pyramid reconstruction method; are largely due to morbidity rather than mortality; and are much higher than those indicated by routine surveillance data. Conclusion Routine surveillance data may indicate foodborne disease burdens that are much lower than the true values. Most of the burden posed by foodborne disease in Japan comes from secondary complications. The tools developed by FERG appear useful in estimating disease burdens and setting priorities in the field of food safety. PMID:26478611

Ill-posed problem and regularization in reconstruction of radiobiological parameters from serial tumor imaging data

NASA Astrophysics Data System (ADS)

Chvetsov, Alevei V.; Sandison, George A.; Schwartz, Jeffrey L.; Rengan, Ramesh

2015-11-01

The main objective of this article is to improve the stability of reconstruction algorithms for estimation of radiobiological parameters using serial tumor imaging data acquired during radiation therapy. Serial images of tumor response to radiation therapy represent a complex summation of several exponential processes as treatment induced cell inactivation, tumor growth rates, and the rate of cell loss. Accurate assessment of treatment response would require separation of these processes because they define radiobiological determinants of treatment response and, correspondingly, tumor control probability. However, the estimation of radiobiological parameters using imaging data can be considered an inverse ill-posed problem because a sum of several exponentials would produce the Fredholm integral equation of the first kind which is ill posed. Therefore, the stability of reconstruction of radiobiological parameters presents a problem even for the simplest models of tumor response. To study stability of the parameter reconstruction problem, we used a set of serial CT imaging data for head and neck cancer and a simplest case of a two-level cell population model of tumor response. Inverse reconstruction was performed using a simulated annealing algorithm to minimize a least squared objective function. Results show that the reconstructed values of cell surviving fractions and cell doubling time exhibit significant nonphysical fluctuations if no stabilization algorithms are applied. However, after applying a stabilization algorithm based on variational regularization, the reconstruction produces statistical distributions for survival fractions and doubling time that are comparable to published in vitro data. This algorithm is an advance over our previous work where only cell surviving fractions were reconstructed. We conclude that variational regularization allows for an increase in the number of free parameters in our model which enables development of more-advanced parameter reconstruction algorithms.

Human Pose Estimation from Monocular Images: A Comprehensive Survey

PubMed Central

Gong, Wenjuan; Zhang, Xuena; Gonzàlez, Jordi; Sobral, Andrews; Bouwmans, Thierry; Tu, Changhe; Zahzah, El-hadi

2016-01-01

Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation can be found in the literature, but they focus on a certain category; for example, model-based approaches or human motion analysis, etc. As far as we know, an overall review of this problem domain has yet to be provided. Furthermore, recent advancements based on deep learning have brought novel algorithms for this problem. In this paper, a comprehensive survey of human pose estimation from monocular images is carried out including milestone works and recent advancements. Based on one standard pipeline for the solution of computer vision problems, this survey splits the problem into several modules: feature extraction and description, human body models, and modeling methods. Problem modeling methods are approached based on two means of categorization in this survey. One way to categorize includes top-down and bottom-up methods, and another way includes generative and discriminative methods. Considering the fact that one direct application of human pose estimation is to provide initialization for automatic video surveillance, there are additional sections for motion-related methods in all modules: motion features, motion models, and motion-based methods. Finally, the paper also collects 26 publicly available data sets for validation and provides error measurement methods that are frequently used. PMID:27898003

Relative Pose Estimation Using Image Feature Triplets

NASA Astrophysics Data System (ADS)

Chuang, T. Y.; Rottensteiner, F.; Heipke, C.

2015-03-01

A fully automated reconstruction of the trajectory of image sequences using point correspondences is turning into a routine practice. However, there are cases in which point features are hardly detectable, cannot be localized in a stable distribution, and consequently lead to an insufficient pose estimation. This paper presents a triplet-wise scheme for calibrated relative pose estimation from image point and line triplets, and investigates the effectiveness of the feature integration upon the relative pose estimation. To this end, we employ an existing point matching technique and propose a method for line triplet matching in which the relative poses are resolved during the matching procedure. The line matching method aims at establishing hypotheses about potential minimal line matches that can be used for determining the parameters of relative orientation (pose estimation) of two images with respect to the reference one; then, quantifying the agreement using the estimated orientation parameters. Rather than randomly choosing the line candidates in the matching process, we generate an associated lookup table to guide the selection of potential line matches. In addition, we integrate the homologous point and line triplets into a common adjustment procedure. In order to be able to also work with image sequences the adjustment is formulated in an incremental manner. The proposed scheme is evaluated with both synthetic and real datasets, demonstrating its satisfactory performance and revealing the effectiveness of image feature integration.

Sampling in rugged terrain

USGS Publications Warehouse

Dawson, D.K.; Ralph, C. John; Scott, J. Michael

1981-01-01

Work in rugged terrain poses some unique problems that should be considered before research is initiated. Besides the obvious physical difficulties of crossing uneven terrain, topography can influence the bird species? composition of a forest and the observer's ability to detect birds and estimate distances. Census results can also be affected by the slower rate of travel on rugged terrain. Density figures may be higher than results obtained from censuses in similar habitat on level terrain because of the greater likelihood of double-recording of individuals and of recording species that sing infrequently. In selecting a census technique, the researcher should weigh the efficiency and applicability of a technique for the objectives of his study in light of the added difficulties posed by rugged terrain. The variable circular-plot method is probably the most effective technique for estimating bird numbers. Bird counts and distance estimates are facilitated because the observer is stationary, and calculations of species? densities take into account differences in effective area covered amongst stations due to variability in terrain or vegetation structure. Institution of precautions that minimize the risk of injury to field personnel can often enhance the observer?s ability to detect birds.

Efficient visual grasping alignment for cylinders

NASA Technical Reports Server (NTRS)

Nicewarner, Keith E.; Kelley, Robert B.

1992-01-01

Monocular information from a gripper-mounted camera is used to servo the robot gripper to grasp a cylinder. The fundamental concept for rapid pose estimation is to reduce the amount of information that needs to be processed during each vision update interval. The grasping procedure is divided into four phases: learn, recognition, alignment, and approach. In the learn phase, a cylinder is placed in the gripper and the pose estimate is stored and later used as the servo target. This is performed once as a calibration step. The recognition phase verifies the presence of a cylinder in the camera field of view. An initial pose estimate is computed and uncluttered scan regions are selected. The radius of the cylinder is estimated by moving the robot a fixed distance toward the cylinder and observing the change in the image. The alignment phase processes only the scan regions obtained previously. Rapid pose estimates are used to align the robot with the cylinder at a fixed distance from it. The relative motion of the cylinder is used to generate an extrapolated pose-based trajectory for the robot controller. The approach phase guides the robot gripper to a grasping position. The cylinder can be grasped with a minimal reaction force and torque when only rough global pose information is initially available.

Efficient visual grasping alignment for cylinders

NASA Technical Reports Server (NTRS)

Nicewarner, Keith E.; Kelley, Robert B.

1991-01-01

Monocular information from a gripper-mounted camera is used to servo the robot gripper to grasp a cylinder. The fundamental concept for rapid pose estimation is to reduce the amount of information that needs to be processed during each vision update interval. The grasping procedure is divided into four phases: learn, recognition, alignment, and approach. In the learn phase, a cylinder is placed in the gripper and the pose estimate is stored and later used as the servo target. This is performed once as a calibration step. The recognition phase verifies the presence of a cylinder in the camera field of view. An initial pose estimate is computed and uncluttered scan regions are selected. The radius of the cylinder is estimated by moving the robot a fixed distance toward the cylinder and observing the change in the image. The alignment phase processes only the scan regions obtained previously. Rapid pose estimates are used to align the robot with the cylinder at a fixed distance from it. The relative motion of the cylinder is used to generate an extrapolated pose-based trajectory for the robot controller. The approach phase guides the robot gripper to a grasping position. The cylinder can be grasped with a minimal reaction force and torque when only rough global pose information is initially available.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

NASA Astrophysics Data System (ADS)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter.

PubMed

Alatise, Mary B; Hancke, Gerhard P

2017-09-21

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs).

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter

PubMed Central

Hancke, Gerhard P.

2017-01-01

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs). PMID:28934102

Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions.

PubMed

Drouard, Vincent; Horaud, Radu; Deleforge, Antoine; Ba, Sileye; Evangelidis, Georgios

2017-03-01

Head-pose estimation has many applications, such as social event analysis, human-robot and human-computer interaction, driving assistance, and so forth. Head-pose estimation is challenging, because it must cope with changing illumination conditions, variabilities in face orientation and in appearance, partial occlusions of facial landmarks, as well as bounding-box-to-face alignment errors. We propose to use a mixture of linear regressions with partially-latent output. This regression method learns to map high-dimensional feature vectors (extracted from bounding boxes of faces) onto the joint space of head-pose angles and bounding-box shifts, such that they are robustly predicted in the presence of unobservable phenomena. We describe in detail the mapping method that combines the merits of unsupervised manifold learning techniques and of mixtures of regressions. We validate our method with three publicly available data sets and we thoroughly benchmark four variants of the proposed algorithm with several state-of-the-art head-pose estimation methods.

Vision-guided gripping of a cylinder

NASA Technical Reports Server (NTRS)

Nicewarner, Keith E.; Kelley, Robert B.

1991-01-01

The motivation for vision-guided servoing is taken from tasks in automated or telerobotic space assembly and construction. Vision-guided servoing requires the ability to perform rapid pose estimates and provide predictive feature tracking. Monocular information from a gripper-mounted camera is used to servo the gripper to grasp a cylinder. The procedure is divided into recognition and servo phases. The recognition stage verifies the presence of a cylinder in the camera field of view. Then an initial pose estimate is computed and uncluttered scan regions are selected. The servo phase processes only the selected scan regions of the image. Given the knowledge, from the recognition phase, that there is a cylinder in the image and knowing the radius of the cylinder, 4 of the 6 pose parameters can be estimated with minimal computation. The relative motion of the cylinder is obtained by using the current pose and prior pose estimates. The motion information is then used to generate a predictive feature-based trajectory for the path of the gripper.

3D ocular ultrasound using gaze tracking on the contralateral eye: a feasibility study.

PubMed

Afsham, Narges; Najafi, Mohammad; Abolmaesumi, Purang; Rohling, Robert

2011-01-01

A gaze-deviated examination of the eye with a 2D ultrasound transducer is a common and informative ophthalmic test; however, the complex task of the pose estimation of the ultrasound images relative to the eye affects 3D interpretation. To tackle this challenge, a novel system for 3D image reconstruction based on gaze tracking of the contralateral eye has been proposed. The gaze fixates on several target points and, for each fixation, the pose of the examined eye is inferred from the gaze tracking. A single camera system has been developed for pose estimation combined with subject-specific parameter identification. The ultrasound images are then transformed to the coordinate system of the examined eye to create a 3D volume. Accuracy of the proposed gaze tracking system and the pose estimation of the eye have been validated in a set of experiments. Overall system error, including pose estimation and calibration, are 3.12 mm and 4.68 degrees.

Three-dimensional deformable-model-based localization and recognition of road vehicles.

PubMed

Zhang, Zhaoxiang; Tan, Tieniu; Huang, Kaiqi; Wang, Yunhong

2012-01-01

We address the problem of model-based object recognition. Our aim is to localize and recognize road vehicles from monocular images or videos in calibrated traffic scenes. A 3-D deformable vehicle model with 12 shape parameters is set up as prior information, and its pose is determined by three parameters, which are its position on the ground plane and its orientation about the vertical axis under ground-plane constraints. An efficient local gradient-based method is proposed to evaluate the fitness between the projection of the vehicle model and image data, which is combined into a novel evolutionary computing framework to estimate the 12 shape parameters and three pose parameters by iterative evolution. The recovery of pose parameters achieves vehicle localization, whereas the shape parameters are used for vehicle recognition. Numerous experiments are conducted in this paper to demonstrate the performance of our approach. It is shown that the local gradient-based method can evaluate accurately and efficiently the fitness between the projection of the vehicle model and the image data. The evolutionary computing framework is effective for vehicles of different types and poses is robust to all kinds of occlusion.

The application of mean field theory to image motion estimation.

PubMed

Zhang, J; Hanauer, G G

1995-01-01

Previously, Markov random field (MRF) model-based techniques have been proposed for image motion estimation. Since motion estimation is usually an ill-posed problem, various constraints are needed to obtain a unique and stable solution. The main advantage of the MRF approach is its capacity to incorporate such constraints, for instance, motion continuity within an object and motion discontinuity at the boundaries between objects. In the MRF approach, motion estimation is often formulated as an optimization problem, and two frequently used optimization methods are simulated annealing (SA) and iterative-conditional mode (ICM). Although the SA is theoretically optimal in the sense of finding the global optimum, it usually takes many iterations to converge. The ICM, on the other hand, converges quickly, but its results are often unsatisfactory due to its "hard decision" nature. Previously, the authors have applied the mean field theory to image segmentation and image restoration problems. It provides results nearly as good as SA but with much faster convergence. The present paper shows how the mean field theory can be applied to MRF model-based motion estimation. This approach is demonstrated on both synthetic and real-world images, where it produced good motion estimates.

Drogue pose estimation for unmanned aerial vehicle autonomous aerial refueling system based on infrared vision sensor

NASA Astrophysics Data System (ADS)

Chen, Shanjun; Duan, Haibin; Deng, Yimin; Li, Cong; Zhao, Guozhi; Xu, Yan

2017-12-01

Autonomous aerial refueling is a significant technology that can significantly extend the endurance of unmanned aerial vehicles. A reliable method that can accurately estimate the position and attitude of the probe relative to the drogue is the key to such a capability. A drogue pose estimation method based on infrared vision sensor is introduced with the general goal of yielding an accurate and reliable drogue state estimate. First, by employing direct least squares ellipse fitting and convex hull in OpenCV, a feature point matching and interference point elimination method is proposed. In addition, considering the conditions that some infrared LEDs are damaged or occluded, a missing point estimation method based on perspective transformation and affine transformation is designed. Finally, an accurate and robust pose estimation algorithm improved by the runner-root algorithm is proposed. The feasibility of the designed visual measurement system is demonstrated by flight test, and the results indicate that our proposed method enables precise and reliable pose estimation of the probe relative to the drogue, even in some poor conditions.

An eye model for uncalibrated eye gaze estimation under variable head pose

NASA Astrophysics Data System (ADS)

Hnatow, Justin; Savakis, Andreas

2007-04-01

Gaze estimation is an important component of computer vision systems that monitor human activity for surveillance, human-computer interaction, and various other applications including iris recognition. Gaze estimation methods are particularly valuable when they are non-intrusive, do not require calibration, and generalize well across users. This paper presents a novel eye model that is employed for efficiently performing uncalibrated eye gaze estimation. The proposed eye model was constructed from a geometric simplification of the eye and anthropometric data about eye feature sizes in order to circumvent the requirement of calibration procedures for each individual user. The positions of the two eye corners and the midpupil, the distance between the two eye corners, and the radius of the eye sphere are required for gaze angle calculation. The locations of the eye corners and midpupil are estimated via processing following eye detection, and the remaining parameters are obtained from anthropometric data. This eye model is easily extended to estimating eye gaze under variable head pose. The eye model was tested on still images of subjects at frontal pose (0 °) and side pose (34 °). An upper bound of the model's performance was obtained by manually selecting the eye feature locations. The resulting average absolute error was 2.98 ° for frontal pose and 2.87 ° for side pose. The error was consistent across subjects, which indicates that good generalization was obtained. This level of performance compares well with other gaze estimation systems that utilize a calibration procedure to measure eye features.

Face pose tracking using the four-point algorithm

NASA Astrophysics Data System (ADS)

Fung, Ho Yin; Wong, Kin Hong; Yu, Ying Kin; Tsui, Kwan Pang; Kam, Ho Chuen

2017-06-01

In this paper, we have developed an algorithm to track the pose of a human face robustly and efficiently. Face pose estimation is very useful in many applications such as building virtual reality systems and creating an alternative input method for the disabled. Firstly, we have modified a face detection toolbox called DLib for the detection of a face in front of a camera. The detected face features are passed to a pose estimation method, known as the four-point algorithm, for pose computation. The theory applied and the technical problems encountered during system development are discussed in the paper. It is demonstrated that the system is able to track the pose of a face in real time using a consumer grade laptop computer.

Dual Quaternions as Constraints in 4D-DPM Models for Pose Estimation.

PubMed

Martinez-Berti, Enrique; Sánchez-Salmerón, Antonio-José; Ricolfe-Viala, Carlos

2017-08-19

The goal of this research work is to improve the accuracy of human pose estimation using the Deformation Part Model (DPM) without increasing computational complexity. First, the proposed method seeks to improve pose estimation accuracy by adding the depth channel to DPM, which was formerly defined based only on red-green-blue (RGB) channels, in order to obtain a four-dimensional DPM (4D-DPM). In addition, computational complexity can be controlled by reducing the number of joints by taking it into account in a reduced 4D-DPM. Finally, complete solutions are obtained by solving the omitted joints by using inverse kinematics models. In this context, the main goal of this paper is to analyze the effect on pose estimation timing cost when using dual quaternions to solve the inverse kinematics.

General methodology for simultaneous representation and discrimination of multiple object classes

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.

1998-03-01

We address a new general method for linear and nonlinear feature extraction for simultaneous representation and classification. We call this approach the maximum representation and discrimination feature (MRDF) method. We develop a novel nonlinear eigenfeature extraction technique to represent data with closed-form solutions and use it to derive a nonlinear MRDF algorithm. Results of the MRDF method on synthetic databases are shown and compared with results from standard Fukunaga-Koontz transform and Fisher discriminant function methods. The method is also applied to an automated product inspection problem and for classification and pose estimation of two similar objects under 3D aspect angle variations.

An investigation into multi-dimensional prediction models to estimate the pose error of a quadcopter in a CSP plant setting

NASA Astrophysics Data System (ADS)

Lock, Jacobus C.; Smit, Willie J.; Treurnicht, Johann

2016-05-01

The Solar Thermal Energy Research Group (STERG) is investigating ways to make heliostats cheaper to reduce the total cost of a concentrating solar power (CSP) plant. One avenue of research is to use unmanned aerial vehicles (UAVs) to automate and assist with the heliostat calibration process. To do this, the pose estimation error of each UAV must be determined and integrated into a calibration procedure. A computer vision (CV) system is used to measure the pose of a quadcopter UAV. However, this CV system contains considerable measurement errors. Since this is a high-dimensional problem, a sophisticated prediction model must be used to estimate the measurement error of the CV system for any given pose measurement vector. This paper attempts to train and validate such a model with the aim of using it to determine the pose error of a quadcopter in a CSP plant setting.

Real-time upper-body human pose estimation from depth data using Kalman filter for simulator

NASA Astrophysics Data System (ADS)

Lee, D.; Chi, S.; Park, C.; Yoon, H.; Kim, J.; Park, C. H.

2014-08-01

Recently, many studies show that an indoor horse riding exercise has a positive effect on promoting health and diet. However, if a rider has an incorrect posture, it will be the cause of back pain. In spite of this problem, there is only few research on analyzing rider's posture. Therefore, the purpose of this study is to estimate a rider pose from a depth image using the Asus's Xtion sensor in real time. In the experiments, we show the performance of our pose estimation algorithm in order to comparing the results between our joint estimation algorithm and ground truth data.

An improved silhouette for human pose estimation

NASA Astrophysics Data System (ADS)

Hawes, Anthony H.; Iftekharuddin, Khan M.

2017-08-01

We propose a novel method for analyzing images that exploits the natural lines of a human poses to find areas where self-occlusion could be present. Errors caused by self-occlusion cause several modern human pose estimation methods to mis-identify body parts, which reduces the performance of most action recognition algorithms. Our method is motivated by the observation that, in several cases, occlusion can be reasoned using only boundary lines of limbs. An intelligent edge detection algorithm based on the above principle could be used to augment the silhouette with information useful for pose estimation algorithms and push forward progress on occlusion handling for human action recognition. The algorithm described is applicable to computer vision scenarios involving 2D images and (appropriated flattened) 3D images.

Fast Kalman Filtering for Relative Spacecraft Position and Attitude Estimation for the Raven ISS Hosted Payload

NASA Technical Reports Server (NTRS)

Galante, Joseph M.; Van Eepoel, John; D'Souza, Chris; Patrick, Bryan

2016-01-01

The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors

Fast Kalman Filtering for Relative Spacecraft Position and Attitude Estimation for the Raven ISS Hosted Payload

NASA Technical Reports Server (NTRS)

Galante, Joseph M.; Van Eepoel, John; D' Souza, Chris; Patrick, Bryan

2016-01-01

The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors.

Estimation of Antenna Pose in the Earth Frame Using Camera and IMU Data from Mobile Phones

PubMed Central

Wang, Zhen; Jin, Bingwen; Geng, Weidong

2017-01-01

The poses of base station antennas play an important role in cellular network optimization. Existing methods of pose estimation are based on physical measurements performed either by tower climbers or using additional sensors attached to antennas. In this paper, we present a novel non-contact method of antenna pose measurement based on multi-view images of the antenna and inertial measurement unit (IMU) data captured by a mobile phone. Given a known 3D model of the antenna, we first estimate the antenna pose relative to the phone camera from the multi-view images and then employ the corresponding IMU data to transform the pose from the camera coordinate frame into the Earth coordinate frame. To enhance the resulting accuracy, we improve existing camera-IMU calibration models by introducing additional degrees of freedom between the IMU sensors and defining a new error metric based on both the downtilt and azimuth angles, instead of a unified rotational error metric, to refine the calibration. In comparison with existing camera-IMU calibration methods, our method achieves an improvement in azimuth accuracy of approximately 1.0 degree on average while maintaining the same level of downtilt accuracy. For the pose estimation in the camera coordinate frame, we propose an automatic method of initializing the optimization solver and generating bounding constraints on the resulting pose to achieve better accuracy. With this initialization, state-of-the-art visual pose estimation methods yield satisfactory results in more than 75% of cases when plugged into our pipeline, and our solution, which takes advantage of the constraints, achieves even lower estimation errors on the downtilt and azimuth angles, both on average (0.13 and 0.3 degrees lower, respectively) and in the worst case (0.15 and 7.3 degrees lower, respectively), according to an evaluation conducted on a dataset consisting of 65 groups of data. We show that both of our enhancements contribute to the performance improvement offered by the proposed estimation pipeline, which achieves downtilt and azimuth accuracies of respectively 0.47 and 5.6 degrees on average and 1.38 and 12.0 degrees in the worst case, thereby satisfying the accuracy requirements for network optimization in the telecommunication industry. PMID:28397765

Solution to the SLAM problem in low dynamic environments using a pose graph and an RGB-D sensor.

PubMed

Lee, Donghwa; Myung, Hyun

2014-07-11

In this study, we propose a solution to the simultaneous localization and mapping (SLAM) problem in low dynamic environments by using a pose graph and an RGB-D (red-green-blue depth) sensor. The low dynamic environments refer to situations in which the positions of objects change over long intervals. Therefore, in the low dynamic environments, robots have difficulty recognizing the repositioning of objects unlike in highly dynamic environments in which relatively fast-moving objects can be detected using a variety of moving object detection algorithms. The changes in the environments then cause groups of false loop closing when the same moved objects are observed for a while, which means that conventional SLAM algorithms produce incorrect results. To address this problem, we propose a novel SLAM method that handles low dynamic environments. The proposed method uses a pose graph structure and an RGB-D sensor. First, to prune the falsely grouped constraints efficiently, nodes of the graph, that represent robot poses, are grouped according to the grouping rules with noise covariances. Next, false constraints of the pose graph are pruned according to an error metric based on the grouped nodes. The pose graph structure is reoptimized after eliminating the false information, and the corrected localization and mapping results are obtained. The performance of the method was validated in real experiments using a mobile robot system.

Material and shape perception based on two types of intensity gradient information

PubMed Central

Nishida, Shin'ya

2018-01-01

Visual estimation of the material and shape of an object from a single image includes a hard ill-posed computational problem. However, in our daily life we feel we can estimate both reasonably well. The neural computation underlying this ability remains poorly understood. Here we propose that the human visual system uses different aspects of object images to separately estimate the contributions of the material and shape. Specifically, material perception relies mainly on the intensity gradient magnitude information, while shape perception relies mainly on the intensity gradient order information. A clue to this hypothesis was provided by the observation that luminance-histogram manipulation, which changes luminance gradient magnitudes but not the luminance-order map, effectively alters the material appearance but not the shape of an object. In agreement with this observation, we found that the simulated physical material changes do not significantly affect the intensity order information. A series of psychophysical experiments further indicate that human surface shape perception is robust against intensity manipulations provided they do not disturb the intensity order information. In addition, we show that the two types of gradient information can be utilized for the discrimination of albedo changes from highlights. These findings suggest that the visual system relies on these diagnostic image features to estimate physical properties in a distal world. PMID:29702644

Marker Registration Technique for Handwritten Text Marker in Augmented Reality Applications

NASA Astrophysics Data System (ADS)

Thanaborvornwiwat, N.; Patanukhom, K.

2018-04-01

Marker registration is a fundamental process to estimate camera poses in marker-based Augmented Reality (AR) systems. We developed AR system that creates correspondence virtual objects on handwritten text markers. This paper presents a new method for registration that is robust for low-content text markers, variation of camera poses, and variation of handwritten styles. The proposed method uses Maximally Stable Extremal Regions (MSER) and polygon simplification for a feature point extraction. The experiment shows that we need to extract only five feature points per image which can provide the best registration results. An exhaustive search is used to find the best matching pattern of the feature points in two images. We also compared performance of the proposed method to some existing registration methods and found that the proposed method can provide better accuracy and time efficiency.

Ill Posed Problems: Numerical and Statistical Methods for Mildly, Moderately and Severely Ill Posed Problems with Noisy Data.

DTIC Science & Technology

1980-02-01

to estimate f -..ell, -noderately ,-ell, or- poorly. 1 ’The sansitivity *of a rec-ilarized estimate of f to the noise is made explicit. After giving the...AD-A 7 .SA92 925 WISCONSIN UN! V-MADISON DEFT OF STATISTICS F /S 11,’ 1 ILL POSED PRORLEMS: NUMERICAL ANn STATISTICAL METHODS FOR MILOL-ETC(U FEB 80 a...estimate f given z. We first define the 1 intrinsic rank of the problem where jK(tit) f (t)dt is known exactly. This 0 definition is used to provide insight

Re-entry survivability and risk

NASA Astrophysics Data System (ADS)

Fudge, Michael L.

1998-11-01

This paper is the culmination of the research effort which was reported on last year while still in-progress. As previously reported, statistical methods for expressing the impact risk posed to space systems in general [and the International Space Station (ISS) in particular] by other resident space objects have been examined. One of the findings of this investigation is that there are legitimate physical modeling reasons for the common statistical expression of the collision risk. A combination of statistical methods and physical modeling is also used to express the impact risk posed by reentering space systems to objects of interest (e.g., people and property) on Earth. One of the largest uncertainties in the expressing of this risk is the estimation of survivable material which survives reentry to impact Earth's surface. This point was demonstrated in dramatic fashion in January 1997 by the impact of an intact expendable launch vehicle (ELV) upper stage near a private residence in the continental United States. Since approximately half of the missions supporting ISS will utilize ELVs, it is appropriate to examine the methods used to estimate the amount and physical characteristics of ELV debris surviving reentry to impact Earth's surface. This report details reentry survivability estimation methodology, including the specific methodology used by ITT Systems' (formerly Kaman Sciences) 'SURVIVE' model. The major change to the model in the last twelve months has been the increase in the fidelity with which upper- atmospheric aerodynamics has been modeled. This has resulted in an adjustment in the factor relating the amount of kinetic energy loss to the amount of heating entering and reentering body, and also validated and removed the necessity for certain empirically-based adjustments made to the theoretical heating expressions. Comparisons between empirical results (observations of objects which have been recovered on Earth after surviving reentry) and SURVIVE estimates are presented for selected generic upper stage or spacecraft components, a Soyuz launch vehicle second stage, and for a Delta II launch vehicle second stage and its significant components. Significant similarity is demonstrated between the type and dispersion pattern of the recovered debris from the January 1997 Delta II 2nd stage event and the simulation of that reentry and breakup.

Estimating aquatic hazards posed by prescription pharmaceutical residues from municipal wastewater

EPA Science Inventory

Risks posed by pharmaceuticals in the environment are hard to estimate due to limited monitoring capacity and difficulty interpreting monitoring results. In order to partially address these issues, we suggest a method for prioritizing pharmaceuticals for monitoring, and a framewo...

Vision based control of unmanned aerial vehicles with applications to an autonomous four-rotor helicopter, quadrotor

NASA Astrophysics Data System (ADS)

Altug, Erdinc

Our work proposes a vision-based stabilization and output tracking control method for a model helicopter. This is a part of our effort to produce a rotorcraft based autonomous Unmanned Aerial Vehicle (UAV). Due to the desired maneuvering ability, a four-rotor helicopter has been chosen as the testbed. On previous research on flying vehicles, vision is usually used as a secondary sensor. Unlike previous research, our goal is to use visual feedback as the main sensor, which is not only responsible for detecting where the ground objects are but also for helicopter localization. A novel two-camera method has been introduced for estimating the full six degrees of freedom (DOF) pose of the helicopter. This two-camera system consists of a pan-tilt ground camera and an onboard camera. The pose estimation algorithm is compared through simulation to other methods, such as four-point, and stereo method and is shown to be less sensitive to feature detection errors. Helicopters are highly unstable flying vehicles; although this is good for agility, it makes the control harder. To build an autonomous helicopter, two methods of control are studied---one using a series of mode-based, feedback linearizing controllers and the other using a back-stepping control law. Various simulations with 2D and 3D models demonstrate the implementation of these controllers. We also show global convergence of the 3D quadrotor controller even with large calibration errors or presence of large errors on the image plane. Finally, we present initial flight experiments where the proposed pose estimation algorithm and non-linear control techniques have been implemented on a remote-controlled helicopter. The helicopter was restricted with a tether to vertical, yaw motions and limited x and y translations.

DIAC object recognition system

NASA Astrophysics Data System (ADS)

Buurman, Johannes

1992-03-01

This paper describes the object recognition system used in an intelligent robot cell. It is used to recognize and estimate pose and orientation of parts as they enter the cell. The parts are mostly metal and consist of polyhedral and cylindrical shapes. The system uses feature-based stereo vision to acquire a wireframe of the observed part. Features are defined as straight lines and ellipses, which lead to a wireframe of straight lines and circular arcs (the latter using a new algorithm). This wireframe is compared to a number of wire frame models obtained from the CAD database. Experimental results show that image processing hardware and parallelization may add considerably to the speed of the system.

Localized Dictionaries Based Orientation Field Estimation for Latent Fingerprints.

PubMed

Xiao Yang; Jianjiang Feng; Jie Zhou

2014-05-01

Dictionary based orientation field estimation approach has shown promising performance for latent fingerprints. In this paper, we seek to exploit stronger prior knowledge of fingerprints in order to further improve the performance. Realizing that ridge orientations at different locations of fingerprints have different characteristics, we propose a localized dictionaries-based orientation field estimation algorithm, in which noisy orientation patch at a location output by a local estimation approach is replaced by real orientation patch in the local dictionary at the same location. The precondition of applying localized dictionaries is that the pose of the latent fingerprint needs to be estimated. We propose a Hough transform-based fingerprint pose estimation algorithm, in which the predictions about fingerprint pose made by all orientation patches in the latent fingerprint are accumulated. Experimental results on challenging latent fingerprint datasets show the proposed method outperforms previous ones markedly.

New Evidence for a Black Hole in the Compact Binary Cygnus X-3

NASA Technical Reports Server (NTRS)

Shrader, Chris R.; Titarchuk, Lev; Shaposhnikov, Nikolai

2010-01-01

The bright and highly variable X-ray and radio source known as Cygnus X-3 was among the first X-ray sources discovered, yet it remains in many ways an enigma. Its known to consist of a massive. Wolf-Rayet primary in an extremely tight orbit with a compact object. Yet one of the most basic of pa.ranietern the mass of the compact object - is not known. Nor is it even clear whether its is a neutron star or a black hole. In this Paper we present our analysis of the broad-band high-energy continua covering a substantial range in luminosity and spectral morphology. We apply these results to a recently identified scaling relationship which has been demonstrated to provide reliable estimates of the compact object mass in a number of accretion powered binaries. This analysis leads us to conclude that the compact object in Cygnus X-3 has a mass greater than 4.2 solar mass thus clearly indicative of a black hole and as such resolving a longstanding issue. The full range of uncertainty in our analysis and from using a. range of recently published distance estimates constrains the compact object mass to lie between 4.2 solar mass and 14.4 solar mass. Our favored estimate, based on a 9.0 kpc distance estimate is approx. l0 solar mass, with the. error margin of 3.2 solar masses. This result may thus pose challenges to shared-envelope evolutionary models of compact binaries. as well as establishing Cygnus X-3 as the first confirmed accretion-powered galactic gamma: ray source.

A New 3D Object Pose Detection Method Using LIDAR Shape Set

PubMed Central

Kim, Jung-Un

2018-01-01

In object detection systems for autonomous driving, LIDAR sensors provide very useful information. However, problems occur because the object representation is greatly distorted by changes in distance. To solve this problem, we propose a LIDAR shape set that reconstructs the shape surrounding the object more clearly by using the LIDAR point information projected on the object. The LIDAR shape set restores object shape edges from a bird’s eye view by filtering LIDAR points projected on a 2D pixel-based front view. In this study, we use this shape set for two purposes. The first is to supplement the shape set with a LIDAR Feature map, and the second is to divide the entire shape set according to the gradient of the depth and density to create a 2D and 3D bounding box proposal for each object. We present a multimodal fusion framework that classifies objects and restores the 3D pose of each object using enhanced feature maps and shape-based proposals. The network structure consists of a VGG -based object classifier that receives multiple inputs and a LIDAR-based Region Proposal Networks (RPN) that identifies object poses. It works in a very intuitive and efficient manner and can be extended to other classes other than vehicles. Our research has outperformed object classification accuracy (Average Precision, AP) and 3D pose restoration accuracy (3D bounding box recall rate) based on the latest studies conducted with KITTI data sets. PMID:29547551

A New 3D Object Pose Detection Method Using LIDAR Shape Set.

PubMed

Kim, Jung-Un; Kang, Hang-Bong

2018-03-16

In object detection systems for autonomous driving, LIDAR sensors provide very useful information. However, problems occur because the object representation is greatly distorted by changes in distance. To solve this problem, we propose a LIDAR shape set that reconstructs the shape surrounding the object more clearly by using the LIDAR point information projected on the object. The LIDAR shape set restores object shape edges from a bird's eye view by filtering LIDAR points projected on a 2D pixel-based front view. In this study, we use this shape set for two purposes. The first is to supplement the shape set with a LIDAR Feature map, and the second is to divide the entire shape set according to the gradient of the depth and density to create a 2D and 3D bounding box proposal for each object. We present a multimodal fusion framework that classifies objects and restores the 3D pose of each object using enhanced feature maps and shape-based proposals. The network structure consists of a VGG -based object classifier that receives multiple inputs and a LIDAR-based Region Proposal Networks (RPN) that identifies object poses. It works in a very intuitive and efficient manner and can be extended to other classes other than vehicles. Our research has outperformed object classification accuracy (Average Precision, AP) and 3D pose restoration accuracy (3D bounding box recall rate) based on the latest studies conducted with KITTI data sets.

A Bayesian Framework for Human Body Pose Tracking from Depth Image Sequences

PubMed Central

Zhu, Youding; Fujimura, Kikuo

2010-01-01

This paper addresses the problem of accurate and robust tracking of 3D human body pose from depth image sequences. Recovering the large number of degrees of freedom in human body movements from a depth image sequence is challenging due to the need to resolve the depth ambiguity caused by self-occlusions and the difficulty to recover from tracking failure. Human body poses could be estimated through model fitting using dense correspondences between depth data and an articulated human model (local optimization method). Although it usually achieves a high accuracy due to dense correspondences, it may fail to recover from tracking failure. Alternately, human pose may be reconstructed by detecting and tracking human body anatomical landmarks (key-points) based on low-level depth image analysis. While this method (key-point based method) is robust and recovers from tracking failure, its pose estimation accuracy depends solely on image-based localization accuracy of key-points. To address these limitations, we present a flexible Bayesian framework for integrating pose estimation results obtained by methods based on key-points and local optimization. Experimental results are shown and performance comparison is presented to demonstrate the effectiveness of the proposed approach. PMID:22399933

An evaluation of 3D head pose estimation using the Microsoft Kinect v2.

PubMed

Darby, John; Sánchez, María B; Butler, Penelope B; Loram, Ian D

2016-07-01

The Kinect v2 sensor supports real-time non-invasive 3D head pose estimation. Because the sensor is small, widely available and relatively cheap it has great potential as a tool for groups interested in measuring head posture. In this paper we compare the Kinect's head pose estimates with a marker-based record of ground truth in order to establish its accuracy. During movement of the head and neck alone (with static torso), we find average errors in absolute yaw, pitch and roll angles of 2.0±1.2°, 7.3±3.2° and 2.6±0.7°, and in rotations relative to the rest pose of 1.4±0.5°, 2.1±0.4° and 2.0±0.8°. Larger head rotations where it becomes difficult to see facial features can cause estimation to fail (10.2±6.1% of all poses in our static torso range of motion tests) but we found no significant changes in performance with the participant standing further away from Kinect - additionally enabling full-body pose estimation - or without performing face shape calibration, something which is not always possible for younger or disabled participants. Where facial features remain visible, the sensor has applications in the non-invasive assessment of postural control, e.g. during a programme of physical therapy. In particular, a multi-Kinect setup covering the full range of head (and body) movement would appear to be a promising way forward. Copyright © 2016 Elsevier B.V. All rights reserved.

Real-time video analysis for retail stores

NASA Astrophysics Data System (ADS)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

Algorithms and Array Design Criteria for Robust Imaging in Interferometry

NASA Astrophysics Data System (ADS)

Kurien, Binoy George

Optical interferometry is a technique for obtaining high-resolution imagery of a distant target by interfering light from multiple telescopes. Image restoration from interferometric measurements poses a unique set of challenges. The first challenge is that the measurement set provides only a sparse-sampling of the object's Fourier Transform and hence image formation from these measurements is an inherently ill-posed inverse problem. Secondly, atmospheric turbulence causes severe distortion of the phase of the Fourier samples. We develop array design conditions for unique Fourier phase recovery, as well as a comprehensive algorithmic framework based on the notion of redundant-spaced-calibration (RSC), which together achieve reliable image reconstruction in spite of these challenges. Within this framework, we see that classical interferometric observables such as the bispectrum and closure phase can limit sensitivity, and that generalized notions of these observables can improve both theoretical and empirical performance. Our framework leverages techniques from lattice theory to resolve integer phase ambiguities in the interferometric phase measurements, and from graph theory, to select a reliable set of generalized observables. We analyze the expected shot-noise-limited performance of our algorithm for both pairwise and Fizeau interferometric architectures and corroborate this analysis with simulation results. We apply techniques from the field of compressed sensing to perform image reconstruction from the estimates of the object's Fourier coefficients. The end result is a comprehensive strategy to achieve well-posed and easily-predictable reconstruction performance in optical interferometry.

A comparison of spacecraft penetration hazards due to meteoroids and manmade earth-orbiting objects

NASA Technical Reports Server (NTRS)

Brooks, D. R.

1976-01-01

The ability of a typical double-walled spacecraft structure to protect against penetration by high-velocity incident objects is reviewed. The hazards presented by meteoroids are compared to the current and potential hazards due to manmade orbiting objects. It is shown that the nature of the meteoroid number-mass relationship makes adequate protection for large space facilities a conceptually straightforward structural problem. The present level of manmade orbiting objects (an estimated 10,000 in early 1975) does not pose an unacceptable risk to manned space operations proposed for the near future, but it does produce penetration probabilities in the range of 1-10 percent for a 100-m diameter sphere in orbit for 1,000 days. The number-size distribution of manmade objects is such that adequate protection is difficult to achieve for large permanent space facilities, to the extent that future restrictions on such facilities may result if the growth of orbiting objects continues at its historical rate.

An interactive framework for acquiring vision models of 3-D objects from 2-D images.

PubMed

Motai, Yuichi; Kak, Avinash

2004-02-01

This paper presents a human-computer interaction (HCI) framework for building vision models of three-dimensional (3-D) objects from their two-dimensional (2-D) images. Our framework is based on two guiding principles of HCI: 1) provide the human with as much visual assistance as possible to help the human make a correct input; and 2) verify each input provided by the human for its consistency with the inputs previously provided. For example, when stereo correspondence information is elicited from a human, his/her job is facilitated by superimposing epipolar lines on the images. Although that reduces the possibility of error in the human marked correspondences, such errors are not entirely eliminated because there can be multiple candidate points close together for complex objects. For another example, when pose-to-pose correspondence is sought from a human, his/her job is made easier by allowing the human to rotate the partial model constructed in the previous pose in relation to the partial model for the current pose. While this facility reduces the incidence of human-supplied pose-to-pose correspondence errors, such errors cannot be eliminated entirely because of confusion created when multiple candidate features exist close together. Each input provided by the human is therefore checked against the previous inputs by invoking situation-specific constraints. Different types of constraints (and different human-computer interaction protocols) are needed for the extraction of polygonal features and for the extraction of curved features. We will show results on both polygonal objects and object containing curved features.

Endoscopic feature tracking for augmented-reality assisted prosthesis selection in mitral valve repair

NASA Astrophysics Data System (ADS)

Engelhardt, Sandy; Kolb, Silvio; De Simone, Raffaele; Karck, Matthias; Meinzer, Hans-Peter; Wolf, Ivo

2016-03-01

Mitral valve annuloplasty describes a surgical procedure where an artificial prosthesis is sutured onto the anatomical structure of the mitral annulus to re-establish the valve's functionality. Choosing an appropriate commercially available ring size and shape is a difficult decision the surgeon has to make intraoperatively according to his experience. In our augmented-reality framework, digitalized ring models are superimposed onto endoscopic image streams without using any additional hardware. To place the ring model on the proper position within the endoscopic image plane, a pose estimation is performed that depends on the localization of sutures placed by the surgeon around the leaflet origins and punctured through the stiffer structure of the annulus. In this work, the tissue penetration points are tracked by the real-time capable Lucas Kanade optical flow algorithm. The accuracy and robustness of this tracking algorithm is investigated with respect to the question whether outliers influence the subsequent pose estimation. Our results suggest that optical flow is very stable for a variety of different endoscopic scenes and tracking errors do not affect the position of the superimposed virtual objects in the scene, making this approach a viable candidate for annuloplasty augmented reality-enhanced decision support.

Fusion of Building Information and Range Imaging for Autonomous Location Estimation in Indoor Environments

PubMed Central

Kohoutek, Tobias K.; Mautz, Rainer; Wegner, Jan D.

2013-01-01

We present a novel approach for autonomous location estimation and navigation in indoor environments using range images and prior scene knowledge from a GIS database (CityGML). What makes this task challenging is the arbitrary relative spatial relation between GIS and Time-of-Flight (ToF) range camera further complicated by a markerless configuration. We propose to estimate the camera's pose solely based on matching of GIS objects and their detected location in image sequences. We develop a coarse-to-fine matching strategy that is able to match point clouds without any initial parameters. Experiments with a state-of-the-art ToF point cloud show that our proposed method delivers an absolute camera position with decimeter accuracy, which is sufficient for many real-world applications (e.g., collision avoidance). PMID:23435055

Mapping land water and energy balance relations through conditional sampling of remote sensing estimates of atmospheric forcing and surface states

NASA Astrophysics Data System (ADS)

Farhadi, Leila; Entekhabi, Dara; Salvucci, Guido

2016-04-01

In this study, we develop and apply a mapping estimation capability for key unknown parameters that link the surface water and energy balance equations. The method is applied to the Gourma region in West Africa. The accuracy of the estimation method at point scale was previously examined using flux tower data. In this study, the capability is scaled to be applicable with remotely sensed data products and hence allow mapping. Parameters of the system are estimated through a process that links atmospheric forcing (precipitation and incident radiation), surface states, and unknown parameters. Based on conditional averaging of land surface temperature and moisture states, respectively, a single objective function is posed that measures moisture and temperature-dependent errors solely in terms of observed forcings and surface states. This objective function is minimized with respect to parameters to identify evapotranspiration and drainage models and estimate water and energy balance flux components. The uncertainty of the estimated parameters (and associated statistical confidence limits) is obtained through the inverse of Hessian of the objective function, which is an approximation of the covariance matrix. This calibration-free method is applied to the mesoscale region of Gourma in West Africa using multiplatform remote sensing data. The retrievals are verified against tower-flux field site data and physiographic characteristics of the region. The focus is to find the functional form of the evaporative fraction dependence on soil moisture, a key closure function for surface and subsurface heat and moisture dynamics, using remote sensing data.

Attribute And-Or Grammar for Joint Parsing of Human Pose, Parts and Attributes.

PubMed

Park, Seyoung; Nie, Xiaohan; Zhu, Song-Chun

2017-07-25

This paper presents an attribute and-or grammar (A-AOG) model for jointly inferring human body pose and human attributes in a parse graph with attributes augmented to nodes in the hierarchical representation. In contrast to other popular methods in the current literature that train separate classifiers for poses and individual attributes, our method explicitly represents the decomposition and articulation of body parts, and account for the correlations between poses and attributes. The A-AOG model is an amalgamation of three traditional grammar formulations: (i)Phrase structure grammar representing the hierarchical decomposition of the human body from whole to parts; (ii)Dependency grammar modeling the geometric articulation by a kinematic graph of the body pose; and (iii)Attribute grammar accounting for the compatibility relations between different parts in the hierarchy so that their appearances follow a consistent style. The parse graph outputs human detection, pose estimation, and attribute prediction simultaneously, which are intuitive and interpretable. We conduct experiments on two tasks on two datasets, and experimental results demonstrate the advantage of joint modeling in comparison with computing poses and attributes independently. Furthermore, our model obtains better performance over existing methods for both pose estimation and attribute prediction tasks.

IMU-based Real-time Pose Measurement system for Anterior Pelvic Plane in Total Hip Replacement Surgeries.

PubMed

Zhe Cao; Shaojie Su; Hao Tang; Yixin Zhou; Zhihua Wang; Hong Chen

2017-07-01

With the aging of population, the number of Total Hip Replacement Surgeries (THR) increased year by year. In THR, inaccurate position of the implanted prosthesis may lead to the failure of the operation. In order to reduce the failure rate and acquire the real-time pose of Anterior Pelvic Plane (APP), we propose a measurement system in this paper. The measurement system includes two parts: Initial Pose Measurement Instrument (IPMI) and Real-time Pose Measurement Instrument (RPMI). IPMI is used to acquire the initial pose of the APP, and RPMI is used to estimate the real-time pose of the APP. Both are composed of an Inertial Measurement Unit (IMU) and magnetometer sensors. To estimate the attitude of the measurement system, the Extended Kalman Filter (EKF) is adopted in this paper. The real-time pose of the APP could be acquired together with the algorithm designed in the paper. The experiment results show that the Root Mean Square Error (RMSE) is within 1.6 degrees, which meets the requirement of THR operations.

The impact rate on Earth.

PubMed

Bland, Philip A

2005-12-15

Recent data, and modelling of the interaction between asteroids and the atmosphere, has defined a complete size-frequency distribution for terrestrial impactors, from meteorite-sized objects up to kilometre-sized asteroids, for both the upper atmosphere and the Earth's surface. Although there remain significant uncertainties in the incidence of specific size-fractions of impactors, these estimates allow us to constrain the threat posed by impacts to human populations. It is clear that impacts remain a significant natural hazard, but uniquely, they are a threat that we can accurately predict, and take steps to avoid.

Design and implementation of a vision-based hovering and feature tracking algorithm for a quadrotor

NASA Astrophysics Data System (ADS)

Lee, Y. H.; Chahl, J. S.

2016-10-01

This paper demonstrates an approach to the vision-based control of the unmanned quadrotors for hover and object tracking. The algorithms used the Speed Up Robust Features (SURF) algorithm to detect objects. The pose of the object in the image was then calculated in order to pass the pose information to the flight controller. Finally, the flight controller steered the quadrotor to approach the object based on the calculated pose data. The above processes was run using standard onboard resources found in the 3DR Solo quadrotor in an embedded computing environment. The obtained results showed that the algorithm behaved well during its missions, tracking and hovering, although there were significant latencies due to low CPU performance of the onboard image processing system.

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications.

PubMed

Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

2016-09-14

Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments.

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications

PubMed Central

Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

2016-01-01

Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments. PMID:27649178

Discriminating Projections for Estimating Face Age in Wild Images

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

Tokola, Ryan A; Bolme, David S; Ricanek, Karl

2014-01-01

We introduce a novel approach to estimating the age of a human from a single uncontrolled image. Current face age estimation algorithms work well in highly controlled images, and some are robust to changes in illumination, but it is usually assumed that images are close to frontal. This bias is clearly seen in the datasets that are commonly used to evaluate age estimation, which either entirely or mostly consist of frontal images. Using pose-specific projections, our algorithm maps image features into a pose-insensitive latent space that is discriminative with respect to age. Age estimation is then performed using a multi-classmore » SVM. We show that our approach outperforms other published results on the Images of Groups dataset, which is the only age-related dataset with a non-trivial number of off-axis face images, and that we are competitive with recent age estimation algorithms on the mostly-frontal FG-NET dataset. We also experimentally demonstrate that our feature projections introduce insensitivity to pose.« less

Model-based tomographic reconstruction of objects containing known components.

PubMed

Stayman, J Webster; Otake, Yoshito; Prince, Jerry L; Khanna, A Jay; Siewerdsen, Jeffrey H

2012-10-01

The likelihood of finding manufactured components (surgical tools, implants, etc.) within a tomographic field-of-view has been steadily increasing. One reason is the aging population and proliferation of prosthetic devices, such that more people undergoing diagnostic imaging have existing implants, particularly hip and knee implants. Another reason is that use of intraoperative imaging (e.g., cone-beam CT) for surgical guidance is increasing, wherein surgical tools and devices such as screws and plates are placed within or near to the target anatomy. When these components contain metal, the reconstructed volumes are likely to contain severe artifacts that adversely affect the image quality in tissues both near and far from the component. Because physical models of such components exist, there is a unique opportunity to integrate this knowledge into the reconstruction algorithm to reduce these artifacts. We present a model-based penalized-likelihood estimation approach that explicitly incorporates known information about component geometry and composition. The approach uses an alternating maximization method that jointly estimates the anatomy and the position and pose of each of the known components. We demonstrate that the proposed method can produce nearly artifact-free images even near the boundary of a metal implant in simulated vertebral pedicle screw reconstructions and even under conditions of substantial photon starvation. The simultaneous estimation of device pose also provides quantitative information on device placement that could be valuable to quality assurance and verification of treatment delivery.

Imaging artificial satellites: An observational challenge

NASA Astrophysics Data System (ADS)

Smith, D. A.; Hill, D. C.

2016-10-01

According to the Union of Concerned Scientists, as of the beginning of 2016 there are 1381 active satellites orbiting the Earth, and the United States' Space Surveillance Network tracks about 8000 manmade orbiting objects of baseball-size and larger. NASA estimates debris larger than 1 cm to number more than half a million. The largest ones can be seen by eye—unresolved dots of light that move across the sky in minutes. For most astrophotographers, satellites are annoying streaks that can ruin hours of work. However, capturing a resolved image of an artificial satellite can pose an interesting challenge for a student, and such a project can provide connections between objects in the sky and commercial and political activities here on Earth.

Appearance-based face recognition and light-fields.

PubMed

Gross, Ralph; Matthews, Iain; Baker, Simon

2004-04-01

Arguably the most important decision to be made when developing an object recognition algorithm is selecting the scene measurements or features on which to base the algorithm. In appearance-based object recognition, the features are chosen to be the pixel intensity values in an image of the object. These pixel intensities correspond directly to the radiance of light emitted from the object along certain rays in space. The set of all such radiance values over all possible rays is known as the plenoptic function or light-field. In this paper, we develop a theory of appearance-based object recognition from light-fields. This theory leads directly to an algorithm for face recognition across pose that uses as many images of the face as are available, from one upwards. All of the pixels, whichever image they come from, are treated equally and used to estimate the (eigen) light-field of the object. The eigen light-field is then used as the set of features on which to base recognition, analogously to how the pixel intensities are used in appearance-based face and object recognition.

Neuro-fuzzy model for estimating race and gender from geometric distances of human face across pose

NASA Astrophysics Data System (ADS)

Nanaa, K.; Rahman, M. N. A.; Rizon, M.; Mohamad, F. S.; Mamat, M.

2018-03-01

Classifying human face based on race and gender is a vital process in face recognition. It contributes to an index database and eases 3D synthesis of the human face. Identifying race and gender based on intrinsic factor is problematic, which is more fitting to utilizing nonlinear model for estimating process. In this paper, we aim to estimate race and gender in varied head pose. For this purpose, we collect dataset from PICS and CAS-PEAL databases, detect the landmarks and rotate them to the frontal pose. After geometric distances are calculated, all of distance values will be normalized. Implementation is carried out by using Neural Network Model and Fuzzy Logic Model. These models are combined by using Adaptive Neuro-Fuzzy Model. The experimental results showed that the optimization of address fuzzy membership. Model gives a better assessment rate and found that estimating race contributing to a more accurate gender assessment.

Incremental inverse kinematics based vision servo for autonomous robotic capture of non-cooperative space debris

NASA Astrophysics Data System (ADS)

Dong, Gangqi; Zhu, Z. H.

2016-04-01

This paper proposed a new incremental inverse kinematics based vision servo approach for robotic manipulators to capture a non-cooperative target autonomously. The target's pose and motion are estimated by a vision system using integrated photogrammetry and EKF algorithm. Based on the estimated pose and motion of the target, the instantaneous desired position of the end-effector is predicted by inverse kinematics and the robotic manipulator is moved incrementally from its current configuration subject to the joint speed limits. This approach effectively eliminates the multiple solutions in the inverse kinematics and increases the robustness of the control algorithm. The proposed approach is validated by a hardware-in-the-loop simulation, where the pose and motion of the non-cooperative target is estimated by a real vision system. The simulation results demonstrate the effectiveness and robustness of the proposed estimation approach for the target and the incremental control strategy for the robotic manipulator.

Combining color and shape information for illumination-viewpoint invariant object recognition.

PubMed

Diplaros, Aristeidis; Gevers, Theo; Patras, Ioannis

2006-01-01

In this paper, we propose a new scheme that merges color- and shape-invariant information for object recognition. To obtain robustness against photometric changes, color-invariant derivatives are computed first. Color invariance is an important aspect of any object recognition scheme, as color changes considerably with the variation in illumination, object pose, and camera viewpoint. These color invariant derivatives are then used to obtain similarity invariant shape descriptors. Shape invariance is equally important as, under a change in camera viewpoint and object pose, the shape of a rigid object undergoes a perspective projection on the image plane. Then, the color and shape invariants are combined in a multidimensional color-shape context which is subsequently used as an index. As the indexing scheme makes use of a color-shape invariant context, it provides a high-discriminative information cue robust against varying imaging conditions. The matching function of the color-shape context allows for fast recognition, even in the presence of object occlusion and cluttering. From the experimental results, it is shown that the method recognizes rigid objects with high accuracy in 3-D complex scenes and is robust against changing illumination, camera viewpoint, object pose, and noise.

Hand pose estimation in depth image using CNN and random forest

NASA Astrophysics Data System (ADS)

Chen, Xi; Cao, Zhiguo; Xiao, Yang; Fang, Zhiwen

2018-03-01

Thanks to the availability of low cost depth cameras, like Microsoft Kinect, 3D hand pose estimation attracted special research attention in these years. Due to the large variations in hand`s viewpoint and the high dimension of hand motion, 3D hand pose estimation is still challenging. In this paper we propose a two-stage framework which joint with CNN and Random Forest to boost the performance of hand pose estimation. First, we use a standard Convolutional Neural Network (CNN) to regress the hand joints` locations. Second, using a Random Forest to refine the joints from the first stage. In the second stage, we propose a pyramid feature which merges the information flow of the CNN. Specifically, we get the rough joints` location from first stage, then rotate the convolutional feature maps (and image). After this, for each joint, we map its location to each feature map (and image) firstly, then crop features at each feature map (and image) around its location, put extracted features to Random Forest to refine at last. Experimentally, we evaluate our proposed method on ICVL dataset and get the mean error about 11mm, our method is also real-time on a desktop.

Vision Based SLAM in Dynamic Scenes

DTIC Science & Technology

2012-12-20

the correct relative poses between cameras at frame F. For this purpose, we detect and match SURF features between cameras in dilierent groups, and...all cameras in s uch a challenging case. For a compa rison, we disabled the ’ inte r-camera pose estimation’ and applied the ’ intra-camera pose esti

An approach to ground based space surveillance of geostationary on-orbit servicing operations

NASA Astrophysics Data System (ADS)

Scott, Robert (Lauchie); Ellery, Alex

2015-07-01

On Orbit Servicing (OOS) is a class of dual-use robotic space missions that could potentially extend the life of orbiting satellites by fuel replenishment, repair, inspection, orbital maintenance or satellite repurposing, and possibly reduce the rate of space debris generation. OOS performed in geostationary orbit poses a unique challenge for the optical space surveillance community. Both satellites would be performing proximity operations in tight formation flight with separations less than 500 m making atmospheric seeing (turbulence) a challenge to resolving a geostationary satellite pair when viewed from the ground. The two objects would appear merged in an image as the resolving power of the telescope and detector, coupled with atmospheric seeing, limits the ability to resolve the two objects. This poses an issue for obtaining orbital data for conjunction flight safety or, in matters pertaining to space security, inferring the intent and trajectory of an unexpected object perched very close to one's satellite asset on orbit. In order to overcome this problem speckle interferometry using a cross spectrum approach is examined as a means to optically resolve the client and servicer's relative positions to enable a means to perform relative orbit determination of the two spacecraft. This paper explores cases where client and servicing satellites are in unforced relative motion flight and examines the observability of the objects. Tools are described that exploit cross-spectrum speckle interferometry to (1) determine the presence of a secondary in the vicinity of the client satellite and (2) estimate the servicing satellite's motion relative to the client. Experimental observations performed with the Mont Mégantic 1.6 m telescope on co-located geostationary satellites (acting as OOS proxy objects) are described. Apparent angular separations between Anik G1 and Anik F1R from 5 to 1 arcsec were observed as the two satellites appeared to graze one another. Data reduction using differential angular measurements derived from speckle images collected by the 1.6 m telescope produced relative orbit estimates with better than 90 m accuracy in the cross-track and in-track directions but exhibited highly variable behavior in the radial component from 50 to 1800 m. Simulations of synthetic tracking data indicated that the radial component requires approximately six hours of tracking data for an Extended Kalman Filter to converge on an relative orbit estimate with less than 100 m overall uncertainty. The cross-spectrum approach takes advantage of the Fast Fourier Transform (FFT) permitting near real-time estimation of the relative orbit of the two satellites. This also enables the use of relatively larger detector arrays (>106 pixels) helping to ease acquisition process to acquire optical angular data.

Depth-resolved registration of transesophageal echo to x-ray fluoroscopy using an inverse geometry fluoroscopy system

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

Hatt, Charles R.; Tomkowiak, Michael T.; Dunkerley, David A. P.

2015-12-15

Purpose: Image registration between standard x-ray fluoroscopy and transesophageal echocardiography (TEE) has recently been proposed. Scanning-beam digital x-ray (SBDX) is an inverse geometry fluoroscopy system designed for cardiac procedures. This study presents a method for 3D registration of SBDX and TEE images based on the tomosynthesis and 3D tracking capabilities of SBDX. Methods: The registration algorithm utilizes the stack of tomosynthetic planes produced by the SBDX system to estimate the physical 3D coordinates of salient key-points on the TEE probe. The key-points are used to arrive at an initial estimate of the probe pose, which is then refined using amore » 2D/3D registration method adapted for inverse geometry fluoroscopy. A phantom study was conducted to evaluate probe pose estimation accuracy relative to the ground truth, as defined by a set of coregistered fiducial markers. This experiment was conducted with varying probe poses and levels of signal difference-to-noise ratio (SDNR). Additional phantom and in vivo studies were performed to evaluate the correspondence of catheter tip positions in TEE and x-ray images following registration of the two modalities. Results: Target registration error (TRE) was used to characterize both pose estimation and registration accuracy. In the study of pose estimation accuracy, successful pose estimates (3D TRE < 5.0 mm) were obtained in 97% of cases when the SDNR was 5.9 or higher in seven out of eight poses. Under these conditions, 3D TRE was 2.32 ± 1.88 mm, and 2D (projection) TRE was 1.61 ± 1.36 mm. Probe localization error along the source-detector axis was 0.87 ± 1.31 mm. For the in vivo experiments, mean 3D TRE ranged from 2.6 to 4.6 mm and mean 2D TRE ranged from 1.1 to 1.6 mm. Anatomy extracted from the echo images appeared well aligned when projected onto the SBDX images. Conclusions: Full 6 DOF image registration between SBDX and TEE is feasible and accurate to within 5 mm. Future studies will focus on real-time implementation and application-specific analysis.« less

Adaptation of an articulated fetal skeleton model to three-dimensional fetal image data

NASA Astrophysics Data System (ADS)

Klinder, Tobias; Wendland, Hannes; Wachter-Stehle, Irina; Roundhill, David; Lorenz, Cristian

2015-03-01

The automatic interpretation of three-dimensional fetal images poses specific challenges compared to other three-dimensional diagnostic data, especially since the orientation of the fetus in the uterus and the position of the extremities is highly variable. In this paper, we present a comprehensive articulated model of the fetal skeleton and the adaptation of the articulation for pose estimation in three-dimensional fetal images. The model is composed out of rigid bodies where the articulations are represented as rigid body transformations. Given a set of target landmarks, the model constellation can be estimated by optimization of the pose parameters. Experiments are carried out on 3D fetal MRI data yielding an average error per case of 12.03+/-3.36 mm between target and estimated landmark positions.

Space structures insulating material's thermophysical and radiation properties estimation

NASA Astrophysics Data System (ADS)

Nenarokomov, A. V.; Alifanov, O. M.; Titov, D. M.

2007-11-01

In many practical situations in aerospace technology it is impossible to measure directly such properties of analyzed materials (for example, composites) as thermal and radiation characteristics. The only way that can often be used to overcome these difficulties is indirect measurements. This type of measurement is usually formulated as the solution of inverse heat transfer problems. Such problems are ill-posed in mathematical sense and their main feature shows itself in the solution instabilities. That is why special regularizing methods are needed to solve them. The experimental methods of identification of the mathematical models of heat transfer based on solving the inverse problems are one of the modern effective solving manners. The objective of this paper is to estimate thermal and radiation properties of advanced materials using the approach based on inverse methods.

Autonomous intelligent assembly systems LDRD 105746 final report.

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

Anderson, Robert J.

2013-04-01

This report documents a three-year to develop technology that enables mobile robots to perform autonomous assembly tasks in unstructured outdoor environments. This is a multi-tier problem that requires an integration of a large number of different software technologies including: command and control, estimation and localization, distributed communications, object recognition, pose estimation, real-time scanning, and scene interpretation. Although ultimately unsuccessful in achieving a target brick stacking task autonomously, numerous important component technologies were nevertheless developed. Such technologies include: a patent-pending polygon snake algorithm for robust feature tracking, a color grid algorithm for uniquely identification and calibration, a command and control frameworkmore » for abstracting robot commands, a scanning capability that utilizes a compact robot portable scanner, and more. This report describes this project and these developed technologies.« less

Strategies for Coordination of a Serosurvey in Parallel with an Immunization Coverage Survey

PubMed Central

Travassos, Mark A.; Beyene, Berhane; Adam, Zenaw; Campbell, James D.; Mulholland, Nigisti; Diarra, Seydou S.; Kassa, Tassew; Oot, Lisa; Sequeira, Jenny; Reymann, Mardi; Blackwelder, William C.; Pasetti, Marcela F.; Sow, Samba O.; Steinglass, Robert; Kebede, Amha; Levine, Myron M.

2015-01-01

A community-based immunization coverage survey is the standard way to estimate effective vaccination delivery to a target population in a region. Accompanying serosurveys can provide objective measures of protective immunity against vaccine-preventable diseases but pose considerable challenges with respect to specimen collection and preservation and community compliance. We performed serosurveys coupled to immunization coverage surveys in three administrative districts (woredas) in rural Ethiopia. Critical to the success of this effort were serosurvey equipment and supplies, team composition, and tight coordination with the coverage survey. Application of these techniques to future studies may foster more widespread use of serosurveys to derive more objective assessments of vaccine-derived seroprotection and monitor and compare the performance of immunization services in different districts of a country. PMID:26055737

Radiation Exposure and Mortality from Cardiovascular Disease and Cancer in Early NASA Astronauts: Space for Exploration

NASA Technical Reports Server (NTRS)

Elgart, S. R.; Little, M. P.; Campbell, L. J.; Milder, C. M.; Shavers, M. R.; Huff, J. L.; Patel, Z. S.

2018-01-01

Of the many possible health challenges posed during extended exploratory missions to space, the effects of space radiation on cardiovascular disease and cancer are of particular concern. There are unique challenges to estimating those radiation risks; care and appropriate and rigorous methodology should be applied when considering small cohorts such as the NASA astronaut population. The objective of this work was to establish whether there is evidence for excess cardiovascular disease or cancer mortality in an early NASA astronaut cohort and determine if a correlation exists between space radiation exposure and mortality.

Structure-From for Calibration of a Vehicle Camera System with Non-Overlapping Fields-Of in AN Urban Environment

NASA Astrophysics Data System (ADS)

Hanel, A.; Stilla, U.

2017-05-01

Vehicle environment cameras observing traffic participants in the area around a car and interior cameras observing the car driver are important data sources for driver intention recognition algorithms. To combine information from both camera groups, a camera system calibration can be performed. Typically, there is no overlapping field-of-view between environment and interior cameras. Often no marked reference points are available in environments, which are a large enough to cover a car for the system calibration. In this contribution, a calibration method for a vehicle camera system with non-overlapping camera groups in an urban environment is described. A-priori images of an urban calibration environment taken with an external camera are processed with the structure-frommotion method to obtain an environment point cloud. Images of the vehicle interior, taken also with an external camera, are processed to obtain an interior point cloud. Both point clouds are tied to each other with images of both image sets showing the same real-world objects. The point clouds are transformed into a self-defined vehicle coordinate system describing the vehicle movement. On demand, videos can be recorded with the vehicle cameras in a calibration drive. Poses of vehicle environment cameras and interior cameras are estimated separately using ground control points from the respective point cloud. All poses of a vehicle camera estimated for different video frames are optimized in a bundle adjustment. In an experiment, a point cloud is created from images of an underground car park, as well as a point cloud of the interior of a Volkswagen test car is created. Videos of two environment and one interior cameras are recorded. Results show, that the vehicle camera poses are estimated successfully especially when the car is not moving. Position standard deviations in the centimeter range can be achieved for all vehicle cameras. Relative distances between the vehicle cameras deviate between one and ten centimeters from tachymeter reference measurements.

Matching Real and Synthetic Panoramic Images Using a Variant of Geometric Hashing

NASA Astrophysics Data System (ADS)

Li-Chee-Ming, J.; Armenakis, C.

2017-05-01

This work demonstrates an approach to automatically initialize a visual model-based tracker, and recover from lost tracking, without prior camera pose information. These approaches are commonly referred to as tracking-by-detection. Previous tracking-by-detection techniques used either fiducials (i.e. landmarks or markers) or the object's texture. The main contribution of this work is the development of a tracking-by-detection algorithm that is based solely on natural geometric features. A variant of geometric hashing, a model-to-image registration algorithm, is proposed that searches for a matching panoramic image from a database of synthetic panoramic images captured in a 3D virtual environment. The approach identifies corresponding features between the matched panoramic images. The corresponding features are to be used in a photogrammetric space resection to estimate the camera pose. The experiments apply this algorithm to initialize a model-based tracker in an indoor environment using the 3D CAD model of the building.

Finite dimensional approximation of a class of constrained nonlinear optimal control problems

NASA Technical Reports Server (NTRS)

Gunzburger, Max D.; Hou, L. S.

1994-01-01

An abstract framework for the analysis and approximation of a class of nonlinear optimal control and optimization problems is constructed. Nonlinearities occur in both the objective functional and in the constraints. The framework includes an abstract nonlinear optimization problem posed on infinite dimensional spaces, and approximate problem posed on finite dimensional spaces, together with a number of hypotheses concerning the two problems. The framework is used to show that optimal solutions exist, to show that Lagrange multipliers may be used to enforce the constraints, to derive an optimality system from which optimal states and controls may be deduced, and to derive existence results and error estimates for solutions of the approximate problem. The abstract framework and the results derived from that framework are then applied to three concrete control or optimization problems and their approximation by finite element methods. The first involves the von Karman plate equations of nonlinear elasticity, the second, the Ginzburg-Landau equations of superconductivity, and the third, the Navier-Stokes equations for incompressible, viscous flows.

D Point Cloud Model Colorization by Dense Registration of Digital Images

NASA Astrophysics Data System (ADS)

Crombez, N.; Caron, G.; Mouaddib, E.

2015-02-01

Architectural heritage is a historic and artistic property which has to be protected, preserved, restored and must be shown to the public. Modern tools like 3D laser scanners are more and more used in heritage documentation. Most of the time, the 3D laser scanner is completed by a digital camera which is used to enrich the accurate geometric informations with the scanned objects colors. However, the photometric quality of the acquired point clouds is generally rather low because of several problems presented below. We propose an accurate method for registering digital images acquired from any viewpoints on point clouds which is a crucial step for a good colorization by colors projection. We express this image-to-geometry registration as a pose estimation problem. The camera pose is computed using the entire images intensities under a photometric visual and virtual servoing (VVS) framework. The camera extrinsic and intrinsic parameters are automatically estimated. Because we estimates the intrinsic parameters we do not need any informations about the camera which took the used digital image. Finally, when the point cloud model and the digital image are correctly registered, we project the 3D model in the digital image frame and assign new colors to the visible points. The performance of the approach is proven in simulation and real experiments on indoor and outdoor datasets of the cathedral of Amiens, which highlight the success of our method, leading to point clouds with better photometric quality and resolution.

Structure-From-Motion in 3D Space Using 2D Lidars

PubMed Central

Choi, Dong-Geol; Bok, Yunsu; Kim, Jun-Sik; Shim, Inwook; Kweon, In So

2017-01-01

This paper presents a novel structure-from-motion methodology using 2D lidars (Light Detection And Ranging). In 3D space, 2D lidars do not provide sufficient information for pose estimation. For this reason, additional sensors have been used along with the lidar measurement. In this paper, we use a sensor system that consists of only 2D lidars, without any additional sensors. We propose a new method of estimating both the 6D pose of the system and the surrounding 3D structures. We compute the pose of the system using line segments of scan data and their corresponding planes. After discarding the outliers, both the pose and the 3D structures are refined via nonlinear optimization. Experiments with both synthetic and real data show the accuracy and robustness of the proposed method. PMID:28165372

First stereo video dataset with ground truth for remote car pose estimation using satellite markers

NASA Astrophysics Data System (ADS)

Gil, Gustavo; Savino, Giovanni; Pierini, Marco

2018-04-01

Leading causes of PTW (Powered Two-Wheeler) crashes and near misses in urban areas are on the part of a failure or delayed prediction of the changing trajectories of other vehicles. Regrettably, misperception from both car drivers and motorcycle riders results in fatal or serious consequences for riders. Intelligent vehicles could provide early warning about possible collisions, helping to avoid the crash. There is evidence that stereo cameras can be used for estimating the heading angle of other vehicles, which is key to anticipate their imminent location, but there is limited heading ground truth data available in the public domain. Consequently, we employed a marker-based technique for creating ground truth of car pose and create a dataset∗ for computer vision benchmarking purposes. This dataset of a moving vehicle collected from a static mounted stereo camera is a simplification of a complex and dynamic reality, which serves as a test bed for car pose estimation algorithms. The dataset contains the accurate pose of the moving obstacle, and realistic imagery including texture-less and non-lambertian surfaces (e.g. reflectance and transparency).

Driver head pose tracking with thermal camera

NASA Astrophysics Data System (ADS)

Bole, S.; Fournier, C.; Lavergne, C.; Druart, G.; Lépine, T.

2016-09-01

Head pose can be seen as a coarse estimation of gaze direction. In automotive industry, knowledge about gaze direction could optimize Human-Machine Interface (HMI) and Advanced Driver Assistance Systems (ADAS). Pose estimation systems are often based on camera when applications have to be contactless. In this paper, we explore uncooled thermal imagery (8-14μm) for its intrinsic night vision capabilities and for its invariance versus lighting variations. Two methods are implemented and compared, both are aided by a 3D model of the head. The 3D model, mapped with thermal texture, allows to synthesize a base of 2D projected models, differently oriented and labeled in yaw and pitch. The first method is based on keypoints. Keypoints of models are matched with those of the query image. These sets of matchings, aided with the 3D shape of the model, allow to estimate 3D pose. The second method is a global appearance approach. Among all 2D models of the base, algorithm searches the one which is the closest to the query image thanks to a weighted least squares difference.

Towards Unmanned Systems for Dismounted Operations in the Canadian Forces

DTIC Science & Technology

2011-01-01

LIDAR , and RADAR) and lower power/mass, passive imaging techniques such as structure from motion and simultaneous localisation and mapping ( SLAM ...sensors and learning algorithms. 5.1.2 Simultaneous localisation and mapping SLAM algorithms concurrently estimate a robot pose and a map of unique...locations and vehicle pose are part of the SLAM state vector and are estimated in each update step. AISS developed a monocular camera-based SLAM

A Simulation Environment for Benchmarking Sensor Fusion-Based Pose Estimators.

PubMed

Ligorio, Gabriele; Sabatini, Angelo Maria

2015-12-19

In-depth analysis and performance evaluation of sensor fusion-based estimators may be critical when performed using real-world sensor data. For this reason, simulation is widely recognized as one of the most powerful tools for algorithm benchmarking. In this paper, we present a simulation framework suitable for assessing the performance of sensor fusion-based pose estimators. The systems used for implementing the framework were magnetic/inertial measurement units (MIMUs) and a camera, although the addition of further sensing modalities is straightforward. Typical nuisance factors were also included for each sensor. The proposed simulation environment was validated using real-life sensor data employed for motion tracking. The higher mismatch between real and simulated sensors was about 5% of the measured quantity (for the camera simulation), whereas a lower correlation was found for an axis of the gyroscope (0.90). In addition, a real benchmarking example of an extended Kalman filter for pose estimation from MIMU and camera data is presented.

Temporal subtraction of chest radiographs compensating pose differences

NASA Astrophysics Data System (ADS)

von Berg, Jens; Dworzak, Jalda; Klinder, Tobias; Manke, Dirk; Kreth, Adrian; Lamecker, Hans; Zachow, Stefan; Lorenz, Cristian

2011-03-01

Temporal subtraction techniques using 2D image registration improve the detectability of interval changes from chest radiographs. Although such methods are well known for some time they are not widely used in radiologic practice. The reason is the occurrence of strong pose differences between two acquisitions with a time interval of months to years in between. Such strong perspective differences occur in a reasonable number of cases. They cannot be compensated by available image registration methods and thus mask interval changes to be undetectable. In this paper a method is proposed to estimate a 3D pose difference by the adaptation of a 3D rib cage model to both projections. The difference between both is then compensated for, thus producing a subtraction image with virtually no change in pose. The method generally assumes that no 3D image data is available from the patient. The accuracy of pose estimation is validated with chest phantom images acquired under controlled geometric conditions. A subtle interval change simulated by a piece of plastic foam attached to the phantom becomes visible in subtraction images generated with this technique even at strong angular pose differences like an anterior-posterior inclination of 13 degrees.

Design of relative trajectories for in orbit proximity operations

NASA Astrophysics Data System (ADS)

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2018-04-01

This paper presents an innovative approach to design relative trajectories suitable for close-proximity operations in orbit, by assigning high-level constraints regarding their stability, shape and orientation. Specifically, this work is relevant to space mission scenarios, e.g. formation flying, on-orbit servicing, and active debris removal, which involve either the presence of two spacecraft carrying out coordinated maneuvers, or a servicing/recovery spacecraft (chaser) performing monitoring, rendezvous and docking with respect to another space object (target). In the above-mentioned scenarios, an important aspect is the capability of reducing collision risks and of providing robust and accurate relative navigation solutions. To this aim, the proposed approach exploits a relative motion model relevant to two-satellite formations, and developed in mean orbit parameters, which takes the perturbation effect due to secular Earth oblateness, as well as the motion of the target along a small-eccentricity orbit, into account. This model is used to design trajectories which ensure safe relative motion, to minimize collision risks and relax control requirements, providing at the same time favorable conditions, in terms of target-chaser relative observation geometry for pose determination and relative navigation with passive or active electro-optical sensors on board the chaser. Specifically, three design strategies are proposed in the context of a space target monitoring scenario, considering as design cases both operational spacecraft and debris, characterized by highly variable shape, size and absolute rotational dynamics. The effectiveness of the proposed design approach in providing favorable observation conditions for target-chaser relative pose estimation is demonstrated within a simulation environment which reproduces the designed target-chaser relative trajectory, the operation of an active LIDAR installed on board the chaser, and pose estimation algorithms.

Surface Color Perception and Equivalent Illumination Models

PubMed Central

Brainard, David H.; Maloney, Laurence T.

2011-01-01

Vision provides information about the properties and identity of objects. The ease with which we make such judgments belies the difficulty of the information-processing task that accomplishes it. In the case of object color, retinal information about object reflectance is confounded with information about the illumination as well as about the object’s shape and pose. Because of these factors, there is no obvious rule that allows transformation of the retinal images of an object to a color representation that depends primarily on the object’s surface reflectance properties. Despite the difficulty of this task, however, under many circumstances object color appearance is remarkably stable across scenes in which the object is viewed. Here we review experiments and theory that aim to understand how the visual system stabilizes the color appearance of object surfaces. Our emphasis is on a class of models derived from explicit analysis of the computational problem of estimating the physical properties of illuminants and surfaces from the information available in the retinal image and experiments that test these models. We argue that this approach has considerable promise for allowing generalization from simplified laboratory experiments to richer scenes that more closely approximate natural viewing. PMID:21536727

On the optimization of electromagnetic geophysical data: Application of the PSO algorithm

NASA Astrophysics Data System (ADS)

Godio, A.; Santilano, A.

2018-01-01

Particle Swarm optimization (PSO) algorithm resolves constrained multi-parameter problems and is suitable for simultaneous optimization of linear and nonlinear problems, with the assumption that forward modeling is based on good understanding of ill-posed problem for geophysical inversion. We apply PSO for solving the geophysical inverse problem to infer an Earth model, i.e. the electrical resistivity at depth, consistent with the observed geophysical data. The method doesn't require an initial model and can be easily constrained, according to external information for each single sounding. The optimization process to estimate the model parameters from the electromagnetic soundings focuses on the discussion of the objective function to be minimized. We discuss the possibility to introduce in the objective function vertical and lateral constraints, with an Occam-like regularization. A sensitivity analysis allowed us to check the performance of the algorithm. The reliability of the approach is tested on synthetic, real Audio-Magnetotelluric (AMT) and Long Period MT data. The method appears able to solve complex problems and allows us to estimate the a posteriori distribution of the model parameters.

Self-expressive Dictionary Learning for Dynamic 3D Reconstruction.

PubMed

Zheng, Enliang; Ji, Dinghuang; Dunn, Enrique; Frahm, Jan-Michael

2017-08-22

We target the problem of sparse 3D reconstruction of dynamic objects observed by multiple unsynchronized video cameras with unknown temporal overlap. To this end, we develop a framework to recover the unknown structure without sequencing information across video sequences. Our proposed compressed sensing framework poses the estimation of 3D structure as the problem of dictionary learning, where the dictionary is defined as an aggregation of the temporally varying 3D structures. Given the smooth motion of dynamic objects, we observe any element in the dictionary can be well approximated by a sparse linear combination of other elements in the same dictionary (i.e. self-expression). Our formulation optimizes a biconvex cost function that leverages a compressed sensing formulation and enforces both structural dependency coherence across video streams, as well as motion smoothness across estimates from common video sources. We further analyze the reconstructability of our approach under different capture scenarios, and its comparison and relation to existing methods. Experimental results on large amounts of synthetic data as well as real imagery demonstrate the effectiveness of our approach.

Sensing Strategies for Disambiguating among Multiple Objects in Known Poses.

DTIC Science & Technology

1985-08-01

ELEMENT. PROIECT. TASK Artificial Inteligence Laboratory AE OKUI UBR 545 Technology Square Cambridge, MA 021.39 11. CONTROLLING OFFICE NAME AND ADDRESS 12...AD-Ali65 912 SENSING STRATEGIES FOR DISAMBIGURTING MONG MULTIPLE 1/1 OBJECTS IN KNOWN POSES(U) MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL ...or Dist Special 1 ’ MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A. I. Memo 855 August, 1985 Sensing Strategies for

Body Parts Dependent Joint Regressors for Human Pose Estimation in Still Images.

PubMed

Dantone, Matthias; Gall, Juergen; Leistner, Christian; Van Gool, Luc

2014-11-01

In this work, we address the problem of estimating 2d human pose from still images. Articulated body pose estimation is challenging due to the large variation in body poses and appearances of the different body parts. Recent methods that rely on the pictorial structure framework have shown to be very successful in solving this task. They model the body part appearances using discriminatively trained, independent part templates and the spatial relations of the body parts using a tree model. Within such a framework, we address the problem of obtaining better part templates which are able to handle a very high variation in appearance. To this end, we introduce parts dependent body joint regressors which are random forests that operate over two layers. While the first layer acts as an independent body part classifier, the second layer takes the estimated class distributions of the first one into account and is thereby able to predict joint locations by modeling the interdependence and co-occurrence of the parts. This helps to overcome typical ambiguities of tree structures, such as self-similarities of legs and arms. In addition, we introduce a novel data set termed FashionPose that contains over 7,000 images with a challenging variation of body part appearances due to a large variation of dressing styles. In the experiments, we demonstrate that the proposed parts dependent joint regressors outperform independent classifiers or regressors. The method also performs better or similar to the state-of-the-art in terms of accuracy, while running with a couple of frames per second.

Pose estimation of teeth through crown-shape matching

NASA Astrophysics Data System (ADS)

Mok, Vevin; Ong, Sim Heng; Foong, Kelvin W. C.; Kondo, Toshiaki

2002-05-01

This paper presents a technique for determining a tooth's pose given a dental plaster cast and a set of generic tooth models. The ultimate goal of pose estimation is to obtain information about the sizes and positions of the roots, which lie hidden within the gums, without the use of X-rays, CT or MRI. In our approach, the tooth of interest is first extracted from the 3D dental cast image through segmentation. 2D views are then generated from the extracted tooth and are matched against a target view generated from the generic model with known pose. Additional views are generated in the vicinity of the best view and the entire process is repeated until convergence. Upon convergence, the generic tooth is superimposed onto the dental cast to show the position of the root. The results of applying the technique to canines demonstrate the excellent potential of the algorithm for generic tooth fitting.

3D tomographic reconstruction using geometrical models

NASA Astrophysics Data System (ADS)

Battle, Xavier L.; Cunningham, Gregory S.; Hanson, Kenneth M.

1997-04-01

We address the issue of reconstructing an object of constant interior density in the context of 3D tomography where there is prior knowledge about the unknown shape. We explore the direct estimation of the parameters of a chosen geometrical model from a set of radiographic measurements, rather than performing operations (segmentation for example) on a reconstructed volume. The inverse problem is posed in the Bayesian framework. A triangulated surface describes the unknown shape and the reconstruction is computed with a maximum a posteriori (MAP) estimate. The adjoint differentiation technique computes the derivatives needed for the optimization of the model parameters. We demonstrate the usefulness of the approach and emphasize the techniques of designing forward and adjoint codes. We use the system response of the University of Arizona Fast SPECT imager to illustrate this method by reconstructing the shape of a heart phantom.

Using climate models to estimate the quality of global observational data sets.

PubMed

Massonnet, François; Bellprat, Omar; Guemas, Virginie; Doblas-Reyes, Francisco J

2016-10-28

Observational estimates of the climate system are essential to monitoring and understanding ongoing climate change and to assessing the quality of climate models used to produce near- and long-term climate information. This study poses the dual and unconventional question: Can climate models be used to assess the quality of observational references? We show that this question not only rests on solid theoretical grounds but also offers insightful applications in practice. By comparing four observational products of sea surface temperature with a large multimodel climate forecast ensemble, we find compelling evidence that models systematically score better against the most recent, advanced, but also most independent product. These results call for generalized procedures of model-observation comparison and provide guidance for a more objective observational data set selection. Copyright © 2016, American Association for the Advancement of Science.

Recovery of the parameters of cancellous bone by inversion of effective velocities, and transmission and reflection coefficients

NASA Astrophysics Data System (ADS)

Buchanan, James L.; Gilbert, Robert P.; Ou, Miao-jung Y.

2011-12-01

Estimating the parameters of an elastic or poroelastic medium from reflected or transmitted acoustic data is an important but difficult problem. Use of the Nelder-Mead simplex method to minimize an objective function measuring the discrepancy between some observable and its value calculated from a model for a trial set of parameters has been tried by several authors. In this paper, the difficulty with this direct approach, which is the existence of numerous local minima of the objective function, is documented for the in vitro experiment in which a specimen in a water tank is subject to an ultrasonic pulse. An indirect approach, based on the numerical solution of the equations for a set of ‘effective’ velocities and transmission coefficients, is then observed empirically to ameliorate the difficulties posed by the direct approach.

Ball-scale based hierarchical multi-object recognition in 3D medical images

NASA Astrophysics Data System (ADS)

Bağci, Ulas; Udupa, Jayaram K.; Chen, Xinjian

2010-03-01

This paper investigates, using prior shape models and the concept of ball scale (b-scale), ways of automatically recognizing objects in 3D images without performing elaborate searches or optimization. That is, the goal is to place the model in a single shot close to the right pose (position, orientation, and scale) in a given image so that the model boundaries fall in the close vicinity of object boundaries in the image. This is achieved via the following set of key ideas: (a) A semi-automatic way of constructing a multi-object shape model assembly. (b) A novel strategy of encoding, via b-scale, the pose relationship between objects in the training images and their intensity patterns captured in b-scale images. (c) A hierarchical mechanism of positioning the model, in a one-shot way, in a given image from a knowledge of the learnt pose relationship and the b-scale image of the given image to be segmented. The evaluation results on a set of 20 routine clinical abdominal female and male CT data sets indicate the following: (1) Incorporating a large number of objects improves the recognition accuracy dramatically. (2) The recognition algorithm can be thought as a hierarchical framework such that quick replacement of the model assembly is defined as coarse recognition and delineation itself is known as finest recognition. (3) Scale yields useful information about the relationship between the model assembly and any given image such that the recognition results in a placement of the model close to the actual pose without doing any elaborate searches or optimization. (4) Effective object recognition can make delineation most accurate.

Fast Grasp Contact Computation for a Serial Robot

NASA Technical Reports Server (NTRS)

Hargrave, Brian (Inventor); Shi, Jianying (Inventor); Diftler, Myron A. (Inventor)

2015-01-01

A system includes a controller and a serial robot having links that are interconnected by a joint, wherein the robot can grasp a three-dimensional (3D) object in response to a commanded grasp pose. The controller receives input information, including the commanded grasp pose, a first set of information describing the kinematics of the robot, and a second set of information describing the position of the object to be grasped. The controller also calculates, in a two-dimensional (2D) plane, a set of contact points between the serial robot and a surface of the 3D object needed for the serial robot to achieve the commanded grasp pose. A required joint angle is then calculated in the 2D plane between the pair of links using the set of contact points. A control action is then executed with respect to the motion of the serial robot using the required joint angle.

Fuzzy set methods for object recognition in space applications

NASA Technical Reports Server (NTRS)

Keller, James M.

1992-01-01

Progress on the following tasks is reported: feature calculation; membership calculation; clustering methods (including initial experiments on pose estimation); and acquisition of images (including camera calibration information for digitization of model). The report consists of 'stand alone' sections, describing the activities in each task. We would like to highlight the fact that during this quarter, we believe that we have made a major breakthrough in the area of fuzzy clustering. We have discovered a method to remove the probabilistic constraints that the sum of the memberships across all classes must add up to 1 (as in the fuzzy c-means). A paper, describing this approach, is included.

Robust Feature Matching in Terrestrial Image Sequences

NASA Astrophysics Data System (ADS)

Abbas, A.; Ghuffar, S.

2018-04-01

From the last decade, the feature detection, description and matching techniques are most commonly exploited in various photogrammetric and computer vision applications, which includes: 3D reconstruction of scenes, image stitching for panoramic creation, image classification, or object recognition etc. However, in terrestrial imagery of urban scenes contains various issues, which include duplicate and identical structures (i.e. repeated windows and doors) that cause the problem in feature matching phase and ultimately lead to failure of results specially in case of camera pose and scene structure estimation. In this paper, we will address the issue related to ambiguous feature matching in urban environment due to repeating patterns.

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.

A combined joint diagonalization-MUSIC algorithm for subsurface targets localization

NASA Astrophysics Data System (ADS)

Wang, Yinlin; Sigman, John B.; Barrowes, Benjamin E.; O'Neill, Kevin; Shubitidze, Fridon

2014-06-01

This paper presents a combined joint diagonalization (JD) and multiple signal classification (MUSIC) algorithm for estimating subsurface objects locations from electromagnetic induction (EMI) sensor data, without solving ill-posed inverse-scattering problems. JD is a numerical technique that finds the common eigenvectors that diagonalize a set of multistatic response (MSR) matrices measured by a time-domain EMI sensor. Eigenvalues from targets of interest (TOI) can be then distinguished automatically from noise-related eigenvalues. Filtering is also carried out in JD to improve the signal-to-noise ratio (SNR) of the data. The MUSIC algorithm utilizes the orthogonality between the signal and noise subspaces in the MSR matrix, which can be separated with information provided by JD. An array of theoreticallycalculated Green's functions are then projected onto the noise subspace, and the location of the target is estimated by the minimum of the projection owing to the orthogonality. This combined method is applied to data from the Time-Domain Electromagnetic Multisensor Towed Array Detection System (TEMTADS). Examples of TEMTADS test stand data and field data collected at Spencer Range, Tennessee are analyzed and presented. Results indicate that due to its noniterative mechanism, the method can be executed fast enough to provide real-time estimation of objects' locations in the field.

A robotic orbital emulator with lidar-based SLAM and AMCL for multiple entity pose estimation

NASA Astrophysics Data System (ADS)

Shen, Dan; Xiang, Xingyu; Jia, Bin; Wang, Zhonghai; Chen, Genshe; Blasch, Erik; Pham, Khanh

2018-05-01

This paper revises and evaluates an orbital emulator (OE) for space situational awareness (SSA). The OE can produce 3D satellite movements using capabilities generated from omni-wheeled robot and robotic arm motions. The 3D motion of satellite is partitioned into the movements in the equatorial plane and the up-down motions in the vertical plane. The 3D actions are emulated by omni-wheeled robot models while the up-down motions are performed by a stepped-motorcontrolled- ball along a rod (robotic arm), which is attached to the robot. Lidar only measurements are used to estimate the pose information of the multiple robots. SLAM (simultaneous localization and mapping) is running on one robot to generate the map and compute the pose for the robot. Based on the SLAM map maintained by the robot, the other robots run the adaptive Monte Carlo localization (AMCL) method to estimate their poses. The controller is designed to guide the robot to follow a given orbit. The controllability is analyzed by using a feedback linearization method. Experiments are conducted to show the convergence of AMCL and the orbit tracking performance.

FPGA-based architecture for motion recovering in real-time

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel; Maya-Rueda, Selene E.; Torres-Huitzil, Cesar

2002-03-01

A key problem in the computer vision field is the measurement of object motion in a scene. The main goal is to compute an approximation of the 3D motion from the analysis of an image sequence. Once computed, this information can be used as a basis to reach higher level goals in different applications. Motion estimation algorithms pose a significant computational load for the sequential processors limiting its use in practical applications. In this work we propose a hardware architecture for motion estimation in real time based on FPGA technology. The technique used for motion estimation is Optical Flow due to its accuracy, and the density of velocity estimation, however other techniques are being explored. The architecture is composed of parallel modules working in a pipeline scheme to reach high throughput rates near gigaflops. The modules are organized in a regular structure to provide a high degree of flexibility to cover different applications. Some results will be presented and the real-time performance will be discussed and analyzed. The architecture is prototyped in an FPGA board with a Virtex device interfaced to a digital imager.

Dimensional analyses of frontal posed smile attractiveness in Japanese female patients.

PubMed

Hata, Kyoko; Arai, Kazuhito

2016-01-01

To identify appropriate dimensional items in objective diagnostic analysis for attractiveness of frontal posed smile in Japanese female patients by comparing with the result of human judgments. Photographs of frontal posed smiles of 100 Japanese females after orthodontic treatment were evaluated by 20 dental students (10 males and 10 females) using a visual analogue scale (VAS). The photographs were ranked based on the VAS evaluations and the 25 photographs with the highest evaluations were selected as group A, and the 25 photos with the lowest evaluations were designated group B. Then 12 dimensional items of objective analysis selected from a literature review were measured. Means and standard deviations for measurements of the dimensional items were compared between the groups using the unpaired t-test with a significance level of P < .05. Mean values were significantly smaller in group A than in group B for interlabial gap, intervermilion distance, maxillary gingival display, maximum incisor exposure, and lower lip to incisor (P < .05). Significant differences were observed only in the vertical dimension, not in the transverse dimension. Five of the 12 objective diagnostic items were correlated with human judgments of the attractiveness of frontal posed smile in Japanese females after orthodontic treatment.

Anticancer drugs in Portuguese surface waters - Estimation of concentrations and identification of potentially priority drugs.

PubMed

Santos, Mónica S F; Franquet-Griell, Helena; Lacorte, Silvia; Madeira, Luis M; Alves, Arminda

2017-10-01

Anticancer drugs, used in chemotherapy, have emerged as new water contaminants due to their increasing consumption trends and poor elimination efficiency in conventional water treatment processes. As a result, anticancer drugs have been reported in surface and even drinking waters, posing the environment and human health at risk. However, the occurrence and distribution of anticancer drugs depend on the area studied and the hydrological dynamics, which determine the risk towards the environment. The main objective of the present study was to evaluate the risk of anticancer drugs in Portugal. This work includes an extensive analysis of the consumption trends of 171 anticancer drugs, sold or dispensed in Portugal between 2007 and 2015. The consumption data was processed aiming at the estimation of predicted environmental loads of anticancer drugs and 11 compounds were identified as potentially priority drugs based on an exposure-based approach (PEC b > 10 ng L -1 and/or PEC c > 1 ng L -1 ). In a national perspective, mycophenolic acid and mycophenolate mofetil are suspected to pose high risk to aquatic biota. Moderate and low risk was also associated to cyclophosphamide and bicalutamide exposition, respectively. Although no evidences of risk exist yet for the other anticancer drugs, concerns may be associated with long term effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sensor agnostic object recognition using a map seeking circuit

NASA Astrophysics Data System (ADS)

Overman, Timothy L.; Hart, Michael

2012-05-01

Automatic object recognition capabilities are traditionally tuned to exploit the specific sensing modality they were designed to. Their successes (and shortcomings) are tied to object segmentation from the background, they typically require highly skilled personnel to train them, and they become cumbersome with the introduction of new objects. In this paper we describe a sensor independent algorithm based on the biologically inspired technology of map seeking circuits (MSC) which overcomes many of these obstacles. In particular, the MSC concept offers transparency in object recognition from a common interface to all sensor types, analogous to a USB device. It also provides a common core framework that is independent of the sensor and expandable to support high dimensionality decision spaces. Ease in training is assured by using commercially available 3D models from the video game community. The search time remains linear no matter how many objects are introduced, ensuring rapid object recognition. Here, we report results of an MSC algorithm applied to object recognition and pose estimation from high range resolution radar (1D), electrooptical imagery (2D), and LIDAR point clouds (3D) separately. By abstracting the sensor phenomenology from the underlying a prior knowledge base, MSC shows promise as an easily adaptable tool for incorporating additional sensor inputs.

Solving Navigational Uncertainty Using Grid Cells on Robots

PubMed Central

Milford, Michael J.; Wiles, Janet; Wyeth, Gordon F.

2010-01-01

To successfully navigate their habitats, many mammals use a combination of two mechanisms, path integration and calibration using landmarks, which together enable them to estimate their location and orientation, or pose. In large natural environments, both these mechanisms are characterized by uncertainty: the path integration process is subject to the accumulation of error, while landmark calibration is limited by perceptual ambiguity. It remains unclear how animals form coherent spatial representations in the presence of such uncertainty. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Here we show how conjunctive grid cells in dorsocaudal medial entorhinal cortex (dMEC) may maintain multiple estimates of pose using a brain-based robot navigation system known as RatSLAM. Based both on rodent spatially-responsive cells and functional engineering principles, the cells at the core of the RatSLAM computational model have similar characteristics to rodent grid cells, which we demonstrate by replicating the seminal Moser experiments. We apply the RatSLAM model to a new experimental paradigm designed to examine the responses of a robot or animal in the presence of perceptual ambiguity. Our computational approach enables us to observe short-term population coding of multiple location hypotheses, a phenomenon which would not be easily observable in rodent recordings. We present behavioral and neural evidence demonstrating that the conjunctive grid cells maintain and propagate multiple estimates of pose, enabling the correct pose estimate to be resolved over time even without uniquely identifying cues. While recent research has focused on the grid-like firing characteristics, accuracy and representational capacity of grid cells, our results identify a possible critical and unique role for conjunctive grid cells in filtering sensory uncertainty. We anticipate our study to be a starting point for animal experiments that test navigation in perceptually ambiguous environments. PMID:21085643

A Monocular Vision Measurement System of Three-Degree-of-Freedom Air-Bearing Test-Bed Based on FCCSP

NASA Astrophysics Data System (ADS)

Gao, Zhanyu; Gu, Yingying; Lv, Yaoyu; Xu, Zhenbang; Wu, Qingwen

2018-06-01

A monocular vision-based pose measurement system is provided for real-time measurement of a three-degree-of-freedom (3-DOF) air-bearing test-bed. Firstly, a circular plane cooperative target is designed. An image of a target fixed on the test-bed is then acquired. Blob analysis-based image processing is used to detect the object circles on the target. A fast algorithm (FCCSP) based on pixel statistics is proposed to extract the centers of object circles. Finally, pose measurements can be obtained when combined with the centers and the coordinate transformation relation. Experiments show that the proposed method is fast, accurate, and robust enough to satisfy the requirement of the pose measurement.

Marker detection evaluation by phantom and cadaver experiments for C-arm pose estimation pattern

NASA Astrophysics Data System (ADS)

Steger, Teena; Hoßbach, Martin; Wesarg, Stefan

2013-03-01

C-arm fluoroscopy is used for guidance during several clinical exams, e.g. in bronchoscopy to locate the bronchoscope inside the airways. Unfortunately, these images provide only 2D information. However, if the C-arm pose is known, it can be used to overlay the intrainterventional fluoroscopy images with 3D visualizations of airways, acquired from preinterventional CT images. Thus, the physician's view is enhanced and localization of the instrument at the correct position inside the bronchial tree is facilitated. We present a novel method for C-arm pose estimation introducing a marker-based pattern, which is placed on the patient table. The steel markers form a pattern, allowing to deduce the C-arm pose by use of the projective invariant cross-ratio. Simulations show that the C-arm pose estimation is reliable and accurate for translations inside an imaging area of 30 cm x 50 cm and rotations up to 30°. Mean error values are 0.33 mm in 3D space and 0.48 px in the 2D imaging plane. First tests on C-arm images resulted in similarly compelling accuracy values and high reliability in an imaging area of 30 cm x 42.5 cm. Even in the presence of interfering structures, tested both with anatomy phantoms and a turkey cadaver, high success rates over 90% and fully satisfying execution times below 4 sec for 1024 px × 1024 px images could be achieved.

Model-based elastography: a survey of approaches to the inverse elasticity problem

PubMed Central

Doyley, M M

2012-01-01

Elastography is emerging as an imaging modality that can distinguish normal versus diseased tissues via their biomechanical properties. This article reviews current approaches to elastography in three areas — quasi-static, harmonic, and transient — and describes inversion schemes for each elastographic imaging approach. Approaches include: first-order approximation methods; direct and iterative inversion schemes for linear elastic; isotropic materials; and advanced reconstruction methods for recovering parameters that characterize complex mechanical behavior. The paper’s objective is to document efforts to develop elastography within the framework of solving an inverse problem, so that elastography may provide reliable estimates of shear modulus and other mechanical parameters. We discuss issues that must be addressed if model-based elastography is to become the prevailing approach to quasi-static, harmonic, and transient elastography: (1) developing practical techniques to transform the ill-posed problem with a well-posed one; (2) devising better forward models to capture the transient behavior of soft tissue; and (3) developing better test procedures to evaluate the performance of modulus elastograms. PMID:22222839

Baseline Face Detection, Head Pose Estimation, and Coarse Direction Detection for Facial Data in the SHRP2 Naturalistic Driving Study

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

Paone, Jeffrey R; Bolme, David S; Ferrell, Regina Kay

Keeping a driver focused on the road is one of the most critical steps in insuring the safe operation of a vehicle. The Strategic Highway Research Program 2 (SHRP2) has over 3,100 recorded videos of volunteer drivers during a period of 2 years. This extensive naturalistic driving study (NDS) contains over one million hours of video and associated data that could aid safety researchers in understanding where the driver s attention is focused. Manual analysis of this data is infeasible, therefore efforts are underway to develop automated feature extraction algorithms to process and characterize the data. The real-world nature, volume,more » and acquisition conditions are unmatched in the transportation community, but there are also challenges because the data has relatively low resolution, high compression rates, and differing illumination conditions. A smaller dataset, the head pose validation study, is available which used the same recording equipment as SHRP2 but is more easily accessible with less privacy constraints. In this work we report initial head pose accuracy using commercial and open source face pose estimation algorithms on the head pose validation data set.« less

Moving from pixel to object scale when inverting radiative transfer models for quantitative estimation of biophysical variables in vegetation (Invited)

NASA Astrophysics Data System (ADS)

Atzberger, C.

2013-12-01

The robust and accurate retrieval of vegetation biophysical variables using RTM is seriously hampered by the ill-posedness of the inverse problem. The contribution presents our object-based inversion approach and evaluate it against measured data. The proposed method takes advantage of the fact that nearby pixels are generally more similar than those at a larger distance. For example, within a given vegetation patch, nearby pixels often share similar leaf angular distributions. This leads to spectral co-variations in the n-dimensional spectral features space, which can be used for regularization purposes. Using a set of leaf area index (LAI) measurements (n=26) acquired over alfalfa, sugar beet and garlic crops of the Barrax test site (Spain), it is demonstrated that the proposed regularization using neighbourhood information yields more accurate results compared to the traditional pixel-based inversion. Principle of the ill-posed inverse problem and the proposed solution illustrated in the red-nIR feature space using (PROSAIL). [A] spectral trajectory ('soil trajectory') obtained for one leaf angle (ALA) and one soil brightness (αsoil), when LAI varies between 0 and 10, [B] 'soil trajectories' for 5 soil brightness values and three leaf angles, [C] ill-posed inverse problem: different combinations of ALA × αsoil yield an identical crossing point, [D] object-based RTM inversion; only one 'soil trajectory' fits all nine pixelswithin a gliding (3×3) window. The black dots (plus the rectangle=central pixel) represent the hypothetical position of nine pixels within a 3×3 (gliding) window. Assuming that over short distances (× 1 pixel) variations in soil brightness can be neglected, the proposed object-based inversion searches for one common set of ALA × αsoil so that the resulting 'soil trajectory' best fits the nine measured pixels. Ground measured vs. retrieved LAI values for three crops. Left: proposed object-based approach. Right: pixel-based inversion

Magnetometer-augmented IMU simulator: in-depth elaboration.

PubMed

Brunner, Thomas; Lauffenburger, Jean-Philippe; Changey, Sébastien; Basset, Michel

2015-03-04

The location of objects is a growing research topic due, for instance, to the expansion of civil drones or intelligent vehicles. This expansion was made possible through the development of microelectromechanical systems (MEMS), inexpensive and miniaturized inertial sensors. In this context, this article describes the development of a new simulator which generates sensor measurements, giving a specific input trajectory. This will allow the comparison of pose estimation algorithms. To develop this simulator, the measurement equations of every type of sensor have to be analytically determined. To achieve this objective, classical kinematic equations are used for the more common sensors, i.e., accelerometers and rate gyroscopes. As nowadays, the MEMS inertial measurement units (IMUs) are generally magnetometer-augmented, an absolute world magnetic model is implemented. After the determination of the perfect measurement (through the error-free sensor models), realistic error models are developed to simulate real IMU behavior. Finally, the developed simulator is subjected to different validation tests.

Magnetometer-Augmented IMU Simulator: In-Depth Elaboration

PubMed Central

Brunner, Thomas; Lauffenburger, Jean-Philippe; Changey, Sébastien; Basset, Michel

2015-01-01

The location of objects is a growing research topic due, for instance, to the expansion of civil drones or intelligent vehicles. This expansion was made possible through the development of microelectromechanical systems (MEMS), inexpensive and miniaturized inertial sensors. In this context, this article describes the development of a new simulator which generates sensor measurements, giving a specific input trajectory. This will allow the comparison of pose estimation algorithms. To develop this simulator, the measurement equations of every type of sensor have to be analytically determined. To achieve this objective, classical kinematic equations are used for the more common sensors, i.e., accelerometers and rate gyroscopes. As nowadays, the MEMS inertial measurement units (IMUs) are generally magnetometer-augmented, an absolute world magnetic model is implemented. After the determination of the perfect measurement (through the error-free sensor models), realistic error models are developed to simulate real IMU behavior. Finally, the developed simulator is subjected to different validation tests. PMID:25746095

Robust automatic measurement of 3D scanned models for the human body fat estimation.

PubMed

Giachetti, Andrea; Lovato, Christian; Piscitelli, Francesco; Milanese, Chiara; Zancanaro, Carlo

2015-03-01

In this paper, we present an automatic tool for estimating geometrical parameters from 3-D human scans independent on pose and robustly against the topological noise. It is based on an automatic segmentation of body parts exploiting curve skeleton processing and ad hoc heuristics able to remove problems due to different acquisition poses and body types. The software is able to locate body trunk and limbs, detect their directions, and compute parameters like volumes, areas, girths, and lengths. Experimental results demonstrate that measurements provided by our system on 3-D body scans of normal and overweight subjects acquired in different poses are highly correlated with the body fat estimates obtained on the same subjects with dual-energy X-rays absorptiometry (DXA) scanning. In particular, maximal lengths and girths, not requiring precise localization of anatomical landmarks, demonstrate a good correlation (up to 96%) with the body fat and trunk fat. Regression models based on our automatic measurements can be used to predict body fat values reasonably well.

Robust feature tracking for endoscopic pose estimation and structure recovery

NASA Astrophysics Data System (ADS)

Speidel, S.; Krappe, S.; Röhl, S.; Bodenstedt, S.; Müller-Stich, B.; Dillmann, R.

2013-03-01

Minimally invasive surgery is a highly complex medical discipline with several difficulties for the surgeon. To alleviate these difficulties, augmented reality can be used for intraoperative assistance. For visualization, the endoscope pose must be known which can be acquired with a SLAM (Simultaneous Localization and Mapping) approach using the endoscopic images. In this paper we focus on feature tracking for SLAM in minimally invasive surgery. Robust feature tracking and minimization of false correspondences is crucial for localizing the endoscope. As sensory input we use a stereo endoscope and evaluate different feature types in a developed SLAM framework. The accuracy of the endoscope pose estimation is validated with synthetic and ex vivo data. Furthermore we test the approach with in vivo image sequences from da Vinci interventions.

Model-based Estimation for Pose, Velocity of Projectile from Stereo Linear Array Image

NASA Astrophysics Data System (ADS)

Zhao, Zhuxin; Wen, Gongjian; Zhang, Xing; Li, Deren

2012-01-01

The pose (position and attitude) and velocity of in-flight projectiles have major influence on the performance and accuracy. A cost-effective method for measuring the gun-boosted projectiles is proposed. The method adopts only one linear array image collected by the stereo vision system combining a digital line-scan camera and a mirror near the muzzle. From the projectile's stereo image, the motion parameters (pose and velocity) are acquired by using a model-based optimization algorithm. The algorithm achieves optimal estimation of the parameters by matching the stereo projection of the projectile and that of the same size 3D model. The speed and the AOA (angle of attack) could also be determined subsequently. Experiments are made to test the proposed method.

Effects of radon mitigation vs smoking cessation in reducing radon-related risk of lung cancer.

PubMed Central

Mendez, D; Warner, K E; Courant, P N

1998-01-01

OBJECTIVES: The purpose of this paper is to provide smokers with information on the relative benefits of mitigating radon and quitting smoking in reducing radon-related lung cancer risk. METHODS: The standard radon risk model, linked with models characterizing residential radon exposure and patterns of moving to new homes, was used to estimate the risk reduction produced by remediating high-radon homes, quitting smoking, or both. RESULTS: Quitting smoking reduces lung cancer risk from radon more than does reduction of radon exposure itself. CONCLUSIONS: Smokers should understand that, in addition to producing other health benefits, quitting smoking dominates strategies to deal with the problem posed by radon. PMID:9585753

Correlation Techniques as Applied to Pose Estimation in Space Station Docking

NASA Technical Reports Server (NTRS)

Rollins, J. Michael; Juday, Richard D.; Monroe, Stanley E., Jr.

2002-01-01

The telerobotic assembly of space-station components has become the method of choice for the International Space Station (ISS) because it offers a safe alternative to the more hazardous option of space walks. The disadvantage of telerobotic assembly is that it does not provide for direct arbitrary views of mating interfaces for the teleoperator. Unless cameras are present very close to the interface positions, such views must be generated graphically, based on calculated pose relationships derived from images. To assist in this photogrammetric pose estimation, circular targets, or spots, of high contrast have been affixed on each connecting module at carefully surveyed positions. The appearance of a subset of spots essentially must form a constellation of specific relative positions in the incoming digital image stream in order for the docking to proceed. Spot positions are expressed in terms of their apparent centroids in an image. The precision of centroid estimation is required to be as fine as 1I20th pixel, in some cases. This paper presents an approach to spot centroid estimation using cross correlation between spot images and synthetic spot models of precise centration. Techniques for obtaining sub-pixel accuracy and for shadow, obscuration and lighting irregularity compensation are discussed.

Robust infrared target tracking using discriminative and generative approaches

NASA Astrophysics Data System (ADS)

Asha, C. S.; Narasimhadhan, A. V.

2017-09-01

The process of designing an efficient tracker for thermal infrared imagery is one of the most challenging tasks in computer vision. Although a lot of advancement has been achieved in RGB videos over the decades, textureless and colorless properties of objects in thermal imagery pose hard constraints in the design of an efficient tracker. Tracking of an object using a single feature or a technique often fails to achieve greater accuracy. Here, we propose an effective method to track an object in infrared imagery based on a combination of discriminative and generative approaches. The discriminative technique makes use of two complementary methods such as kernelized correlation filter with spatial feature and AdaBoost classifier with pixel intesity features to operate in parallel. After obtaining optimized locations through discriminative approaches, the generative technique is applied to determine the best target location using a linear search method. Unlike the baseline algorithms, the proposed method estimates the scale of the target by Lucas-Kanade homography estimation. To evaluate the proposed method, extensive experiments are conducted on 17 challenging infrared image sequences obtained from LTIR dataset and a significant improvement of mean distance precision and mean overlap precision is accomplished as compared with the existing trackers. Further, a quantitative and qualitative assessment of the proposed approach with the state-of-the-art trackers is illustrated to clearly demonstrate an overall increase in performance.

Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

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

Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin

Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics

DOE PAGES

Van Aardt, Jan; Romanczyk, Paul; van Leeuwen, Martin; ...

2016-04-04

Terrestrial laser scanning (TLS) has emerged as an effective tool for rapid comprehensive measurement of object structure. Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. However, due to the high dissimilarity of point cloud data collected from disparate viewpoints in the forest environment, adequate marker-free registration approaches have not been developed. The majority of studies instead rely on the utilization of artificial tie points (e.g., reflective tooling balls) placed within a scene to aid in coordinate transformation. We present a technique for generating view-invariant feature descriptors that are intrinsic to the point cloud datamore » and, thus, enable blind marker-free registration in forest environments. To overcome the limitation of initial pose estimation, we employ a voting method to blindly determine the optimal pairwise transformation parameters, without an a priori estimate of the initial sensor pose. To provide embedded error metrics, we developed a set theory framework in which a circular transformation is traversed between disjoint tie point subsets. This provides an upper estimate of the Root Mean Square Error (RMSE) confidence associated with each pairwise transformation. Output RMSE errors are commensurate with the RMSE of input tie points locations. Thus, while the mean output RMSE=16.3cm, improved results could be achieved with a more precise laser scanning system. This study 1) quantifies the RMSE of the proposed marker-free registration approach, 2) assesses the validity of embedded confidence metrics using receiver operator characteristic (ROC) curves, and 3) informs optimal sample spacing considerations for TLS data collection in New England forests. Furthermore, while the implications for rapid, accurate, and precise forest inventory are obvious, the conceptual framework outlined here could potentially be extended to built environments.« less

CAD-model-based vision for space applications

NASA Technical Reports Server (NTRS)

Shapiro, Linda G.

1988-01-01

A pose acquisition system operating in space must be able to perform well in a variety of different applications including automated guidance and inspections tasks with many different, but known objects. Since the space station is being designed with automation in mind, there will be CAD models of all the objects, including the station itself. The construction of vision models and procedures directly from the CAD models is the goal of this project. The system that is being designed and implementing must convert CAD models to vision models, predict visible features from a given view point from the vision models, construct view classes representing views of the objects, and use the view class model thus derived to rapidly determine the pose of the object from single images and/or stereo pairs.

Optical fringe-reflection deflectometry with bundle adjustment

NASA Astrophysics Data System (ADS)

Xiao, Yong-Liang; Li, Sikun; Zhang, Qican; Zhong, Jianxin; Su, Xianyu; You, Zhisheng

2018-06-01

Liquid crystal display (LCD) screens are located outside of a camera's field of view in fringe-reflection deflectometry. Therefore, fringes that are displayed on LCD screens are obtained through specular reflection by a fixed camera. Thus, the pose calibration between the camera and LCD screen is one of the main challenges in fringe-reflection deflectometry. A markerless planar mirror is used to reflect the LCD screen more than three times, and the fringes are mapped into the fixed camera. The geometrical calibration can be accomplished by estimating the pose between the camera and the virtual image of fringes. Considering the relation between their pose, the incidence and reflection rays can be unified in the camera frame, and a forward triangulation intersection can be operated in the camera frame to measure three-dimensional (3D) coordinates of the specular surface. In the final optimization, constraint-bundle adjustment is operated to refine simultaneously the camera intrinsic parameters, including distortion coefficients, estimated geometrical pose between the LCD screen and camera, and 3D coordinates of the specular surface, with the help of the absolute phase collinear constraint. Simulation and experiment results demonstrate that the pose calibration with planar mirror reflection is simple and feasible, and the constraint-bundle adjustment can enhance the 3D coordinate measurement accuracy in fringe-reflection deflectometry.

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

PubMed

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

Motion compensation using origin ensembles in awake small animal positron emission tomography

NASA Astrophysics Data System (ADS)

Gillam, John E.; Angelis, Georgios I.; Kyme, Andre Z.; Meikle, Steven R.

2017-02-01

In emission tomographic imaging, the stochastic origin ensembles algorithm provides unique information regarding the detected counts given the measured data. Precision in both voxel and region-wise parameters may be determined for a single data set based on the posterior distribution of the count density allowing uncertainty estimates to be allocated to quantitative measures. Uncertainty estimates are of particular importance in awake animal neurological and behavioral studies for which head motion, unique for each acquired data set, perturbs the measured data. Motion compensation can be conducted when rigid head pose is measured during the scan. However, errors in pose measurements used for compensation can degrade the data and hence quantitative outcomes. In this investigation motion compensation and detector resolution models were incorporated into the basic origin ensembles algorithm and an efficient approach to computation was developed. The approach was validated against maximum liklihood—expectation maximisation and tested using simulated data. The resultant algorithm was then used to analyse quantitative uncertainty in regional activity estimates arising from changes in pose measurement precision. Finally, the posterior covariance acquired from a single data set was used to describe correlations between regions of interest providing information about pose measurement precision that may be useful in system analysis and design. The investigation demonstrates the use of origin ensembles as a powerful framework for evaluating statistical uncertainty of voxel and regional estimates. While in this investigation rigid motion was considered in the context of awake animal PET, the extension to arbitrary motion may provide clinical utility where respiratory or cardiac motion perturb the measured data.

A Filtering Approach for Image-Guided Surgery With a Highly Articulated Surgical Snake Robot.

PubMed

Tully, Stephen; Choset, Howie

2016-02-01

The objective of this paper is to introduce a probabilistic filtering approach to estimate the pose and internal shape of a highly flexible surgical snake robot during minimally invasive surgery. Our approach renders a depiction of the robot that is registered to preoperatively reconstructed organ models to produce a 3-D visualization that can be used for surgical feedback. Our filtering method estimates the robot shape using an extended Kalman filter that fuses magnetic tracker data with kinematic models that define the motion of the robot. Using Lie derivative analysis, we show that this estimation problem is observable, and thus, the shape and configuration of the robot can be successfully recovered with a sufficient number of magnetic tracker measurements. We validate this study with benchtop and in-vivo image-guidance experiments in which the surgical robot was driven along the epicardial surface of a porcine heart. This paper introduces a filtering approach for shape estimation that can be used for image guidance during minimally invasive surgery. The methods being introduced in this paper enable informative image guidance for highly articulated surgical robots, which benefits the advancement of robotic surgery.

ILIAD Testing; and a Kalman Filter for 3-D Pose Estimation

NASA Technical Reports Server (NTRS)

Richardson, A. O.

1996-01-01

This report presents the results of a two-part project. The first part presents results of performance assessment tests on an Internet Library Information Assembly Data Base (ILIAD). It was found that ILLAD performed best when queries were short (one-to-three keywords), and were made up of rare, unambiguous words. In such cases as many as 64% of the typically 25 returned documents were found to be relevant. It was also found that a query format that was not so rigid with respect to spelling errors and punctuation marks would be more user-friendly. The second part of the report shows the design of a Kalman Filter for estimating motion parameters of a three dimensional object from sequences of noisy data derived from two-dimensional pictures. Given six measured deviation values represendng X, Y, Z, pitch, yaw, and roll, twelve parameters were estimated comprising the six deviations and their time rate of change. Values for the state transiton matrix, the observation matrix, the system noise covariance matrix, and the observation noise covariance matrix were determined. A simple way of initilizing the error covariance matrix was pointed out.

Trajectory-based visual localization in underwater surveying missions.

PubMed

Burguera, Antoni; Bonin-Font, Francisco; Oliver, Gabriel

2015-01-14

We present a new vision-based localization system applied to an autonomous underwater vehicle (AUV) with limited sensing and computation capabilities. The traditional EKF-SLAM approaches are usually expensive in terms of execution time; the approach presented in this paper strengthens this method by adopting a trajectory-based schema that reduces the computational requirements. The pose of the vehicle is estimated using an extended Kalman filter (EKF), which predicts the vehicle motion by means of a visual odometer and corrects these predictions using the data associations (loop closures) between the current frame and the previous ones. One of the most important steps in this procedure is the image registration method, as it reinforces the data association and, thus, makes it possible to close loops reliably. Since the use of standard EKFs entail linearization errors that can distort the vehicle pose estimations, the approach has also been tested using an iterated Kalman filter (IEKF). Experiments have been conducted using a real underwater vehicle in controlled scenarios and in shallow sea waters, showing an excellent performance with very small errors, both in the vehicle pose and in the overall trajectory estimates.

Relevant Scatterers Characterization in SAR Images

NASA Astrophysics Data System (ADS)

Chaabouni, Houda; Datcu, Mihai

2006-11-01

Recognizing scenes in a single look meter resolution Synthetic Aperture Radar (SAR) images, requires the capability to identify relevant signal signatures in condition of variable image acquisition geometry, arbitrary objects poses and configurations. Among the methods to detect relevant scatterers in SAR images, we can mention the internal coherence. The SAR spectrum splitted in azimuth generates a series of images which preserve high coherence only for particular object scattering. The detection of relevant scatterers can be done by correlation study or Independent Component Analysis (ICA) methods. The present article deals with the state of the art for SAR internal correlation analysis and proposes further extensions using elements of inference based on information theory applied to complex valued signals. The set of azimuth looks images is analyzed using mutual information measures and an equivalent channel capacity is derived. The localization of the "target" requires analysis in a small image window, thus resulting in imprecise estimation of the second order statistics of the signal. For a better precision, a Hausdorff measure is introduced. The method is applied to detect and characterize relevant objects in urban areas.

One Shot Detection with Laplacian Object and Fast Matrix Cosine Similarity.

PubMed

Biswas, Sujoy Kumar; Milanfar, Peyman

2016-03-01

One shot, generic object detection involves searching for a single query object in a larger target image. Relevant approaches have benefited from features that typically model the local similarity patterns. In this paper, we combine local similarity (encoded by local descriptors) with a global context (i.e., a graph structure) of pairwise affinities among the local descriptors, embedding the query descriptors into a low dimensional but discriminatory subspace. Unlike principal components that preserve global structure of feature space, we actually seek a linear approximation to the Laplacian eigenmap that permits us a locality preserving embedding of high dimensional region descriptors. Our second contribution is an accelerated but exact computation of matrix cosine similarity as the decision rule for detection, obviating the computationally expensive sliding window search. We leverage the power of Fourier transform combined with integral image to achieve superior runtime efficiency that allows us to test multiple hypotheses (for pose estimation) within a reasonably short time. Our approach to one shot detection is training-free, and experiments on the standard data sets confirm the efficacy of our model. Besides, low computation cost of the proposed (codebook-free) object detector facilitates rather straightforward query detection in large data sets including movie videos.

Tracking Control of Mobile Robots Localized via Chained Fusion of Discrete and Continuous Epipolar Geometry, IMU and Odometry.

PubMed

Tick, David; Satici, Aykut C; Shen, Jinglin; Gans, Nicholas

2013-08-01

This paper presents a novel navigation and control system for autonomous mobile robots that includes path planning, localization, and control. A unique vision-based pose and velocity estimation scheme utilizing both the continuous and discrete forms of the Euclidean homography matrix is fused with inertial and optical encoder measurements to estimate the pose, orientation, and velocity of the robot and ensure accurate localization and control signals. A depth estimation system is integrated in order to overcome the loss of scale inherent in vision-based estimation. A path following control system is introduced that is capable of guiding the robot along a designated curve. Stability analysis is provided for the control system and experimental results are presented that prove the combined localization and control system performs with high accuracy.

A study on facial expressions recognition

NASA Astrophysics Data System (ADS)

Xu, Jingjing

2017-09-01

In terms of communication, postures and facial expressions of such feelings like happiness, anger and sadness play important roles in conveying information. With the development of the technology, recently a number of algorithms dealing with face alignment, face landmark detection, classification, facial landmark localization and pose estimation have been put forward. However, there are a lot of challenges and problems need to be fixed. In this paper, a few technologies have been concluded and analyzed, and they all relate to handling facial expressions recognition and poses like pose-indexed based multi-view method for face alignment, robust facial landmark detection under significant head pose and occlusion, partitioning the input domain for classification, robust statistics face formalization.

The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation

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

Lehoucq, R. B.; Reu, P. L.; Turner, D. Z.

Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.

The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation

DOE PAGES

Lehoucq, R. B.; Reu, P. L.; Turner, D. Z.

2017-11-27

Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.

Solving ill-posed control problems by stabilized finite element methods: an alternative to Tikhonov regularization

NASA Astrophysics Data System (ADS)

Burman, Erik; Hansbo, Peter; Larson, Mats G.

2018-03-01

Tikhonov regularization is one of the most commonly used methods for the regularization of ill-posed problems. In the setting of finite element solutions of elliptic partial differential control problems, Tikhonov regularization amounts to adding suitably weighted least squares terms of the control variable, or derivatives thereof, to the Lagrangian determining the optimality system. In this note we show that the stabilization methods for discretely ill-posed problems developed in the setting of convection-dominated convection-diffusion problems, can be highly suitable for stabilizing optimal control problems, and that Tikhonov regularization will lead to less accurate discrete solutions. We consider some inverse problems for Poisson’s equation as an illustration and derive new error estimates both for the reconstruction of the solution from the measured data and reconstruction of the source term from the measured data. These estimates include both the effect of the discretization error and error in the measurements.

A switched systems approach to image-based estimation

NASA Astrophysics Data System (ADS)

Parikh, Anup

With the advent of technological improvements in imaging systems and computational resources, as well as the development of image-based reconstruction techniques, it is necessary to understand algorithm performance when subject to real world conditions. Specifically, this dissertation focuses on the stability and performance of a class of image-based observers in the presence of intermittent measurements, caused by e.g., occlusions, limited FOV, feature tracking losses, communication losses, or finite frame rates. Observers or filters that are exponentially stable under persistent observability may have unbounded error growth during intermittent sensing, even while providing seemingly accurate state estimates. In Chapter 3, dwell time conditions are developed to guarantee state estimation error convergence to an ultimate bound for a class of observers while undergoing measurement loss. Bounds are developed on the unstable growth of the estimation errors during the periods when the object being tracked is not visible. A Lyapunov-based analysis for the switched system is performed to develop an inequality in terms of the duration of time the observer can view the moving object and the duration of time the object is out of the field of view. In Chapter 4, a motion model is used to predict the evolution of the states of the system while the object is not visible. This reduces the growth rate of the bounding function to an exponential and enables the use of traditional switched systems Lyapunov analysis techniques. The stability analysis results in an average dwell time condition to guarantee state error convergence with a known decay rate. In comparison with the results in Chapter 3, the estimation errors converge to zero rather than a ball, with relaxed switching conditions, at the cost of requiring additional information about the motion of the feature. In some applications, a motion model of the object may not be available. Numerous adaptive techniques have been developed to compensate for unknown parameters or functions in system dynamics; however, persistent excitation (PE) conditions are typically required to ensure parameter convergence, i.e., learning. Since the motion model is needed in the predictor, model learning is desired; however, PE is difficult to insure a priori and infeasible to check online for nonlinear systems. Concurrent learning (CL) techniques have been developed to use recorded data and a relaxed excitation condition to ensure convergence. In CL, excitation is only required for a finite period of time, and the recorded data can be checked to determine if it is sufficiently rich. However, traditional CL requires knowledge of state derivatives, which are typically not measured and require extensive filter design and tuning to develop satisfactory estimates. In Chapter 5 of this dissertation, a novel formulation of CL is developed in terms of an integral (ICL), removing the need to estimate state derivatives while preserving parameter convergence properties. Using ICL, an estimator is developed in Chapter 6 for simultaneously estimating the pose of an object as well as learning a model of its motion for use in a predictor when the object is not visible. A switched systems analysis is provided to demonstrate the stability of the estimation and prediction with learning scheme. Dwell time conditions as well as excitation conditions are developed to ensure estimation errors converge to an arbitrarily small bound. Experimental results are provided to illustrate the performance of each of the developed estimation schemes. The dissertation concludes with a discussion of the contributions and limitations of the developed techniques, as well as avenues for future extensions.

3D Reconstruction of Space Objects from Multi-Views by a Visible Sensor

PubMed Central

Zhang, Haopeng; Wei, Quanmao; Jiang, Zhiguo

2017-01-01

In this paper, a novel 3D reconstruction framework is proposed to recover the 3D structural model of a space object from its multi-view images captured by a visible sensor. Given an image sequence, this framework first estimates the relative camera poses and recovers the depths of the surface points by the structure from motion (SFM) method, then the patch-based multi-view stereo (PMVS) algorithm is utilized to generate a dense 3D point cloud. To resolve the wrong matches arising from the symmetric structure and repeated textures of space objects, a new strategy is introduced, in which images are added to SFM in imaging order. Meanwhile, a refining process exploiting the structural prior knowledge that most sub-components of artificial space objects are composed of basic geometric shapes is proposed and applied to the recovered point cloud. The proposed reconstruction framework is tested on both simulated image datasets and real image datasets. Experimental results illustrate that the recovered point cloud models of space objects are accurate and have a complete coverage of the surface. Moreover, outliers and points with severe noise are effectively filtered out by the refinement, resulting in an distinct improvement of the structure and visualization of the recovered points. PMID:28737675

Orbital debris removal using ground-based lasers

NASA Technical Reports Server (NTRS)

Taylor, Charles R.

1996-01-01

Orbiting the Earth are spent rocket stages, non-functioning satellites, hardware from satellite deployment and staging, fragments of exploded spacecraft, and other relics of decades of space exploration: orbital debris. The United States Space Command tracks and maintains a catalog of the largest objects. The catalog contains over 7000 objects. Recent studies have assessed the debris environment in an effort to estimate the number of smaller particles and the probability of a collision causing catastrophic damage to a functioning spacecraft. The results of the studies can be used to show, for example, that the likelihood of a collision of a particle larger than about one centimeter in diameter with the International Space Station during a 10-year period is a few percent, roughly in agreement with earlier estimates for Space Station Freedom. Particles greater than about one centimeter in diameter pose the greatest risk to shielded spacecraft. There are on the order of 105 such particles in low Earth orbit. The United States National Space Policy, begun in 1988, is to minimize debris consistent with mission requirements. Measures such as venting unused fuel to prevent explosions, retaining staging and deployment hardware, and shielding against smaller debris have been taken by the U.S. and other space faring nations. There is at present no program to remove debris from orbit. The natural tendency for upper atmospheric drag to remove objects from low Earth orbit is more than balanced by the increase in the number of debris objects from new launches and fragmentation of existing objects. In this paper I describe a concept under study by the Program Development Laboratory of Marshall Space Flight Center and others to remove debris with a ground-based laser. A longer version of this report, including figures, is available from the author.

An evaluation of three-dimensional sensors for the extravehicular activity helper/retreiver

NASA Technical Reports Server (NTRS)

Magee, Michael

1993-01-01

The Extravehicular Activity Retriever/Helper (EVAHR) is a robotic device currently under development at the NASA Johnson Space Center that is designed to fetch objects or to assist in retrieving an astronaut who may have become inadvertently de-tethered. The EVAHR will be required to exhibit a high degree of intelligent autonomous operation and will base much of its reasoning upon information obtained from one or more three-dimensional sensors that it will carry and control. At the highest level of visual cognition and reasoning, the EVAHR will be required to detect objects, recognize them, and estimate their spatial orientation and location. The recognition phase and estimation of spatial pose will depend on the ability of the vision system to reliably extract geometric features of the objects such as whether the surface topologies observed are planar or curved and the spatial relationships between the component surfaces. In order to achieve these tasks, accurate sensing of the operational environment and objects in the environment will therefore be critical. The qualitative and quantitative results of empirical studies of three sensors that are capable of providing three-dimensional information to the EVAHR, but using completely different hardware approaches are documented. The first of these devices is a phase shift laser with an effective operating range (ambiguity interval) of approximately 15 meters. The second sensor is a laser triangulation system designed to operate at much closer range and to provide higher resolution images. The third sensor is a dual camera stereo imaging system from which range images can also be obtained. The remainder of the report characterizes the strengths and weaknesses of each of these systems relative to quality of data extracted and how different object characteristics affect sensor operation.

Optimal reentry prediction of space objects from LEO using RSM and GA

NASA Astrophysics Data System (ADS)

Mutyalarao, M.; Raj, M. Xavier James

2012-07-01

The accurate estimation of the orbital life time (OLT) of decaying near-Earth objects is of considerable importance for the prediction of risk object re-entry time and hazard assessment as well as for mitigation strategies. Recently, due to the reentries of large number of risk objects, which poses threat to the human life and property, a great concern is developed in the space scientific community all over the World. The evolution of objects in Low Earth Orbit (LEO) is determined by a complex interplay of the perturbing forces, mainly due to atmospheric drag and Earth gravity. These orbits are mostly in low eccentric (eccentricity < 0.2) and have variations in perigee and apogee altitudes due to perturbations during a revolution. The changes in the perigee and apogee altitudes of these orbits are mainly due to the gravitational perturbations of the Earth and the atmospheric density. It has become necessary to use extremely complex force models to match with the present operational requirements and observational techniques. Further the re-entry time of the objects in such orbits is sensitive to the initial conditions. In this paper the problem of predicting re-entry time is attempted as an optimal estimation problem. It is known that the errors are more in eccentricity for the observations based on two line elements (TLEs). Thus two parameters, initial eccentricity and ballistic coefficient, are chosen for optimal estimation. These two parameters are computed with response surface method (RSM) using a genetic algorithm (GA) for the selected time zones, based on rough linear variation of response parameter, the mean semi-major axis during orbit evolution. Error minimization between the observed and predicted mean Semi-major axis is achieved by the application of an optimization algorithm such as Genetic Algorithm (GA). The basic feature of the present approach is that the model and measurement errors are accountable in terms of adjusting the ballistic coefficient and eccentricity. The methodology is tested with the recently reentered objects ROSAT and PHOBOS GRUNT satellites. The study reveals a good agreement with the actual reentry time of these objects. It is also observed that the absolute percentage error in re-entry prediction time for all the two objects is found to be very less. Keywords: low eccentric, Response surface method, Genetic algorithm, apogee altitude, Ballistic coefficient

Learning-Based Object Identification and Segmentation Using Dual-Energy CT Images for Security.

PubMed

Martin, Limor; Tuysuzoglu, Ahmet; Karl, W Clem; Ishwar, Prakash

2015-11-01

In recent years, baggage screening at airports has included the use of dual-energy X-ray computed tomography (DECT), an advanced technology for nondestructive evaluation. The main challenge remains to reliably find and identify threat objects in the bag from DECT data. This task is particularly hard due to the wide variety of objects, the high clutter, and the presence of metal, which causes streaks and shading in the scanner images. Image noise and artifacts are generally much more severe than in medical CT and can lead to splitting of objects and inaccurate object labeling. The conventional approach performs object segmentation and material identification in two decoupled processes. Dual-energy information is typically not used for the segmentation, and object localization is not explicitly used to stabilize the material parameter estimates. We propose a novel learning-based framework for joint segmentation and identification of objects directly from volumetric DECT images, which is robust to streaks, noise and variability due to clutter. We focus on segmenting and identifying a small set of objects of interest with characteristics that are learned from training images, and consider everything else as background. We include data weighting to mitigate metal artifacts and incorporate an object boundary field to reduce object splitting. The overall formulation is posed as a multilabel discrete optimization problem and solved using an efficient graph-cut algorithm. We test the method on real data and show its potential for producing accurate labels of the objects of interest without splits in the presence of metal and clutter.

Estimation of Full-Body Poses Using Only Five Inertial Sensors: An Eager or Lazy Learning Approach?

PubMed Central

Wouda, Frank J.; Giuberti, Matteo; Bellusci, Giovanni; Veltink, Peter H.

2016-01-01

Human movement analysis has become easier with the wide availability of motion capture systems. Inertial sensing has made it possible to capture human motion without external infrastructure, therefore allowing measurements in any environment. As high-quality motion capture data is available in large quantities, this creates possibilities to further simplify hardware setups, by use of data-driven methods to decrease the number of body-worn sensors. In this work, we contribute to this field by analyzing the capabilities of using either artificial neural networks (eager learning) or nearest neighbor search (lazy learning) for such a problem. Sparse orientation features, resulting from sensor fusion of only five inertial measurement units with magnetometers, are mapped to full-body poses. Both eager and lazy learning algorithms are shown to be capable of constructing this mapping. The full-body output poses are visually plausible with an average joint position error of approximately 7 cm, and average joint angle error of 7∘. Additionally, the effects of magnetic disturbances typical in orientation tracking on the estimation of full-body poses was also investigated, where nearest neighbor search showed better performance for such disturbances. PMID:27983676

Estimation of Full-Body Poses Using Only Five Inertial Sensors: An Eager or Lazy Learning Approach?

PubMed

Wouda, Frank J; Giuberti, Matteo; Bellusci, Giovanni; Veltink, Peter H

2016-12-15

Human movement analysis has become easier with the wide availability of motion capture systems. Inertial sensing has made it possible to capture human motion without external infrastructure, therefore allowing measurements in any environment. As high-quality motion capture data is available in large quantities, this creates possibilities to further simplify hardware setups, by use of data-driven methods to decrease the number of body-worn sensors. In this work, we contribute to this field by analyzing the capabilities of using either artificial neural networks (eager learning) or nearest neighbor search (lazy learning) for such a problem. Sparse orientation features, resulting from sensor fusion of only five inertial measurement units with magnetometers, are mapped to full-body poses. Both eager and lazy learning algorithms are shown to be capable of constructing this mapping. The full-body output poses are visually plausible with an average joint position error of approximately 7 cm, and average joint angle error of 7 ∘ . Additionally, the effects of magnetic disturbances typical in orientation tracking on the estimation of full-body poses was also investigated, where nearest neighbor search showed better performance for such disturbances.

A customized vision system for tracking humans wearing reflective safety clothing from industrial vehicles and machinery.

PubMed

Mosberger, Rafael; Andreasson, Henrik; Lilienthal, Achim J

2014-09-26

This article presents a novel approach for vision-based detection and tracking of humans wearing high-visibility clothing with retro-reflective markers. Addressing industrial applications where heavy vehicles operate in the vicinity of humans, we deploy a customized stereo camera setup with active illumination that allows for efficient detection of the reflective patterns created by the worker's safety garments. After segmenting reflective objects from the image background, the interest regions are described with local image feature descriptors and classified in order to discriminate safety garments from other reflective objects in the scene. In a final step, the trajectories of the detected humans are estimated in 3D space relative to the camera. We evaluate our tracking system in two industrial real-world work environments on several challenging video sequences. The experimental results indicate accurate tracking performance and good robustness towards partial occlusions, body pose variation, and a wide range of different illumination conditions.

A Customized Vision System for Tracking Humans Wearing Reflective Safety Clothing from Industrial Vehicles and Machinery

PubMed Central

Mosberger, Rafael; Andreasson, Henrik; Lilienthal, Achim J.

2014-01-01

This article presents a novel approach for vision-based detection and tracking of humans wearing high-visibility clothing with retro-reflective markers. Addressing industrial applications where heavy vehicles operate in the vicinity of humans, we deploy a customized stereo camera setup with active illumination that allows for efficient detection of the reflective patterns created by the worker's safety garments. After segmenting reflective objects from the image background, the interest regions are described with local image feature descriptors and classified in order to discriminate safety garments from other reflective objects in the scene. In a final step, the trajectories of the detected humans are estimated in 3D space relative to the camera. We evaluate our tracking system in two industrial real-world work environments on several challenging video sequences. The experimental results indicate accurate tracking performance and good robustness towards partial occlusions, body pose variation, and a wide range of different illumination conditions. PMID:25264956

Inverse statistical estimation via order statistics: a resolution of the ill-posed inverse problem of PERT scheduling

NASA Astrophysics Data System (ADS)

Pickard, William F.

2004-10-01

The classical PERT inverse statistics problem requires estimation of the mean, \\skew1\\bar{m} , and standard deviation, s, of a unimodal distribution given estimates of its mode, m, and of the smallest, a, and largest, b, values likely to be encountered. After placing the problem in historical perspective and showing that it is ill-posed because it is underdetermined, this paper offers an approach to resolve the ill-posedness: (a) by interpreting a and b modes of order statistic distributions; (b) by requiring also an estimate of the number of samples, N, considered in estimating the set {m, a, b}; and (c) by maximizing a suitable likelihood, having made the traditional assumption that the underlying distribution is beta. Exact formulae relating the four parameters of the beta distribution to {m, a, b, N} and the assumed likelihood function are then used to compute the four underlying parameters of the beta distribution; and from them, \\skew1\\bar{m} and s are computed using exact formulae.

Analyzing costs of space debris mitigation methods

NASA Astrophysics Data System (ADS)

Wiedemann, C.; Krag, H.; Bendisch, J.; Sdunnus, H.

2004-01-01

The steadily increasing number of space objects poses a considerable hazard to all kinds of spacecraft. To reduce the risks to future space missions different debris mitigation measures and spacecraft protection techniques have been investigated during the last years. However, the economic efficiency has not been considered yet in this context. Current studies have the objective to evaluate the mission costs due to space debris in a business as usual (no mitigation) scenario compared to the missions costs considering debris mitigation. The aim is an estimation of the time until the investment in debris mitigation will lead to an effective reduction of mission costs. This paper presents the results of investigations on the key issues of cost estimation for spacecraft and the influence of debris mitigation and shielding on cost. Mitigation strategies like the reduction of orbital lifetime and de- or re-orbit of non-operational satellites are methods to control the space debris environment. These methods result in an increase of costs. In a first step the overall costs of different types of unmanned satellites are analyzed. A selected cost model is simplified and generalized for an application on all operational satellites. In a next step the influence of space debris on cost is treated, if the implementation of mitigation strategies is considered.

An integrated approach to endoscopic instrument tracking for augmented reality applications in surgical simulation training.

PubMed

Loukas, Constantinos; Lahanas, Vasileios; Georgiou, Evangelos

2013-12-01

Despite the popular use of virtual and physical reality simulators in laparoscopic training, the educational potential of augmented reality (AR) has not received much attention. A major challenge is the robust tracking and three-dimensional (3D) pose estimation of the endoscopic instrument, which are essential for achieving interaction with the virtual world and for realistic rendering when the virtual scene is occluded by the instrument. In this paper we propose a method that addresses these issues, based solely on visual information obtained from the endoscopic camera. Two different tracking algorithms are combined for estimating the 3D pose of the surgical instrument with respect to the camera. The first tracker creates an adaptive model of a colour strip attached to the distal part of the tool (close to the tip). The second algorithm tracks the endoscopic shaft, using a combined Hough-Kalman approach. The 3D pose is estimated with perspective geometry, using appropriate measurements extracted by the two trackers. The method has been validated on several complex image sequences for its tracking efficiency, pose estimation accuracy and applicability in AR-based training. Using a standard endoscopic camera, the absolute average error of the tip position was 2.5 mm for working distances commonly found in laparoscopic training. The average error of the instrument's angle with respect to the camera plane was approximately 2°. The results are also supplemented by video segments of laparoscopic training tasks performed in a physical and an AR environment. The experiments yielded promising results regarding the potential of applying AR technologies for laparoscopic skills training, based on a computer vision framework. The issue of occlusion handling was adequately addressed. The estimated trajectory of the instruments may also be used for surgical gesture interpretation and assessment. Copyright © 2013 John Wiley & Sons, Ltd.

Three-dimensional face pose detection and tracking using monocular videos: tool and application.

PubMed

Dornaika, Fadi; Raducanu, Bogdan

2009-08-01

Recently, we have proposed a real-time tracker that simultaneously tracks the 3-D head pose and facial actions in monocular video sequences that can be provided by low quality cameras. This paper has two main contributions. First, we propose an automatic 3-D face pose initialization scheme for the real-time tracker by adopting a 2-D face detector and an eigenface system. Second, we use the proposed methods-the initialization and tracking-for enhancing the human-machine interaction functionality of an AIBO robot. More precisely, we show how the orientation of the robot's camera (or any active vision system) can be controlled through the estimation of the user's head pose. Applications based on head-pose imitation such as telepresence, virtual reality, and video games can directly exploit the proposed techniques. Experiments on real videos confirm the robustness and usefulness of the proposed methods.

Second Iteration of Photogrammetric Pipeline to Enhance the Accuracy of Image Pose Estimation

NASA Astrophysics Data System (ADS)

Nguyen, T. G.; Pierrot-Deseilligny, M.; Muller, J.-M.; Thom, C.

2017-05-01

In classical photogrammetric processing pipeline, the automatic tie point extraction plays a key role in the quality of achieved results. The image tie points are crucial to pose estimation and have a significant influence on the precision of calculated orientation parameters. Therefore, both relative and absolute orientations of the 3D model can be affected. By improving the precision of image tie point measurement, one can enhance the quality of image orientation. The quality of image tie points is under the influence of several factors such as the multiplicity, the measurement precision and the distribution in 2D images as well as in 3D scenes. In complex acquisition scenarios such as indoor applications and oblique aerial images, tie point extraction is limited while only image information can be exploited. Hence, we propose here a method which improves the precision of pose estimation in complex scenarios by adding a second iteration to the classical processing pipeline. The result of a first iteration is used as a priori information to guide the extraction of new tie points with better quality. Evaluated with multiple case studies, the proposed method shows its validity and its high potiential for precision improvement.

Estimating ecological integrity in the interior Columbia River basin.

Treesearch

Thomas M. Quigley; Richard W. Haynes; Wendel J. Hann

2001-01-01

The adoption of ecosystem-based management strategies focuses attention on the need for broad scale estimates of ecological conditions; this poses two challenges for the science community: estimating broad scale ecosystem conditions from highly disparate data, often observed at different spatial scales, and interpreting these conditions relative to goals such as...

Advanced human machine interaction for an image interpretation workstation

NASA Astrophysics Data System (ADS)

Maier, S.; Martin, M.; van de Camp, F.; Peinsipp-Byma, E.; Beyerer, J.

2016-05-01

In recent years, many new interaction technologies have been developed that enhance the usability of computer systems and allow for novel types of interaction. The areas of application for these technologies have mostly been in gaming and entertainment. However, in professional environments, there are especially demanding tasks that would greatly benefit from improved human machine interfaces as well as an overall improved user experience. We, therefore, envisioned and built an image-interpretation-workstation of the future, a multi-monitor workplace comprised of four screens. Each screen is dedicated to a complex software product such as a geo-information system to provide geographic context, an image annotation tool, software to generate standardized reports and a tool to aid in the identification of objects. Using self-developed systems for hand tracking, pointing gestures and head pose estimation in addition to touchscreens, face identification, and speech recognition systems we created a novel approach to this complex task. For example, head pose information is used to save the position of the mouse cursor on the currently focused screen and to restore it as soon as the same screen is focused again while hand gestures allow for intuitive manipulation of 3d objects in mid-air. While the primary focus is on the task of image interpretation, all of the technologies involved provide generic ways of efficiently interacting with a multi-screen setup and could be utilized in other fields as well. In preliminary experiments, we received promising feedback from users in the military and started to tailor the functionality to their needs

Boundary conditions estimation on a road network using compressed sensing.

DOT National Transportation Integrated Search

2016-02-01

This report presents a new boundary condition estimation framework for transportation networks in which : the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a : Hamilton-Jacobi equation, we pose th...

Enhancement Strategies for Frame-To Uas Stereo Visual Odometry

NASA Astrophysics Data System (ADS)

Kersten, J.; Rodehorst, V.

2016-06-01

Autonomous navigation of indoor unmanned aircraft systems (UAS) requires accurate pose estimations usually obtained from indirect measurements. Navigation based on inertial measurement units (IMU) is known to be affected by high drift rates. The incorporation of cameras provides complementary information due to the different underlying measurement principle. The scale ambiguity problem for monocular cameras is avoided when a light-weight stereo camera setup is used. However, also frame-to-frame stereo visual odometry (VO) approaches are known to accumulate pose estimation errors over time. Several valuable real-time capable techniques for outlier detection and drift reduction in frame-to-frame VO, for example robust relative orientation estimation using random sample consensus (RANSAC) and bundle adjustment, are available. This study addresses the problem of choosing appropriate VO components. We propose a frame-to-frame stereo VO method based on carefully selected components and parameters. This method is evaluated regarding the impact and value of different outlier detection and drift-reduction strategies, for example keyframe selection and sparse bundle adjustment (SBA), using reference benchmark data as well as own real stereo data. The experimental results demonstrate that our VO method is able to estimate quite accurate trajectories. Feature bucketing and keyframe selection are simple but effective strategies which further improve the VO results. Furthermore, introducing the stereo baseline constraint in pose graph optimization (PGO) leads to significant improvements.

Smile line assessment comparing quantitative measurement and visual estimation.

PubMed

Van der Geld, Pieter; Oosterveld, Paul; Schols, Jan; Kuijpers-Jagtman, Anne Marie

2011-02-01

Esthetic analysis of dynamic functions such as spontaneous smiling is feasible by using digital videography and computer measurement for lip line height and tooth display. Because quantitative measurements are time-consuming, digital videography and semiquantitative (visual) estimation according to a standard categorization are more practical for regular diagnostics. Our objective in this study was to compare 2 semiquantitative methods with quantitative measurements for reliability and agreement. The faces of 122 male participants were individually registered by using digital videography. Spontaneous and posed smiles were captured. On the records, maxillary lip line heights and tooth display were digitally measured on each tooth and also visually estimated according to 3-grade and 4-grade scales. Two raters were involved. An error analysis was performed. Reliability was established with kappa statistics. Interexaminer and intraexaminer reliability values were high, with median kappa values from 0.79 to 0.88. Agreement of the 3-grade scale estimation with quantitative measurement showed higher median kappa values (0.76) than the 4-grade scale estimation (0.66). Differentiating high and gummy smile lines (4-grade scale) resulted in greater inaccuracies. The estimation of a high, average, or low smile line for each tooth showed high reliability close to quantitative measurements. Smile line analysis can be performed reliably with a 3-grade scale (visual) semiquantitative estimation. For a more comprehensive diagnosis, additional measuring is proposed, especially in patients with disproportional gingival display. Copyright © 2011 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Pose-Invariant Face Recognition via RGB-D Images.

PubMed

Sang, Gaoli; Li, Jing; Zhao, Qijun

2016-01-01

Three-dimensional (3D) face models can intrinsically handle large pose face recognition problem. In this paper, we propose a novel pose-invariant face recognition method via RGB-D images. By employing depth, our method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images in the gallery can be rendered to the same view as the probe via depth. Meanwhile, depth is also used for similarity measure via frontalization and symmetric filling. Finally, both texture and depth contribute to the final identity estimation. Experiments on Bosphorus, CurtinFaces, Eurecom, and Kiwi databases demonstrate that the additional depth information has improved the performance of face recognition with large pose variations and under even more challenging conditions.

Evocative Objects: Reflections on Teaching, Learning, and Living in between

ERIC Educational Resources Information Center

Hesse, Doug; Sommers, Nancy; Yancey, Kathleen Blake

2012-01-01

Objects are rich sources of inquiry; they invite individuals to observe closely, pose questions, forge connections, and anchor ideas in the concrete. By examining a son's craft project, a family photograph, and an image of tectonic plates, the authors demonstrate how objects can elicit rhetorical invention. While this venture started as a writing…

Aquatic concentrations of chemical analytes compared to ecotoxicity estimates

EPA Science Inventory

We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part of a joint USGS/USEPA drinking water plant study. Measured concentrations were compared to biological effect concent...

Evaluation of Fuel Oxygenate Degradation in the Vadose Zone

DTIC Science & Technology

2005-03-01

Goltz (Member) date AFIT/GES/ENV/05M-05 Abstract Groundwater contamination by petroleum products poses a potential human health...this experiment. The column porosity was estimated from work conducted by a contractor, Jason Lach. An estimate of the column soil porosity

Sparse Unorganized Point Cloud Based Relative Pose Estimation for Uncooperative Space Target.

PubMed

Yin, Fang; Chou, Wusheng; Wu, Yun; Yang, Guang; Xu, Song

2018-03-28

This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method.

Sparse Unorganized Point Cloud Based Relative Pose Estimation for Uncooperative Space Target

PubMed Central

Chou, Wusheng; Wu, Yun; Yang, Guang; Xu, Song

2018-01-01

This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method. PMID:29597323

Robustly Aligning a Shape Model and Its Application to Car Alignment of Unknown Pose.

PubMed

Li, Yan; Gu, Leon; Kanade, Takeo

2011-09-01

Precisely localizing in an image a set of feature points that form a shape of an object, such as car or face, is called alignment. Previous shape alignment methods attempted to fit a whole shape model to the observed data, based on the assumption of Gaussian observation noise and the associated regularization process. However, such an approach, though able to deal with Gaussian noise in feature detection, turns out not to be robust or precise because it is vulnerable to gross feature detection errors or outliers resulting from partial occlusions or spurious features from the background or neighboring objects. We address this problem by adopting a randomized hypothesis-and-test approach. First, a Bayesian inference algorithm is developed to generate a shape-and-pose hypothesis of the object from a partial shape or a subset of feature points. For alignment, a large number of hypotheses are generated by randomly sampling subsets of feature points, and then evaluated to find the one that minimizes the shape prediction error. This method of randomized subset-based matching can effectively handle outliers and recover the correct object shape. We apply this approach on a challenging data set of over 5,000 different-posed car images, spanning a wide variety of car types, lighting, background scenes, and partial occlusions. Experimental results demonstrate favorable improvements over previous methods on both accuracy and robustness.

Deep Learning for Computer Vision: A Brief Review

PubMed Central

Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

2018-01-01

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein. PMID:29487619

Real-time classification of vehicles by type within infrared imagery

NASA Astrophysics Data System (ADS)

Kundegorski, Mikolaj E.; Akçay, Samet; Payen de La Garanderie, Grégoire; Breckon, Toby P.

2016-10-01

Real-time classification of vehicles into sub-category types poses a significant challenge within infra-red imagery due to the high levels of intra-class variation in thermal vehicle signatures caused by aspects of design, current operating duration and ambient thermal conditions. Despite these challenges, infra-red sensing offers significant generalized target object detection advantages in terms of all-weather operation and invariance to visual camouflage techniques. This work investigates the accuracy of a number of real-time object classification approaches for this task within the wider context of an existing initial object detection and tracking framework. Specifically we evaluate the use of traditional feature-driven bag of visual words and histogram of oriented gradient classification approaches against modern convolutional neural network architectures. Furthermore, we use classical photogrammetry, within the context of current target detection and classification techniques, as a means of approximating 3D target position within the scene based on this vehicle type classification. Based on photogrammetric estimation of target position, we then illustrate the use of regular Kalman filter based tracking operating on actual 3D vehicle trajectories. Results are presented using a conventional thermal-band infra-red (IR) sensor arrangement where targets are tracked over a range of evaluation scenarios.

Robust image features: concentric contrasting circles and their image extraction

NASA Astrophysics Data System (ADS)

Gatrell, Lance B.; Hoff, William A.; Sklair, Cheryl W.

1992-03-01

Many computer vision tasks can be simplified if special image features are placed on the objects to be recognized. A review of special image features that have been used in the past is given and then a new image feature, the concentric contrasting circle, is presented. The concentric contrasting circle image feature has the advantages of being easily manufactured, easily extracted from the image, robust extraction (true targets are found, while few false targets are found), it is a passive feature, and its centroid is completely invariant to the three translational and one rotational degrees of freedom and nearly invariant to the remaining two rotational degrees of freedom. There are several examples of existing parallel implementations which perform most of the extraction work. Extraction robustness was measured by recording the probability of correct detection and the false alarm rate in a set of images of scenes containing mockups of satellites, fluid couplings, and electrical components. A typical application of concentric contrasting circle features is to place them on modeled objects for monocular pose estimation or object identification. This feature is demonstrated on a visually challenging background of a specular but wrinkled surface similar to a multilayered insulation spacecraft thermal blanket.

An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation

PubMed Central

He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

2015-01-01

Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions. PMID:26184191

An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation.

PubMed

He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

2015-07-08

Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions.

Hardware in the Loop Performance Assessment of LIDAR-Based Spacecraft Pose Determination

PubMed Central

Fasano, Giancarmine; Grassi, Michele

2017-01-01

In this paper an original, easy to reproduce, semi-analytic calibration approach is developed for hardware-in-the-loop performance assessment of pose determination algorithms processing point cloud data, collected by imaging a non-cooperative target with LIDARs. The laboratory setup includes a scanning LIDAR, a monocular camera, a scaled-replica of a satellite-like target, and a set of calibration tools. The point clouds are processed by uncooperative model-based algorithms to estimate the target relative position and attitude with respect to the LIDAR. Target images, acquired by a monocular camera operated simultaneously with the LIDAR, are processed applying standard solutions to the Perspective-n-Points problem to get high-accuracy pose estimates which can be used as a benchmark to evaluate the accuracy attained by the LIDAR-based techniques. To this aim, a precise knowledge of the extrinsic relative calibration between the camera and the LIDAR is essential, and it is obtained by implementing an original calibration approach which does not need ad-hoc homologous targets (e.g., retro-reflectors) easily recognizable by the two sensors. The pose determination techniques investigated by this work are of interest to space applications involving close-proximity maneuvers between non-cooperative platforms, e.g., on-orbit servicing and active debris removal. PMID:28946651

Hardware in the Loop Performance Assessment of LIDAR-Based Spacecraft Pose Determination.

PubMed

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2017-09-24

In this paper an original, easy to reproduce, semi-analytic calibration approach is developed for hardware-in-the-loop performance assessment of pose determination algorithms processing point cloud data, collected by imaging a non-cooperative target with LIDARs. The laboratory setup includes a scanning LIDAR, a monocular camera, a scaled-replica of a satellite-like target, and a set of calibration tools. The point clouds are processed by uncooperative model-based algorithms to estimate the target relative position and attitude with respect to the LIDAR. Target images, acquired by a monocular camera operated simultaneously with the LIDAR, are processed applying standard solutions to the Perspective- n -Points problem to get high-accuracy pose estimates which can be used as a benchmark to evaluate the accuracy attained by the LIDAR-based techniques. To this aim, a precise knowledge of the extrinsic relative calibration between the camera and the LIDAR is essential, and it is obtained by implementing an original calibration approach which does not need ad-hoc homologous targets (e.g., retro-reflectors) easily recognizable by the two sensors. The pose determination techniques investigated by this work are of interest to space applications involving close-proximity maneuvers between non-cooperative platforms, e.g., on-orbit servicing and active debris removal.

Methodology for an occupational risk assessment: an evaluation of four processes for the fabrication of photovoltaic cells.

PubMed

Ungers, L J; Moskowitz, P D; Owens, T W; Harmon, A D; Briggs, T M

1982-02-01

Determining occupational health and safety risks posed by emerging technologies is difficult because of limited statistics. Nevertheless, estimates of such risks must be constructed to permit comparison of various technologies to identify the most attractive processes. One way to estimate risks is to use statistics on related industries. Based on process labor requirements and associated occupational health data, risks to workers and to society posed by an emerging technology can be calculated. Using data from the California semiconductor industry, this study applies a five-step occupational risk assessment procedure to four processes for the fabrication of photovoltaic cells. The validity of the occupational risk assessment method is discussed.

Landmark based localization in urban environment

NASA Astrophysics Data System (ADS)

Qu, Xiaozhi; Soheilian, Bahman; Paparoditis, Nicolas

2018-06-01

A landmark based localization with uncertainty analysis based on cameras and geo-referenced landmarks is presented in this paper. The system is developed to adapt different camera configurations for six degree-of-freedom pose estimation. Local bundle adjustment is applied for optimization and the geo-referenced landmarks are integrated to reduce the drift. In particular, the uncertainty analysis is taken into account. On the one hand, we estimate the uncertainties of poses to predict the precision of localization. On the other hand, uncertainty propagation is considered for matching, tracking and landmark registering. The proposed method is evaluated on both KITTI benchmark and the data acquired by a mobile mapping system. In our experiments, decimeter level accuracy can be reached.

New Data from EPA's Exposure Forecasting (ExpoCast) Project (ISES meeting)

EPA Science Inventory

The health risks posed by the chemicals in our environment depends on both chemical hazard and exposure. However, relatively few chemicals have estimates of exposure intake, limiting risk estimations for thousands of chemicals. The U.S. EPA Exposure Forecasting (ExpoCast) projec...

Thoughts on Improvable Objects, Contradiction and Object/Tool Reciprocity in a Study of Zoo Educator Professional Development

ERIC Educational Resources Information Center

Ash, Doris B.; Kelly, Lisa-Anne DeGregoria

2013-01-01

In this forum we discuss three aspects designed to clarify and extend Kelly and Kassing's paper. These are the roles of improvable objects, contradiction and object/tool reciprocity. In each case we cite relevant literature and pose questions to the field. Our goal is to seed ideas for future discussions concerning the role of activity theory…

Quantifying roadside assessment for highway safety.

DOT National Transportation Integrated Search

2017-09-01

Many of Kentuckys two-lane rural roads pose an above average risk for fixed object crashes. In Kentucky, run-off-road (ROR) collisions with fixed objects account for 18.9% of all crashes and 41.6% of fatal crashes. Accordingly, ROR crashes are a s...

Make Task Constraints Work for You: Teaching Object-Control Skills to Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Colombo-Dougovito, Andrew M.; Block, Martin

2016-01-01

Teaching object-control skills to students with autism spectrum disorder (ASD) can be difficult due to the unique challenges posed by the individual; however, it is necessary for the students' future success and ability to perform physical activities. Utilizing concepts from dynamic systems theory and Newell's constraint approach, object-control…

Comparison of different methods for gender estimation from face image of various poses

NASA Astrophysics Data System (ADS)

Ishii, Yohei; Hongo, Hitoshi; Niwa, Yoshinori; Yamamoto, Kazuhiko

2003-04-01

Recently, gender estimation from face images has been studied for frontal facial images. However, it is difficult to obtain such facial images constantly in the case of application systems for security, surveillance and marketing research. In order to build such systems, a method is required to estimate gender from the image of various facial poses. In this paper, three different classifiers are compared in appearance-based gender estimation, which use four directional features (FDF). The classifiers are linear discriminant analysis (LDA), Support Vector Machines (SVMs) and Sparse Network of Winnows (SNoW). Face images used for experiments were obtained from 35 viewpoints. The direction of viewpoints varied +/-45 degrees horizontally, +/-30 degrees vertically at 15 degree intervals respectively. Although LDA showed the best performance for frontal facial images, SVM with Gaussian kernel was found the best performance (86.0%) for the facial images of 35 viewpoints. It is considered that SVM with Gaussian kernel is robust to changes in viewpoint when estimating gender from these results. Furthermore, the estimation rate was quite close to the average estimation rate at 35 viewpoints respectively. It is supposed that the methods are reasonable to estimate gender within the range of experimented viewpoints by learning face images from multiple directions by one class.

Combining facial dynamics with appearance for age estimation.

PubMed

Dibeklioglu, Hamdi; Alnajar, Fares; Ali Salah, Albert; Gevers, Theo

2015-06-01

Estimating the age of a human from the captured images of his/her face is a challenging problem. In general, the existing approaches to this problem use appearance features only. In this paper, we show that in addition to appearance information, facial dynamics can be leveraged in age estimation. We propose a method to extract and use dynamic features for age estimation, using a person's smile. Our approach is tested on a large, gender-balanced database with 400 subjects, with an age range between 8 and 76. In addition, we introduce a new database on posed disgust expressions with 324 subjects in the same age range, and evaluate the reliability of the proposed approach when used with another expression. State-of-the-art appearance-based age estimation methods from the literature are implemented as baseline. We demonstrate that for each of these methods, the addition of the proposed dynamic features results in statistically significant improvement. We further propose a novel hierarchical age estimation architecture based on adaptive age grouping. We test our approach extensively, including an exploration of spontaneous versus posed smile dynamics, and gender-specific age estimation. We show that using spontaneity information reduces the mean absolute error by up to 21%, advancing the state of the art for facial age estimation.

Wheelchair pushing and turning: lumbar spine and shoulder loads and recommended limits.

PubMed

Weston, Eric B; Khan, Safdar N; Marras, William S

2017-12-01

The objective of this study was to determine how simulated manual wheelchair pushing influences biomechanical loading to the lumbar spine and shoulders. Sixty-two subjects performed simulated wheelchair pushing and turning in a laboratory. An electromyography-assisted biomechanical model was used to estimate spinal loads. Moments at the shoulder joint, external hand forces and net turning torque were also assessed. Multiple linear regression techniques were employed to develop biomechanically based wheelchair pushing guidelines relating resultant hand force or net torque to spinal load. Male subjects experienced significantly greater spinal loading (p < 0.01), and spine loads were also increased for wheelchair turning compared to straight wheelchair pushing (p < 0.001). Biomechanically determined maximum acceptable resultant hand forces were 17-18% lower than psychophysically determined limits. We conclude that manual wheelchair pushing and turning can pose biomechanical risk to the lumbar spine and shoulders. Psychophysically determined maximum acceptable push forces do not appear to be protective enough of this biomechanical risk. Practitioner Summary: This laboratory study investigated biomechanical risk to the low back and shoulders during simulated wheelchair pushing. Manual wheelchair pushing posed biomechanical risk to the lumbar spine (in compression and A/P shear) and to the shoulders. Biomechanically determined wheelchair pushing thresholds are presented and are more protective than the closest psychophysically determined equivalents.

Evolutionary Initial Poses of Reduced D.O.F’s Quadruped Robot

NASA Astrophysics Data System (ADS)

Iida, Ken-Ichi; Nakata, Yoshitaka; Hira, Toshio; Kamano, Takuya; Suzuki, Takayuki

In this paper, an application of genetic algorithm for generation of evolutionary initial poses of a quadrupedal robot which reduced degrees of freedom is described. To reduce degree of freedom, each leg of the robot has a slider-crank mechanism and is driven by an actuator. Furthermore we introduced the forward movement mode and the rotating mode because the omnidirection movement should be made possible. To generate the suitable initial pose, the initial angle of four legs are coded under gray code and tuned by an estimation function in each mode with the genetic algorithm. As a result of generation, the cooperation of the legs is realized to move toward the omnidirection. The experimental results demonstrate that the proposed scheme is effective for generation of the suitable initial poses and the robot can walk smoothly with the generated patterns.

Optimization of multi-image pose recovery of fluoroscope tracking (FTRAC) fiducial in an image-guided femoroplasty system

NASA Astrophysics Data System (ADS)

Liu, Wen P.; Armand, Mehran; Otake, Yoshito; Taylor, Russell H.

2011-03-01

Percutaneous femoroplasty [1], or femoral bone augmentation, is a prospective alternative treatment for reducing the risk of fracture in patients with severe osteoporosis. We are developing a surgical robotics system that will assist orthopaedic surgeons in planning and performing a patient-specific, augmentation of the femur with bone cement. This collaborative project, sponsored by the National Institutes of Health (NIH), has been the topic of previous publications [2],[3] from our group. This paper presents modifications to the pose recovery of a fluoroscope tracking (FTRAC) fiducial during our process of 2D/3D registration of X-ray intraoperative images to preoperative CT data. We show improved automata of the initial pose estimation as well as lower projection errors with the advent of a multiimage pose optimization step.

Towards Designing an Integrated Architecture for NEO Characterization, Mitigation, Scientific Evaluation, and Resource Utilization

NASA Technical Reports Server (NTRS)

Adams, Robert B.; LaPointe, Michael; Wilks, Rod; Allen, Brian

2009-01-01

This poster reviews the planning and design for an integrated architecture for characterization, mitigation, scientific evaluation and resource utilization of near earth objects. This includes tracks to observe and characterize the nature of the threat posed by a NEO, and deflect if a significant threat is posed. The observation stack can also be used for a more complete scientific analysis of the NEO.

A Layered Approach for Robust Spatial Virtual Human Pose Reconstruction Using a Still Image

PubMed Central

Guo, Chengyu; Ruan, Songsong; Liang, Xiaohui; Zhao, Qinping

2016-01-01

Pedestrian detection and human pose estimation are instructive for reconstructing a three-dimensional scenario and for robot navigation, particularly when large amounts of vision data are captured using various data-recording techniques. Using an unrestricted capture scheme, which produces occlusions or breezing, the information describing each part of a human body and the relationship between each part or even different pedestrians must be present in a still image. Using this framework, a multi-layered, spatial, virtual, human pose reconstruction framework is presented in this study to recover any deficient information in planar images. In this framework, a hierarchical parts-based deep model is used to detect body parts by using the available restricted information in a still image and is then combined with spatial Markov random fields to re-estimate the accurate joint positions in the deep network. Then, the planar estimation results are mapped onto a virtual three-dimensional space using multiple constraints to recover any deficient spatial information. The proposed approach can be viewed as a general pre-processing method to guide the generation of continuous, three-dimensional motion data. The experiment results of this study are used to describe the effectiveness and usability of the proposed approach. PMID:26907289

AN INFORMATIC APPROACH TO ESTIMATING ECOLOGICAL RISKS POSED BY PHARMACEUTICAL USE

EPA Science Inventory

A new method for estimating risks of human prescription pharmaceuticals based on information found in regulatory filings as well as scientific and trade literature is described in a presentation at the Pharmaceuticals in the Environment Workshop in Las Vegas, NV, August 23-25, 20...

Theoretical implications for the estimation of dinitrogen fixation by large perennial plant species using isotope dilution

Treesearch

Dwight D. Baker; Maurice Fried; John A. Parrotta

1995-01-01

Estimation of symbiotic N2 fixation associated with large perennial plant species, especially trees, poses special problems because the process must be followed over a potentially long period of time to integrate the total amount of fixation. Estimations using isotope dilution methodology have begun to be used for trees in field studies. Because...

Beyond Formalism and Altruism: The Prospects for Moral Personality.

ERIC Educational Resources Information Center

Campbell, Robert C.; Christopher, John Chambers

1996-01-01

Claims that even if objections to eudaimonism are completely correct, critics still have not explained how anyone might develop a eudaimonistic moral conception. Concludes that moral personality is a legitimate object of study and discusses the challenges posed by taking moral personality seriously. (MOK)

Computer vision research with new imaging technology

NASA Astrophysics Data System (ADS)

Hou, Guangqi; Liu, Fei; Sun, Zhenan

2015-12-01

Light field imaging is capable of capturing dense multi-view 2D images in one snapshot, which record both intensity values and directions of rays simultaneously. As an emerging 3D device, the light field camera has been widely used in digital refocusing, depth estimation, stereoscopic display, etc. Traditional multi-view stereo (MVS) methods only perform well on strongly texture surfaces, but the depth map contains numerous holes and large ambiguities on textureless or low-textured regions. In this paper, we exploit the light field imaging technology on 3D face modeling in computer vision. Based on a 3D morphable model, we estimate the pose parameters from facial feature points. Then the depth map is estimated through the epipolar plane images (EPIs) method. At last, the high quality 3D face model is exactly recovered via the fusing strategy. We evaluate the effectiveness and robustness on face images captured by a light field camera with different poses.

3D kinematics of mobile-bearing total knee arthroplasty using X-ray fluoroscopy.

PubMed

Yamazaki, Takaharu; Futai, Kazuma; Tomita, Tetsuya; Sato, Yoshinobu; Yoshikawa, Hideki; Tamura, Shinichi; Sugamoto, Kazuomi

2015-04-01

Total knee arthroplasty (TKA) 3D kinematic analysis requires 2D/3D image registration of X-ray fluoroscopic images and a computer-aided design (CAD) model of the knee implant. However, these techniques cannot provide information on the radiolucent polyethylene insert, since the insert silhouette does not appear clearly in X-ray images. Therefore, it is difficult to obtain the 3D kinematics of the polyethylene insert, particularly the mobile-bearing insert. A technique for 3D kinematic analysis of a mobile-bearing insert used in TKA was developed using X-ray fluoroscopy. The method was tested and a clinical application was evaluated. Tantalum beads and a CAD model of the mobile-bearing TKA insert are used for 3D pose estimation of the mobile-bearing insert used in TKA using X-ray fluoroscopy. The insert model was created using four identical tantalum beads precisely located at known positions in a polyethylene insert using a specially designed insertion device. Finally, the 3D pose of the insert model was estimated using a feature-based 2D/3D registration technique, using the silhouette of beads in fluoroscopic images and the corresponding CAD insert model. In vitro testing for the repeatability of the positioning of the tantalum beads and computer simulations for 3D pose estimation of the mobile-bearing insert were performed. The pose estimation accuracy achieved was sufficient for analyzing mobile-bearing TKA kinematics (RMS error: within 1.0 mm and 1.0°, except for medial-lateral translation). In a clinical application, nine patients with mobile-bearing TKA were investigated and analyzed with respect to a deep knee bending motion. A 3D kinematic analysis technique was developed that enables accurate quantitative evaluation of mobile-bearing TKA kinematics. This method may be useful for improving implant design and optimizing TKA surgical techniques.

Retrieval of LAI and leaf chlorophyll content from remote sensing data by agronomy mechanism knowledge to solve the ill-posed inverse problem

NASA Astrophysics Data System (ADS)

Li, Zhenhai; Nie, Chenwei; Yang, Guijun; Xu, Xingang; Jin, Xiuliang; Gu, Xiaohe

2014-10-01

Leaf area index (LAI) and LCC, as the two most important crop growth variables, are major considerations in management decisions, agricultural planning and policy making. Estimation of canopy biophysical variables from remote sensing data was investigated using a radiative transfer model. However, the ill-posed problem is unavoidable for the unique solution of the inverse problem and the uncertainty of measurements and model assumptions. This study focused on the use of agronomy mechanism knowledge to restrict and remove the ill-posed inversion results. For this purpose, the inversion results obtained using the PROSAIL model alone (NAMK) and linked with agronomic mechanism knowledge (AMK) were compared. The results showed that AMK did not significantly improve the accuracy of LAI inversion. LAI was estimated with high accuracy, and there was no significant improvement after considering AMK. The validation results of the determination coefficient (R2) and the corresponding root mean square error (RMSE) between measured LAI and estimated LAI were 0.635 and 1.022 for NAMK, and 0.637 and 0.999 for AMK, respectively. LCC estimation was significantly improved with agronomy mechanism knowledge; the R2 and RMSE values were 0.377 and 14.495 μg cm-2 for NAMK, and 0.503 and 10.661 μg cm-2 for AMK, respectively. Results of the comparison demonstrated the need for agronomy mechanism knowledge in radiative transfer model inversion.

Automatic pose correction for image-guided nonhuman primate brain surgery planning

NASA Astrophysics Data System (ADS)

Ghafurian, Soheil; Chen, Antong; Hines, Catherine; Dogdas, Belma; Bone, Ashleigh; Lodge, Kenneth; O'Malley, Stacey; Winkelmann, Christopher T.; Bagchi, Ansuman; Lubbers, Laura S.; Uslaner, Jason M.; Johnson, Colena; Renger, John; Zariwala, Hatim A.

2016-03-01

Intracranial delivery of recombinant DNA and neurochemical analysis in nonhuman primate (NHP) requires precise targeting of various brain structures via imaging derived coordinates in stereotactic surgeries. To attain targeting precision, the surgical planning needs to be done on preoperative three dimensional (3D) CT and/or MR images, in which the animals head is fixed in a pose identical to the pose during the stereotactic surgery. The matching of the image to the pose in the stereotactic frame can be done manually by detecting key anatomical landmarks on the 3D MR and CT images such as ear canal and ear bar zero position. This is not only time intensive but also prone to error due to the varying initial poses in the images which affects both the landmark detection and rotation estimation. We have introduced a fast, reproducible, and semi-automatic method to detect the stereotactic coordinate system in the image and correct the pose. The method begins with a rigid registration of the subject images to an atlas and proceeds to detect the anatomical landmarks through a sequence of optimization, deformable and multimodal registration algorithms. The results showed similar precision (maximum difference of 1.71 in average in-plane rotation) to a manual pose correction.

Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition

NASA Astrophysics Data System (ADS)

Yin, Xi; Liu, Xiaoming

2018-02-01

This paper explores multi-task learning (MTL) for face recognition. We answer the questions of how and why MTL can improve the face recognition performance. First, we propose a multi-task Convolutional Neural Network (CNN) for face recognition where identity classification is the main task and pose, illumination, and expression estimations are the side tasks. Second, we develop a dynamic-weighting scheme to automatically assign the loss weight to each side task, which is a crucial problem in MTL. Third, we propose a pose-directed multi-task CNN by grouping different poses to learn pose-specific identity features, simultaneously across all poses. Last but not least, we propose an energy-based weight analysis method to explore how CNN-based MTL works. We observe that the side tasks serve as regularizations to disentangle the variations from the learnt identity features. Extensive experiments on the entire Multi-PIE dataset demonstrate the effectiveness of the proposed approach. To the best of our knowledge, this is the first work using all data in Multi-PIE for face recognition. Our approach is also applicable to in-the-wild datasets for pose-invariant face recognition and achieves comparable or better performance than state of the art on LFW, CFP, and IJB-A datasets.

High-order distance-based multiview stochastic learning in image classification.

PubMed

Yu, Jun; Rui, Yong; Tang, Yuan Yan; Tao, Dacheng

2014-12-01

How do we find all images in a larger set of images which have a specific content? Or estimate the position of a specific object relative to the camera? Image classification methods, like support vector machine (supervised) and transductive support vector machine (semi-supervised), are invaluable tools for the applications of content-based image retrieval, pose estimation, and optical character recognition. However, these methods only can handle the images represented by single feature. In many cases, different features (or multiview data) can be obtained, and how to efficiently utilize them is a challenge. It is inappropriate for the traditionally concatenating schema to link features of different views into a long vector. The reason is each view has its specific statistical property and physical interpretation. In this paper, we propose a high-order distance-based multiview stochastic learning (HD-MSL) method for image classification. HD-MSL effectively combines varied features into a unified representation and integrates the labeling information based on a probabilistic framework. In comparison with the existing strategies, our approach adopts the high-order distance obtained from the hypergraph to replace pairwise distance in estimating the probability matrix of data distribution. In addition, the proposed approach can automatically learn a combination coefficient for each view, which plays an important role in utilizing the complementary information of multiview data. An alternative optimization is designed to solve the objective functions of HD-MSL and obtain different views on coefficients and classification scores simultaneously. Experiments on two real world datasets demonstrate the effectiveness of HD-MSL in image classification.

Soft tissue navigation for laparoscopic prostatectomy: evaluation of camera pose estimation for enhanced visualization

NASA Astrophysics Data System (ADS)

Baumhauer, M.; Simpfendörfer, T.; Schwarz, R.; Seitel, M.; Müller-Stich, B. P.; Gutt, C. N.; Rassweiler, J.; Meinzer, H.-P.; Wolf, I.

2007-03-01

We introduce a novel navigation system to support minimally invasive prostate surgery. The system utilizes transrectal ultrasonography (TRUS) and needle-shaped navigation aids to visualize hidden structures via Augmented Reality. During the intervention, the navigation aids are segmented once from a 3D TRUS dataset and subsequently tracked by the endoscope camera. Camera Pose Estimation methods directly determine position and orientation of the camera in relation to the navigation aids. Accordingly, our system does not require any external tracking device for registration of endoscope camera and ultrasonography probe. In addition to a preoperative planning step in which the navigation targets are defined, the procedure consists of two main steps which are carried out during the intervention: First, the preoperatively prepared planning data is registered with an intraoperatively acquired 3D TRUS dataset and the segmented navigation aids. Second, the navigation aids are continuously tracked by the endoscope camera. The camera's pose can thereby be derived and relevant medical structures can be superimposed on the video image. This paper focuses on the latter step. We have implemented several promising real-time algorithms and incorporated them into the Open Source Toolkit MITK (www.mitk.org). Furthermore, we have evaluated them for minimally invasive surgery (MIS) navigation scenarios. For this purpose, a virtual evaluation environment has been developed, which allows for the simulation of navigation targets and navigation aids, including their measurement errors. Besides evaluating the accuracy of the computed pose, we have analyzed the impact of an inaccurate pose and the resulting displacement of navigation targets in Augmented Reality.

Automatic anatomy recognition using neural network learning of object relationships via virtual landmarks

NASA Astrophysics Data System (ADS)

Yan, Fengxia; Udupa, Jayaram K.; Tong, Yubing; Xu, Guoping; Odhner, Dewey; Torigian, Drew A.

2018-03-01

The recently developed body-wide Automatic Anatomy Recognition (AAR) methodology depends on fuzzy modeling of individual objects, hierarchically arranging objects, constructing an anatomy ensemble of these models, and a dichotomous object recognition-delineation process. The parent-to-offspring spatial relationship in the object hierarchy is crucial in the AAR method. We have found this relationship to be quite complex, and as such any improvement in capturing this relationship information in the anatomy model will improve the process of recognition itself. Currently, the method encodes this relationship based on the layout of the geometric centers of the objects. Motivated by the concept of virtual landmarks (VLs), this paper presents a new one-shot AAR recognition method that utilizes the VLs to learn object relationships by training a neural network to predict the pose and the VLs of an offspring object given the VLs of the parent object in the hierarchy. We set up two neural networks for each parent-offspring object pair in a body region, one for predicting the VLs and another for predicting the pose parameters. The VL-based learning/prediction method is evaluated on two object hierarchies involving 14 objects. We utilize 54 computed tomography (CT) image data sets of head and neck cancer patients and the associated object contours drawn by dosimetrists for routine radiation therapy treatment planning. The VL neural network method is found to yield more accurate object localization than the currently used simple AAR method.

DOCKSCORE: a webserver for ranking protein-protein docked poses.

PubMed

Malhotra, Sony; Mathew, Oommen K; Sowdhamini, Ramanathan

2015-04-24

Proteins interact with a variety of other molecules such as nucleic acids, small molecules and other proteins inside the cell. Structure-determination of protein-protein complexes is challenging due to several reasons such as the large molecular weights of these macromolecular complexes, their dynamic nature, difficulty in purification and sample preparation. Computational docking permits an early understanding of the feasibility and mode of protein-protein interactions. However, docking algorithms propose a number of solutions and it is a challenging task to select the native or near native pose(s) from this pool. DockScore is an objective scoring scheme that can be used to rank protein-protein docked poses. It considers several interface parameters, namely, surface area, evolutionary conservation, hydrophobicity, short contacts and spatial clustering at the interface for scoring. We have implemented DockScore in form of a webserver for its use by the scientific community. DockScore webserver can be employed, subsequent to docking, to perform scoring of the docked solutions, starting from multiple poses as inputs. The results, on scores and ranks for all the poses, can be downloaded as a csv file and graphical view of the interface of best ranking poses is possible. The webserver for DockScore is made freely available for the scientific community at: http://caps.ncbs.res.in/dockscore/ .

Estimation of Tree Position and STEM Diameter Using Simultaneous Localization and Mapping with Data from a Backpack-Mounted Laser Scanner

NASA Astrophysics Data System (ADS)

Holmgren, J.; Tulldahl, H. M.; Nordlöf, J.; Nyström, M.; Olofsson, K.; Rydell, J.; Willén, E.

2017-10-01

A system was developed for automatic estimations of tree positions and stem diameters. The sensor trajectory was first estimated using a positioning system that consists of a low precision inertial measurement unit supported by image matching with data from a stereo-camera. The initial estimation of the sensor trajectory was then calibrated by adjustments of the sensor pose using the laser scanner data. Special features suitable for forest environments were used to solve the correspondence and matching problems. Tree stem diameters were estimated for stem sections using laser data from individual scanner rotations and were then used for calibration of the sensor pose. A segmentation algorithm was used to associate stem sections to individual tree stems. The stem diameter estimates of all stem sections associated to the same tree stem were then combined for estimation of stem diameter at breast height (DBH). The system was validated on four 20 m radius circular plots and manual measured trees were automatically linked to trees detected in laser data. The DBH could be estimated with a RMSE of 19 mm (6 %) and a bias of 8 mm (3 %). The calibrated sensor trajectory and the combined use of circle fits from individual scanner rotations made it possible to obtain reliable DBH estimates also with a low precision positioning system.

Information surfing with the JHU/APL coherent imager

NASA Astrophysics Data System (ADS)

Ratto, Christopher R.; Shipley, Kara R.; Beagley, Nathaniel; Wolfe, Kevin C.

2015-05-01

The ability to perform remote forensics in situ is an important application of autonomous undersea vehicles (AUVs). Forensics objectives may include remediation of mines and/or unexploded ordnance, as well as monitoring of seafloor infrastructure. At JHU/APL, digital holography is being explored for the potential application to underwater imaging and integration with an AUV. In previous work, a feature-based approach was developed for processing the holographic imagery and performing object recognition. In this work, the results of the image processing method were incorporated into a Bayesian framework for autonomous path planning referred to as information surfing. The framework was derived assuming that the location of the object of interest is known a priori, but the type of object and its pose are unknown. The path-planning algorithm adaptively modifies the trajectory of the sensing platform based on historical performance of object and pose classification. The algorithm is called information surfing because the direction of motion is governed by the local information gradient. Simulation experiments were carried out using holographic imagery collected from submerged objects. The autonomous sensing algorithm was compared to a deterministic sensing CONOPS, and demonstrated improved accuracy and faster convergence in several cases.

Frequency of use controls chemical leaching from drinking-water containers subject to disinfection.

PubMed

Andra, Syam S; Makris, Konstantinos C; Shine, James P

2011-12-15

Microbial-, and chemical-based burden of disease associated with lack of access to safe water continues to primarily impact developing countries. Cost-effective health risk-mitigating measures, such as of solar disinfection applied to microbial-contaminated water stored in plastic bottles have been increasingly tested in developing countries adversely impacted by epidemic water-borne diseases. Public health concerns associated with chemical leaching from water packaging materials led us to investigate the magnitude and variability of antimony (Sb) and bromine (Br) leaching from reused plastic containers (polyethylene terephthalate, PET; and polycarbonate, PC) subject to UV and/or temperature-driven disinfection. The overall objective of this study was to determine the main and interactive effects of temperature, UV exposure duration, and frequency of bottle reuse on the extent of leaching of Sb and Br from plastic bottles into water. Regardless of UV exposure duration, frequency of reuse (up to 27 times) was the major factor that linearly increased Sb leaching from PET bottles at all temperatures tested (13-47 °C). Leached Sb concentrations (∼360 ng L(-1)) from the highly reused (27 times) PET bottles (minimal Sb leaching from PC bottles, <15 ng L(-1)) did not pose a serious risk to human health according to current daily Sb acceptable intake estimates. Leached Br concentrations from both PET and PC containers (up to ∼15 μg L(-1)) did not pose a consumer health risk either, however, no acceptable daily dose estimates exist for oral ingestion of organo-brominated, or other plasticizers/additives compounds if they were to be found in bottled water at much lower concentrations. Additional research on potential leaching of organic chemicals from water packaging materials is deemed necessary under relevant environmental conditions. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Contemporary Hazard of Cometary Impacts

NASA Technical Reports Server (NTRS)

Morrison, David

1994-01-01

Cosmic impacts pose a continuing hazard of loss of human life and property. Significant contemporary risk is associated with projectiles in the energy range from about 10 megatons of TNT up to the size of the K/T impactor. The lower threshold for damage is defined by the atmosphere of the Earth, which effectively shields us From smaller projectiles. Up to energies of about a gigaton of TNT, the effects are local or regional for impacts on the land, or coastal for ocean impacts, which can generate large tsunamis. A greater risk is associated with still larger impacts, which are capable of causing global ecological catastrophe, possibly leading to mass mortality From starvation and epidemics. If such a impact took place anywhere on Earth during our lifetimes, we would each be in danger, independent of where the projectile struck. Statistical estimates indicate that each human on this planet runs a risk of roughly 1 in 20,000 of dying from this cause. Prudence suggests that we should be concerned about such impacts and seek ways of avoiding them or mitigating their consequences. The primary objective of any program to deal with this hazard is to determine whether or not such a near-term impact is likely. The best approach for the asteroidal component is a comprehensive telescopic survey, which can discover all Earth-crossing asteroids larger than 1 km in diameter and provide decades of warning in which to plan ways to deflect or destroy a threatening object. Long-period comets, however, pose a much greater challenge, since they cannot be discovered long in advance of a possible impact, their orbits are harder to predict, and they are significantly more difficult to deflect or destroy.

Caffeine as an indicator for the quantification of untreated wastewater in karst systems.

PubMed

Hillebrand, Olav; Nödler, Karsten; Licha, Tobias; Sauter, Martin; Geyer, Tobias

2012-02-01

Contamination from untreated wastewater leakage and related bacterial contamination poses a threat to drinking water quality. However, a quantification of the magnitude of leakage is difficult. The objective of this work is to provide a highly sensitive methodology for the estimation of the mass of untreated wastewater entering karst aquifers with rapid recharge. For this purpose a balance approach is adapted. It is based on the mass flow of caffeine in spring water, the load of caffeine in untreated wastewater and the daily water consumption per person in a spring catchment area. Caffeine is a source-specific indicator for wastewater, consumed and discharged in quantities allowing detection in a karst spring. The methodology was applied to estimate the amount of leaking and infiltrating wastewater to a well investigated karst aquifer on a daily basis. The calculated mean volume of untreated wastewater entering the aquifer was found to be 2.2 ± 0.5 m(3) d(-1) (undiluted wastewater). It corresponds to approximately 0.4% of the total amount of wastewater within the spring catchment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Healthcare burden of depression in adults with arthritis.

PubMed

Sambamoorthi, Usha; Shah, Drishti; Zhao, Xiaohui

2017-02-01

Arthritis and depression are two of the top disabling conditions. When arthritis and depression exist in the same individual, they can interact with each other negatively and pose a significant healthcare burden on the patients, their families, payers, healthcare systems, and society as a whole. Areas covered: The primary objective of this review is to summarize, identify knowledge gaps and discuss the challenges in estimating the healthcare burden of depression among individuals with arthritis. Electronic literature searches were performed on PubMed, Embase, EBSCOhost, Scopus, the Cochrane Library, and Google Scholar to identify relevant studies. Expert Commentary: Our review revealed that the prevalence of depression varied depending on the definition of depression, type of arthritis, tools and threshold points used to identify depression, and the country of residence. Depression exacerbated arthritis-related complications as well as pain and was associated with poor health-related quality of life, disability, mortality, and high financial burden. There were significant knowledge gaps in estimates of incident depression rates, depression attributable disability, and healthcare utilization, direct and indirect healthcare costs among individuals with arthritis.

Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories

PubMed Central

Qiu, Ping; Pang, Ling; Arreaza, Gladys; Maguire, Maureen; Chang, Ken C. N.; Marton, Matthew J.; Levitan, Diane

2016-01-01

Immune checkpoint inhibitors, which unleash a patient’s own T cells to kill tumors, are revolutionizing cancer treatment. Several independent studies suggest that higher non-synonymous mutational burden assessed by whole exome sequencing (WES) in tumors is associated with improved objective response, durable clinical benefit, and progression-free survival in immune checkpoint inhibitors treatment. Next-generation sequencing (NGS) is a promising technology being used in the clinic to direct patient treatment. Cancer genome WES poses a unique challenge due to tumor heterogeneity and sequencing artifacts introduced by formalin-fixed, paraffin-embedded (FFPE) tissue. In order to evaluate the data interoperability of WES data from different sources to survey tumor mutational landscape, we compared WES data of several tumor/normal matched samples from five commercial vendors. A large data discrepancy was observed from vendors’ self-reported data. Independent data analysis from vendors’ raw NGS data shows that whole exome sequencing data from qualified vendors can be combined and analyzed uniformly to derive comparable quantitative estimates of tumor mutational burden. PMID:27136543

On the early thermal state of the moon

NASA Technical Reports Server (NTRS)

Solomon, Sean C.

1986-01-01

New theories for the formation of the moon from an accretion disk thrown into circumterrestrial orbit after the collision of a planet-sized object with the earth have led to a reexamination of the tectonic consequences of an initially molten moon. Even the smallest estimates of radial contraction that would accompany cooling of the moon from an initially molten state predict accumulated near-surface horizontal compressive stresses considerably in excess of the compressive strength of the upper lunar crust, estimated to be 0.5 to 1 kbar on the basis of topographic relief, the stress levels necessary to form mare ridges in mascon mare basins, and measurements of rock friction. Various mechanisms for relieving or modifying such large near-surface stresses are considered, including viscoelastic effects, widespread development of major fault systems, impact gardening, and opposing stresses arising from other global-scale processes. All of these mechanisms face substantial difficulties when tested against geological and mechanical information from the moon and other terrestrial planets. These considerations pose a serious problem for theories of lunar origin that call for an initially molten state.

Healthcare burden of depression in adults with arthritis

PubMed Central

Sambamoorthi, Usha; Shah, Drishti; Zhao, Xiaohui

2017-01-01

Introduction Arthritis and depression are two of the top disabling conditions. When arthritis and depression exist in the same individual, they can interact with each other negatively and pose a significant healthcare burden on the patients, their families, payers, healthcare systems, and society as a whole. Areas covered The primary objective of this review is to summarize, identify knowledge gaps and discuss the challenges in estimating the healthcare burden of depression among individuals with arthritis. Electronic literature searches were performed on PubMed, Embase, EBSCOhost, Scopus, the Cochrane Library, and Google Scholar to identify relevant studies. Expert Commentary Our review revealed that the prevalence of depression varied depending on the definition of depression, type of arthritis, tools and threshold points used to identify depression, and the country of residence. Depression exacerbated arthritis-related complications as well as pain and was associated with poor health-related quality of life, disability, mortality, and high financial burden. There were significant knowledge gaps in estimates of incident depression rates, depression attributable disability, and healthcare utilization, direct and indirect healthcare costs among individuals with arthritis. PMID:28092207

Illegal fishing and territorial user rights in Chile.

PubMed

Oyanedel, Rodrigo; Keim, Andres; Castilla, Juan Carlos; Gelcich, Stefan

2017-11-07

Illegal fishing poses a major threat to conservation of marine resources worldwide. However, there is still limited empirical research that quantifies illegal catch levels. We used the randomized response technique to estimate the proportion of divers and the quantities of loco (Concholepas concholepas) they extracted illegally. Loco have been managed for the past 17 years through a territorial user rights for fisheries system (TURFs) in Chile. Illegal fishing of loco was widespread within the TURFs system. Official reported landings (i.e., legal landings) accounted for 14-30% of the total loco extraction. Our estimates suggest that ignoring the magnitude of illegal fishing and considering only official landing statistics may lead to false conclusions about the status and trends of a TURFs managed fishery. We found evidence of fisher associations authorizing their members to poach inside TURFs, highlighting the need to design TURFs systems so that government agencies and fishers' incentives and objectives align through continuous adaptation. Government support for enforcement is a key element for the TURFs system to secure the rights that are in place. © 2017 Society for Conservation Biology.

Model-based recognition of 3D articulated target using ladar range data.

PubMed

Lv, Dan; Sun, Jian-Feng; Li, Qi; Wang, Qi

2015-06-10

Ladar is suitable for 3D target recognition because ladar range images can provide rich 3D geometric surface information of targets. In this paper, we propose a part-based 3D model matching technique to recognize articulated ground military vehicles in ladar range images. The key of this approach is to solve the decomposition and pose estimation of articulated parts of targets. The articulated components were decomposed into isolate parts based on 3D geometric properties of targets, such as surface point normals, data histogram distribution, and data distance relationships. The corresponding poses of these separate parts were estimated through the linear characteristics of barrels. According to these pose parameters, all parts of the target were roughly aligned to 3D point cloud models in a library and fine matching was finally performed to accomplish 3D articulated target recognition. The recognition performance was evaluated with 1728 ladar range images of eight different articulated military vehicles with various part types and orientations. Experimental results demonstrated that the proposed approach achieved a high recognition rate.

Working and Learning with Knowledge in the Lobes of a Humanoid's Mind

NASA Technical Reports Server (NTRS)

Ambrose, Robert; Savely, Robert; Bluethmann, William; Kortenkamp, David

2003-01-01

Humanoid class robots must have sufficient dexterity to assist people and work in an environment designed for human comfort and productivity. This dexterity, in particular the ability to use tools, requires a cognitive understanding of self and the world that exceeds contemporary robotics. Our hypothesis is that the sense-think-act paradigm that has proven so successful for autonomous robots is missing one or more key elements that will be needed for humanoids to meet their full potential as autonomous human assistants. This key ingredient is knowledge. The presented work includes experiments conducted on the Robonaut system, a NASA and the Defense Advanced research Projects Agency (DARPA) joint project, and includes collaborative efforts with a DARPA Mobile Autonomous Robot Software technical program team of researchers at NASA, MIT, USC, NRL, UMass and Vanderbilt. The paper reports on results in the areas of human-robot interaction (human tracking, gesture recognition, natural language, supervised control), perception (stereo vision, object identification, object pose estimation), autonomous grasping (tactile sensing, grasp reflex, grasp stability) and learning (human instruction, task level sequences, and sensorimotor association).

Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing.

PubMed

Ghesu, Florin C; Krubasik, Edward; Georgescu, Bogdan; Singh, Vivek; Yefeng Zheng; Hornegger, Joachim; Comaniciu, Dorin

2016-05-01

Robust and fast solutions for anatomical object detection and segmentation support the entire clinical workflow from diagnosis, patient stratification, therapy planning, intervention and follow-up. Current state-of-the-art techniques for parsing volumetric medical image data are typically based on machine learning methods that exploit large annotated image databases. Two main challenges need to be addressed, these are the efficiency in scanning high-dimensional parametric spaces and the need for representative image features which require significant efforts of manual engineering. We propose a pipeline for object detection and segmentation in the context of volumetric image parsing, solving a two-step learning problem: anatomical pose estimation and boundary delineation. For this task we introduce Marginal Space Deep Learning (MSDL), a novel framework exploiting both the strengths of efficient object parametrization in hierarchical marginal spaces and the automated feature design of Deep Learning (DL) network architectures. In the 3D context, the application of deep learning systems is limited by the very high complexity of the parametrization. More specifically 9 parameters are necessary to describe a restricted affine transformation in 3D, resulting in a prohibitive amount of billions of scanning hypotheses. The mechanism of marginal space learning provides excellent run-time performance by learning classifiers in clustered, high-probability regions in spaces of gradually increasing dimensionality. To further increase computational efficiency and robustness, in our system we learn sparse adaptive data sampling patterns that automatically capture the structure of the input. Given the object localization, we propose a DL-based active shape model to estimate the non-rigid object boundary. Experimental results are presented on the aortic valve in ultrasound using an extensive dataset of 2891 volumes from 869 patients, showing significant improvements of up to 45.2% over the state-of-the-art. To our knowledge, this is the first successful demonstration of the DL potential to detection and segmentation in full 3D data with parametrized representations.

Yields of biologically significant damage produced in mammalian DNA by irradiation associated with radon decay. Final progress report

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

Ward, J.F.

1994-03-01

The objective of this project was to characterize the difference between damage to DNA caused by alpha particles and by low LET radiation. Estimation of the risk posed by exposure to high LET radiation (such as that from radon) relies at present on epidemiological data, and is therefore largely empirical. This empiricism is evident from the concepts of quality factor or RBE that find use for describing the biological effects of high LET radiation. The author argues that some effort should be made to address the mechanisms of DNA damage by high and low LET forms of radiation, and howmore » these mechanisms might relate to the biological endpoints. This report summarizes the results of the author`s investigations and the current understanding of these mechanisms.« less

Joint recognition and discrimination in nonlinear feature space

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.

1997-09-01

A new general method for linear and nonlinear feature extraction is presented. It is novel since it provides both representation and discrimination while most other methods are concerned with only one of these issues. We call this approach the maximum representation and discrimination feature (MRDF) method and show that the Bayes classifier and the Karhunen- Loeve transform are special cases of it. We refer to our nonlinear feature extraction technique as nonlinear eigen- feature extraction. It is new since it has a closed-form solution and produces nonlinear decision surfaces with higher rank than do iterative methods. Results on synthetic databases are shown and compared with results from standard Fukunaga- Koontz transform and Fisher discriminant function methods. The method is also applied to an automated product inspection problem (discrimination) and to the classification and pose estimation of two similar objects (representation and discrimination).

Computer vision for RGB-D sensors: Kinect and its applications.

PubMed

Shao, Ling; Han, Jungong; Xu, Dong; Shotton, Jamie

2013-10-01

Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use as an off-the-shelf technology. This special issue is specifically dedicated to new algorithms and/or new applications based on the Kinect (or similar RGB-D) sensors. In total, we received over ninety submissions from more than twenty countries all around the world. The submissions cover a wide range of areas including object and scene classification, 3-D pose estimation, visual tracking, data fusion, human action/activity recognition, 3-D reconstruction, mobile robotics, and so on. After two rounds of review by at least two (mostly three) expert reviewers for each paper, the Guest Editors have selected twelve high-quality papers to be included in this highly popular special issue. The papers that comprise this issue are briefly summarized.

Pitch-informed solo and accompaniment separation towards its use in music education applications

NASA Astrophysics Data System (ADS)

Cano, Estefanía; Schuller, Gerald; Dittmar, Christian

2014-12-01

We present a system for the automatic separation of solo instruments and music accompaniment in polyphonic music recordings. Our approach is based on a pitch detection front-end and a tone-based spectral estimation. We assess the plausibility of using sound separation technologies to create practice material in a music education context. To better understand the sound separation quality requirements in music education, a listening test was conducted to determine the most perceptually relevant signal distortions that need to be improved. Results from the listening test show that solo and accompaniment tracks pose different quality requirements and should be optimized differently. We propose and evaluate algorithm modifications to better understand their effects on objective perceptual quality measures. Finally, we outline possible ways of optimizing our separation approach to better suit the requirements of music education applications.

Using linked data to evaluate collisions with fixed objects in Pennsylvania : Crash Outcome Data Evaluation System (CODES) linked data demonstration project

DOT National Transportation Integrated Search

1998-10-01

This report uses police-reported motor vehicle crash data linked to Emergency Medical Services data and hospital discharge data to evaluate the relative risk of injury posed by specific roadside objects in Pennsylvania. The report focuses primarily o...

Multiple-Object Tracking in Children: The "Catch the Spies" Task

ERIC Educational Resources Information Center

Trick, L.M.; Jaspers-Fayer, F.; Sethi, N.

2005-01-01

Multiple-object tracking involves simultaneously tracking positions of a number of target-items as they move among distractors. The standard version of the task poses special challenges for children, demanding extended concentration and the ability to distinguish targets from identical-looking distractors, and may thus underestimate children's…

Relative Clauses in Cantonese-English Bilingual Children: Typological Challenges and Processing Motivations

ERIC Educational Resources Information Center

Yip, Virginia; Matthews, Stephen

2007-01-01

Findings from a longitudinal study of bilingual children acquiring Cantonese and English pose a challenge to the noun phrase accessibility hierarchy (NPAH; Keenan & Comrie, 1977), which predicts that object relatives should not be acquired before subject relatives. In the children's Cantonese, object relatives emerged earlier than or…

Real-Time Identification of Wheel Terrain Interaction Models for Enhanced Autonomous Vehicle Mobility

DTIC Science & Technology

2014-04-24

tim at io n Er ro r ( cm ) 0 2 4 6 8 10 Color Statistics Angelova...Color_Statistics_Error) / Average_Slip_Error Position Estimation Error: Global Pose Po si tio n Es tim at io n Er ro r ( cm ) 0 2 4 6 8 10 12 Color...get some kind of clearance for releasing pose and odometry data) collected at the following sites – Taylor, Gascola, Somerset, Fort Bliss and

The concurrent multiplicative-additive approach for gauge-radar/satellite multisensor precipitation estimates

NASA Astrophysics Data System (ADS)

Garcia-Pintado, J.; Barberá, G. G.; Erena Arrabal, M.; Castillo, V. M.

2010-12-01

Objective analysis schemes (OAS), also called ``succesive correction methods'' or ``observation nudging'', have been proposed for multisensor precipitation estimation combining remote sensing data (meteorological radar or satellite) with data from ground-based raingauge networks. However, opposite to the more complex geostatistical approaches, the OAS techniques for this use are not optimized. On the other hand, geostatistical techniques ideally require, at the least, modelling the covariance from the rain gauge data at every time step evaluated, which commonly cannot be soundly done. Here, we propose a new procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) for operational rainfall estimation using rain gauges and meteorological radar, which does not require explicit modelling of spatial covariances. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on the OAS, whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The approach considers radar estimates as background a priori information (first guess), so that nudging to observations (gauges) may be relaxed smoothly to the first guess, and the relaxation shape is obtained from the sequential optimization. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, an OAS spatially variable adjustment with multiplicative factors, ordinary cokriging, and kriging with external drift. In theory, it could be equally applicable to gauge-satellite estimates and other hydrometeorological variables.

The strategic marketing reaction of conventional nonprofit hospitals to the market entry of alternative care provider organizations.

PubMed

Schul, P L; Remington, S J; Planchon, J M

1994-01-01

A study was conducted examining the competitive reaction of incumbent firms to the market entry of new form competition in the health care services industry. Specifically, the study addressed the relative impact of both objective and perceptual characteristics of the threat potential posed by the entrance of alternative care facilities (ACF's) into markets previously dominated by nonprofit hospital organizations. The results showed that incumbent hospitals tend to rely most extensively on limited, low-risk market differentiation when responding to the threat posed by ACF entrants. Objective characteristics reflective of the structural complexity of the threat were found to be less important in influencing incumbent reaction than were administrators' perceptions of new entrant threat.

Deep learning-based depth estimation from a synthetic endoscopy image training set

NASA Astrophysics Data System (ADS)

Mahmood, Faisal; Durr, Nicholas J.

2018-03-01

Colorectal cancer is the fourth leading cause of cancer deaths worldwide. The detection and removal of premalignant lesions through an endoscopic colonoscopy is the most effective way to reduce colorectal cancer mortality. Unfortunately, conventional colonoscopy has an almost 25% polyp miss rate, in part due to the lack of depth information and contrast of the surface of the colon. Estimating depth using conventional hardware and software methods is challenging in endoscopy due to limited endoscope size and deformable mucosa. In this work, we use a joint deep learning and graphical model-based framework for depth estimation from endoscopy images. Since depth is an inherently continuous property of an object, it can easily be posed as a continuous graphical learning problem. Unlike previous approaches, this method does not require hand-crafted features. Large amounts of augmented data are required to train such a framework. Since there is limited availability of colonoscopy images with ground-truth depth maps and colon texture is highly patient-specific, we generated training images using a synthetic, texture-free colon phantom to train our models. Initial results show that our system can estimate depths for phantom test data with a relative error of 0.164. The resulting depth maps could prove valuable for 3D reconstruction and automated Computer Aided Detection (CAD) to assist in identifying lesions.

Using generalized estimating equations and extensions in randomized trials with missing longitudinal patient reported outcome data.

PubMed

Bell, Melanie L; Horton, Nicholas J; Dhillon, Haryana M; Bray, Victoria J; Vardy, Janette

2018-05-26

Patient reported outcomes (PROs) are important in oncology research; however, missing data can pose a threat to the validity of results. Psycho-oncology researchers should be aware of the statistical options for handling missing data robustly. One rarely used set of methods, which includes extensions for handling missing data, is generalized estimating equations (GEEs). Our objective was to demonstrate use of GEEs to analyze PROs with missing data in randomized trials with assessments at fixed time points. We introduce GEEs and show, with a worked example, how to use GEEs that account for missing data: inverse probability weighted GEEs and multiple imputation with GEE. We use data from an RCT evaluating a web-based brain training for cancer survivors reporting cognitive symptoms after chemotherapy treatment. The primary outcome for this demonstration is the binary outcome of cognitive impairment. Several methods are used, and results are compared. We demonstrate that estimates can vary depending on the choice of analytical approach, with odds ratios for no cognitive impairment ranging from 2.04 to 5.74. While most of these estimates were statistically significant (P < 0.05), a few were not. Researchers using PROs should use statistical methods that handle missing data in a way as to result in unbiased estimates. GEE extensions are analytic options for handling dropouts in longitudinal RCTs, particularly if the outcome is not continuous. Copyright © 2018 John Wiley & Sons, Ltd.

Analysis of CAD Model-based Visual Tracking for Microassembly using a New Block Set for MATLAB/Simulink

NASA Astrophysics Data System (ADS)

Kudryavtsev, Andrey V.; Laurent, Guillaume J.; Clévy, Cédric; Tamadazte, Brahim; Lutz, Philippe

2015-10-01

Microassembly is an innovative alternative to the microfabrication process of MOEMS, which is quite complex. It usually implies the use of microrobots controlled by an operator. The reliability of this approach has been already confirmed for micro-optical technologies. However, the characterization of assemblies has shown that the operator is the main source of inaccuracies in the teleoperated microassembly. Therefore, there is great interest in automating the microassembly process. One of the constraints of automation in microscale is the lack of high precision sensors capable to provide the full information about the object position. Thus, the usage of visual-based feedback represents a very promising approach allowing to automate the microassembly process. The purpose of this article is to characterize the techniques of object position estimation based on the visual data, i.e., visual tracking techniques from the ViSP library. These algorithms enables a 3-D object pose using a single view of the scene and the CAD model of the object. The performance of three main types of model-based trackers is analyzed and quantified: edge-based, texture-based and hybrid tracker. The problems of visual tracking in microscale are discussed. The control of the micromanipulation station used in the framework of our project is performed using a new Simulink block set. Experimental results are shown and demonstrate the possibility to obtain the repeatability below 1 µm.

A chance constraint estimation approach to optimizing resource management under uncertainty

Treesearch

Michael Bevers

2007-01-01

Chance-constrained optimization is an important method for managing risk arising from random variations in natural resource systems, but the probabilistic formulations often pose mathematical programming problems that cannot be solved with exact methods. A heuristic estimation method for these problems is presented that combines a formulation for order statistic...

Accurate estimation of human body orientation from RGB-D sensors.

PubMed

Liu, Wu; Zhang, Yongdong; Tang, Sheng; Tang, Jinhui; Hong, Richang; Li, Jintao

2013-10-01

Accurate estimation of human body orientation can significantly enhance the analysis of human behavior, which is a fundamental task in the field of computer vision. However, existing orientation estimation methods cannot handle the various body poses and appearances. In this paper, we propose an innovative RGB-D-based orientation estimation method to address these challenges. By utilizing the RGB-D information, which can be real time acquired by RGB-D sensors, our method is robust to cluttered environment, illumination change and partial occlusions. Specifically, efficient static and motion cue extraction methods are proposed based on the RGB-D superpixels to reduce the noise of depth data. Since it is hard to discriminate all the 360 (°) orientation using static cues or motion cues independently, we propose to utilize a dynamic Bayesian network system (DBNS) to effectively employ the complementary nature of both static and motion cues. In order to verify our proposed method, we build a RGB-D-based human body orientation dataset that covers a wide diversity of poses and appearances. Our intensive experimental evaluations on this dataset demonstrate the effectiveness and efficiency of the proposed method.

Evaluation of human health risks posed by carcinogenic and non-carcinogenic multiple contaminants associated with consumption of fish from Taihu Lake, China.

PubMed

Yu, Yingxin; Wang, Xinxin; Yang, Dan; Lei, Bingli; Zhang, Xiaolan; Zhang, Xinyu

2014-07-01

The present study estimated the human daily intake and uptake of organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), polycyclic aromatic hydrocarbons (PAHs), and toxic trace elements [mercury (Hg), chromium (Cr), cadmium (Cd), and arsenic (As)] due to consumption of fish from Taihu Lake, China, and the associated potential health risks posed by these contaminants. The health risks posed by the contaminants were assessed using a risk quotient of the fish consumption rate to the maximum allowable fish consumption rate considering the contaminants for carcinogenic and non-carcinogenic effect endpoints. The results showed that fish consumption would not pose non-cancer risks. However, some species would cause a cancer risk. Relative risks of the contaminants were calculated to investigate the contaminant which posed the highest risk to humans. As a result, in view of the contaminants for carcinogenic effects, As was the contaminant which posed the highest risk to humans. However, when non-carcinogenic effects of the contaminants were considered, Hg posed the highest risk. The risk caused by PBDEs was negligible. The results demonstrated that traditional contaminants, such as As, Hg, DDTs (dichlorodiphenyltrichloroethane and its metabolites), and PCBs, require more attention in Taihu Lake than the other target contaminants. Copyright © 2014 Elsevier Ltd. All rights reserved.

Accuracy assessment of fluoroscopy-transesophageal echocardiography registration

NASA Astrophysics Data System (ADS)

Lang, Pencilla; Seslija, Petar; Bainbridge, Daniel; Guiraudon, Gerard M.; Jones, Doug L.; Chu, Michael W.; Holdsworth, David W.; Peters, Terry M.

2011-03-01

This study assesses the accuracy of a new transesophageal (TEE) ultrasound (US) fluoroscopy registration technique designed to guide percutaneous aortic valve replacement. In this minimally invasive procedure, a valve is inserted into the aortic annulus via a catheter. Navigation and positioning of the valve is guided primarily by intra-operative fluoroscopy. Poor anatomical visualization of the aortic root region can result in incorrect positioning, leading to heart valve embolization, obstruction of the coronary ostia and acute kidney injury. The use of TEE US images to augment intra-operative fluoroscopy provides significant improvements to image-guidance. Registration is achieved using an image-based TEE probe tracking technique and US calibration. TEE probe tracking is accomplished using a single-perspective pose estimation algorithm. Pose estimation from a single image allows registration to be achieved using only images collected in standard OR workflow. Accuracy of this registration technique is assessed using three models: a point target phantom, a cadaveric porcine heart with implanted fiducials, and in-vivo porcine images. Results demonstrate that registration can be achieved with an RMS error of less than 1.5mm, which is within the clinical accuracy requirements of 5mm. US-fluoroscopy registration based on single-perspective pose estimation demonstrates promise as a method for providing guidance to percutaneous aortic valve replacement procedures. Future work will focus on real-time implementation and a visualization system that can be used in the operating room.

Developing a particle tracking surrogate model to improve inversion of ground water - Surface water models

NASA Astrophysics Data System (ADS)

Cousquer, Yohann; Pryet, Alexandre; Atteia, Olivier; Ferré, Ty P. A.; Delbart, Célestine; Valois, Rémi; Dupuy, Alain

2018-03-01

The inverse problem of groundwater models is often ill-posed and model parameters are likely to be poorly constrained. Identifiability is improved if diverse data types are used for parameter estimation. However, some models, including detailed solute transport models, are further limited by prohibitive computation times. This often precludes the use of concentration data for parameter estimation, even if those data are available. In the case of surface water-groundwater (SW-GW) models, concentration data can provide SW-GW mixing ratios, which efficiently constrain the estimate of exchange flow, but are rarely used. We propose to reduce computational limits by simulating SW-GW exchange at a sink (well or drain) based on particle tracking under steady state flow conditions. Particle tracking is used to simulate advective transport. A comparison between the particle tracking surrogate model and an advective-dispersive model shows that dispersion can often be neglected when the mixing ratio is computed for a sink, allowing for use of the particle tracking surrogate model. The surrogate model was implemented to solve the inverse problem for a real SW-GW transport problem with heads and concentrations combined in a weighted hybrid objective function. The resulting inversion showed markedly reduced uncertainty in the transmissivity field compared to calibration on head data alone.

Multi-Cone Model for Estimating GPS Ionospheric Delays

NASA Technical Reports Server (NTRS)

Sparks, Lawrence; Komjathy, Attila; Mannucci, Anthony

2009-01-01

The multi-cone model is a computational model for estimating ionospheric delays of Global Positioning System (GPS) signals. It is a direct descendant of the conical-domain model. A primary motivation for the development of this model is the need to find alternatives for modeling slant delays at low latitudes, where ionospheric behavior poses an acute challenge for GPS signal-delay estimates based upon the thin-shell model of the ionosphere.

Pose determination of a blade implant in three dimensions from a single two-dimensional radiograph.

PubMed

Toti, Paolo; Barone, Antonio; Marconcini, Simone; Menchini-Fabris, Giovanni Battista; Martuscelli, Ranieri; Covani, Ugo

2018-05-01

The aim of the study was to introduce a mathematical method to estimate the correct pose of a blade by evaluating the radiographic features obtained from a single two-dimensional image. Blade-form implant bed preparation was performed using the piezosurgery device, and placement was attained with the use of magnetic mallet. The pose determination of the blade was described by means of three consecutive rotations defined by three angles of orientation (triplet φ, θ and ψ). Retrospective analysis on periapical radiographs was performed. This method was used to compare implant (axial length along the marker, i.e. the implant structure) vs angular correction factor (a trigonometric function of the triplet). The accuracy of the method was tested by generating two-dimensional radiographic simulations of the blades, which were then compared with the images of the implants as appearing on the real radiographs. Two patients had to be excluded from further evaluation because the values of the estimated pose angles showed a too-wide range to be effective for a good standardization of serial radiographs: intrapatient range from baseline to 1-year survey was > of a threshold determined by the clinicians (30°). The linear dependence between implant (CF°) and angular correction factor (CF^) was estimated by a robust linear regression, yielding the following coefficients: slope, 0.908; intercept, -0.092; and coefficient of determination, 0.924. The absolute error in accuracy was -0.29 ± 4.35, 0.23 ± 3.81 and 0.64 ± 1.18°, respectively, for the angles φ, θ and ψ. The present theoretical and experimental study established the possibility of determining, a posteriori, a unique triplet of angles (φ, θ and ψ) which described the pose of a blade upon a single two-dimensional radiograph, and of suggesting a method to detect cases in which the standardized geometric projection failed. The angular correction of the bone level yielded results very close to those obtained with an internal marker related to the implant length.

Taking the Missing Propensity Into Account When Estimating Competence Scores

PubMed Central

Pohl, Steffi; Carstensen, Claus H.

2014-01-01

When competence tests are administered, subjects frequently omit items. These missing responses pose a threat to correctly estimating the proficiency level. Newer model-based approaches aim to take nonignorable missing data processes into account by incorporating a latent missing propensity into the measurement model. Two assumptions are typically made when using these models: (1) The missing propensity is unidimensional and (2) the missing propensity and the ability are bivariate normally distributed. These assumptions may, however, be violated in real data sets and could, thus, pose a threat to the validity of this approach. The present study focuses on modeling competencies in various domains, using data from a school sample (N = 15,396) and an adult sample (N = 7,256) from the National Educational Panel Study. Our interest was to investigate whether violations of unidimensionality and the normal distribution assumption severely affect the performance of the model-based approach in terms of differences in ability estimates. We propose a model with a competence dimension, a unidimensional missing propensity and a distributional assumption more flexible than a multivariate normal. Using this model for ability estimation results in different ability estimates compared with a model ignoring missing responses. Implications for ability estimation in large-scale assessments are discussed. PMID:29795844

3D localization of electrophysiology catheters from a single x-ray cone-beam projection

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

Robert, Normand, E-mail: normand.robert@sri.utoronto.ca; Polack, George G.; Sethi, Benu

2015-10-15

Purpose: X-ray images allow the visualization of percutaneous devices such as catheters in real time but inherently lack depth information. The provision of 3D localization of these devices from cone beam x-ray projections would be advantageous for interventions such as electrophysiology (EP), whereby the operator needs to return a device to the same anatomical locations during the procedure. A method to achieve real-time 3D single view localization (SVL) of an object of known geometry from a single x-ray image is presented. SVL exploits the change in the magnification of an object as its distance from the x-ray source is varied.more » The x-ray projection of an object of interest is compared to a synthetic x-ray projection of a model of said object as its pose is varied. Methods: SVL was tested with a 3 mm spherical marker and an electrophysiology catheter. The effect of x-ray acquisition parameters on SVL was investigated. An independent reference localization method was developed to compare results when imaging a catheter translated via a computer controlled three-axes stage. SVL was also performed on clinical fluoroscopy image sequences. A commercial navigation system was used in some clinical image sequences for comparison. Results: SVL estimates exhibited little change as x-ray acquisition parameters were varied. The reproducibility of catheter position estimates in phantoms denoted by the standard deviations, (σ{sub x}, σ{sub y}, σ{sub z}) = (0.099 mm,  0.093 mm,  2.2 mm), where x and y are parallel to the detector plane and z is the distance from the x-ray source. Position estimates (x, y, z) exhibited a 4% systematic error (underestimation) when compared to the reference method. The authors demonstrated that EP catheters can be tracked in clinical fluoroscopic images. Conclusions: It has been shown that EP catheters can be localized in real time in phantoms and clinical images at fluoroscopic exposure rates. Further work is required to characterize performance in clinical images as well as the sensitivity to clinical image quality.« less

Dense-HOG-based drift-reduced 3D face tracking for infant pain monitoring

NASA Astrophysics Data System (ADS)

Saeijs, Ronald W. J. J.; Tjon A Ten, Walther E.; de With, Peter H. N.

2017-03-01

This paper presents a new algorithm for 3D face tracking intended for clinical infant pain monitoring. The algorithm uses a cylinder head model and 3D head pose recovery by alignment of dynamically extracted templates based on dense-HOG features. The algorithm includes extensions for drift reduction, using re-registration in combination with multi-pose state estimation by means of a square-root unscented Kalman filter. The paper reports experimental results on videos of moving infants in hospital who are relaxed or in pain. Results show good tracking behavior for poses up to 50 degrees from upright-frontal. In terms of eye location error relative to inter-ocular distance, the mean tracking error is below 9%.

History matching by spline approximation and regularization in single-phase areal reservoirs

NASA Technical Reports Server (NTRS)

Lee, T. Y.; Kravaris, C.; Seinfeld, J.

1986-01-01

An automatic history matching algorithm is developed based on bi-cubic spline approximations of permeability and porosity distributions and on the theory of regularization to estimate permeability or porosity in a single-phase, two-dimensional real reservoir from well pressure data. The regularization feature of the algorithm is used to convert the ill-posed history matching problem into a well-posed problem. The algorithm employs the conjugate gradient method as its core minimization method. A number of numerical experiments are carried out to evaluate the performance of the algorithm. Comparisons with conventional (non-regularized) automatic history matching algorithms indicate the superiority of the new algorithm with respect to the parameter estimates obtained. A quasioptimal regularization parameter is determined without requiring a priori information on the statistical properties of the observations.

Perceived Weight and Bullying Victimization in Boys and Girls

ERIC Educational Resources Information Center

Carey, Felicia R.; Wilkinson, Anna V.; Ranjit, Nalini; Mandell, Dorothy; Hoelscher, Deanna M.

2018-01-01

Background: Research suggests that perceived weight poses separate risks from objective weight on adolescents' risks of being bullied. We examined if the prevalence of bullying victimization differed by perceived and objective weight status, and how these associations varied by sex. Methods: Data were analyzed for 6716 8th and 11th graders from…

New to Teaching: Small Changes Can Produce Big Results!

ERIC Educational Resources Information Center

Shenton, Megan

2017-01-01

In this article, Megan Shenton, a final-year trainee teacher at Nottinghom Trent University, describes using "The Big Question" in her science teaching in a move away from objectives. The Big Question is an innovative pedagogical choice, where instead of implementing a learning objective, a question is posed at the start of the session…

Designing a Multi-Objective Multi-Support Accuracy Assessment of the 2001 National Land Cover Data (NLCD 2001) of the Conterminous United States

EPA Science Inventory

The database design and diverse application of NLCD 2001 pose significant challenges for accuracy assessment because numerous objectives are of interest, including accuracy of land cover, percent urban imperviousness, percent tree canopy, land-cover composition, and net change. ...

Textbook Presentations of Weight: Conceptual Difficulties and Language Ambiguities

ERIC Educational Resources Information Center

Taibu, Rex; Rudge, David; Schuster, David

2015-01-01

The term "weight" has multiple related meanings in both scientific and everyday usage. Even among experts and in textbooks, weight is ambiguously defined as either the gravitational force on an object or operationally as the magnitude of the force an object exerts on a measuring scale. This poses both conceptual and language difficulties…

Predicting Space Weather Effects on Close Approach Events

NASA Technical Reports Server (NTRS)

Hejduk, Matthew D.; Newman, Lauri K.; Besser, Rebecca L.; Pachura, Daniel A.

2015-01-01

The NASA Robotic Conjunction Assessment Risk Analysis (CARA) team sends ephemeris data to the Joint Space Operations Center (JSpOC) for conjunction assessment screening against the JSpOC high accuracy catalog and then assesses risk posed to protected assets from predicted close approaches. Since most spacecraft supported by the CARA team are located in LEO orbits, atmospheric drag is the primary source of state estimate uncertainty. Drag magnitude and uncertainty is directly governed by atmospheric density and thus space weather. At present the actual effect of space weather on atmospheric density cannot be accurately predicted because most atmospheric density models are empirical in nature, which do not perform well in prediction. The Jacchia-Bowman-HASDM 2009 (JBH09) atmospheric density model used at the JSpOC employs a solar storm active compensation feature that predicts storm sizes and arrival times and thus the resulting neutral density alterations. With this feature, estimation errors can occur in either direction (i.e., over- or under-estimation of density and thus drag). Although the exact effect of a solar storm on atmospheric drag cannot be determined, one can explore the effects of JBH09 model error on conjuncting objects' trajectories to determine if a conjunction is likely to become riskier, less risky, or pass unaffected. The CARA team has constructed a Space Weather Trade-Space tool that systematically alters the drag situation for the conjuncting objects and recalculates the probability of collision for each case to determine the range of possible effects on the collision risk. In addition to a review of the theory and the particulars of the tool, the different types of observed output will be explained, along with statistics of their frequency.

On Sternberg's "Reply to Gottfredson."

ERIC Educational Resources Information Center

Gottfredson, Linda S.

2003-01-01

Comments that R. Sternberg does not address criticisms previously made by L. Gottfredson, but rather discusses his theory of successful intelligence and answers only self-posed objections from unspecified critics. (SLD)

Post Pareto optimization-A case

NASA Astrophysics Data System (ADS)

Popov, Stoyan; Baeva, Silvia; Marinova, Daniela

2017-12-01

Simulation performance may be evaluated according to multiple quality measures that are in competition and their simultaneous consideration poses a conflict. In the current study we propose a practical framework for investigating such simulation performance criteria, exploring the inherent conflicts amongst them and identifying the best available tradeoffs, based upon multi-objective Pareto optimization. This approach necessitates the rigorous derivation of performance criteria to serve as objective functions and undergo vector optimization. We demonstrate the effectiveness of our proposed approach by applying it with multiple stochastic quality measures. We formulate performance criteria of this use-case, pose an optimization problem, and solve it by means of a simulation-based Pareto approach. Upon attainment of the underlying Pareto Frontier, we analyze it and prescribe preference-dependent configurations for the optimal simulation training.

Taking the Missing Propensity into Account When Estimating Competence Scores: Evaluation of Item Response Theory Models for Nonignorable Omissions

ERIC Educational Resources Information Center

Köhler, Carmen; Pohl, Steffi; Carstensen, Claus H.

2015-01-01

When competence tests are administered, subjects frequently omit items. These missing responses pose a threat to correctly estimating the proficiency level. Newer model-based approaches aim to take nonignorable missing data processes into account by incorporating a latent missing propensity into the measurement model. Two assumptions are typically…

Opportunities and Challenges for Personal Heat Exposure Research

PubMed Central

Kuras, Evan R.; Richardson, Molly B.; Calkins, Miriam M.; Ebi, Kristie L.; Hess, Jeremy J.; Kintziger, Kristina W.; Jagger, Meredith A.; Middel, Ariane; Scott, Anna A.; Spector, June T.; Uejio, Christopher K.; Vanos, Jennifer K.; Zaitchik, Benjamin F.; Gohlke, Julia M.

2017-01-01

Background: Environmental heat exposure is a public health concern. The impacts of environmental heat on mortality and morbidity at the population scale are well documented, but little is known about specific exposures that individuals experience. Objectives: The first objective of this work was to catalyze discussion of the role of personal heat exposure information in research and risk assessment. The second objective was to provide guidance regarding the operationalization of personal heat exposure research methods. Discussion: We define personal heat exposure as realized contact between a person and an indoor or outdoor environment that poses a risk of increases in body core temperature and/or perceived discomfort. Personal heat exposure can be measured directly with wearable monitors or estimated indirectly through the combination of time–activity and meteorological data sets. Complementary information to understand individual-scale drivers of behavior, susceptibility, and health and comfort outcomes can be collected from additional monitors, surveys, interviews, ethnographic approaches, and additional social and health data sets. Personal exposure research can help reveal the extent of exposure misclassification that occurs when individual exposure to heat is estimated using ambient temperature measured at fixed sites and can provide insights for epidemiological risk assessment concerning extreme heat. Conclusions: Personal heat exposure research provides more valid and precise insights into how often people encounter heat conditions and when, where, to whom, and why these encounters occur. Published literature on personal heat exposure is limited to date, but existing studies point to opportunities to inform public health practice regarding extreme heat, particularly where fine-scale precision is needed to reduce health consequences of heat exposure. https://doi.org/10.1289/EHP556 PMID:28796630

Covariance Matrix Estimation for the Cryo-EM Heterogeneity Problem*

PubMed Central

Katsevich, E.; Katsevich, A.; Singer, A.

2015-01-01

In cryo-electron microscopy (cryo-EM), a microscope generates a top view of a sample of randomly oriented copies of a molecule. The problem of single particle reconstruction (SPR) from cryo-EM is to use the resulting set of noisy two-dimensional projection images taken at unknown directions to reconstruct the three-dimensional (3D) structure of the molecule. In some situations, the molecule under examination exhibits structural variability, which poses a fundamental challenge in SPR. The heterogeneity problem is the task of mapping the space of conformational states of a molecule. It has been previously suggested that the leading eigenvectors of the covariance matrix of the 3D molecules can be used to solve the heterogeneity problem. Estimating the covariance matrix is challenging, since only projections of the molecules are observed, but not the molecules themselves. In this paper, we formulate a general problem of covariance estimation from noisy projections of samples. This problem has intimate connections with matrix completion problems and high-dimensional principal component analysis. We propose an estimator and prove its consistency. When there are finitely many heterogeneity classes, the spectrum of the estimated covariance matrix reveals the number of classes. The estimator can be found as the solution to a certain linear system. In the cryo-EM case, the linear operator to be inverted, which we term the projection covariance transform, is an important object in covariance estimation for tomographic problems involving structural variation. Inverting it involves applying a filter akin to the ramp filter in tomography. We design a basis in which this linear operator is sparse and thus can be tractably inverted despite its large size. We demonstrate via numerical experiments on synthetic datasets the robustness of our algorithm to high levels of noise. PMID:25699132

A Probabilistic Feature Map-Based Localization System Using a Monocular Camera.

PubMed

Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

2015-08-31

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments.

A Probabilistic Feature Map-Based Localization System Using a Monocular Camera

PubMed Central

Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

2015-01-01

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments. PMID:26404284

Prostate Brachytherapy Seed Reconstruction with Gaussian Blurring and Optimal Coverage Cost

PubMed Central

Lee, Junghoon; Liu, Xiaofeng; Jain, Ameet K.; Song, Danny Y.; Burdette, E. Clif; Prince, Jerry L.; Fichtinger, Gabor

2009-01-01

Intraoperative dosimetry in prostate brachytherapy requires localization of the implanted radioactive seeds. A tomosynthesis-based seed reconstruction method is proposed. A three-dimensional volume is reconstructed from Gaussian-blurred projection images and candidate seed locations are computed from the reconstructed volume. A false positive seed removal process, formulated as an optimal coverage problem, iteratively removes “ghost” seeds that are created by tomosynthesis reconstruction. In an effort to minimize pose errors that are common in conventional C-arms, initial pose parameter estimates are iteratively corrected by using the detected candidate seeds as fiducials, which automatically “focuses” the collected images and improves successive reconstructed volumes. Simulation results imply that the implanted seed locations can be estimated with a detection rate of ≥ 97.9% and ≥ 99.3% from three and four images, respectively, when the C-arm is calibrated and the pose of the C-arm is known. The algorithm was also validated on phantom data sets successfully localizing the implanted seeds from four or five images. In a Phase-1 clinical trial, we were able to localize the implanted seeds from five intraoperative fluoroscopy images with 98.8% (STD=1.6) overall detection rate. PMID:19605321

Camera-pose estimation via projective Newton optimization on the manifold.

PubMed

Sarkis, Michel; Diepold, Klaus

2012-04-01

Determining the pose of a moving camera is an important task in computer vision. In this paper, we derive a projective Newton algorithm on the manifold to refine the pose estimate of a camera. The main idea is to benefit from the fact that the 3-D rigid motion is described by the special Euclidean group, which is a Riemannian manifold. The latter is equipped with a tangent space defined by the corresponding Lie algebra. This enables us to compute the optimization direction, i.e., the gradient and the Hessian, at each iteration of the projective Newton scheme on the tangent space of the manifold. Then, the motion is updated by projecting back the variables on the manifold itself. We also derive another version of the algorithm that employs homeomorphic parameterization to the special Euclidean group. We test the algorithm on several simulated and real image data sets. Compared with the standard Newton minimization scheme, we are now able to obtain the full numerical formula of the Hessian with a 60% decrease in computational complexity. Compared with Levenberg-Marquardt, the results obtained are more accurate while having a rather similar complexity.

Superrotation on Venus, on Titan, and Elsewhere

NASA Astrophysics Data System (ADS)

Read, Peter L.; Lebonnois, Sebastien

2018-05-01

The superrotation of the atmospheres of Venus and Titan has puzzled dynamicists for many years and seems to put these planets in a very different dynamical regime from most other planets. In this review, we consider how to define superrotation objectively and explore the constraints that determine its occurrence. Atmospheric superrotation also occurs elsewhere in the Solar System and beyond, and we compare Venus and Titan with Earth and other planets for which wind estimates are available. The extreme superrotation on Venus and Titan poses some difficult challenges for numerical models of atmospheric circulation, much more difficult than for more rapidly rotating planets such as Earth or Mars. We consider mechanisms for generating and maintaining a superrotating state, all of which involve a global meridional overturning circulation. The role of nonaxisymmetric eddies is crucial, however, but the detailed mechanisms may differ between Venus, Titan, and other planets.

Implications of clinical trial design on sample size requirements.

PubMed

Leon, Andrew C

2008-07-01

The primary goal in designing a randomized controlled clinical trial (RCT) is to minimize bias in the estimate of treatment effect. Randomized group assignment, double-blinded assessments, and control or comparison groups reduce the risk of bias. The design must also provide sufficient statistical power to detect a clinically meaningful treatment effect and maintain a nominal level of type I error. An attempt to integrate neurocognitive science into an RCT poses additional challenges. Two particularly relevant aspects of such a design often receive insufficient attention in an RCT. Multiple outcomes inflate type I error, and an unreliable assessment process introduces bias and reduces statistical power. Here we describe how both unreliability and multiple outcomes can increase the study costs and duration and reduce the feasibility of the study. The objective of this article is to consider strategies that overcome the problems of unreliability and multiplicity.

Prevalence of Salmonella among waterfowl along the Texas Gulf coast.

PubMed

Grigar, M K; Cummings, K J; Rankin, S C

2017-12-01

Migratory waterfowl may play a role in the ecology and transmission of zoonotic pathogens, given their ability to travel long distances and their use of varied habitats. Our objectives were to estimate the prevalence of Salmonella among waterfowl along the Texas Gulf coast and to characterize the isolates. Faecal samples were collected from hunter-harvested waterfowl at four wildlife management areas from September through November, 2016. Standard bacteriologic culture methods were used to isolate Salmonella from samples, and isolates were characterized by serotyping and anti-microbial susceptibility testing. The apparent prevalence of faecal Salmonella shedding was 0.5% (2/375). Serotypes identified were Thompson and Braenderup, and both isolates were susceptible to all anti-microbial agents tested. Although faecal contamination of agricultural fields or surface waters could serve as a potential source of zoonotic Salmonella transmission, waterfowl along the Gulf coast during the fall hunting season appear to pose minimal risk. © 2017 Blackwell Verlag GmbH.

Multithreaded hybrid feature tracking for markerless augmented reality.

PubMed

Lee, Taehee; Höllerer, Tobias

2009-01-01

We describe a novel markerless camera tracking approach and user interaction methodology for augmented reality (AR) on unprepared tabletop environments. We propose a real-time system architecture that combines two types of feature tracking. Distinctive image features of the scene are detected and tracked frame-to-frame by computing optical flow. In order to achieve real-time performance, multiple operations are processed in a synchronized multi-threaded manner: capturing a video frame, tracking features using optical flow, detecting distinctive invariant features, and rendering an output frame. We also introduce user interaction methodology for establishing a global coordinate system and for placing virtual objects in the AR environment by tracking a user's outstretched hand and estimating a camera pose relative to it. We evaluate the speed and accuracy of our hybrid feature tracking approach, and demonstrate a proof-of-concept application for enabling AR in unprepared tabletop environments, using bare hands for interaction.

The research and application of visual saliency and adaptive support vector machine in target tracking field.

PubMed

Chen, Yuantao; Xu, Weihong; Kuang, Fangjun; Gao, Shangbing

2013-01-01

The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking's accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM). Furthermore, the paper's algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target's saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.

Quantitative imaging of aggregated emulsions.

PubMed

Penfold, Robert; Watson, Andrew D; Mackie, Alan R; Hibberd, David J

2006-02-28

Noise reduction, restoration, and segmentation methods are developed for the quantitative structural analysis in three dimensions of aggregated oil-in-water emulsion systems imaged by fluorescence confocal laser scanning microscopy. Mindful of typical industrial formulations, the methods are demonstrated for concentrated (30% volume fraction) and polydisperse emulsions. Following a regularized deconvolution step using an analytic optical transfer function and appropriate binary thresholding, novel application of the Euclidean distance map provides effective discrimination of closely clustered emulsion droplets with size variation over at least 1 order of magnitude. The a priori assumption of spherical nonintersecting objects provides crucial information to combat the ill-posed inverse problem presented by locating individual particles. Position coordinates and size estimates are recovered with sufficient precision to permit quantitative study of static geometrical features. In particular, aggregate morphology is characterized by a novel void distribution measure based on the generalized Apollonius problem. This is also compared with conventional Voronoi/Delauney analysis.

Recovering an elastic obstacle containing embedded objects by the acoustic far-field measurements

NASA Astrophysics Data System (ADS)

Qu, Fenglong; Yang, Jiaqing; Zhang, Bo

2018-01-01

Consider the inverse scattering problem of time-harmonic acoustic waves by a 3D bounded elastic obstacle which may contain embedded impenetrable obstacles inside. We propose a novel and simple technique to show that the elastic obstacle can be uniquely recovered by the acoustic far-field pattern at a fixed frequency, disregarding its contents. Our method is based on constructing a well-posed modified interior transmission problem on a small domain and makes use of an a priori estimate for both the acoustic and elastic wave fields in the usual H 1-norm. In the case when there is no obstacle embedded inside the elastic body, our method gives a much simpler proof for the uniqueness result obtained previously in the literature (Natroshvili et al 2000 Rend. Mat. Serie VII 20 57-92 Monk and Selgas 2009 Inverse Problems Imaging 3 173-98).

User-assisted video segmentation system for visual communication

NASA Astrophysics Data System (ADS)

Wu, Zhengping; Chen, Chun

2002-01-01

Video segmentation plays an important role for efficient storage and transmission in visual communication. In this paper, we introduce a novel video segmentation system using point tracking and contour formation techniques. Inspired by the results from the study of the human visual system, we intend to solve the video segmentation problem into three separate phases: user-assisted feature points selection, feature points' automatic tracking, and contour formation. This splitting relieves the computer of ill-posed automatic segmentation problems, and allows a higher level of flexibility of the method. First, the precise feature points can be found using a combination of user assistance and an eigenvalue-based adjustment. Second, the feature points in the remaining frames are obtained using motion estimation and point refinement. At last, contour formation is used to extract the object, and plus a point insertion process to provide the feature points for next frame's tracking.

Three-dimensional kinematic estimation of mobile-bearing total knee arthroplasty from x-ray fluoroscopic images

NASA Astrophysics Data System (ADS)

Yamazaki, Takaharu; Futai, Kazuma; Tomita, Tetsuya; Sato, Yoshinobu; Yoshikawa, Hideki; Tamura, Shinichi; Sugamoto, Kazuomi

2011-03-01

To achieve 3D kinematic analysis of total knee arthroplasty (TKA), 2D/3D registration techniques, which use X-ray fluoroscopic images and computer-aided design (CAD) model of the knee implant, have attracted attention in recent years. These techniques could provide information regarding the movement of radiopaque femoral and tibial components but could not provide information of radiolucent polyethylene insert, because the insert silhouette on X-ray image did not appear clearly. Therefore, it was difficult to obtain 3D kinemaitcs of polyethylene insert, particularly mobile-bearing insert that move on the tibial component. This study presents a technique and the accuracy for 3D kinematic analysis of mobile-bearing insert in TKA using X-ray fluoroscopy, and finally performs clinical applications. For a 3D pose estimation technique of the mobile-bearing insert in TKA using X-ray fluoroscopy, tantalum beads and CAD model with its beads are utilized, and the 3D pose of the insert model is estimated using a feature-based 2D/3D registration technique. In order to validate the accuracy of the present technique, experiments including computer simulation test were performed. The results showed the pose estimation accuracy was sufficient for analyzing mobile-bearing TKA kinematics (the RMS error: about 1.0 mm, 1.0 degree). In the clinical applications, seven patients with mobile-bearing TKA in deep knee bending motion were studied and analyzed. Consequently, present technique enables us to better understand mobile-bearing TKA kinematics, and this type of evaluation was thought to be helpful for improving implant design and optimizing TKA surgical techniques.

A Single Camera Motion Capture System for Human-Computer Interaction

NASA Astrophysics Data System (ADS)

Okada, Ryuzo; Stenger, Björn

This paper presents a method for markerless human motion capture using a single camera. It uses tree-based filtering to efficiently propagate a probability distribution over poses of a 3D body model. The pose vectors and associated shapes are arranged in a tree, which is constructed by hierarchical pairwise clustering, in order to efficiently evaluate the likelihood in each frame. Anew likelihood function based on silhouette matching is proposed that improves the pose estimation of thinner body parts, i. e. the limbs. The dynamic model takes self-occlusion into account by increasing the variance of occluded body-parts, thus allowing for recovery when the body part reappears. We present two applications of our method that work in real-time on a Cell Broadband Engine™: a computer game and a virtual clothing application.

Adaptive relative pose control for autonomous spacecraft rendezvous and proximity operations with thrust misalignment and model uncertainties

NASA Astrophysics Data System (ADS)

Sun, Liang; Zheng, Zewei

2017-04-01

An adaptive relative pose control strategy is proposed for a pursue spacecraft in proximity operations on a tumbling target. Relative position vector between two spacecraft is required to direct towards the docking port of the target while the attitude of them must be synchronized. With considering the thrust misalignment of pursuer, an integrated controller for relative translational and relative rotational dynamics is developed by using norm-wise adaptive estimations. Parametric uncertainties, unknown coupled dynamics, and bounded external disturbances are compensated online by adaptive update laws. It is proved via Lyapunov stability theory that the tracking errors of relative pose converge to zero asymptotically. Numerical simulations including six degrees-of-freedom rigid body dynamics are performed to demonstrate the effectiveness of the proposed controller.

Flight Results from the HST SM4 Relative Navigation Sensor System

NASA Technical Reports Server (NTRS)

Naasz, Bo; Eepoel, John Van; Queen, Steve; Southward, C. Michael; Hannah, Joel

2010-01-01

On May 11, 2009, Space Shuttle Atlantis roared off of Launch Pad 39A enroute to the Hubble Space Telescope (HST) to undertake its final servicing of HST, Servicing Mission 4. Onboard Atlantis was a small payload called the Relative Navigation Sensor experiment, which included three cameras of varying focal ranges, avionics to record images and estimate, in real time, the relative position and attitude (aka "pose") of the telescope during rendezvous and deploy. The avionics package, known as SpaceCube and developed at the Goddard Space Flight Center, performed image processing using field programmable gate arrays to accelerate this process, and in addition executed two different pose algorithms in parallel, the Goddard Natural Feature Image Recognition and the ULTOR Passive Pose and Position Engine (P3E) algorithms

Mobile camera-space manipulation

NASA Technical Reports Server (NTRS)

Seelinger, Michael J. (Inventor); Yoder, John-David S. (Inventor); Skaar, Steven B. (Inventor)

2001-01-01

The invention is a method of using computer vision to control systems consisting of a combination of holonomic and nonholonomic degrees of freedom such as a wheeled rover equipped with a robotic arm, a forklift, and earth-moving equipment such as a backhoe or a front-loader. Using vision sensors mounted on the mobile system and the manipulator, the system establishes a relationship between the internal joint configuration of the holonomic degrees of freedom of the manipulator and the appearance of features on the manipulator in the reference frames of the vision sensors. Then, the system, perhaps with the assistance of an operator, identifies the locations of the target object in the reference frames of the vision sensors. Using this target information, along with the relationship described above, the system determines a suitable trajectory for the nonholonomic degrees of freedom of the base to follow towards the target object. The system also determines a suitable pose or series of poses for the holonomic degrees of freedom of the manipulator. With additional visual samples, the system automatically updates the trajectory and final pose of the manipulator so as to allow for greater precision in the overall final position of the system.

Pose estimation and tracking of non-cooperative rocket bodies using Time-of-Flight cameras

NASA Astrophysics Data System (ADS)

Gómez Martínez, Harvey; Giorgi, Gabriele; Eissfeller, Bernd

2017-10-01

This paper presents a methodology for estimating the position and orientation of a rocket body in orbit - the target - undergoing a roto-translational motion, with respect to a chaser spacecraft, whose task is to match the target dynamics for a safe rendezvous. During the rendezvous maneuver the chaser employs a Time-of-Flight camera that acquires a point cloud of 3D coordinates mapping the sensed target surface. Once the system identifies the target, it initializes the chaser-to-target relative position and orientation. After initialization, a tracking procedure enables the system to sense the evolution of the target's pose between frames. The proposed algorithm is evaluated using simulated point clouds, generated with a CAD model of the Cosmos-3M upper stage and the PMD CamCube 3.0 camera specifications.

An objective rationale for the choice of regularisation parameter with application to global multiple-frequency S-wave tomography

NASA Astrophysics Data System (ADS)

Zaroli, C.; Sambridge, M.; Lévêque, J.-J.; Debayle, E.; Nolet, G.

2013-06-01

In a linear ill-posed inverse problem, the regularisation parameter (damping) controls the balance between minimising both the residual data misfit and the model norm. Poor knowledge of data uncertainties often makes the selection of damping rather arbitrary. To go beyond that subjectivity, an objective rationale for the choice of damping is presented, which is based on the coherency of delay-time estimates in different frequency bands. Our method is tailored to the problem of global Multiple-Frequency Tomography (MFT), using a data set of 287 078 S-wave delay-times measured in five frequency bands (10, 15, 22, 34, 51 s central periods). Whereas for each ray path the delay-time estimates should vary coherently from one period to the other, the noise most likely is not coherent. Thus, the lack of coherency of the information in different frequency bands is exploited, using an analogy with the cross-validation method, to identify models dominated by noise. In addition, a sharp change of behaviour of the model ℓ∞-norm, as the damping becomes lower than a threshold value, is interpreted as the signature of data noise starting to significantly pollute at least one model component. Models with damping larger than this threshold are diagnosed as being constructed with poor data exploitation. Finally, a preferred model is selected from the remaining range of permitted model solutions. This choice is quasi-objective in terms of model interpretation, as the selected model shows a high degree of similarity with almost all other permitted models (correlation superior to 98% up to spherical harmonic degree 80). The obtained tomographic model is displayed in mid lower-mantle (660-1910 km depth), and is shown to be compatible with three other recent global shear-velocity models. A wider application of the presented rationale should permit us to converge towards more objective seismic imaging of the Earth's mantle.

An objective rationale for the choice of regularisation parameter with application to global multiple-frequency S-wave tomography

NASA Astrophysics Data System (ADS)

Zaroli, C.; Sambridge, M.; Lévêque, J.-J.; Debayle, E.; Nolet, G.

2013-10-01

In a linear ill-posed inverse problem, the regularisation parameter (damping) controls the balance between minimising both the residual data misfit and the model norm. Poor knowledge of data uncertainties often makes the selection of damping rather arbitrary. To go beyond that subjectivity, an objective rationale for the choice of damping is presented, which is based on the coherency of delay-time estimates in different frequency bands. Our method is tailored to the problem of global multiple-frequency tomography (MFT), using a data set of 287 078 S-wave delay times measured in five frequency bands (10, 15, 22, 34, and 51 s central periods). Whereas for each ray path the delay-time estimates should vary coherently from one period to the other, the noise most likely is not coherent. Thus, the lack of coherency of the information in different frequency bands is exploited, using an analogy with the cross-validation method, to identify models dominated by noise. In addition, a sharp change of behaviour of the model ℓ∞-norm, as the damping becomes lower than a threshold value, is interpreted as the signature of data noise starting to significantly pollute at least one model component. Models with damping larger than this threshold are diagnosed as being constructed with poor data exploitation. Finally, a preferred model is selected from the remaining range of permitted model solutions. This choice is quasi-objective in terms of model interpretation, as the selected model shows a high degree of similarity with almost all other permitted models (correlation superior to 98% up to spherical harmonic degree 80). The obtained tomographic model is displayed in the mid lower-mantle (660-1910 km depth), and is shown to be compatible with three other recent global shear-velocity models. A wider application of the presented rationale should permit us to converge towards more objective seismic imaging of Earth's mantle.

Optical neural network system for pose determination of spinning satellites

NASA Technical Reports Server (NTRS)

Lee, Andrew; Casasent, David

1990-01-01

An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

Hand Pose Estimation by Fusion of Inertial and Magnetic Sensing Aided by a Permanent Magnet.

PubMed

Kortier, Henk G; Antonsson, Jacob; Schepers, H Martin; Gustafsson, Fredrik; Veltink, Peter H

2015-09-01

Tracking human body motions using inertial sensors has become a well-accepted method in ambulatory applications since the subject is not confined to a lab-bounded volume. However, a major drawback is the inability to estimate relative body positions over time because inertial sensor information only allows position tracking through strapdown integration, but does not provide any information about relative positions. In addition, strapdown integration inherently results in drift of the estimated position over time. We propose a novel method in which a permanent magnet combined with 3-D magnetometers and 3-D inertial sensors are used to estimate the global trunk orientation and relative pose of the hand with respect to the trunk. An Extended Kalman Filter is presented to fuse estimates obtained from inertial sensors with magnetic updates such that the position and orientation between the human hand and trunk as well as the global trunk orientation can be estimated robustly. This has been demonstrated in multiple experiments in which various hand tasks were performed. The most complex task in which simultaneous movements of both trunk and hand were performed resulted in an average rms position difference with an optical reference system of 19.7±2.2 mm whereas the relative trunk-hand and global trunk orientation error was 2.3±0.9 and 8.6±8.7 deg respectively.

A Geology-Based Estimate of Connate Water Salinity Distribution

DTIC Science & Technology

2014-09-01

poses serious environmental concerns if connate water is mobilized into shallow aquifers or surface water systems. Estimating the distribution of...groundwater flow and salinity transport near the Herbert Hoover Dike (HHD) surrounding Lake Okeechobee in Florida . The simulations were conducted using the...on the geologic configuration at equilibrium, and the horizontal salinity distribution is strongly linked to aquifer connectivity because

Automatically Determining Scale Within Unstructured Point Clouds

NASA Astrophysics Data System (ADS)

Kadamen, Jayren; Sithole, George

2016-06-01

Three dimensional models obtained from imagery have an arbitrary scale and therefore have to be scaled. Automatically scaling these models requires the detection of objects in these models which can be computationally intensive. Real-time object detection may pose problems for applications such as indoor navigation. This investigation poses the idea that relational cues, specifically height ratios, within indoor environments may offer an easier means to obtain scales for models created using imagery. The investigation aimed to show two things, (a) that the size of objects, especially the height off ground is consistent within an environment, and (b) that based on this consistency, objects can be identified and their general size used to scale a model. To test the idea a hypothesis is first tested on a terrestrial lidar scan of an indoor environment. Later as a proof of concept the same test is applied to a model created using imagery. The most notable finding was that the detection of objects can be more readily done by studying the ratio between the dimensions of objects that have their dimensions defined by human physiology. For example the dimensions of desks and chairs are related to the height of an average person. In the test, the difference between generalised and actual dimensions of objects were assessed. A maximum difference of 3.96% (2.93cm) was observed from automated scaling. By analysing the ratio between the heights (distance from the floor) of the tops of objects in a room, identification was also achieved.

Pose tracking for augmented reality applications in outdoor archaeological sites

NASA Astrophysics Data System (ADS)

Younes, Georges; Asmar, Daniel; Elhajj, Imad; Al-Harithy, Howayda

2017-01-01

In recent years, agencies around the world have invested huge amounts of effort toward digitizing many aspects of the world's cultural heritage. Of particular importance is the digitization of outdoor archaeological sites. In the spirit of valorization of this digital information, many groups have developed virtual or augmented reality (AR) computer applications themed around a particular archaeological object. The problem of pose tracking in outdoor AR applications is addressed. Different positional systems are analyzed, resulting in the selection of a monocular camera-based user tracker. The limitations that challenge this technique from map generation, scale, anchoring, to lighting conditions are analyzed and systematically addressed. Finally, as a case study, our pose tracking system is implemented within an AR experience in the Byblos Roman theater in Lebanon.

Robust Vision-Based Pose Estimation Algorithm for AN Uav with Known Gravity Vector

NASA Astrophysics Data System (ADS)

Kniaz, V. V.

2016-06-01

Accurate estimation of camera external orientation with respect to a known object is one of the central problems in photogrammetry and computer vision. In recent years this problem is gaining an increasing attention in the field of UAV autonomous flight. Such application requires a real-time performance and robustness of the external orientation estimation algorithm. The accuracy of the solution is strongly dependent on the number of reference points visible on the given image. The problem only has an analytical solution if 3 or more reference points are visible. However, in limited visibility conditions it is often needed to perform external orientation with only 2 visible reference points. In such case the solution could be found if the gravity vector direction in the camera coordinate system is known. A number of algorithms for external orientation estimation for the case of 2 known reference points and a gravity vector were developed to date. Most of these algorithms provide analytical solution in the form of polynomial equation that is subject to large errors in the case of complex reference points configurations. This paper is focused on the development of a new computationally effective and robust algorithm for external orientation based on positions of 2 known reference points and a gravity vector. The algorithm implementation for guidance of a Parrot AR.Drone 2.0 micro-UAV is discussed. The experimental evaluation of the algorithm proved its computational efficiency and robustness against errors in reference points positions and complex configurations.

Postprocessing of docked protein-ligand complexes using implicit solvation models.

PubMed

Lindström, Anton; Edvinsson, Lotta; Johansson, Andreas; Andersson, C David; Andersson, Ida E; Raubacher, Florian; Linusson, Anna

2011-02-28

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.

45 CFR 89.3 - Organizational integrity of recipients.

Code of Federal Regulations, 2014 CFR

2014-10-01

... prostitution and sex trafficking because of the psychological and physical risks they pose for women, men and children (“restricted activities”). A recipient will be found to have objective integrity and independence...

45 CFR 89.3 - Organizational integrity of recipients.

Code of Federal Regulations, 2013 CFR

2013-10-01

... prostitution and sex trafficking because of the psychological and physical risks they pose for women, men and children (“restricted activities”). A recipient will be found to have objective integrity and independence...

45 CFR 89.3 - Organizational integrity of recipients.

Code of Federal Regulations, 2012 CFR

2012-10-01

... prostitution and sex trafficking because of the psychological and physical risks they pose for women, men and children (“restricted activities”). A recipient will be found to have objective integrity and independence...

45 CFR 89.3 - Organizational integrity of recipients.

Code of Federal Regulations, 2011 CFR

2011-10-01

... prostitution and sex trafficking because of the psychological and physical risks they pose for women, men and children (“restricted activities”). A recipient will be found to have objective integrity and independence...

Auditory risk estimates for youth target shooting

PubMed Central

Meinke, Deanna K.; Murphy, William J.; Finan, Donald S.; Lankford, James E.; Flamme, Gregory A.; Stewart, Michael; Soendergaard, Jacob; Jerome, Trevor W.

2015-01-01

Objective To characterize the impulse noise exposure and auditory risk for youth recreational firearm users engaged in outdoor target shooting events. The youth shooting positions are typically standing or sitting at a table, which places the firearm closer to the ground or reflective surface when compared to adult shooters. Design Acoustic characteristics were examined and the auditory risk estimates were evaluated using contemporary damage-risk criteria for unprotected adult listeners and the 120-dB peak limit suggested by the World Health Organization (1999) for children. Study sample Impulses were generated by 26 firearm/ammunition configurations representing rifles, shotguns, and pistols used by youth. Measurements were obtained relative to a youth shooter’s left ear. Results All firearms generated peak levels that exceeded the 120 dB peak limit suggested by the WHO for children. In general, shooting from the seated position over a tabletop increases the peak levels, LAeq8 and reduces the unprotected maximum permissible exposures (MPEs) for both rifles and pistols. Pistols pose the greatest auditory risk when fired over a tabletop. Conclusion Youth should utilize smaller caliber weapons, preferably from the standing position, and always wear hearing protection whenever engaging in shooting activities to reduce the risk for auditory damage. PMID:24564688

Destructive materials thermal characteristics determination with application for spacecraft structures testing

NASA Astrophysics Data System (ADS)

Alifanov, O. M.; Budnik, S. A.; Nenarokomov, A. V.; Netelev, A. V.; Titov, D. M.

2013-04-01

In many practical situations it is impossible to measure directly thermal and thermokinetic properties of analyzed composite materials. The only way that can often be used to overcome these difficulties is indirect measurements. This type of measurements is usually formulated as the solution of inverse heat transfer problems. Such problems are ill-posed in mathematical sense and their main feature shows itself in the solution instabilities. That is why special regularizing methods are needed to solve them. The general method of iterative regularization is concerned with application to the estimation of materials properties. The objective of this paper is to estimate thermal and thermokinetic properties of advanced materials using the approach based on inverse methods. An experimental-computational system is presented for investigating the thermal and kinetics properties of composite materials by methods of inverse heat transfer problems and which is developed at the Thermal Laboratory of Department Space Systems Engineering, of Moscow Aviation Institute (MAI). The system is aimed at investigating the materials in conditions of unsteady contact and/or radiation heating over a wide range of temperature changes and heating rates in a vacuum, air and inert gas medium.

Robust face alignment under occlusion via regional predictive power estimation.

PubMed

Heng Yang; Xuming He; Xuhui Jia; Patras, Ioannis

2015-08-01

Face alignment has been well studied in recent years, however, when a face alignment model is applied on facial images with heavy partial occlusion, the performance deteriorates significantly. In this paper, instead of training an occlusion-aware model with visibility annotation, we address this issue via a model adaptation scheme that uses the result of a local regression forest (RF) voting method. In the proposed scheme, the consistency of the votes of the local RF in each of several oversegmented regions is used to determine the reliability of predicting the location of the facial landmarks. The latter is what we call regional predictive power (RPP). Subsequently, we adapt a holistic voting method (cascaded pose regression based on random ferns) by putting weights on the votes of each fern according to the RPP of the regions used in the fern tests. The proposed method shows superior performance over existing face alignment models in the most challenging data sets (COFW and 300-W). Moreover, it can also estimate with high accuracy (72.4% overlap ratio) which image areas belong to the face or nonface objects, on the heavily occluded images of the COFW data set, without explicit occlusion modeling.

STS-48 Pilot Reightler on OV-103's aft flight deck poses for ESC photo

NASA Technical Reports Server (NTRS)

1991-01-01

STS-48 Pilot Kenneth S. Reightler, Jr, positioned under overhead window W8, poses for an electronic still camera (ESC) photo on the aft flight deck of the earth-orbiting Discovery, Orbiter Vehicle (OV) 103. Crewmembers were testing the ESC as part of Development Test Objective (DTO) 648, Electronic Still Photography. The digital image was stored on a removable hard disk or small optical disk, and could be converted to a format suitable for downlink transmission. The ESC is making its initial appearance on this Space Shuttle mission.

Combined use of a priori data for fast system self-calibration of a non-rigid multi-camera fringe projection system

NASA Astrophysics Data System (ADS)

Stavroulakis, Petros I.; Chen, Shuxiao; Sims-Waterhouse, Danny; Piano, Samanta; Southon, Nicholas; Bointon, Patrick; Leach, Richard

2017-06-01

In non-rigid fringe projection 3D measurement systems, where either the camera or projector setup can change significantly between measurements or the object needs to be tracked, self-calibration has to be carried out frequently to keep the measurements accurate1. In fringe projection systems, it is common to use methods developed initially for photogrammetry for the calibration of the camera(s) in the system in terms of extrinsic and intrinsic parameters. To calibrate the projector(s) an extra correspondence between a pre-calibrated camera and an image created by the projector is performed. These recalibration steps are usually time consuming and involve the measurement of calibrated patterns on planes, before the actual object can continue to be measured after a motion of a camera or projector has been introduced in the setup and hence do not facilitate fast 3D measurement of objects when frequent experimental setup changes are necessary. By employing and combining a priori information via inverse rendering, on-board sensors, deep learning and leveraging a graphics processor unit (GPU), we assess a fine camera pose estimation method which is based on optimising the rendering of a model of a scene and the object to match the view from the camera. We find that the success of this calibration pipeline can be greatly improved by using adequate a priori information from the aforementioned sources.

A new approach to flood loss estimation and vulnerability assessment for historic buildings in England

NASA Astrophysics Data System (ADS)

Stephenson, V.; D'Ayala, D.

2013-10-01

The recent increase in frequency and severity of flooding in the UK has led to a shift in the perception of risk associated with flood hazards. This has extended to the conservation community, and the risks posed to historic structures that suffer from flooding are particularly concerning for those charged with preserving and maintaining such buildings. In order to fully appraise the risks in a manner appropriate to the complex issue of preservation, a new methodology is proposed that studies the nature of vulnerability of such structures, and places it in the context of risk assessment, accounting for the vulnerable object and the subsequent exposure of that object to flood hazards. The testing of the methodology is carried out using three urban case studies and the results of the survey analysis provide key findings and guidance on the development of fragility curves for historic structures exposed to flooding. This occurs through appraisal of key vulnerability indicators related to building form, structural and fabric integrity, and preservation of architectural and archaeological values. This in turn facilitates the production of strategies for mitigating and managing the losses threatened by such extreme climate events.

A Concise Guide to Feature Histograms with Applications to LIDAR-Based Spacecraft Relative Navigation

NASA Astrophysics Data System (ADS)

Rhodes, Andrew P.; Christian, John A.; Evans, Thomas

2017-12-01

With the availability and popularity of 3D sensors, it is advantageous to re-examine the use of point cloud descriptors for the purpose of pose estimation and spacecraft relative navigation. One popular descriptor is the oriented unique repeatable clustered viewpoint feature histogram (OUR-CVFH), which is most often utilized in personal and industrial robotics to simultaneously recognize and navigate relative to an object. Recent research into using the OUR-CVFH descriptor for spacecraft navigation has produced favorable results. Since OUR-CVFH is the most recent innovation in a large family of feature histogram point cloud descriptors, discussions of parameter settings and insights into its functionality are spread among various publications and online resources. This paper organizes the history of feature histogram point cloud descriptors for a straightforward explanation of their evolution. This article compiles all the requisite information needed to implement OUR-CVFH into one location, as well as providing useful suggestions on how to tune the generation parameters. This work is beneficial for anyone interested in using this histogram descriptor for object recognition or navigation - may it be personal robotics or spacecraft navigation.

3-D Object Pose Determination Using Complex EGI

DTIC Science & Technology

1990-10-01

the length of edges of the polyhedron from the EGI. Dane and Bajcsy [4] make use of the Gaussian Image to spatially segment a group of range points...involving real range data of two smooth objects were conducted. The two smooth objects are the torus and ellipsoid, whose databases have been created...in the simulations earlier. 5.0.1 Implementational Issues The torus and ellipsoid were crafted out of clay to resemble the models whose databases were

An Underwater Target Detection System for Electro-Optical Imagery Data

DTIC Science & Technology

2010-06-01

detection and segmentation of underwater mine-like objects in the EO images captured with a CCD-based image sensor. The main focus of this research is to...develop a robust detection algorithm that can be used to detect low contrast and partial underwater objects from the EO imagery with low false alarm rate...underwater target detection I. INTRODUCTION Automatic detection and recognition of underwater objects from EO imagery poses a serious challenge due to poor

Estimating initial contaminant mass based on fitting mass-depletion functions to contaminant mass discharge data: Testing method efficacy with SVE operations data

NASA Astrophysics Data System (ADS)

Mainhagu, J.; Brusseau, M. L.

2016-09-01

The mass of contaminant present at a site, particularly in the source zones, is one of the key parameters for assessing the risk posed by contaminated sites, and for setting and evaluating remediation goals and objectives. This quantity is rarely known and is challenging to estimate accurately. This work investigated the efficacy of fitting mass-depletion functions to temporal contaminant mass discharge (CMD) data as a means of estimating initial mass. Two common mass-depletion functions, exponential and power functions, were applied to historic soil vapor extraction (SVE) CMD data collected from 11 contaminated sites for which the SVE operations are considered to be at or close to essentially complete mass removal. The functions were applied to the entire available data set for each site, as well as to the early-time data (the initial 1/3 of the data available). Additionally, a complete differential-time analysis was conducted. The latter two analyses were conducted to investigate the impact of limited data on method performance, given that the primary mode of application would be to use the method during the early stages of a remediation effort. The estimated initial masses were compared to the total masses removed for the SVE operations. The mass estimates obtained from application to the full data sets were reasonably similar to the measured masses removed for both functions (13 and 15% mean error). The use of the early-time data resulted in a minimally higher variation for the exponential function (17%) but a much higher error (51%) for the power function. These results suggest that the method can produce reasonable estimates of initial mass useful for planning and assessing remediation efforts.

From belt picking to bin packing

NASA Astrophysics Data System (ADS)

Balslev, Ivar; Eriksen, René D.

2002-10-01

We face the problem of computer-vision aided robot grasping of objects with more or less random positions. This field is of vital importance in the further progress in flexible automation of industrial processes, since conventional methods using fixtures and/or vibration bowls are expensive and inflexible. We study various types of disorder: A) visually isolated objects lying in distinct resting modes on a flat homogenous conveyer belt, B) partially occluded objects lying in distinct resting modes on a flat homogenous conveyer belt, C) visually separated objects, unrestricted object-camera pose, and fully surrounded by background, D) partially occluded objects, unrestricted relative orientation, but with a sizeable fraction of their contour detectable using foreground-background separation, E) partially occluded objects with unrestricted pose and no help from foreground-background separation. The cases A), B), and - to some extend - D) are encountered in belt picking, while case E) is true bin picking. Since physical storage of products and components in industry is based on deep containers with many layers of somewhat disordered objects, the belt-picking concept is only the first step for achieving flexible, unsupervised parts feeding. We have developed and tested a generic, fast, and easily trainable system for the cases A) and B). The system is unique because it handles the perspective effects exactly so there is no restriction concerning object dimensions relative to the distance to the camera. We report on a strategy to be used in treating case C) using the principles developed for the cases A-B). We discuss possible strategies to be employed when going all the way to cases of D) and E).

Inappropriate Alarm Rates and Driver Annoyance

DOT National Transportation Integrated Search

1996-02-01

Future in-vehicle crash avoidance warning systems will inevitably deliver : inappropriate alarms from time to time, caused for example, by situations where : algorithms have correctly identified an object but pose no threat or danger to : the driver....

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

Kelbe, David; Oak Ridge National Lab.; van Aardt, Jan

Terrestrial laser scanning has demonstrated increasing potential for rapid comprehensive measurement of forest structure, especially when multiple scans are spatially registered in order to reduce the limitations of occlusion. Although marker-based registration techniques (based on retro-reflective spherical targets) are commonly used in practice, a blind marker-free approach is preferable, insofar as it supports rapid operational data acquisition. To support these efforts, we extend the pairwise registration approach of our earlier work, and develop a graph-theoretical framework to perform blind marker-free global registration of multiple point cloud data sets. Pairwise pose estimates are weighted based on their estimated error, in ordermore » to overcome pose conflict while exploiting redundant information and improving precision. The proposed approach was tested for eight diverse New England forest sites, with 25 scans collected at each site. Quantitative assessment was provided via a novel embedded confidence metric, with a mean estimated root-mean-square error of 7.2 cm and 89% of scans connected to the reference node. Lastly, this paper assesses the validity of the embedded multiview registration confidence metric and evaluates the performance of the proposed registration algorithm.« less

Modeling and Calculator Tools for State and Local Transportation Resources

EPA Pesticide Factsheets

Air quality models, calculators, guidance and strategies are offered for estimating and projecting vehicle air pollution, including ozone or smog-forming pollutants, particulate matter and other emissions that pose public health and air quality concerns.

Prioritizing pharmaceuticals in municipal wastewater

EPA Science Inventory

Oral presentation at SETAC North America 32nd annual meeting, describing our prioritization of active pharmaceutical ingredients (APIs), based on estimates of risks posed by API residues originating from municipal wastewater. Goals of this project include prioritization of APIs f...

Dynamic Human Body Modeling Using a Single RGB Camera.

PubMed

Zhu, Haiyu; Yu, Yao; Zhou, Yu; Du, Sidan

2016-03-18

In this paper, we present a novel automatic pipeline to build personalized parametric models of dynamic people using a single RGB camera. Compared to previous approaches that use monocular RGB images, our system can model a 3D human body automatically and incrementally, taking advantage of human motion. Based on coarse 2D and 3D poses estimated from image sequences, we first perform a kinematic classification of human body parts to refine the poses and obtain reconstructed body parts. Next, a personalized parametric human model is generated by driving a general template to fit the body parts and calculating the non-rigid deformation. Experimental results show that our shape estimation method achieves comparable accuracy with reconstructed models using depth cameras, yet requires neither user interaction nor any dedicated devices, leading to the feasibility of using this method on widely available smart phones.

Dynamic Human Body Modeling Using a Single RGB Camera

PubMed Central

Zhu, Haiyu; Yu, Yao; Zhou, Yu; Du, Sidan

2016-01-01

In this paper, we present a novel automatic pipeline to build personalized parametric models of dynamic people using a single RGB camera. Compared to previous approaches that use monocular RGB images, our system can model a 3D human body automatically and incrementally, taking advantage of human motion. Based on coarse 2D and 3D poses estimated from image sequences, we first perform a kinematic classification of human body parts to refine the poses and obtain reconstructed body parts. Next, a personalized parametric human model is generated by driving a general template to fit the body parts and calculating the non-rigid deformation. Experimental results show that our shape estimation method achieves comparable accuracy with reconstructed models using depth cameras, yet requires neither user interaction nor any dedicated devices, leading to the feasibility of using this method on widely available smart phones. PMID:26999159

Graph cuts with invariant object-interaction priors: application to intervertebral disc segmentation.

PubMed

Ben Ayed, Ismail; Punithakumar, Kumaradevan; Garvin, Gregory; Romano, Walter; Li, Shuo

2011-01-01

This study investigates novel object-interaction priors for graph cut image segmentation with application to intervertebral disc delineation in magnetic resonance (MR) lumbar spine images. The algorithm optimizes an original cost function which constrains the solution with learned prior knowledge about the geometric interactions between different objects in the image. Based on a global measure of similarity between distributions, the proposed priors are intrinsically invariant with respect to translation and rotation. We further introduce a scale variable from which we derive an original fixed-point equation (FPE), thereby achieving scale-invariance with only few fast computations. The proposed priors relax the need of costly pose estimation (or registration) procedures and large training sets (we used a single subject for training), and can tolerate shape deformations, unlike template-based priors. Our formulation leads to an NP-hard problem which does not afford a form directly amenable to graph cut optimization. We proceeded to a relaxation of the problem via an auxiliary function, thereby obtaining a nearly real-time solution with few graph cuts. Quantitative evaluations over 60 intervertebral discs acquired from 10 subjects demonstrated that the proposed algorithm yields a high correlation with independent manual segmentations by an expert. We further demonstrate experimentally the invariance of the proposed geometric attributes. This supports the fact that a single subject is sufficient for training our algorithm, and confirms the relevance of the proposed priors to disc segmentation.

Visual Object Recognition and Tracking of Tools

NASA Technical Reports Server (NTRS)

English, James; Chang, Chu-Yin; Tardella, Neil

2011-01-01

A method has been created to automatically build an algorithm off-line, using computer-aided design (CAD) models, and to apply this at runtime. The object type is discriminated, and the position and orientation are identified. This system can work with a single image and can provide improved performance using multiple images provided from videos. The spatial processing unit uses three stages: (1) segmentation; (2) initial type, pose, and geometry (ITPG) estimation; and (3) refined type, pose, and geometry (RTPG) calculation. The image segmentation module files all the tools in an image and isolates them from the background. For this, the system uses edge-detection and thresholding to find the pixels that are part of a tool. After the pixels are identified, nearby pixels are grouped into blobs. These blobs represent the potential tools in the image and are the product of the segmentation algorithm. The second module uses matched filtering (or template matching). This approach is used for condensing synthetic images using an image subspace that captures key information. Three degrees of orientation, three degrees of position, and any number of degrees of freedom in geometry change are included. To do this, a template-matching framework is applied. This framework uses an off-line system for calculating template images, measurement images, and the measurements of the template images. These results are used online to match segmented tools against the templates. The final module is the RTPG processor. Its role is to find the exact states of the tools given initial conditions provided by the ITPG module. The requirement that the initial conditions exist allows this module to make use of a local search (whereas the ITPG module had global scope). To perform the local search, 3D model matching is used, where a synthetic image of the object is created and compared to the sensed data. The availability of low-cost PC graphics hardware allows rapid creation of synthetic images. In this approach, a function of orientation, distance, and articulation is defined as a metric on the difference between the captured image and a synthetic image with an object in the given orientation, distance, and articulation. The synthetic image is created using a model that is looked up in an object-model database. A composable software architecture is used for implementation. Video is first preprocessed to remove sensor anomalies (like dead pixels), and then is processed sequentially by a prioritized list of tracker-identifiers.

The nature of the giant exomoon candidate Kepler-1625 b-i

NASA Astrophysics Data System (ADS)

Heller, René

2018-02-01

The recent announcement of a Neptune-sized exomoon candidate around the transiting Jupiter-sized object Kepler-1625 b could indicate the presence of a hitherto unknown kind of gas giant moon, if confirmed. Three transits of Kepler-1625 b have been observed, allowing estimates of the radii of both objects. Mass estimates, however, have not been backed up by radial velocity measurements of the host star. Here we investigate possible mass regimes of the transiting system that could produce the observed signatures and study them in the context of moon formation in the solar system, i.e., via impacts, capture, or in-situ accretion. The radius of Kepler-1625 b suggests it could be anything from a gas giant planet somewhat more massive than Saturn (0.4 MJup) to a brown dwarf (BD; up to 75 MJup) or even a very-low-mass star (VLMS; MJup ≈ 0.11 M⊙). The proposed companion would certainly have a planetary mass. Possible extreme scenarios range from a highly inflated Earth-mass gas satellite to an atmosphere-free water-rock companion of about 180 M⊕. Furthermore, the planet-moon dynamics during the transits suggest a total system mass of 17.6-12.6+19.2 MJup. A Neptune-mass exomoon around a giant planet or low-mass BD would not be compatible with the common mass scaling relation of the solar system moons about gas giants. The case of a mini-Neptune around a high-mass BD or a VLMS, however, would be located in a similar region of the satellite-to-host mass ratio diagram as Proxima b, the TRAPPIST-1 system, and LHS 1140 b. The capture of a Neptune-mass object around a 10 MJup planet during a close binary encounter is possible in principle. The ejected object, however, would have had to be a super-Earth object, raising further questions of how such a system could have formed. In summary, this exomoon candidate is barely compatible with established moon formation theories. If it can be validated as orbiting a super-Jovian planet, then it would pose an exquisite riddle for formation theorists to solve.

Synthesis and identification of three-dimensional faces from image(s) and three-dimensional generic models

NASA Astrophysics Data System (ADS)

Liu, Zexi; Cohen, Fernand

2017-11-01

We describe an approach for synthesizing a three-dimensional (3-D) face structure from an image or images of a human face taken at a priori unknown poses using gender and ethnicity specific 3-D generic models. The synthesis process starts with a generic model, which is personalized as images of the person become available using preselected landmark points that are tessellated to form a high-resolution triangular mesh. From a single image, two of the three coordinates of the model are reconstructed in accordance with the given image of the person, while the third coordinate is sampled from the generic model, and the appearance is made in accordance with the image. With multiple images, all coordinates and appearance are reconstructed in accordance with the observed images. This method allows for accurate pose estimation as well as face identification in 3-D rendering of a difficult two-dimensional (2-D) face recognition problem into a much simpler 3-D surface matching problem. The estimation of the unknown pose is achieved using the Levenberg-Marquardt optimization process. Encouraging experimental results are obtained in a controlled environment with high-resolution images under a good illumination condition, as well as for images taken in an uncontrolled environment under arbitrary illumination with low-resolution cameras.

Dense 3D Face Alignment from 2D Video for Real-Time Use

PubMed Central

Jeni, László A.; Cohn, Jeffrey F.; Kanade, Takeo

2018-01-01

To enable real-time, person-independent 3D registration from 2D video, we developed a 3D cascade regression approach in which facial landmarks remain invariant across pose over a range of approximately 60 degrees. From a single 2D image of a person’s face, a dense 3D shape is registered in real time for each frame. The algorithm utilizes a fast cascade regression framework trained on high-resolution 3D face-scans of posed and spontaneous emotion expression. The algorithm first estimates the location of a dense set of landmarks and their visibility, then reconstructs face shapes by fitting a part-based 3D model. Because no assumptions are required about illumination or surface properties, the method can be applied to a wide range of imaging conditions that include 2D video and uncalibrated multi-view video. The method has been validated in a battery of experiments that evaluate its precision of 3D reconstruction, extension to multi-view reconstruction, temporal integration for videos and 3D head-pose estimation. Experimental findings strongly support the validity of real-time, 3D registration and reconstruction from 2D video. The software is available online at http://zface.org. PMID:29731533

Handheld pose tracking using vision-inertial sensors with occlusion handling

NASA Astrophysics Data System (ADS)

Li, Juan; Slembrouck, Maarten; Deboeverie, Francis; Bernardos, Ana M.; Besada, Juan A.; Veelaert, Peter; Aghajan, Hamid; Casar, José R.; Philips, Wilfried

2016-07-01

Tracking of a handheld device's three-dimensional (3-D) position and orientation is fundamental to various application domains, including augmented reality (AR), virtual reality, and interaction in smart spaces. Existing systems still offer limited performance in terms of accuracy, robustness, computational cost, and ease of deployment. We present a low-cost, accurate, and robust system for handheld pose tracking using fused vision and inertial data. The integration of measurements from embedded accelerometers reduces the number of unknown parameters in the six-degree-of-freedom pose calculation. The proposed system requires two light-emitting diode (LED) markers to be attached to the device, which are tracked by external cameras through a robust algorithm against illumination changes. Three data fusion methods have been proposed, including the triangulation-based stereo-vision system, constraint-based stereo-vision system with occlusion handling, and triangulation-based multivision system. Real-time demonstrations of the proposed system applied to AR and 3-D gaming are also included. The accuracy assessment of the proposed system is carried out by comparing with the data generated by the state-of-the-art commercial motion tracking system OptiTrack. Experimental results show that the proposed system has achieved high accuracy of few centimeters in position estimation and few degrees in orientation estimation.

3D sensor algorithms for spacecraft pose determination

NASA Astrophysics Data System (ADS)

Trenkle, John M.; Tchoryk, Peter, Jr.; Ritter, Greg A.; Pavlich, Jane C.; Hickerson, Aaron S.

2006-05-01

Researchers at the Michigan Aerospace Corporation have developed accurate and robust 3-D algorithms for pose determination (position and orientation) of satellites as part of an on-going effort supporting autonomous rendezvous, docking and space situational awareness activities. 3-D range data from a LAser Detection And Ranging (LADAR) sensor is the expected input; however, the approach is unique in that the algorithms are designed to be sensor independent. Parameterized inputs allow the algorithms to be readily adapted to any sensor of opportunity. The cornerstone of our approach is the ability to simulate realistic range data that may be tailored to the specifications of any sensor. We were able to modify an open-source raytracing package to produce point cloud information from which high-fidelity simulated range images are generated. The assumptions made in our experimentation are as follows: 1) we have access to a CAD model of the target including information about the surface scattering and reflection characteristics of the components; 2) the satellite of interest may appear at any 3-D attitude; 3) the target is not necessarily rigid, but does have a limited number of configurations; and, 4) the target is not obscured in any way and is the only object in the field of view of the sensor. Our pose estimation approach then involves rendering a large number of exemplars (100k to 5M), extracting 2-D (silhouette- and projection-based) and 3-D (surface-based) features, and then training ensembles of decision trees to predict: a) the 4-D regions on a unit hypersphere into which the unit quaternion that represents the vehicle [Q X, Q Y, Q Z, Q W] is pointing, and, b) the components of that unit quaternion. Results have been quite promising and the tools and simulation environment developed for this application may also be applied to non-cooperative spacecraft operations, Autonomous Hazard Detection and Avoidance (AHDA) for landing craft, terrain mapping, vehicle guidance, path planning and obstacle avoidance.

PharmDock: a pharmacophore-based docking program

PubMed Central

2014-01-01

Background Protein-based pharmacophore models are enriched with the information of potential interactions between ligands and the protein target. We have shown in a previous study that protein-based pharmacophore models can be applied for ligand pose prediction and pose ranking. In this publication, we present a new pharmacophore-based docking program PharmDock that combines pose sampling and ranking based on optimized protein-based pharmacophore models with local optimization using an empirical scoring function. Results Tests of PharmDock on ligand pose prediction, binding affinity estimation, compound ranking and virtual screening yielded comparable or better performance to existing and widely used docking programs. The docking program comes with an easy-to-use GUI within PyMOL. Two features have been incorporated in the program suite that allow for user-defined guidance of the docking process based on previous experimental data. Docking with those features demonstrated superior performance compared to unbiased docking. Conclusion A protein pharmacophore-based docking program, PharmDock, has been made available with a PyMOL plugin. PharmDock and the PyMOL plugin are freely available from http://people.pharmacy.purdue.edu/~mlill/software/pharmdock. PMID:24739488

Critical issues related to registration of space objects and transparency of space activities

NASA Astrophysics Data System (ADS)

Jakhu, Ram S.; Jasani, Bhupendra; McDowell, Jonathan C.

2018-02-01

The main purpose of the 1975 Registration Convention is to achieve transparency in space activities and this objective is motivated by the belief that a mandatory registration system would assist in the identification of space objects launched into outer space. This would also consequently contribute to the application and development of international law governing the exploration and use of outer space. States Parties to the Convention furnish the required information to the United Nations' Register of Space Objects. However, the furnished information is often so general that it may not be as helpful in creating transparency as had been hoped by the drafters of the Convention. While registration of civil satellites has been furnished with some general details, till today, none of the Parties have described the objects as having military functions despite the fact that a large number of such objects do perform military functions as well. In some cases, the best they have done is to indicate that the space objects are for their defense establishments. Moreover, the number of registrations of space objects is declining. This paper addresses the challenges posed by the non-registration of space objects. Particularly, the paper provides some data about the registration and non-registration of satellites and the States that have and have not complied with their legal obligations. It also analyses the specific requirements of the Convention, the reasons for non-registration, new challenges posed by the registration of small satellites and the on-orbit transfer of satellites. Finally, the paper provides some recommendations on how to enhance the registration of space objects, on the monitoring of the implementation of the Registration Convention and consequently how to achieve maximum transparency in space activities.

MRI of the Prostate

MedlinePlus

... cardiac defibrillators and pacemakers You should tell the technologist if you have medical or electronic devices in your body. These objects may interfere with the exam or potentially pose a risk, depending on their nature and the strength of the MRI ...

Tethers as Debris: Hydrocode Simulation of Impacts of Polymer Tether Fragments on Aluminum Plates

NASA Technical Reports Server (NTRS)

Evans, Steven W.

2003-01-01

Tethers promise to find use in a variety of space applications. Despite being narrow objects, their great lengths result in them having large total areas. Consequently, tethers are very susceptible to being severed by orbital debris. Extensive work has been done designing tethers that resist severs by small debris objects, in order to lengthen their working lives. It is from this perspective that most recent work has considered the tether - debris question. The potential of intact tethers, or severed tether fragments, as debris, to pose a significant collision risk to other spacecraft has been less well studied. Understanding the consequences of such collisions is important in assessing the risks tethers pose to other spacecraft. This paper discusses the damage that polymer tethers may produce on aluminum plates, as revealed by hypervelocity impact simulations using the SPHC hydrodynamic code.

A robust motion estimation system for minimal invasive laparoscopy

NASA Astrophysics Data System (ADS)

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

2012-02-01

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

Risks to aquatic organisms posed by human pharmaceutical use

EPA Science Inventory

In order to help prioritize future research efforts within the US, risks associated with exposure to human prescription pharmaceutical residues in wastewater were estimated from marketing and pharmacological data. Masses of 371 active pharmaceutical ingredients (APIs) dispensed ...

An estimate for the thermal photon rate from lattice QCD

NASA Astrophysics Data System (ADS)

Brandt, Bastian B.; Francis, Anthony; Harris, Tim; Meyer, Harvey B.; Steinberg, Aman

2018-03-01

We estimate the production rate of photons by the quark-gluon plasma in lattice QCD. We propose a new correlation function which provides better control over the systematic uncertainty in estimating the photon production rate at photon momenta in the range πT/2 to 2πT. The relevant Euclidean vector current correlation functions are computed with Nf = 2 Wilson clover fermions in the chirally-symmetric phase. In order to estimate the photon rate, an ill-posed problem for the vector-channel spectral function must be regularized. We use both a direct model for the spectral function and a modelindependent estimate from the Backus-Gilbert method to give an estimate for the photon rate.

Backward semi-linear parabolic equations with time-dependent coefficients and local Lipschitz source

NASA Astrophysics Data System (ADS)

Nho Hào, Dinh; Van Duc, Nguyen; Van Thang, Nguyen

2018-05-01

Let H be a Hilbert space with the inner product and the norm , a positive self-adjoint unbounded time-dependent operator on H and . We establish stability estimates of Hölder type and propose a regularization method with error estimates of Hölder type for the ill-posed backward semi-linear parabolic equation with the source function f satisfying a local Lipschitz condition.

Pose and Wind Estimation for Autonomous Parafoils

DTIC Science & Technology

2014-09-01

Communications GT Georgia Institute of Technology IDVD Inverse Dynamics in the Virtual Domain IMU inertial measurement unit INRIA Institut National de Recherche en...sensor. The method used is a nonlinear estimator that combines the visual sensor measurements with those of an inertial measurement unit ( IMU ) on... isolated on the left side of the equation. On the other hand, when the measurement equation of (3.27) is implemented, the probabil- 58 ity

Use of autonomous maximal smile to evaluate dental and gingival exposure

PubMed Central

Lin, Hengzhe; Yang, Yan; Zhao, Xin; Mei, Li; Zheng, Wei; Zhao, Zhihe

2018-01-01

Objective This study was performed to validate the autonomous maximal smile (AMS) as a new reference for evaluating dental and gingival exposure. Methods Digital video clips of 100 volunteers showing posed smiles and AMS at different verbal directives were recorded for evaluation a total of three times at 1-week intervals. Lip-teeth relationship width (LTRW) and buccal corridor width (BCW) were measured. LTRW represented the vertical distance between the inferior border of the upper vermilion and the edge of the maxillary central incisors. Intraclass correlation coefficients (ICCs) for reproducibility, and the m-value (minimum number of repeated measurements required for an ICC level over 0.75), were calculated. Results LTRW and BCW of the AMS were 1.41 and 2.04 mm, respectively, greater than those of the posed smile (p < 0.05), indicating significantly larger dental and gingival exposure in the AMS. The reproducibility of the AMS (0.74 to 0.77) was excellent, and higher than that of the posed smile (0.62 to 0.65), which had fair-to-good reproducibility. Moreover, the m-value of the AMS (0.88 to 1.05) was lower than that of the posed smile (1.59 to 1.85). Conclusions Compared to the posed smile, the AMS shows significantly larger LTRW and BCW, with significantly higher reproducibility. The AMS might serve as an adjunctive reference, in addition to the posed smile, in orthodontic and other dentomaxillofacial treatments. PMID:29732304

A mission to preserve the geostationary region

NASA Astrophysics Data System (ADS)

Smith, D. A.; Martin, C.; Kassebom, M.; Petersen, H.; Shaw, A.; Skidmore, B.; Smith, D.; Stokes, H.; Willig, A.

2004-01-01

The RObotic Geostationary orbit Restorer, ROGER, is a programme aimed at reducing the risk to satellite operations posed by the existence of failed and spent satellites and other categories of space debris. To achieve this, the concept of mass removal by an intervention mission is considered for the GEO region. This paper describes the results of studies into the level of risk posed at present and in the near future to GEO assets. It also investigates practical means for re-orbiting objects that can no longer be manoeuvred away from the operational GEO region by ground command.

An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design.

PubMed

Ballante, Flavio; Marshall, Garland R

2016-01-25

Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e., by determining the docking accuracy (DA)) in order to select the most appropriate docking procedure and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different root-mean-square deviation (RMSD) formulas, scoring functions, and format results, it is both difficult and time-consuming to consistently determine and compare their predictive capabilities in order to identify the best protocol to use for the target of interest and to extrapolate the binding poses (i.e., best-docked (BD), best-cluster (BC), and best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures called Clusterizer and DockAccessor have been developed and implemented for use with some common and "free-for-academics" programs such as AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC, and BF poses as well as to perform consistent cluster and DA analyses. Clusterizer and DockAccessor (code available over the Internet) represent two novel tools to collect computationally determined poses and detect the most predictive docking approach. Herein an application to human lysine deacetylase (hKDAC) inhibitors is illustrated.

Free-viewpoint video of human actors using multiple handheld Kinects.

PubMed

Ye, Genzhi; Liu, Yebin; Deng, Yue; Hasler, Nils; Ji, Xiangyang; Dai, Qionghai; Theobalt, Christian

2013-10-01

We present an algorithm for creating free-viewpoint video of interacting humans using three handheld Kinect cameras. Our method reconstructs deforming surface geometry and temporal varying texture of humans through estimation of human poses and camera poses for every time step of the RGBZ video. Skeletal configurations and camera poses are found by solving a joint energy minimization problem, which optimizes the alignment of RGBZ data from all cameras, as well as the alignment of human shape templates to the Kinect data. The energy function is based on a combination of geometric correspondence finding, implicit scene segmentation, and correspondence finding using image features. Finally, texture recovery is achieved through jointly optimization on spatio-temporal RGB data using matrix completion. As opposed to previous methods, our algorithm succeeds on free-viewpoint video of human actors under general uncontrolled indoor scenes with potentially dynamic background, and it succeeds even if the cameras are moving.

SCREENING TO IDENTIFY AND PREVENT URBAN STORM WATER PROBLEMS: ESTIMATING IMPERVIOUS AREA ACCURATELY AND CHEAPLY

EPA Science Inventory

Complete identification and eventual prevention of urban/suburban water quality problems pose significant monitoring challenges. Uncontrolled growth of impervious surfaces (roads, buildings and parking) causes detrimental hydrologic changes, stream channel erosion, habitat degra...

20171015 - Predicting Exposure Pathways with Machine Learning (ISES)

EPA Science Inventory

Prioritizing the risk posed to human health from the thousands of chemicals in the environment requires tools that can estimate exposure rates from limited information. High throughput models exist to make predictions of exposure via specific, important pathways such as residenti...

Improving estimation of phytoplankton isotopic values from bulk POM samples in rivers

EPA Science Inventory

Background/Questions/MethodsResponses of phytoplankton to excessive nutrients in rivers cause many ecological problems, including harmful algal blooms, hypoxia and even food web collapse, posing serious risks to fish and human health. Successful remediation requires identificati...

SCREENING TO IDENTIFY AND PREVENT URBAN STORM WATER PROBLEMS: ESTIMATING IMPERVIOUS AREA ACCURATELY AND INEXPENSIVELY

EPA Science Inventory

Complete identification and eventual prevention of urban water quality problems pose significant monitoring, "smart growth" and water quality management challenges. Uncontrolled increase of impervious surface area (roads, buildings, and parking lots) causes detrimental hydrologi...

Exposure-Based Prioritization of Chemicals for Risk Assessment

EPA Science Inventory

Manufactured chemicals are used extensively to produce a wide variety of consumer goods and are required by important industrial sectors. Presently, information is insufficient to estimate risks posed to human health and the environment from the over ten thousand chemical substan...

Advances in marker-assisted breeding of sugarcane

USDA-ARS?s Scientific Manuscript database

Despite the challenges posed by sugarcane, geneticists and breeders have actively sought to use DNA marker technology to enhance breeding efforts. Markers have been used to explore taxonomy, estimate genetic diversity, and to develop unique molecular fingerprints. Numerous studies have been undertak...

Advancing Land-Sea Conservation Planning: Integrating Modelling of Catchments, Land-Use Change, and River Plumes to Prioritise Catchment Management and Protection.

PubMed

Álvarez-Romero, Jorge G; Pressey, Robert L; Ban, Natalie C; Brodie, Jon

2015-01-01

Human-induced changes to river loads of nutrients and sediments pose a significant threat to marine ecosystems. Ongoing land-use change can further increase these loads, and amplify the impacts of land-based threats on vulnerable marine ecosystems. Consequently, there is a need to assess these threats and prioritise actions to mitigate their impacts. A key question regarding prioritisation is whether actions in catchments to maintain coastal-marine water quality can be spatially congruent with actions for other management objectives, such as conserving terrestrial biodiversity. In selected catchments draining into the Gulf of California, Mexico, we employed Land Change Modeller to assess the vulnerability of areas with native vegetation to conversion into crops, pasture, and urban areas. We then used SedNet, a catchment modelling tool, to map the sources and estimate pollutant loads delivered to the Gulf by these catchments. Following these analyses, we used modelled river plumes to identify marine areas likely influenced by land-based pollutants. Finally, we prioritised areas for catchment management based on objectives for conservation of terrestrial biodiversity and objectives for water quality that recognised links between pollutant sources and affected marine areas. Our objectives for coastal-marine water quality were to reduce sediment and nutrient discharges from anthropic areas, and minimise future increases in coastal sedimentation and eutrophication. Our objectives for protection of terrestrial biodiversity covered species of vertebrates. We used Marxan, a conservation planning tool, to prioritise interventions and explore spatial differences in priorities for both objectives. Notable differences in the distributions of land values for terrestrial biodiversity and coastal-marine water quality indicated the likely need for trade-offs between catchment management objectives. However, there were priority areas that contributed to both sets of objectives. Our study demonstrates a practical approach to integrating models of catchments, land-use change, and river plumes with conservation planning software to inform prioritisation of catchment management.

Advancing Land-Sea Conservation Planning: Integrating Modelling of Catchments, Land-Use Change, and River Plumes to Prioritise Catchment Management and Protection

PubMed Central

Álvarez-Romero, Jorge G.; Pressey, Robert L.; Ban, Natalie C.; Brodie, Jon

2015-01-01

Human-induced changes to river loads of nutrients and sediments pose a significant threat to marine ecosystems. Ongoing land-use change can further increase these loads, and amplify the impacts of land-based threats on vulnerable marine ecosystems. Consequently, there is a need to assess these threats and prioritise actions to mitigate their impacts. A key question regarding prioritisation is whether actions in catchments to maintain coastal-marine water quality can be spatially congruent with actions for other management objectives, such as conserving terrestrial biodiversity. In selected catchments draining into the Gulf of California, Mexico, we employed Land Change Modeller to assess the vulnerability of areas with native vegetation to conversion into crops, pasture, and urban areas. We then used SedNet, a catchment modelling tool, to map the sources and estimate pollutant loads delivered to the Gulf by these catchments. Following these analyses, we used modelled river plumes to identify marine areas likely influenced by land-based pollutants. Finally, we prioritised areas for catchment management based on objectives for conservation of terrestrial biodiversity and objectives for water quality that recognised links between pollutant sources and affected marine areas. Our objectives for coastal-marine water quality were to reduce sediment and nutrient discharges from anthropic areas, and minimise future increases in coastal sedimentation and eutrophication. Our objectives for protection of terrestrial biodiversity covered species of vertebrates. We used Marxan, a conservation planning tool, to prioritise interventions and explore spatial differences in priorities for both objectives. Notable differences in the distributions of land values for terrestrial biodiversity and coastal-marine water quality indicated the likely need for trade-offs between catchment management objectives. However, there were priority areas that contributed to both sets of objectives. Our study demonstrates a practical approach to integrating models of catchments, land-use change, and river plumes with conservation planning software to inform prioritisation of catchment management. PMID:26714166

The epidemiology of tuberculosis in the Pacific, 2000 to 2013

PubMed Central

Hoy, Damian; Roth, Adam; Kelly, Paul; Harley, David; Sleigh, Adrian

2015-01-01

Objective Tuberculosis (TB) poses a significant public health challenge in the 22 Pacific island countries and territories. Using TB surveillance data and World Health Organization (WHO) estimates from 2000 to 2013, we summarize the epidemiology of TB in the Pacific. Methods This was a descriptive study of incident TB cases reported annually by Pacific island national TB programmes to WHO. We counted cases and calculated proportions and case notification rates per 100 000 population. We calculated the proportion of TB patients who completed TB treatment and summed estimates of national incidence, prevalence and mortality, provided by WHO, to produce regional incidence, prevalence and mortality rates per 100 000 population. Results Estimated TB incidence in the Pacific has remained high but stable from 2000 to 2013; estimated prevalence and mortality have fallen by 20% and 47%, respectively. The TB case notification rate increased by 58%, from 146 to 231 per 100 000 population in the same time period. In 2013, 24 145 TB cases were notified, most (94% or 22 657) were from Papua New Guinea. Kiribati had the highest TB case notification rate at 398 cases per 100 000 population. TB case notification rates were also high in Papua New Guinea, the Marshall Islands and Tuvalu (309, 283 and 182, respectively). Discussion TB in the Pacific is improving in some areas; however, high rates affect many countries and the estimated regional incidence rate is stable. To further reduce the burden of TB, a combination of dedicated public health and system-wide approaches are required along with poverty reduction and social protection initiatives. PMID:26668768

Evaluating re-identification risks with respect to the HIPAA privacy rule

PubMed Central

Benitez, Kathleen

2010-01-01

Objective Many healthcare organizations follow data protection policies that specify which patient identifiers must be suppressed to share “de-identified” records. Such policies, however, are often applied without knowledge of the risk of “re-identification”. The goals of this work are: (1) to estimate re-identification risk for data sharing policies of the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule; and (2) to evaluate the risk of a specific re-identification attack using voter registration lists. Measurements We define several risk metrics: (1) expected number of re-identifications; (2) estimated proportion of a population in a group of size g or less, and (3) monetary cost per re-identification. For each US state, we estimate the risk posed to hypothetical datasets, protected by the HIPAA Safe Harbor and Limited Dataset policies by an attacker with full knowledge of patient identifiers and with limited knowledge in the form of voter registries. Results The percentage of a state's population estimated to be vulnerable to unique re-identification (ie, g=1) when protected via Safe Harbor and Limited Datasets ranges from 0.01% to 0.25% and 10% to 60%, respectively. In the voter attack, this number drops for many states, and for some states is 0%, due to the variable availability of voter registries in the real world. We also find that re-identification cost ranges from $0 to $17 000, further confirming risk variability. Conclusions This work illustrates that blanket protection policies, such as Safe Harbor, leave different organizations vulnerable to re-identification at different rates. It provides justification for locally performed re-identification risk estimates prior to sharing data. PMID:20190059

Estimation and Control of Distributed Models for Certain Elastic Systems Arising in Large Space Structures.

DTIC Science & Technology

1987-09-30

igennfy by ""aU numiir,) PIAL GROUP Sue. Go. RCI (Cm, inve o owuera Ineeemerv 4R an~ b-, bloca number) The goal of this research was to study...estimation and control of elastic systems compoited of beams and plates. Specifically, the research con- sidered the problem of lcating the optimal placement...estimation and control of elastic systems com- posed of beams and plates. This general goal has served as a guide for our research over the last several

Migration protocol to estimate metal exposure from mouthing copper and tin alloy objects

PubMed Central

2014-01-01

Background Low blood lead levels previously thought to pose no health risks may have an adverse impact on the cognitive development of children. This concern has given rise to new regulatory restrictions upon lead metal containing products intended for child use. However few reliable experimental testing methods to estimate exposure levels from these materials are available. Methods The present work describes a migration test using a mimetic saliva fluid to estimate the chronic exposure of children to metals such as lead while mouthing metallic objects. The surrogate saliva medium was composed of: 150 mM NaCl, 0.16% porcine Mucin and 5 mM buffer MOPS, adjusted to pH 7.2. Alloys samples, in the form of polished metallic disc of known surface area, were subjected to an eight hours test. Results Two whitemetal alloys Sn/Pb/Sb/Cu and three brass alloys Cu/Zn/Pb were tested using the saliva migration protocol. In the case of the whitemetal alloys, first order release kinetics resulting in the release of 0.03 and 0.51 μg lead/cm2 after 8 hours of tests were observed, for lead contents of 0.05-0.07% and 5.5%, respectively. Brasses exhibited linear incremental release rates of 0.043, 0.175 and 0.243 μg lead/cm2h for lead contents of 0.1-0.2%, 1.7-2.2% and 3.1-3.5%, respectively. The linear regression analysis of lead release rates relative to Pb content in brasses yielded a slope of 0.08 μg lead/cm2h%Pb (r2 = 0.92). Lead release rates were used to estimate the mean daily mouthing exposure of a child to lead, according to age-specific estimates of mouthing time behavior. Calculated daily intakes were used as oral inputs for the IEUBK toxicokinetic model, predicting only marginal changes in blood lead levels (0.2 μg lead/dL or less) for children aged 0.5 to 1 years old exposed to either class of alloy. Conclusions The results of this study as a whole support the use of migration data of metal ions, rather than total metal content, to estimate health risk from exposure to metals and metal alloys substances in children. PMID:25113236

14 CFR 1214.805 - Unforeseen customer delay.

Code of Federal Regulations, 2013 CFR

2013-01-01

... problem pose a threat of delay to the Shuttle launch schedule or critical off-line activities, NASA shall... availability of facilities, equipment, and personnel. In requesting NASA to make such special efforts, the customer shall agree to reimburse NASA the estimated additional cost incurred. ...

14 CFR 1214.805 - Unforeseen customer delay.

Code of Federal Regulations, 2011 CFR

2011-01-01

... problem pose a threat of delay to the Shuttle launch schedule or critical off-line activities, NASA shall... availability of facilities, equipment, and personnel. In requesting NASA to make such special efforts, the customer shall agree to reimburse NASA the estimated additional cost incurred. ...

14 CFR 1214.805 - Unforeseen customer delay.

Code of Federal Regulations, 2012 CFR

2012-01-01

... problem pose a threat of delay to the Shuttle launch schedule or critical off-line activities, NASA shall... availability of facilities, equipment, and personnel. In requesting NASA to make such special efforts, the customer shall agree to reimburse NASA the estimated additional cost incurred. ...

Product Deformulation to Inform High-throughput Exposure Predictions (SOT)

EPA Science Inventory

The health risks posed by the thousands of chemicals in our environment depends on both chemical hazard and exposure. However, relatively few chemicals have estimates of exposure intake, limiting the understanding of risks. We have previously developed a heuristics-based exposur...

Assessing nanoparticle risk poses prodigious challenges

EPA Science Inventory

Risk assessment is used both formally and informally to estimate the likelihood of an adverse event occurring, for example, as a consequence of exposure to a hazardous chemical, drug or other agent. Formal risk assessments in government regulatory agencies have a long history of ...

Comparative assessment of bone pose estimation using Point Cluster Technique and OpenSim.

PubMed

Lathrop, Rebecca L; Chaudhari, Ajit M W; Siston, Robert A

2011-11-01

Estimating the position of the bones from optical motion capture data is a challenge associated with human movement analysis. Bone pose estimation techniques such as the Point Cluster Technique (PCT) and simulations of movement through software packages such as OpenSim are used to minimize soft tissue artifact and estimate skeletal position; however, using different methods for analysis may produce differing kinematic results which could lead to differences in clinical interpretation such as a misclassification of normal or pathological gait. This study evaluated the differences present in knee joint kinematics as a result of calculating joint angles using various techniques. We calculated knee joint kinematics from experimental gait data using the standard PCT, the least squares approach in OpenSim applied to experimental marker data, and the least squares approach in OpenSim applied to the results of the PCT algorithm. Maximum and resultant RMS differences in knee angles were calculated between all techniques. We observed differences in flexion/extension, varus/valgus, and internal/external rotation angles between all approaches. The largest differences were between the PCT results and all results calculated using OpenSim. The RMS differences averaged nearly 5° for flexion/extension angles with maximum differences exceeding 15°. Average RMS differences were relatively small (< 1.08°) between results calculated within OpenSim, suggesting that the choice of marker weighting is not critical to the results of the least squares inverse kinematics calculations. The largest difference between techniques appeared to be a constant offset between the PCT and all OpenSim results, which may be due to differences in the definition of anatomical reference frames, scaling of musculoskeletal models, and/or placement of virtual markers within OpenSim. Different methods for data analysis can produce largely different kinematic results, which could lead to the misclassification of normal or pathological gait. Improved techniques to allow non-uniform scaling of generic models to more accurately reflect subject-specific bone geometries and anatomical reference frames may reduce differences between bone pose estimation techniques and allow for comparison across gait analysis platforms.

Fast 5DOF needle tracking in iOCT.

PubMed

Weiss, Jakob; Rieke, Nicola; Nasseri, Mohammad Ali; Maier, Mathias; Eslami, Abouzar; Navab, Nassir

2018-06-01

Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument-tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU.

Multiview marker-free registration of forest terrestrial laser scanner data with embedded confidence metrics

DOE PAGES

Kelbe, David; Oak Ridge National Lab.; van Aardt, Jan; ...

2016-10-18

Terrestrial laser scanning has demonstrated increasing potential for rapid comprehensive measurement of forest structure, especially when multiple scans are spatially registered in order to reduce the limitations of occlusion. Although marker-based registration techniques (based on retro-reflective spherical targets) are commonly used in practice, a blind marker-free approach is preferable, insofar as it supports rapid operational data acquisition. To support these efforts, we extend the pairwise registration approach of our earlier work, and develop a graph-theoretical framework to perform blind marker-free global registration of multiple point cloud data sets. Pairwise pose estimates are weighted based on their estimated error, in ordermore » to overcome pose conflict while exploiting redundant information and improving precision. The proposed approach was tested for eight diverse New England forest sites, with 25 scans collected at each site. Quantitative assessment was provided via a novel embedded confidence metric, with a mean estimated root-mean-square error of 7.2 cm and 89% of scans connected to the reference node. Lastly, this paper assesses the validity of the embedded multiview registration confidence metric and evaluates the performance of the proposed registration algorithm.« less

The spatial concentration of dust emissions measured by using 3D scanning lidar in the open storage yards of steel-making company

NASA Astrophysics Data System (ADS)

Chiang, Chih-Wei; Chiang, Hong-Wei; Chou, Huann-Ming; Sun, Shu-Huang; Lee, Jiann-Shen

2017-06-01

The wind-blown dust emissions frequently occur in the open storage yards of steel-making companies. Tracking the dust source and monitoring their dispersion are rather difficult. This type of open-air storage yards poses many environmental hazards. The 3-D scanning lidar system is effective in environmental monitoring (e.g., dust) with high temporal and spatial resolution, which is lacking in traditional ground-based measurement. The objective of this paper is to make an attempt for the flux estimation of dust concentration by using lidar system. Further, we investigate the dynamical process of dust and their relationship with local air quality monitoring data. The results show that the material storage erosion by wind ( 3.6 m/s) could cause dust to elevate up to 20m height above the material storage, and produces the flux of dust around 674 mg/s. The flux of dust is proportional to the dust mass concentration (PM10) measured by commercial ambient particular monitors.

High Accuracy Monocular SFM and Scale Correction for Autonomous Driving.

PubMed

Song, Shiyu; Chandraker, Manmohan; Guest, Clark C

2016-04-01

We present a real-time monocular visual odometry system that achieves high accuracy in real-world autonomous driving applications. First, we demonstrate robust monocular SFM that exploits multithreading to handle driving scenes with large motions and rapidly changing imagery. To correct for scale drift, we use known height of the camera from the ground plane. Our second contribution is a novel data-driven mechanism for cue combination that allows highly accurate ground plane estimation by adapting observation covariances of multiple cues, such as sparse feature matching and dense inter-frame stereo, based on their relative confidences inferred from visual data on a per-frame basis. Finally, we demonstrate extensive benchmark performance and comparisons on the challenging KITTI dataset, achieving accuracy comparable to stereo and exceeding prior monocular systems. Our SFM system is optimized to output pose within 50 ms in the worst case, while average case operation is over 30 fps. Our framework also significantly boosts the accuracy of applications like object localization that rely on the ground plane.

Residential releases of number 2 fuel oil: a contributor to indoor air pollution.

PubMed Central

Kaplan, M B; Brandt-Rauf, P; Axley, J W; Shen, T T; Sewell, G H

1993-01-01

OBJECTIVES. Analysis of data from the New York City Fire Department showed that residential fuel oil releases frequently occur in quantities ranging from 5 to 1000 gal, primarily from storage tank leaks and overfill. A risk assessment was conducted to determine whether Number 2 fuel oil basement spills pose a significant risk to human health. METHODS. Exposure was derived from a simulated field study spill of Number 2 fuel oil in a townhouse basement to develop emission rates for the indicator constituent xylene. Distribution of xylene throughout the townhouse was determined using a multizone contaminant dispersal model. RESULTS. Spills of 85 and 21 gal resulted in xylene exposure estimates as high as 20 and 5 mg/kg/day, respectively. CONCLUSIONS. A spill of about 21 gal or more of Number 2 fuel oil would present a human health risk for central nervous and reproductive systems for 8 days or longer. Tank inspection and supervised delivery would provide effective prevention at minimal expense. PMID:8417613

Analyzing costs of space debris mitigation methods

NASA Astrophysics Data System (ADS)

Wiedemann, C.; Krag, H.; Bendisch, J.; Sdunnus, H.

The steadily increasing number of space objects poses a considerable hazard to all kinds of spacecraft. To reduce the risks to future space missions different debris mitigation measures and spacecraft protection techniques have been investigated during the last years. However, the economic efficiency has not been considered yet in this context. This economical background is not always clear to satellite operators and the space industry. Current studies have the objective to evaluate the mission costs due to space debris in a business as usual (no mitigation) scenario compared to the missions costs considering debris mitigation. The aim i an estimation of thes time until the investment in debris mitigation will lead to an effective reduction of mission costs. This paper presents the results of investigations on the key problems of cost estimation for spacecraft and the influence of debris mitigation and shielding on cost. The shielding of a satellite can be an effective method to protect the spacecraft against debris impact. Mitigation strategies like the reduction of orbital lifetime and de- or re-orbit of non-operational satellites are methods to control the space debris environment. These methods result in an increase of costs. In a first step the overall costs of different types of unmanned satellites are analyzed. The key problem is, that it is not possible to provide a simple cost model that can be applied to all types of satellites. Unmanned spacecraft differ very much in mission, complexity of design, payload and operational lifetime. It is important to classify relevant cost parameters and investigate their influence on the respective mission. The theory of empirical cost estimation and existing cost models are discussed. A selected cost model is simplified and generalized for an application on all operational satellites. In a next step the influence of space debris on cost is treated, if the implementation of mitigation strategies is considered.

Obesity and People with Disabilities: The Implications for Health Care Expenditures

PubMed Central

Anderson, Wayne L.; Wiener, Joshua M.; Khatutsky, Galina; Armour, Brian S.

2015-01-01

Objective This study estimates additional average health care expenditures for overweight and obesity for adults with disabilities vs. without. Design and Methods Descriptive and multivariate methods were used to estimate additional health expenditures by service type, age group, and payer using 2004–2007 Medical Expenditure Panel Survey data. Results In 2007, 37% of community-dwelling Americans with disabilities were obese vs. 27% of the total population. People with disabilities had almost three times ($2,459) the additional average obesity cost of people without disabilities ($889). Prescription drug expenditures for obese people with disabilities were three times as high and outpatient expenditures were 74% higher. People with disabilities in the 45- to 64-year age group had the highest obesity expenditures. Medicare had the highest additional average obesity expenditures among payers. Among people with prescription drug expenditures, obese people with disabilities had nine times the prevalence of diabetes as normal weight people with disabilities. Overweight people with and without disabilities had lower expenditures than normal-weight people with and without disabilities. Conclusions Obesity results in substantial additional health care expenditures for people with disabilities. These additional expenditures pose a serious current and future problem, given the potential for higher obesity prevalence in the coming decade. PMID:23804319

Bayesian Recurrent Neural Network for Language Modeling.

PubMed

Chien, Jen-Tzung; Ku, Yuan-Chu

2016-02-01

A language model (LM) is calculated as the probability of a word sequence that provides the solution to word prediction for a variety of information systems. A recurrent neural network (RNN) is powerful to learn the large-span dynamics of a word sequence in the continuous space. However, the training of the RNN-LM is an ill-posed problem because of too many parameters from a large dictionary size and a high-dimensional hidden layer. This paper presents a Bayesian approach to regularize the RNN-LM and apply it for continuous speech recognition. We aim to penalize the too complicated RNN-LM by compensating for the uncertainty of the estimated model parameters, which is represented by a Gaussian prior. The objective function in a Bayesian classification network is formed as the regularized cross-entropy error function. The regularized model is constructed not only by calculating the regularized parameters according to the maximum a posteriori criterion but also by estimating the Gaussian hyperparameter by maximizing the marginal likelihood. A rapid approximation to a Hessian matrix is developed to implement the Bayesian RNN-LM (BRNN-LM) by selecting a small set of salient outer-products. The proposed BRNN-LM achieves a sparser model than the RNN-LM. Experiments on different corpora show the robustness of system performance by applying the rapid BRNN-LM under different conditions.

Intelligence-aided multitarget tracking for urban operations - a case study: counter terrorism

NASA Astrophysics Data System (ADS)

Sathyan, T.; Bharadwaj, K.; Sinha, A.; Kirubarajan, T.

2006-05-01

In this paper, we present a framework for tracking multiple mobile targets in an urban environment based on data from multiple sources of information, and for evaluating the threat these targets pose to assets of interest (AOI). The motivating scenario is one where we have to track many targets, each with different (unknown) destinations and/or intents. The tracking algorithm is aided by information about the urban environment (e.g., road maps, buildings, hideouts), and strategic and intelligence data. The tracking algorithm needs to be dynamic in that it has to handle a time-varying number of targets and the ever-changing urban environment depending on the locations of the moving objects and AOI. Our solution uses the variable structure interacting multiple model (VS-IMM) estimator, which has been shown to be effective in tracking targets based on road map information. Intelligence information is represented as target class information and incorporated through a combined likelihood calculation within the VS-IMM estimator. In addition, we develop a model to calculate the probability that a particular target can attack a given AOI. This model for the calculation of the probability of attack is based on the target kinematic and class information. Simulation results are presented to demonstrate the operation of the proposed framework on a representative scenario.

Real-time 3D human pose recognition from reconstructed volume via voxel classifiers

NASA Astrophysics Data System (ADS)

Yoo, ByungIn; Choi, Changkyu; Han, Jae-Joon; Lee, Changkyo; Kim, Wonjun; Suh, Sungjoo; Park, Dusik; Kim, Junmo

2014-03-01

This paper presents a human pose recognition method which simultaneously reconstructs a human volume based on ensemble of voxel classifiers from a single depth image in real-time. The human pose recognition is a difficult task since a single depth camera can capture only visible surfaces of a human body. In order to recognize invisible (self-occluded) surfaces of a human body, the proposed algorithm employs voxel classifiers trained with multi-layered synthetic voxels. Specifically, ray-casting onto a volumetric human model generates a synthetic voxel, where voxel consists of a 3D position and ID corresponding to the body part. The synthesized volumetric data which contain both visible and invisible body voxels are utilized to train the voxel classifiers. As a result, the voxel classifiers not only identify the visible voxels but also reconstruct the 3D positions and the IDs of the invisible voxels. The experimental results show improved performance on estimating the human poses due to the capability of inferring the invisible human body voxels. It is expected that the proposed algorithm can be applied to many fields such as telepresence, gaming, virtual fitting, wellness business, and real 3D contents control on real 3D displays.

PREDICTING CHLORINE RESIDUAL DECAY IN DRINKING WATER: A SECOND ORDER MODEL

EPA Science Inventory

A major objective of drinking water treatment is to provide water that is both microbiologically and chemically safe for human consumption. Drinking water chlorination, therefore, poses a dilemma. Chemical disinfection reduces the risk of infectious disease but the interaction be...

Camera Network Topology Discovery Literature Review

DTIC Science & Technology

2011-11-01

essential for 21st century military, enviromental and surveillance applications [Devarajan, Cheng & Radke 2008]. Computer networks pose several research...starting and ending points of object trajectories into entry/exit regions [Makris & Ellis 2003]. 3LDA is a new standard for document analysis. The model

Establishment of a new relationship between posed smile width and lower facial height: A cross-sectional study

PubMed Central

Abraham, Aby; George, Jinu; Peter, Elbe; Philip, Koshi; Chankramath, Rajesh; Johns, Dexton Antony; Bhaskar, Anitha

2015-01-01

Objective: The present study is intended to add a new parameter that would be useful in orthodontic clinical evaluation, treatment planning, and determination of vertical dimension (at occlusion). Materials and Methods: Standardized videographic recording of 79 subjects during posed smile was captured. Each video was then cut into 30 photos using the free studio software. The widest commissure-to-commissure posed smile frame (posed smile width [SW]) was selected as one of 10 or more frames showing an identical smile. Lower third of the face is measured from subnasale to soft tissue menton using a digital vernier caliper. Two values were then compared. Ratio between lower facial height and posed SW was calculated. Results: The co-relation between smiling width and lower facial height was found to be statistically significant (P < 0.01). The ratio of lower facial height and smiling width was calculated as 1.0016 with a standard deviation (SD) = 0.04 in males and 1.0301 with an SD = 0.07 in females. The difference between the mean lower facial height in males and females was statistically significant with a t = 10.231 and P = 0.000. The difference between the mean smiling width in males and females was also statistically significant with a t = 5.653 and P = 0.000. Conclusion: In class I subjects with pleasing appearance, normal facial proportions, normal overjet and overbite, and average Frankfort mandibular angle, the lower facial height (subnasale to soft tissue menton) is equal to posed SW. PMID:26430369

Binary Detection using Multi-Hypothesis Log-Likelihood, Image Processing

DTIC Science & Technology

2014-03-27

geosynchronous orbit and other scenarios important to the USAF. 2 1.3 Research objectives The question posed in this thesis is how well, if at all, can a...is important to compare them to another modern technique. The third objective is to compare results from another image detection method, specifically...Although adaptive optics is an important technique in moving closer to diffraction limited imaging, it is not currently a practical solution for all

14 CFR § 1214.805 - Unforeseen customer delay.

Code of Federal Regulations, 2014 CFR

2014-01-01

... problem pose a threat of delay to the Shuttle launch schedule or critical off-line activities, NASA shall... availability of facilities, equipment, and personnel. In requesting NASA to make such special efforts, the customer shall agree to reimburse NASA the estimated additional cost incurred. ...

76 FR 50904 - Thiamethoxam; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-17

... exposure and risk. A separate assessment was done for clothianidin. i. Acute exposure. Quantitative acute... not expected to pose a cancer risk, a quantitative dietary exposure assessment for the purposes of...-dietary sources of post application exposure to obtain an estimate of potential combined exposure. These...

AN INFORMATIC APPROACH TO ESTIMATING ECOLOGICAL RISKS POSED BY PHARMACEUTICAL USE

EPA Science Inventory

Pharmaceuticals administered to humans and other animals are often excreted from treated organisms as intact drug or as active metabolites. Some of these active materials have been shown to make their way into the environment. However, the environmental concentrations of the vast...

Scintillometer networks for calibration and validation of energy balance and soil moisture remote sensing algorithms

NASA Astrophysics Data System (ADS)

Hendrickx, Jan M. H.; Kleissl, Jan; Gómez Vélez, Jesús D.; Hong, Sung-ho; Fábrega Duque, José R.; Vega, David; Moreno Ramírez, Hernán A.; Ogden, Fred L.

2007-04-01

Accurate estimation of sensible and latent heat fluxes as well as soil moisture from remotely sensed satellite images poses a great challenge. Yet, it is critical to face this challenge since the estimation of spatial and temporal distributions of these parameters over large areas is impossible using only ground measurements. A major difficulty for the calibration and validation of operational remote sensing methods such as SEBAL, METRIC, and ALEXI is the ground measurement of sensible heat fluxes at a scale similar to the spatial resolution of the remote sensing image. While the spatial length scale of remote sensing images covers a range from 30 m (LandSat) to 1000 m (MODIS) direct methods to measure sensible heat fluxes such as eddy covariance (EC) only provide point measurements at a scale that may be considerably smaller than the estimate obtained from a remote sensing method. The Large Aperture scintillometer (LAS) flux footprint area is larger (up to 5000 m long) and its spatial extent better constraint than that of EC systems. Therefore, scintillometers offer the unique possibility of measuring the vertical flux of sensible heat averaged over areas comparable with several pixels of a satellite image (up to about 40 Landsat thermal pixels or about 5 MODIS thermal pixels). The objective of this paper is to present our experiences with an existing network of seven scintillometers in New Mexico and a planned network of three scintillometers in the humid tropics of Panama and Colombia.

Using Elicited Choice Probabilities in Hypothetical Elections to Study Decisions to Vote

PubMed Central

Delavande, Adeline; Manski, Charles F.

2015-01-01

This paper demonstrates the feasibility and usefulness of survey research asking respondents to report voting probabilities in hypothetical election scenarios. Posing scenarios enriches the data available for studies of voting decisions, as a researcher can pose many more and varied scenarios than the elections that persons actually face. Multiple scenarios were presented to over 4,000 participants in the American Life Panel (ALP). Each described a hypothetical presidential election, giving characteristics measuring candidate preference, closeness of the election, and the time cost of voting. Persons were asked the probability that they would vote in this election and were willing and able to respond. We analyzed the data through direct study of the variation of voting probabilities with election characteristics and through estimation of a random utility model of voting. Voting time and election closeness were notable determinants of decisions to vote, but not candidate preference. Most findings were corroborated through estimation of a model fit to ALP data on respondents' actual voting behavior in the 2012 election. PMID:25705068

Refraction-compensated motion tracking of unrestrained small animals in positron emission tomography.

PubMed

Kyme, Andre; Meikle, Steven; Baldock, Clive; Fulton, Roger

2012-08-01

Motion-compensated radiotracer imaging of fully conscious rodents represents an important paradigm shift for preclinical investigations. In such studies, if motion tracking is performed through a transparent enclosure containing the awake animal, light refraction at the interface will introduce errors in stereo pose estimation. We have performed a thorough investigation of how this impacts the accuracy of pose estimates and the resulting motion correction, and developed an efficient method to predict and correct for refraction-based error. The refraction model underlying this study was validated using a state-of-the-art motion tracking system. Refraction-based error was shown to be dependent on tracking marker size, working distance, and interface thickness and tilt. Correcting for refraction error improved the spatial resolution and quantitative accuracy of motion-corrected positron emission tomography images. Since the methods are general, they may also be useful in other contexts where data are corrupted by refraction effects. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Autonomous proximity operations using machine vision for trajectory control and pose estimation

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Sternberg, Stanley R.

1991-01-01

A machine vision algorithm was developed which permits guidance control to be maintained during autonomous proximity operations. At present this algorithm exists as a simulation, running upon an 80386 based personal computer, using a ModelMATE CAD package to render the target vehicle. However, the algorithm is sufficiently simple, so that following off-line training on a known target vehicle, it should run in real time with existing vision hardware. The basis of the algorithm is a sequence of single camera images of the target vehicle, upon which radial transforms were performed. Selected points of the resulting radial signatures are fed through a decision tree, to determine whether the signature matches that of the known reference signatures for a particular view of the target. Based upon recognized scenes, the position of the maneuvering vehicle with respect to the target vehicles can be calculated, and adjustments made in the former's trajectory. In addition, the pose and spin rates of the target satellite can be estimated using this method.

Traffic Light Detection Using Conic Section Geometry

NASA Astrophysics Data System (ADS)

Hosseinyalmdary, S.; Yilmaz, A.

2016-06-01

Traffic lights detection and their state recognition is a crucial task that autonomous vehicles must reliably fulfill. Despite scientific endeavors, it still is an open problem due to the variations of traffic lights and their perception in image form. Unlike previous studies, this paper investigates the use of inaccurate and publicly available GIS databases such as OpenStreetMap. In addition, we are the first to exploit conic section geometry to improve the shape cue of the traffic lights in images. Conic section also enables us to estimate the pose of the traffic lights with respect to the camera. Our approach can detect multiple traffic lights in the scene, it also is able to detect the traffic lights in the absence of prior knowledge, and detect the traffics lights as far as 70 meters. The proposed approach has been evaluated for different scenarios and the results show that the use of stereo cameras significantly improves the accuracy of the traffic lights detection and pose estimation.

Microplastics in bivalves cultured for human consumption.

PubMed

Van Cauwenberghe, Lisbeth; Janssen, Colin R

2014-10-01

Microplastics are present throughout the marine environment and ingestion of these plastic particles (<1 mm) has been demonstrated in a laboratory setting for a wide array of marine organisms. Here, we investigate the presence of microplastics in two species of commercially grown bivalves: Mytilus edulis and Crassostrea gigas. Microplastics were recovered from the soft tissues of both species. At time of human consumption, M. edulis contains on average 0.36 ± 0.07 particles g(-1) (wet weight), while a plastic load of 0.47 ± 0.16 particles g(-1) ww was detected in C. gigas. As a result, the annual dietary exposure for European shellfish consumers can amount to 11,000 microplastics per year. The presence of marine microplastics in seafood could pose a threat to food safety, however, due to the complexity of estimating microplastic toxicity, estimations of the potential risks for human health posed by microplastics in food stuffs is not (yet) possible. Copyright © 2014 Elsevier Ltd. All rights reserved.

Relative cancer risks of chemical contaminants in the great lakes

NASA Astrophysics Data System (ADS)

Bro, Kenneth M.; Sonzogni, William C.; Hanson, Mark E.

1987-08-01

Anyone who drinks water or eats fish from the Great Lakes consumes potentially carcinogenic chemicals. In choosing how to respond to such pollution, it is important to put the risks these contaminants pose in perspective. Based on recent measurements of carcinogens in Great Lakes fish and water, calculations of lifetime risks of cancer indicate that consumers of sport fish face cancer risks from Great Lakes contaminants that are several orders of magnitude higher than the risks posed by drinking Great Lakes water. But drinking urban groundwater and breathing urban air may be as hazardous as frequent consumption of sport fish from the Great Lakes. Making such comparisons is difficult because of variation in types and quality of information available and in the methods for estimating risk. Much uncertainty pervades the risk assessment process in such areas as estimating carcinogenic potency and human exposure to contaminants. If risk assessment is to be made more useful, it is important to quantify this uncertainty.

Implication of adaptive smoothness constraint and Helmert variance component estimation in seismic slip inversion

NASA Astrophysics Data System (ADS)

Fan, Qingbiao; Xu, Caijun; Yi, Lei; Liu, Yang; Wen, Yangmao; Yin, Zhi

2017-10-01

When ill-posed problems are inverted, the regularization process is equivalent to adding constraint equations or prior information from a Bayesian perspective. The veracity of the constraints (or the regularization matrix R) significantly affects the solution, and a smoothness constraint is usually added in seismic slip inversions. In this paper, an adaptive smoothness constraint (ASC) based on the classic Laplacian smoothness constraint (LSC) is proposed. The ASC not only improves the smoothness constraint, but also helps constrain the slip direction. A series of experiments are conducted in which different magnitudes of noise are imposed and different densities of observation are assumed, and the results indicated that the ASC was superior to the LSC. Using the proposed ASC, the Helmert variance component estimation method is highlighted as the best for selecting the regularization parameter compared with other methods, such as generalized cross-validation or the mean squared error criterion method. The ASC may also benefit other ill-posed problems in which a smoothness constraint is required.

Smoothing-Based Relative Navigation and Coded Aperture Imaging

NASA Technical Reports Server (NTRS)

Saenz-Otero, Alvar; Liebe, Carl Christian; Hunter, Roger C.; Baker, Christopher

2017-01-01

This project will develop an efficient smoothing software for incremental estimation of the relative poses and velocities between multiple, small spacecraft in a formation, and a small, long range depth sensor based on coded aperture imaging that is capable of identifying other spacecraft in the formation. The smoothing algorithm will obtain the maximum a posteriori estimate of the relative poses between the spacecraft by using all available sensor information in the spacecraft formation.This algorithm will be portable between different satellite platforms that possess different sensor suites and computational capabilities, and will be adaptable in the case that one or more satellites in the formation become inoperable. It will obtain a solution that will approach an exact solution, as opposed to one with linearization approximation that is typical of filtering algorithms. Thus, the algorithms developed and demonstrated as part of this program will enhance the applicability of small spacecraft to multi-platform operations, such as precisely aligned constellations and fractionated satellite systems.

STS-48 MS Brown on OV-103's aft flight deck poses for ESC photo

NASA Technical Reports Server (NTRS)

1991-01-01

STS-48 Mission Specialist (MS) Mark N. Brown looks away from the portable laptop computer screen to pose for an Electronic Still Camera (ESC) photo on the aft flight deck of the earth-orbiting Discovery, Orbiter Vehicle (OV) 103. Brown was working at the payload station before the interruption. Crewmembers were testing the ESC as part of Development Test Objective (DTO) 648, Electronic Still Photography. The digital image was stored on a removable hard disk or small optical disk, and could be converted to a format suitable for downlink transmission. The ESC is making its initial appearance on this Space Shuttle mission.

The Kinect as an interventional tracking system

NASA Astrophysics Data System (ADS)

Wang, Xiang L.; Stolka, Philipp J.; Boctor, Emad; Hager, Gregory; Choti, Michael

2012-02-01

This work explores the suitability of low-cost sensors for "serious" medical applications, such as tracking of interventional tools in the OR, for simulation, and for education. Although such tracking - i.e. the acquisition of pose data e.g. for ultrasound probes, tissue manipulation tools, needles, but also tissue, bone etc. - is well established, it relies mostly on external devices such as optical or electromagnetic trackers, both of which mandate the use of special markers or sensors attached to each single entity whose pose is to be recorded, and also require their calibration to the tracked entity, i.e. the determination of the geometric relationship between the marker's and the object's intrinsic coordinate frames. The Microsoft Kinect sensor is a recently introduced device for full-body tracking in the gaming market, but it was quickly hacked - due to its wide range of tightly integrated sensors (RGB camera, IR depth and greyscale camera, microphones, accelerometers, and basic actuation) - and used beyond this area. As its field of view and its accuracy are within reasonable usability limits, we describe a medical needle-tracking system for interventional applications based on the Kinect sensor, standard biopsy needles, and no necessary attachments, thus saving both cost and time. Its twin cameras are used as a stereo pair to detect needle-shaped objects, reconstruct their pose in four degrees of freedom, and provide information about the most likely candidate.

Adaptive object tracking via both positive and negative models matching

NASA Astrophysics Data System (ADS)

Li, Shaomei; Gao, Chao; Wang, Yawen

2015-03-01

To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as abinary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm can not only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.

An Objective Rationale for the Choice of Regularisation Parameter with Application to Global Multiple-Frequency S-Wave Tomography

NASA Astrophysics Data System (ADS)

Zaroli, C.; Sambridge, M.; Leveque, J. J.; Debayle, E.; Nolet, G.

2014-12-01

In a linear ill-posed inverse problem, the regularisation parameter (damping) controls the balance between minimising both the residual data misfit and the model norm. Poor knowledge of data uncertainties often makes the selection of damping rather arbitrary. To go beyond that subjectivity, an objective rationale for the choice of damping is presented, which is based on the coherency of delay-time estimates in different frequency bands. Our method is tailored to the problem of global Multiple-Frequency Tomography, using a data set of 287078 S-wave delay-times measured in five frequency bands (10, 15, 22, 34, 51 s central periods). Whereas for each ray path the delay-time estimates should vary coherently from one period to the other, the noise most likely is not coherent. Thus, the lack of coherency of the information in different frequency bands is exploited, using an analogy with the cross-validation method, to identify models dominated by noise.In addition, a sharp change of behaviour of the model infinity-norm, as the damping becomes lower than a threshold value, is interpreted as the signature of data noise starting to significantly pollute at least one model component. Models with damping larger than this threshold are diagnosed as being constructed with poor data exploitation.Finally, a preferred model is selected from the remaining range of permitted model solutions. This choice is quasi-objective in terms of model interpretation, as the selected model shows a high degree of similarity with almost all other permitted models. The obtained tomographic model is displayed in mid lower-mantle (660-1910 km depth), and is shown to be mostly compatible with three other recent global shear-velocity models, while significant differences can be noticed. A wider application of the presented rationale should permit us to converge towards more objective seismic imaging of the Earth's mantle, using as much as possible of the relevant structural information in the data. This work was recently published: Zaroli, C., Sambridge, M., Lévêque, J.-J., Debayle, E., and Nolet, G. (2013) - Solid Earth, 4, 357-371, doi:10.5194/se-4-357-2013

Representing and Learning Complex Object Interactions

PubMed Central

Zhou, Yilun; Konidaris, George

2017-01-01

We present a framework for representing scenarios with complex object interactions, in which a robot cannot directly interact with the object it wishes to control, but must instead do so via intermediate objects. For example, a robot learning to drive a car can only indirectly change its pose, by rotating the steering wheel. We formalize such complex interactions as chains of Markov decision processes and show how they can be learned and used for control. We describe two systems in which a robot uses learning from demonstration to achieve indirect control: playing a computer game, and using a hot water dispenser to heat a cup of water. PMID:28593181

Vision Assisted Navigation for Miniature Unmanned Aerial Vehicles (MAVs)

DTIC Science & Technology

2009-11-01

commanded to orbit a target of known location. The error in target geolocation is shown for 200 frames with filtering (dashed line) and without (solid...so the performance of the filter was determined by using the estimated poses to solve a geolocation problem. An MAV flying at an altitude of 70 meters... geolocation as well as significantly reducing the short-term variance in the estimates based on the GPS/IMU alone. Due to the nature of the autopilot

Lower limb estimation from sparse landmarks using an articulated shape model.

PubMed

Zhang, Ju; Fernandez, Justin; Hislop-Jambrich, Jacqui; Besier, Thor F

2016-12-08

Rapid generation of lower limb musculoskeletal models is essential for clinically applicable patient-specific gait modeling. Estimation of muscle and joint contact forces requires accurate representation of bone geometry and pose, as well as their muscle attachment sites, which define muscle moment arms. Motion-capture is a routine part of gait assessment but contains relatively sparse geometric information. Standard methods for creating customized models from motion-capture data scale a reference model without considering natural shape variations. We present an articulated statistical shape model of the left lower limb with embedded anatomical landmarks and muscle attachment regions. This model is used in an automatic workflow, implemented in an easy-to-use software application, that robustly and accurately estimates realistic lower limb bone geometry, pose, and muscle attachment regions from seven commonly used motion-capture landmarks. Estimated bone models were validated on noise-free marker positions to have a lower (p=0.001) surface-to-surface root-mean-squared error of 4.28mm, compared to 5.22mm using standard isotropic scaling. Errors at a variety of anatomical landmarks were also lower (8.6mm versus 10.8mm, p=0.001). We improve upon standard lower limb model scaling methods with shape model-constrained realistic bone geometries, regional muscle attachment sites, and higher accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Data-Driven Hierarchical Structure Kernel for Multiscale Part-Based Object Recognition

PubMed Central

Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Zheng, Yuan F.

2017-01-01

Detecting generic object categories in images and videos are a fundamental issue in computer vision. However, it faces the challenges from inter and intraclass diversity, as well as distortions caused by viewpoints, poses, deformations, and so on. To solve object variations, this paper constructs a structure kernel and proposes a multiscale part-based model incorporating the discriminative power of kernels. The structure kernel would measure the resemblance of part-based objects in three aspects: 1) the global similarity term to measure the resemblance of the global visual appearance of relevant objects; 2) the part similarity term to measure the resemblance of the visual appearance of distinctive parts; and 3) the spatial similarity term to measure the resemblance of the spatial layout of parts. In essence, the deformation of parts in the structure kernel is penalized in a multiscale space with respect to horizontal displacement, vertical displacement, and scale difference. Part similarities are combined with different weights, which are optimized efficiently to maximize the intraclass similarities and minimize the interclass similarities by the normalized stochastic gradient ascent algorithm. In addition, the parameters of the structure kernel are learned during the training process with regard to the distribution of the data in a more discriminative way. With flexible part sizes on scale and displacement, it can be more robust to the intraclass variations, poses, and viewpoints. Theoretical analysis and experimental evaluations demonstrate that the proposed multiscale part-based representation model with structure kernel exhibits accurate and robust performance, and outperforms state-of-the-art object classification approaches. PMID:24808345

A Computer Security Course in the Undergraduate Computer Science Curriculum.

ERIC Educational Resources Information Center

Spillman, Richard

1992-01-01

Discusses the importance of computer security and considers criminal, national security, and personal privacy threats posed by security breakdown. Several examples are given, including incidents involving computer viruses. Objectives, content, instructional strategies, resources, and a sample examination for an experimental undergraduate computer…

Evaluation of USDA Lupinus sp. collection for seed-borne potyviruses

USDA-ARS?s Scientific Manuscript database

Plant viruses pose a threat to the acquisition, maintenance, and distribution of lupin germplasm (genus Lupinus, family Fabaceae). The availability of sufficient quantities of healthy and virus-free seed from maintained lupin collections is mandatory for conducting lupin research. The objective of t...

Antibiotic effects on microbial community characteristics in soils under conservation management practices

USDA-ARS?s Scientific Manuscript database

Veterinary antibiotics (VAs) administered to livestock are introduced to agroecosystems via land application of manure, posing a potential human and environmental health risk. These Antibiotics may adversely affect soil microbial communities. The objectives of this research were to investigate poten...

STS-93 Commander Collins poses in front of Columbia

NASA Technical Reports Server (NTRS)

1999-01-01

STS-93 Commander Eileen Collins poses in front of the Space Shuttle orbiter Columbia following her textbook landing on runway 33 at the Shuttle Landing Facility. Main gear touchdown occurred at 11:20:35 p.m. EDT on July 27. On this mission, Collins became the first woman to serve as a Shuttle commander. Also on board were her fellow STS-93 crew members: Pilot Jeffrey S. Ashby and Mission Specialists Stephen A. Hawley (Ph.D.), Catherine G. Coleman (Ph.D.) and Michel Tognini of France, with the Centre National d'Etudes Spatiales (CNES). The mission's primary objective was to deploy the Chandra X-ray Observatory, which will allow scientists from around the world to study some of the most distant, powerful and dynamic objects in the universe. This was the 95th flight in the Space Shuttle program and the 26th for Columbia. The landing was the 19th consecutive Shuttle landing in Florida and the 12th night landing in Shuttle program history.

The STS-93 crew pose in front of Columbia

NASA Technical Reports Server (NTRS)

1999-01-01

The STS-93 crew pose in front of the Space Shuttle orbiter Columbia following their landing on runway 33 at the Shuttle Landing Facility. Main gear touchdown occurred at 11:20:35 p.m. EDT on July 27. From left to right, they are Mission Specialists Catherine G. Coleman (Ph.D.) and Stephen A. Hawley (Ph.D.), Pilot Jeffrey S. Ashby, Commander Eileen Collins, and Mission Specialist Michel Tognini of France, with the Centre National d'Etudes Spatiales (CNES). The mission's primary objective was to deploy the Chandra X-ray Observatory, which will allow scientists from around the world to study some of the most distant, powerful and dynamic objects in the universe. This was the 95th flight in the Space Shuttle program and the 26th for Columbia. The landing was the 19th consecutive Shuttle landing in Florida and the 12th night landing in Shuttle program history. On this mission, Collins became the first woman to serve as a Shuttle commander.

Fiducial Marker Detection and Pose Estimation From LIDAR Range Data

DTIC Science & Technology

2010-03-01

of View FPA Focal Plane Array FPS Frames Per Second FRE Fiducial Registration Error GIS Geographic Information Systems GPS Global...applications to image analysis and automated cartography. Communications of the ACM, 24(6), 381–395. Bradski, G., & Kaehler, A. (2008). Learning OpenCV

AN INFORMATIC APPROACH TO ESTIMATING ECOLOGICAL RISKS POSED BY PHARMACEUTICAL USE: HUMAN PRESCRIPTION PHARMACEUTICALS

EPA Science Inventory

Pharmaceuticals are often excreted from patients as the parent compound or as active metabolites. Some of these compounds have been found in the environment. However, the environmental concentrations of the majority of pharmaceuticals and their metabolites are not known. The re...

A robust statistical estimation (RoSE) algorithm jointly recovers the 3D location and intensity of single molecules accurately and precisely

NASA Astrophysics Data System (ADS)

Mazidi, Hesam; Nehorai, Arye; Lew, Matthew D.

2018-02-01

In single-molecule (SM) super-resolution microscopy, the complexity of a biological structure, high molecular density, and a low signal-to-background ratio (SBR) may lead to imaging artifacts without a robust localization algorithm. Moreover, engineered point spread functions (PSFs) for 3D imaging pose difficulties due to their intricate features. We develop a Robust Statistical Estimation algorithm, called RoSE, that enables joint estimation of the 3D location and photon counts of SMs accurately and precisely using various PSFs under conditions of high molecular density and low SBR.

Dynamic Network Security Control Using Software Defined Networking

DTIC Science & Technology

2016-03-24

Most importantly I thank my family for understanding, loving , and thriving in the hectic world of military spouse and children. Michael C. Todd v...RBAC poses access to objects as a user to member-of group relationship . This construct results in a set of rules to govern access to objects based...API. Agent Agent.py Event.py Message.py ModSysStatus.py Event Message ModSysStatus Event - Message - ModSysStatus Relationship Figure 12. Agent Design

Culture, Communication, and the Challenge of Globalization.

ERIC Educational Resources Information Center

Shome, Raka; Hegde, Radha S.

2002-01-01

Deals with the problematics that globalization poses for critical communication scholarship. Address how uneven patterns of global processes are enacted through cultural practices produced by the transnational flows of images and capital. Explores several areas of contemporary global growth with the overall objective of demonstrating the urgency…

Managing Knowledge through "Hoshin Kanri"

ERIC Educational Resources Information Center

Tennant C.; Roberts P.

2003-01-01

A fundamental challenge within business organizations (whether manufacturing or service, large or small) is posed by the difficulties associated with managing knowledge to integrate the long-term vision and strategic goals with daily working processes and with people. The traditional Western approach of "Management by Objectives" (MbO)…

IN VITRO DERMAL ABSORPTION OF FLAME RETARDANT CHEMICALS

EPA Science Inventory

ABSTRACT
The use of flame retardant chemicals in furniture fabric could pose a potential health risk to consumers from dermal absorption of these compounds. The objective of this study was to examine the in vitro dermal absorption of two flame retardant chemicals, [14C]-d...

An empirical determination of the minimum number of measurements needed to estimate the mean random vitrinite reflectance of disseminated organic matter

USGS Publications Warehouse

Barker, C.E.; Pawlewicz, M.J.

1993-01-01

In coal samples, published recommendations based on statistical methods suggest 100 measurements are needed to estimate the mean random vitrinite reflectance (Rv-r) to within ??2%. Our survey of published thermal maturation studies indicates that those using dispersed organic matter (DOM) mostly have an objective of acquiring 50 reflectance measurements. This smaller objective size in DOM versus that for coal samples poses a statistical contradiction because the standard deviations of DOM reflectance distributions are typically larger indicating a greater sample size is needed to accurately estimate Rv-r in DOM. However, in studies of thermal maturation using DOM, even 50 measurements can be an unrealistic requirement given the small amount of vitrinite often found in such samples. Furthermore, there is generally a reduced need for assuring precision like that needed for coal applications. Therefore, a key question in thermal maturation studies using DOM is how many measurements of Rv-r are needed to adequately estimate the mean. Our empirical approach to this problem is to compute the reflectance distribution statistics: mean, standard deviation, skewness, and kurtosis in increments of 10 measurements. This study compares these intermediate computations of Rv-r statistics with a final one computed using all measurements for that sample. Vitrinite reflectance was measured on mudstone and sandstone samples taken from borehole M-25 in the Cerro Prieto, Mexico geothermal system which was selected because the rocks have a wide range of thermal maturation and a comparable humic DOM with depth. The results of this study suggest that after only 20-30 measurements the mean Rv-r is generally known to within 5% and always to within 12% of the mean Rv-r calculated using all of the measured particles. Thus, even in the worst case, the precision after measuring only 20-30 particles is in good agreement with the general precision of one decimal place recommended for mean Rv-r measurements on DOM. The coefficient of variation (V = standard deviation/mean) is proposed as a statistic to indicate the reliability of the mean Rv-r estimates made at n ??? 20. This preliminary study suggests a V 0.2 suggests an unreliable mean in such small samples. ?? 1993.

Abattoir based survey of bovine cystic echinococcosis in selected commercial abattoir in Ethiopia

USDA-ARS?s Scientific Manuscript database

Hydatidosis is a widespread parasitic disease posing a significant public health and economic burden in developing countries. Abattoir survey was conducted to determine the prevalence of cystic echinococcosis (CE) in cattle, its organ distribution and to estimate financial loss due to organ condemna...

A Monocular SLAM Method to Estimate Relative Pose During Satellite Proximity Operations

DTIC Science & Technology

2015-03-26

localization and mapping with efficient outlier handling. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2013. 5. Herbert Bay...S.H. Spencer . Next generation advanced video guidance sensor. In Aerospace Conference, 2008 IEEE, pages 1–8, March 2008. 12. Michael Calonder, Vincent

Exposure Pathways, Biomarkers and the Exposome: Predictions, Insight, and Uncertainty (SOT presentation - CE lecture)

EPA Science Inventory

The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the hazard presented by the chemical and the extent of exposure. However, many chemicals lack estimates of exposure intake, limiting the understandi...

Emerging Tools to Estimate and to Predict Exposures to Chemicals

EPA Science Inventory

The timely assessment of the human and ecological risk posed by thousands of existing and emerging commercial chemicals is a critical challenge facing EPA in its mission to protect public health and the environment The US EPA has been conducting research to enhance methods used t...

DECISION-SUPPORT SOFTWARE FOR SOIL VAPOR EXTRACTION TECHNOLOGY APPLICATION: HYPERVENTILATE

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) estimate* that 15% to 20% of the approximately 1.7 million underground storage tank (UST) systems containing petroleum products are either leaking or will leak In the near future. These UST systems could pose a serious threat to p...

Rank and Sparsity in Language Processing

ERIC Educational Resources Information Center

Hutchinson, Brian

2013-01-01

Language modeling is one of many problems in language processing that have to grapple with naturally high ambient dimensions. Even in large datasets, the number of unseen sequences is overwhelmingly larger than the number of observed ones, posing clear challenges for estimation. Although existing methods for building smooth language models tend to…

Inverse problems and optimal experiment design in unsteady heat transfer processes identification

NASA Technical Reports Server (NTRS)

Artyukhin, Eugene A.

1991-01-01

Experimental-computational methods for estimating characteristics of unsteady heat transfer processes are analyzed. The methods are based on the principles of distributed parameter system identification. The theoretical basis of such methods is the numerical solution of nonlinear ill-posed inverse heat transfer problems and optimal experiment design problems. Numerical techniques for solving problems are briefly reviewed. The results of the practical application of identification methods are demonstrated when estimating effective thermophysical characteristics of composite materials and thermal contact resistance in two-layer systems.

Hydrological Parameter Estimations from a Conservative Tracer Test With Variable-Density Effects at the Boise Hydrogeophysical Research Site

DTIC Science & Technology

2011-12-15

the measured porosity values can be taken as equivalent to effective porosity values for this aquifer with the risk of only very limited overestimation...information to constrain/control an increasingly ill-posed problem, and (3) risk estimation of a model with more heterogeneity than is needed to explain...coarse fluvial deposits: Boise Hydrogeophysical Research Site, Geological Society of America Bulletin, 116(9–10), 1059–1073. Barrash, W., T. Clemo

Face landmark point tracking using LK pyramid optical flow

NASA Astrophysics Data System (ADS)

Zhang, Gang; Tang, Sikan; Li, Jiaquan

2018-04-01

LK pyramid optical flow is an effective method to implement object tracking in a video. It is used for face landmark point tracking in a video in the paper. The landmark points, i.e. outer corner of left eye, inner corner of left eye, inner corner of right eye, outer corner of right eye, tip of a nose, left corner of mouth, right corner of mouth, are considered. It is in the first frame that the landmark points are marked by hand. For subsequent frames, performance of tracking is analyzed. Two kinds of conditions are considered, i.e. single factors such as normalized case, pose variation and slowly moving, expression variation, illumination variation, occlusion, front face and rapidly moving, pose face and rapidly moving, and combination of the factors such as pose and illumination variation, pose and expression variation, pose variation and occlusion, illumination and expression variation, expression variation and occlusion. Global measures and local ones are introduced to evaluate performance of tracking under different factors or combination of the factors. The global measures contain the number of images aligned successfully, average alignment error, the number of images aligned before failure, and the local ones contain the number of images aligned successfully for components of a face, average alignment error for the components. To testify performance of tracking for face landmark points under different cases, tests are carried out for image sequences gathered by us. Results show that the LK pyramid optical flow method can implement face landmark point tracking under normalized case, expression variation, illumination variation which does not affect facial details, pose variation, and that different factors or combination of the factors have different effect on performance of alignment for different landmark points.

Evaluating pixel and object based image classification techniques for mapping plant invasions from UAV derived aerial imagery: Harrisia pomanensis as a case study

NASA Astrophysics Data System (ADS)

Mafanya, Madodomzi; Tsele, Philemon; Botai, Joel; Manyama, Phetole; Swart, Barend; Monate, Thabang

2017-07-01

Invasive alien plants (IAPs) not only pose a serious threat to biodiversity and water resources but also have impacts on human and animal wellbeing. To support decision making in IAPs monitoring, semi-automated image classifiers which are capable of extracting valuable information in remotely sensed data are vital. This study evaluated the mapping accuracies of supervised and unsupervised image classifiers for mapping Harrisia pomanensis (a cactus plant commonly known as the Midnight Lady) using two interlinked evaluation strategies i.e. point and area based accuracy assessment. Results of the point-based accuracy assessment show that with reference to 219 ground control points, the supervised image classifiers (i.e. Maxver and Bhattacharya) mapped H. pomanensis better than the unsupervised image classifiers (i.e. K-mediuns, Euclidian Length and Isoseg). In this regard, user and producer accuracies were 82.4% and 84% respectively for the Maxver classifier. The user and producer accuracies for the Bhattacharya classifier were 90% and 95.7%, respectively. Though the Maxver produced a higher overall accuracy and Kappa estimate than the Bhattacharya classifier, the Maxver Kappa estimate of 0.8305 is not significantly (statistically) greater than the Bhattacharya Kappa estimate of 0.8088 at a 95% confidence interval. The area based accuracy assessment results show that the Bhattacharya classifier estimated the spatial extent of H. pomanensis with an average mapping accuracy of 86.1% whereas the Maxver classifier only gave an average mapping accuracy of 65.2%. Based on these results, the Bhattacharya classifier is therefore recommended for mapping H. pomanensis. These findings will aid in the algorithm choice making for the development of a semi-automated image classification system for mapping IAPs.

Modeling emission rates and exposures from outdoor cooking

NASA Astrophysics Data System (ADS)

Edwards, Rufus; Princevac, Marko; Weltman, Robert; Ghasemian, Masoud; Arora, Narendra K.; Bond, Tami

2017-09-01

Approximately 3 billion individuals rely on solid fuels for cooking globally. For a large portion of these - an estimated 533 million - cooking is outdoors, where emissions from cookstoves pose a health risk to both cooks and other household and village members. Models that estimate emissions rates from stoves in indoor environments that would meet WHO air quality guidelines (AQG), explicitly don't account for outdoor cooking. The objectives of this paper are to link health based exposure guidelines with emissions from outdoor cookstoves, using a Monte Carlo simulation of cooking times from Haryana India coupled with inverse Gaussian dispersion models. Mean emission rates for outdoor cooking that would result in incremental increases in personal exposure equivalent to the WHO AQG during a 24-h period were 126 ± 13 mg/min for cooking while squatting and 99 ± 10 mg/min while standing. Emission rates modeled for outdoor cooking are substantially higher than emission rates for indoor cooking to meet AQG, because the models estimate impact of emissions on personal exposure concentrations rather than microenvironment concentrations, and because the smoke disperses more readily outdoors compared to indoor environments. As a result, many more stoves including the best performing solid-fuel biomass stoves would meet AQG when cooking outdoors, but may also result in substantial localized neighborhood pollution depending on housing density. Inclusion of the neighborhood impact of pollution should be addressed more formally both in guidelines on emissions rates from stoves that would be protective of health, and also in wider health impact evaluation efforts and burden of disease estimates. Emissions guidelines should better represent the different contexts in which stoves are being used, especially because in these contexts the best performing solid fuel stoves have the potential to provide significant benefits.

Hand-Eye Calibration in Visually-Guided Robot Grinding.

PubMed

Li, Wen-Long; Xie, He; Zhang, Gang; Yan, Si-Jie; Yin, Zhou-Ping

2016-11-01

Visually-guided robot grinding is a novel and promising automation technique for blade manufacturing. One common problem encountered in robot grinding is hand-eye calibration, which establishes the pose relationship between the end effector (hand) and the scanning sensor (eye). This paper proposes a new calibration approach for robot belt grinding. The main contribution of this paper is its consideration of both joint parameter errors and pose parameter errors in a hand-eye calibration equation. The objective function of the hand-eye calibration is built and solved, from which 30 compensated values (corresponding to 24 joint parameters and six pose parameters) are easily calculated in a closed solution. The proposed approach is economic and simple because only a criterion sphere is used to calculate the calibration parameters, avoiding the need for an expensive and complicated tracking process using a laser tracker. The effectiveness of this method is verified using a calibration experiment and a blade grinding experiment. The code used in this approach is attached in the Appendix.

Human action recognition based on kinematic similarity in real time

PubMed Central

Chen, Longting; Luo, Ailing; Zhang, Sicong

2017-01-01

Human action recognition using 3D pose data has gained a growing interest in the field of computer robotic interfaces and pattern recognition since the availability of hardware to capture human pose. In this paper, we propose a fast, simple, and powerful method of human action recognition based on human kinematic similarity. The key to this method is that the action descriptor consists of joints position, angular velocity and angular acceleration, which can meet the different individual sizes and eliminate the complex normalization. The angular parameters of joints within a short sliding time window (approximately 5 frames) around the current frame are used to express each pose frame of human action sequence. Moreover, three modified KNN (k-nearest-neighbors algorithm) classifiers are employed in our method: one for achieving the confidence of every frame in the training step, one for estimating the frame label of each descriptor, and one for classifying actions. Additional estimating of the frame’s time label makes it possible to address single input frames. This approach can be used on difficult, unsegmented sequences. The proposed method is efficient and can be run in real time. The research shows that many public datasets are irregularly segmented, and a simple method is provided to regularize the datasets. The approach is tested on some challenging datasets such as MSR-Action3D, MSRDailyActivity3D, and UTD-MHAD. The results indicate our method achieves a higher accuracy. PMID:29073131

HeatWave: the next generation of thermography devices

NASA Astrophysics Data System (ADS)

Moghadam, Peyman; Vidas, Stephen

2014-05-01

Energy sustainability is a major challenge of the 21st century. To reduce environmental impact, changes are required not only on the supply side of the energy chain by introducing renewable energy sources, but also on the demand side by reducing energy usage and improving energy efficiency. Currently, 2D thermal imaging is used for energy auditing, which measures the thermal radiation from the surfaces of objects and represents it as a set of color-mapped images that can be analysed for the purpose of energy efficiency monitoring. A limitation of such a method for energy auditing is that it lacks information on the geometry and location of objects with reference to each other, particularly across separate images. Such a limitation prevents any quantitative analysis to be done, for example, detecting any energy performance changes before and after retrofitting. To address these limitations, we have developed a next generation thermography device called Heat Wave. Heat Wave is a hand-held 3D thermography device that consists of a thermal camera, a range sensor and color camera, and can be used to generate precise 3D model of objects with augmented temperature and visible information. As an operator holding the device smoothly waves it around the objects of interest, Heat Wave can continuously track its own pose in space and integrate new information from the range and thermal and color cameras into a single, and precise 3D multi-modal model. Information from multiple viewpoints can be incorporated together to improve the accuracy, reliability and robustness of the global model. The approach also makes it possible to reduce any systematic errors associated with the estimation of surface temperature from the thermal images.

Camera pose estimation to improve accuracy and reliability of joint angles assessed with attitude and heading reference systems.

PubMed

Lebel, Karina; Hamel, Mathieu; Duval, Christian; Nguyen, Hung; Boissy, Patrick

2018-01-01

Joint kinematics can be assessed using orientation estimates from Attitude and Heading Reference Systems (AHRS). However, magnetically-perturbed environments affect the accuracy of the estimated orientations. This study investigates, both in controlled and human mobility conditions, a trial calibration technic based on a 2D photograph with a pose estimation algorithm to correct initial difference in AHRS Inertial reference frames and improve joint angle accuracy. In controlled conditions, two AHRS were solidly affixed onto a wooden stick and a series of static and dynamic trials were performed in varying environments. Mean accuracy of relative orientation between the two AHRS was improved from 24.4° to 2.9° using the proposed correction method. In human conditions, AHRS were placed on the shank and the foot of a participant who performed repeated trials of straight walking and walking while turning, varying the level of magnetic perturbation in the starting environment and the walking speed. Mean joint orientation accuracy went from 6.7° to 2.8° using the correction algorithm. The impact of starting environment was also greatly reduced, up to a point where one could consider it as non-significant from a clinical point of view (maximum mean difference went from 8° to 0.6°). The results obtained demonstrate that the proposed method improves significantly the mean accuracy of AHRS joint orientation estimations in magnetically-perturbed environments and can be implemented in post processing of AHRS data collected during biomechanical evaluation of motion. Copyright © 2017 Elsevier B.V. All rights reserved.

Seismic hazard and risk assessment in the intraplate environment: The New Madrid seismic zone of the central United States

USGS Publications Warehouse

Wang, Z.

2007-01-01

Although the causes of large intraplate earthquakes are still not fully understood, they pose certain hazard and risk to societies. Estimating hazard and risk in these regions is difficult because of lack of earthquake records. The New Madrid seismic zone is one such region where large and rare intraplate earthquakes (M = 7.0 or greater) pose significant hazard and risk. Many different definitions of hazard and risk have been used, and the resulting estimates differ dramatically. In this paper, seismic hazard is defined as the natural phenomenon generated by earthquakes, such as ground motion, and is quantified by two parameters: a level of hazard and its occurrence frequency or mean recurrence interval; seismic risk is defined as the probability of occurrence of a specific level of seismic hazard over a certain time and is quantified by three parameters: probability, a level of hazard, and exposure time. Probabilistic seismic hazard analysis (PSHA), a commonly used method for estimating seismic hazard and risk, derives a relationship between a ground motion parameter and its return period (hazard curve). The return period is not an independent temporal parameter but a mathematical extrapolation of the recurrence interval of earthquakes and the uncertainty of ground motion. Therefore, it is difficult to understand and use PSHA. A new method is proposed and applied here for estimating seismic hazard in the New Madrid seismic zone. This method provides hazard estimates that are consistent with the state of our knowledge and can be easily applied to other intraplate regions. ?? 2007 The Geological Society of America.

Concepts for design of an energy management system incorporating dispersed storage and generation

NASA Technical Reports Server (NTRS)

Kirkham, H.; Koerner, T.; Nightingale, D.

1981-01-01

New forms of generation based on renewable resources must be managed as part of existing power systems in order to be utilized with maximum effectiveness. Many of these generators are by their very nature dispersed or small, so that they will be connected to the distribution part of the power system. This situation poses new questions of control and protection, and the intermittent nature of some of the energy sources poses problems of scheduling and dispatch. Under the assumption that the general objectives of energy management will remain unchanged, the impact of dispersed storage and generation on some of the specific functions of power system control and its hardware are discussed.

Text-Dependent Questions: Reflecting and Transcending the Text

ERIC Educational Resources Information Center

Boelé, Amy L.

2016-01-01

Posing text-dependent questions is crucial for facilitating students' comprehension of the text. However, text-dependent questions should not merely ask students to reflect the author's literal or even inferential meaning. The author's message is the starting place for comprehension, rather than the end goal or object of comprehension. The text…

TYPES AND QUANTITIES OF LEFTOVER DRUGS ENTERING THE ENVIRONMENT VIA DISPOSAL TO SEWAGE - REVEALED BY CORONERS' RECORDS

EPA Science Inventory

BACKGROUND: Pharmaceuticals designed for humans and animals often remain unused. Leftover and accumulated drugs represent suboptimal delivery of health care and environmentally unsound disposal, which can pose exposure risks for humans and wildlife.

OBJECTIVES: A major unk...

Making the "Minority" Voice Heard: Critical Communication Pedagogy and Dissent

ERIC Educational Resources Information Center

Lawless, Brandi

2018-01-01

Courses: Intercultural Communication, Argumentation and Advocacy, Communication and Education. Objectives: This activity is designed to help students to problem-pose and think critically about policies/laws that influence education. Students will be exposed to U.S. policy and will be able to articulate a critical dissent of such documents.

Examining Autism Spectrum Disorders by Biomarkers: Example from the Oxytocin and Serotonin Systems

ERIC Educational Resources Information Center

Hammock, Elizabeth; Veenstra-VanderWeele, Jeremy; Yan, Zhongyu; Kerr, Travis M.; Morris, Marianna; Anderson, George M.; Carter, C. Sue; Cook, Edwin H.; Jacob, Suma

2012-01-01

Objective: Autism spectrum disorder (ASD) is a heritable but highly heterogeneous neuropsychiatric syndrome, which poses challenges for research relying solely on behavioral symptoms or diagnosis. Examining biomarkers may give us ways to identify individuals who demonstrate specific developmental trajectories and etiological factors related to…

49 CFR 109.7 - Removal from transportation.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 2 2013-10-01 2013-10-01 false Removal from transportation. 109.7 Section 109.7... when the agent has an objectively reasonable and articulable belief that the packages may pose an imminent hazard. The agent must record this belief in writing as soon as practicable and provide written...

49 CFR 109.7 - Removal from transportation.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 2 2012-10-01 2012-10-01 false Removal from transportation. 109.7 Section 109.7... to forty-eight (48) hours when the agent has an objectively reasonable and articulable belief that the packages may pose an imminent hazard. The agent must record this belief in writing as soon as...

49 CFR 109.7 - Removal from transportation.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 2 2011-10-01 2011-10-01 false Removal from transportation. 109.7 Section 109.7... to forty-eight (48) hours when the agent has an objectively reasonable and articulable belief that the packages may pose an imminent hazard. The agent must record this belief in writing as soon as...

Visual reconciliation of alternative similarity spaces in climate modeling

Treesearch

J Poco; A Dasgupta; Y Wei; William Hargrove; C.R. Schwalm; D.N. Huntzinger; R Cook; E Bertini; C.T. Silva

2015-01-01

Visual data analysis often requires grouping of data objects based on their similarity. In many application domains researchers use algorithms and techniques like clustering and multidimensional scaling to extract groupings from data. While extracting these groups using a single similarity criteria is relatively straightforward, comparing alternative criteria poses...

DEVELOPMENT OF A DISTURBANCE INDEX TO ASSESS THE CONDITION OF AQUATIC ECOSYSTEMS

EPA Science Inventory

An objective of aquatic monitoring is to assess the condition of aquatic habitats and biota. To rationally interpret aquatic condition, we must identify the range of human activities and the risks they pose to aquatic ecosystems. Placing stream reaches and their watersheds on a...

Institutional Support | Grid Modernization | NREL

Science.gov Websites

the challenges posed by grid modernization. Photo of two people standing in front of a display showing results from a grid study. The demand for objective technical assistance and information on grid related to grid modernization and increasing deployment of distributed energy and renewable resources. As

Interdisciplinarity in Swiss Schools: A Difficult Step into the Future

ERIC Educational Resources Information Center

Ghisla, Gianni; Bausch, Luca; Bonoli, Lorenzo

2010-01-01

Multi- and interdisciplinary education is a major postulate in the Swiss school system and has considerable weight in educational programs and learning objectives, both in compulsory school and at the upper secondary school level. However, materializing this postulate still poses problems at the political and institutional level, where the…

Global Perspectives: Some Questions and Answers.

ERIC Educational Resources Information Center

Center for Global Perspectives, New York, NY.

To enlighten the reader on the status, objectives, and needs of global education, this paper poses and answers questions related to global perspectives. A global perspective is interpreted to include heightened awareness and understanding of the global system as well as increased consciousness of the intimate relationship of self, humankind, and…

Compton imaging tomography technique for NDE of large nonuniform structures

NASA Astrophysics Data System (ADS)

Grubsky, Victor; Romanov, Volodymyr; Patton, Ned; Jannson, Tomasz

2011-09-01

In this paper we describe a new nondestructive evaluation (NDE) technique called Compton Imaging Tomography (CIT) for reconstructing the complete three-dimensional internal structure of an object, based on the registration of multiple two-dimensional Compton-scattered x-ray images of the object. CIT provides high resolution and sensitivity with virtually any material, including lightweight structures and organics, which normally pose problems in conventional x-ray computed tomography because of low contrast. The CIT technique requires only one-sided access to the object, has no limitation on the object's size, and can be applied to high-resolution real-time in situ NDE of large aircraft/spacecraft structures and components. Theoretical and experimental results will be presented.

Catchment scale assessment of risk posed by traffic generated heavy metals and polycyclic aromatic hydrocarbons.

PubMed

Ma, Yukun; McGree, James; Liu, An; Deilami, Kaveh; Egodawatta, Prasanna; Goonetilleke, Ashantha

2017-10-01

Heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) are among the most toxic chemical pollutants present in urban stormwater. Consequently, urban stormwater reuse is constrained due to the human health risk posed by these pollutants. This study developed a scientifically robust approach to assess the risk to human health posed by HMs and PAHs in urban stormwater in order to enhance its reuse. Accordingly, an innovative methodology was created consisting of four stages: quantification of traffic and land use parameters; estimation of pollutant concentrations for model development; risk assessment, and risk map presentation. This methodology will contribute to catchment scale assessment of the risk associated with urban stormwater and for risk mitigation. The risk map developed provides a simple and efficient approach to identify the critical areas within a large catchment. The study also found that heavy molecular weight PAHs (PAHs with 5-6 benzene rings) in urban stormwater pose higher risk to human health compared to light molecular PAHs (PAHs with 2-4 benzene rings). These outcomes will facilitate the development of practical approaches for applying appropriate mitigation measures for the safe management of urban stormwater pollution and for the identification of enhanced reuse opportunities. Copyright © 2017 Elsevier Inc. All rights reserved.

Dual-Hierarchy Graph Method for Object Indexing and Recognition

DTIC Science & Technology

2014-07-01

from examples would be too late for the prey. Mythical monsters in movies or cartoons can look quite scary even though we have never seen their...uniform, at 25 blocks per parent, but depends on the number of SIFT features in the parent blocks. If we have more features we create more children for...method mentioned above to these descriptors to derive the 3D structure and pose of the object. In effect , we replace the previous “spatial verification

A Numerical Approach to Estimate the Ballistic Coefficient of Space Debris from TLE Orbital Data

NASA Technical Reports Server (NTRS)

Narkeliunas, Jonas

2016-01-01

Low Earth Orbit (LEO) is full of space debris, which consist of spent rocket stages, old satellites and fragments from explosions and collisions. As of 2009, more than 21,000 orbital debris larger than 10 cm are known to exist], and while it is hard to track anything smaller than that, the estimated population of particles between 1 and 10 cm in diameter is approximately 500,000, whereas small as 1 cm exceeds 100 million. These objects orbit Earth with huge kinetic energies speeds usually exceed 7 kms. The shape of their orbit varies from almost circular to highly elliptical and covers all LEO, a region in space between 160 and 2,000 km above sea level. Unfortunately, LEO is also the place where most of our active satellites are situated, as well as, International Space Station (ISS) and Hubble Space Telescope, whose orbits are around 400 and 550 km above sea level, respectively.This poses a real threat as debris can collide with satellites and deal substantial damage or even destroy them.Collisions between two or more debris create clouds of smaller debris, which are harder to track and increase overall object density and collision probability. At some point, the debris density couldthen reach a critical value, which would start a chain reaction and the number of space debris would grow exponentially. This phenomenon was first described by Kessler in 1978 and he concluded that it would lead to creation of debris belt, which would vastly complicate satellite operations in LEO. The debris density is already relatively high, as seen from several necessary debris avoidance maneuvers done by Shuttle, before it was discontinued, and ISS. But not all satellites have a propulsion system to avoid collision, hence different methods need to be applied. One of the proposed collision avoidance concepts is called LightForce and it suggests using photon pressure to induce small orbital corrections to deflect debris from colliding. This method is very efficient as seen from theoretical simulations, even few continuous mode 10 kW ground-based lasers, focused by 1.5 m telescopes with adaptive optics, were enough to prevent significant amount of the debris collisions. Simulations were done by propagating all space objects in LEO by 1 year into the future and checking whether the probability of collision was high. For those space objects different ground-based lasers were used to divert them, afterwards collision probabilities were reevaluated. However, the actual accuracy of the LightForce software, which has been developed at NASA AmesResearch Center, depends on the veracity of the input parameters, one of which is the objects ballistic coefficient. It is a measure of bodys ability to overcome air resistance, which has a significant impact on the debris in LEO, and thus it is responsible for the shape of the trajectory of the debris. Having the exact values of the ballistic coefficient would make significantly better collision predictions, unfortunately, we do not know what are the values for most of the objects.In this research, we were working with part of LightForce code, which estimates the ballistic coefficient from ephemerides. Previously used method gave highly inaccurate values, when compared to known objects, and it needed to be changed. The goal of this work was to try out a different method of estimating the ballistic coefficient and to check whether or not it gives noticeable improvements.

Whole-arm tactile sensing for beneficial and acceptable contact during robotic assistance.

PubMed

Grice, Phillip M; Killpack, Marc D; Jain, Advait; Vaish, Sarvagya; Hawke, Jeffrey; Kemp, Charles C

2013-06-01

Many assistive tasks involve manipulation near the care-receiver's body, including self-care tasks such as dressing, feeding, and personal hygiene. A robot can provide assistance with these tasks by moving its end effector to poses near the care-receiver's body. However, perceiving and maneuvering around the care-receiver's body can be challenging due to a variety of issues, including convoluted geometry, compliant materials, body motion, hidden surfaces, and the object upon which the body is resting (e.g., a wheelchair or bed). Using geometric simulations, we first show that an assistive robot can achieve a much larger percentage of end-effector poses near the care-receiver's body if its arm is allowed to make contact. Second, we present a novel system with a custom controller and whole-arm tactile sensor array that enables a Willow Garage PR2 to regulate contact forces across its entire arm while moving its end effector to a commanded pose. We then describe tests with two people with motor impairments, one of whom used the system to grasp and pull a blanket over himself and to grab a cloth and wipe his face, all while in bed at his home. Finally, we describe a study with eight able-bodied users in which they used the system to place objects near their bodies. On average, users perceived the system to be safe and comfortable, even though substantial contact occurred between the robot's arm and the user's body.

Proto-object categorisation and local gist vision using low-level spatial features.

PubMed

Martins, Jaime A; Rodrigues, J M F; du Buf, J M H

2015-09-01

Object categorisation is a research area with significant challenges, especially in conditions with bad lighting, occlusions, different poses and similar objects. This makes systems that rely on precise information unable to perform efficiently, like a robotic arm that needs to know which objects it can reach. We propose a biologically inspired object detection and categorisation framework that relies on robust low-level object shape. Using only edge conspicuity and disparity features for scene figure-ground segregation and object categorisation, a trained neural network classifier can quickly categorise broad object families and consequently bootstrap a low-level scene gist system. We argue that similar processing is possibly located in the parietal pathway leading to the LIP cortex and, via areas V5/MT and MST, providing useful information to the superior colliculus for eye and head control. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Setting a research question, aim and objective.

PubMed

Doody, Owen; Bailey, Maria E

2016-03-01

To describe the development of a research question, aim and objective. The first steps of any study are developing the research question, aim and objective. Subsequent steps develop from these and they govern the researchers' choice of population, setting, data to be collected and time period for the study. Clear, succinctly posed research questions, aims and objectives are essential if studies are to be successful. Researchers developing their research questions, aims and objectives generally experience difficulties. They are often overwhelmed trying to convert what they see as a relevant issue from practice into research. This necessitates engaging with the relevant published literature and knowledgeable people. This paper identifies the issues to be considered when developing a research question, aim and objective. Understanding these considerations will enable researchers to effectively present their research question, aim and objective. To conduct successful studies, researchers should develop clear research questions, aims and objectives.

Estimation of Faults in DC Electrical Power System

NASA Technical Reports Server (NTRS)

Gorinevsky, Dimitry; Boyd, Stephen; Poll, Scott

2009-01-01

This paper demonstrates a novel optimization-based approach to estimating fault states in a DC power system. Potential faults changing the circuit topology are included along with faulty measurements. Our approach can be considered as a relaxation of the mixed estimation problem. We develop a linear model of the circuit and pose a convex problem for estimating the faults and other hidden states. A sparse fault vector solution is computed by using 11 regularization. The solution is computed reliably and efficiently, and gives accurate diagnostics on the faults. We demonstrate a real-time implementation of the approach for an instrumented electrical power system testbed, the ADAPT testbed at NASA ARC. The estimates are computed in milliseconds on a PC. The approach performs well despite unmodeled transients and other modeling uncertainties present in the system.

The Autoregressive Method: A Method of Approximating and Estimating Positive Functions

DTIC Science & Technology

1976-08-01

in drawing the curves, thanks to computer graphics. A few people ha’ very imaginatively pro- posed - td developed new ways of visualizing the data...k= -= it turns out that , , 0ki < 0 is a sufficient condition for all our k= -cc ( operations to be valid. Ii_ _ _ _ _ _ __ __ _ _ _ _ -106- We will

Policies To Help Disadvantaged Children: Financing Options for the 1990s. Changing Domestic Priorities Discussion Paper.

ERIC Educational Resources Information Center

Barnes, Roberta Ott; And Others

This paper estimates the costs of several approaches to increasing federal assistance to disadvantaged children and evaluates major funding strategies that could overcome the restrictions posed by the federal budget deficit. Approaches favored by conservatives, such as strengthening behavioral standards for children, sponsoring demonstration…

Managing the emerald ash borer in Canada

Treesearch

Kenneth R. Marchant

2007-01-01

The Emerald ash borer, (EAB, Agrilus planipennis Fairmaire) continues to pose a major risk to Canadian urban and rural forests and parklands. EAB now occurs in four counties in southwestern Ontario. An estimated 1 million ash trees in Essex County, Ontario, and millions more in adjacent counties are in peril. Little natural resistance has been...

Evaluating source area contributions from aircraft flux measurements over heterogeneous land cover by large eddy simulation

USDA-ARS?s Scientific Manuscript database

The estimation of spatial patterns in surface fluxes from aircraft observations poses several challenges in presence of heterogeneous land cover. In particular, the effects of turbulence on scalar transport and the different behavior of passive (e.g. moisture) versus active (e.g. temperature) scalar...