Comparative assessment of techniques for initial pose estimation using monocular vision
NASA Astrophysics Data System (ADS)
Sharma, Sumant; D`Amico, Simone
2016-06-01
This work addresses the comparative assessment of initial pose estimation techniques for monocular navigation to enable formation-flying and on-orbit servicing missions. Monocular navigation relies on finding an initial pose, i.e., a coarse estimate of the attitude and position of the space resident object with respect to the camera, based on a minimum number of features from a three dimensional computer model and a single two dimensional image. The initial pose is estimated without the use of fiducial markers, without any range measurements or any apriori relative motion information. Prior work has been done to compare different pose estimators for terrestrial applications, but there is a lack of functional and performance characterization of such algorithms in the context of missions involving rendezvous operations in the space environment. Use of state-of-the-art pose estimation algorithms designed for terrestrial applications is challenging in space due to factors such as limited on-board processing power, low carrier to noise ratio, and high image contrasts. This paper focuses on performance characterization of three initial pose estimation algorithms in the context of such missions and suggests improvements.
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.
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.
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.
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.
Point Cloud Based Relative Pose Estimation of a Satellite in Close Range
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
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.
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.
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.
Exemplar-based human action pose correction.
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.
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
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.
Neuromorphic Event-Based 3D Pose Estimation
Reverter Valeiras, David; Orchard, Garrick; Ieng, Sio-Hoi; Benosman, Ryad B.
2016-01-01
Pose estimation is a fundamental step in many artificial vision tasks. It consists of estimating the 3D pose of an object with respect to a camera from the object's 2D projection. Current state of the art implementations operate on images. These implementations are computationally expensive, especially for real-time applications. Scenes with fast dynamics exceeding 30–60 Hz can rarely be processed in real-time using conventional hardware. This paper presents a new method for event-based 3D object pose estimation, making full use of the high temporal resolution (1 μs) of asynchronous visual events output from a single neuromorphic camera. Given an initial estimate of the pose, each incoming event is used to update the pose by combining both 3D and 2D criteria. We show that the asynchronous high temporal resolution of the neuromorphic camera allows us to solve the problem in an incremental manner, achieving real-time performance at an update rate of several hundreds kHz on a conventional laptop. We show that the high temporal resolution of neuromorphic cameras is a key feature for performing accurate pose estimation. Experiments are provided showing the performance of the algorithm on real data, including fast moving objects, occlusions, and cases where the neuromorphic camera and the object are both in motion. PMID:26834547
A model-based 3D template matching technique for pose acquisition of an uncooperative space object.
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.
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°.
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.
Estimation of Antenna Pose in the Earth Frame Using Camera and IMU Data from Mobile Phones
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
Human Pose Estimation from Monocular Images: A Comprehensive Survey
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
Three-dimensional face pose detection and tracking using monocular videos: tool and application.
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.
3-D rigid body tracking using vision and depth sensors.
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.
Sparse Unorganized Point Cloud Based Relative Pose Estimation for Uncooperative Space Target.
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
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
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.
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.
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.
A Probabilistic Feature Map-Based Localization System Using a Monocular Camera.
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
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
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
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.
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
Mapping debris-flow hazard in Honolulu using a DEM
Ellen, Stephen D.; Mark, Robert K.; ,
1993-01-01
A method for mapping hazard posed by debris flows has been developed and applied to an area near Honolulu, Hawaii. The method uses studies of past debris flows to characterize sites of initiation, volume at initiation, and volume-change behavior during flow. Digital simulations of debris flows based on these characteristics are then routed through a digital elevation model (DEM) to estimate degree of hazard over the area.
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.
NASA Astrophysics Data System (ADS)
Fu, Deqian; Gao, Lisheng; Jhang, Seong Tae
2012-04-01
The mobile computing device has many limitations, such as relative small user interface and slow computing speed. Usually, augmented reality requires face pose estimation can be used as a HCI and entertainment tool. As far as the realtime implementation of head pose estimation on relatively resource limited mobile platforms is concerned, it is required to face different constraints while leaving enough face pose estimation accuracy. The proposed face pose estimation method met this objective. Experimental results running on a testing Android mobile device delivered satisfactory performing results in the real-time and accurately.
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 modeling using the homogeneous transformation for non-cooperative pose estimation
NASA Astrophysics Data System (ADS)
Lim, Tae W.
2015-06-01
A modeling process to simulate point cloud range data that a lidar (light detection and ranging) sensor produces is presented in this paper in order to support the development of non-cooperative pose (relative attitude and position) estimation approaches which will help improve proximity operation capabilities between two adjacent vehicles. The algorithms in the modeling process were based on the homogeneous transformation, which has been employed extensively in robotics and computer graphics, as well as in recently developed pose estimation algorithms. Using a flash lidar in a laboratory testing environment, point cloud data of a test article was simulated and compared against the measured point cloud data. The simulated and measured data sets match closely, validating the modeling process. The modeling capability enables close examination of the characteristics of point cloud images of an object as it undergoes various translational and rotational motions. Relevant characteristics that will be crucial in non-cooperative pose estimation were identified such as shift, shadowing, perspective projection, jagged edges, and differential point cloud density. These characteristics will have to be considered in developing effective non-cooperative pose estimation algorithms. The modeling capability will allow extensive non-cooperative pose estimation performance simulations prior to field testing, saving development cost and providing performance metrics of the pose estimation concepts and algorithms under evaluation. The modeling process also provides "truth" pose of the test objects with respect to the sensor frame so that the pose estimation error can be quantified.
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.
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.
Quantitative Compactness Estimates for Hamilton-Jacobi Equations
NASA Astrophysics Data System (ADS)
Ancona, Fabio; Cannarsa, Piermarco; Nguyen, Khai T.
2016-02-01
We study quantitative compactness estimates in {W^{1,1}_{loc}} for the map {S_t}, {t > 0} that is associated with the given initial data {u_0in Lip (R^N)} for the corresponding solution {S_t u_0} of a Hamilton-Jacobi equation u_t+Hbig(nabla_{x} ubig)=0, qquad t≥ 0,quad xinR^N, with a uniformly convex Hamiltonian {H=H(p)}. We provide upper and lower estimates of order {1/\\varepsilon^N} on the Kolmogorov {\\varepsilon}-entropy in {W^{1,1}} of the image through the map S t of sets of bounded, compactly supported initial data. Estimates of this type are inspired by a question posed by Lax (Course on Hyperbolic Systems of Conservation Laws. XXVII Scuola Estiva di Fisica Matematica, Ravello, 2002) within the context of conservation laws, and could provide a measure of the order of "resolution" of a numerical method implemented for this equation.
A robust vision-based sensor fusion approach for real-time pose estimation.
Assa, Akbar; Janabi-Sharifi, Farrokh
2014-02-01
Object pose estimation is of great importance to many applications, such as augmented reality, localization and mapping, motion capture, and visual servoing. Although many approaches based on a monocular camera have been proposed, only a few works have concentrated on applying multicamera sensor fusion techniques to pose estimation. Higher accuracy and enhanced robustness toward sensor defects or failures are some of the advantages of these schemes. This paper presents a new Kalman-based sensor fusion approach for pose estimation that offers higher accuracy and precision, and is robust to camera motion and image occlusion, compared to its predecessors. Extensive experiments are conducted to validate the superiority of this fusion method over currently employed vision-based pose estimation algorithms.
An Optimization-Based State Estimatioin Framework for Large-Scale Natural Gas Networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jalving, Jordan; Zavala, Victor M.
We propose an optimization-based state estimation framework to track internal spacetime flow and pressure profiles of natural gas networks during dynamic transients. We find that the estimation problem is ill-posed (because of the infinite-dimensional nature of the states) and that this leads to instability of the estimator when short estimation horizons are used. To circumvent this issue, we propose moving horizon strategies that incorporate prior information. In particular, we propose a strategy that initializes the prior using steady-state information and compare its performance against a strategy that does not initialize the prior. We find that both strategies are capable ofmore » tracking the state profiles but we also find that superior performance is obtained with steady-state prior initialization. We also find that, under the proposed framework, pressure sensor information at junctions is sufficient to track the state profiles. We also derive approximate transport models and show that some of these can be used to achieve significant computational speed-ups without sacrificing estimation performance. We show that the estimator can be easily implemented in the graph-based modeling framework Plasmo.jl and use a multipipeline network study to demonstrate the developments.« less
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.
Head pose estimation in computer vision: a survey.
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.
Prostate Brachytherapy Seed Reconstruction with Gaussian Blurring and Optimal Coverage Cost
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
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.
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.
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.
Pose estimation of industrial objects towards robot operation
NASA Astrophysics Data System (ADS)
Niu, Jie; Zhou, Fuqiang; Tan, Haishu; Cao, Yu
2017-10-01
With the advantages of wide range, non-contact and high flexibility, the visual estimation technology of target pose has been widely applied in modern industry, robot guidance and other engineering practices. However, due to the influence of complicated industrial environment, outside interference factors, lack of object characteristics, restrictions of camera and other limitations, the visual estimation technology of target pose is still faced with many challenges. Focusing on the above problems, a pose estimation method of the industrial objects is developed based on 3D models of targets. By matching the extracted shape characteristics of objects with the priori 3D model database of targets, the method realizes the recognition of target. Thus a pose estimation of objects can be determined based on the monocular vision measuring model. The experimental results show that this method can be implemented to estimate the position of rigid objects based on poor images information, and provides guiding basis for the operation of the industrial robot.
Robust head pose estimation via supervised manifold learning.
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.
Increasing the automation of a 2D-3D registration system.
Varnavas, Andreas; Carrell, Tom; Penney, Graeme
2013-02-01
Routine clinical use of 2D-3D registration algorithms for Image Guided Surgery remains limited. A key aspect for routine clinical use of this technology is its degree of automation, i.e., the amount of necessary knowledgeable interaction between the clinicians and the registration system. Current image-based registration approaches usually require knowledgeable manual interaction during two stages: for initial pose estimation and for verification of produced results. We propose four novel techniques, particularly suited to vertebra-based registration systems, which can significantly automate both of the above stages. Two of these techniques are based upon the intraoperative "insertion" of a virtual fiducial marker into the preoperative data. The remaining two techniques use the final registration similarity value between multiple CT vertebrae and a single fluoroscopy vertebra. The proposed methods were evaluated with data from 31 operations (31 CT scans, 419 fluoroscopy images). Results show these methods can remove the need for manual vertebra identification during initial pose estimation, and were also very effective for result verification, producing a combined true positive rate of 100% and false positive rate equal to zero. This large decrease in required knowledgeable interaction is an important contribution aiming to enable more widespread use of 2D-3D registration technology.
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.
Nonlinear features for classification and pose estimation of machined parts from single views
NASA Astrophysics Data System (ADS)
Talukder, Ashit; Casasent, David P.
1998-10-01
A new nonlinear feature extraction method is presented for classification and pose estimation of objects from single views. The feature extraction method is called the maximum representation and discrimination feature (MRDF) method. The nonlinear MRDF transformations to use are obtained in closed form, and offer significant advantages compared to nonlinear neural network implementations. The features extracted are useful for both object discrimination (classification) and object representation (pose estimation). We consider MRDFs on image data, provide a new 2-stage nonlinear MRDF solution, and show it specializes to well-known linear and nonlinear image processing transforms under certain conditions. We show the use of MRDF in estimating the class and pose of images of rendered solid CAD models of machine parts from single views using a feature-space trajectory neural network classifier. We show new results with better classification and pose estimation accuracy than are achieved by standard principal component analysis and Fukunaga-Koontz feature extraction methods.
Chen, Chin-Sheng; Chen, Po-Chun; Hsu, Chih-Ming
2016-01-01
This paper presents a novel 3D feature descriptor for object recognition and to identify poses when there are six-degrees-of-freedom for mobile manipulation and grasping applications. Firstly, a Microsoft Kinect sensor is used to capture 3D point cloud data. A viewpoint feature histogram (VFH) descriptor for the 3D point cloud data then encodes the geometry and viewpoint, so an object can be simultaneously recognized and registered in a stable pose and the information is stored in a database. The VFH is robust to a large degree of surface noise and missing depth information so it is reliable for stereo data. However, the pose estimation for an object fails when the object is placed symmetrically to the viewpoint. To overcome this problem, this study proposes a modified viewpoint feature histogram (MVFH) descriptor that consists of two parts: a surface shape component that comprises an extended fast point feature histogram and an extended viewpoint direction component. The MVFH descriptor characterizes an object’s pose and enhances the system’s ability to identify objects with mirrored poses. Finally, the refined pose is further estimated using an iterative closest point when the object has been recognized and the pose roughly estimated by the MVFH descriptor and it has been registered on a database. The estimation results demonstrate that the MVFH feature descriptor allows more accurate pose estimation. The experiments also show that the proposed method can be applied in vision-guided robotic grasping systems. PMID:27886080
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.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Hahn, Markus; Barrois, Björn; Krüger, Lars; Wöhler, Christian; Sagerer, Gerhard; Kummert, Franz
2010-09-01
This study introduces an approach to model-based 3D pose estimation and instantaneous motion analysis of the human hand-forearm limb in the application context of safe human-robot interaction. 3D pose estimation is performed using two approaches: The Multiocular Contracting Curve Density (MOCCD) algorithm is a top-down technique based on pixel statistics around a contour model projected into the images from several cameras. The Iterative Closest Point (ICP) algorithm is a bottom-up approach which uses a motion-attributed 3D point cloud to estimate the object pose. Due to their orthogonal properties, a fusion of these algorithms is shown to be favorable. The fusion is performed by a weighted combination of the extracted pose parameters in an iterative manner. The analysis of object motion is based on the pose estimation result and the motion-attributed 3D points belonging to the hand-forearm limb using an extended constraint-line approach which does not rely on any temporal filtering. A further refinement is obtained using the Shape Flow algorithm, a temporal extension of the MOCCD approach, which estimates the temporal pose derivative based on the current and the two preceding images, corresponding to temporal filtering with a short response time of two or at most three frames. Combining the results of the two motion estimation stages provides information about the instantaneous motion properties of the object. Experimental investigations are performed on real-world image sequences displaying several test persons performing different working actions typically occurring in an industrial production scenario. In all example scenes, the background is cluttered, and the test persons wear various kinds of clothes. For evaluation, independently obtained ground truth data are used. [Figure not available: see fulltext.
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.
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.
Classification and pose estimation of objects using nonlinear features
NASA Astrophysics Data System (ADS)
Talukder, Ashit; Casasent, David P.
1998-03-01
A new nonlinear feature extraction method called the maximum representation and discrimination feature (MRDF) method is presented for extraction of features from input image data. It implements transformations similar to the Sigma-Pi neural network. However, the weights of the MRDF are obtained in closed form, and offer advantages compared to nonlinear neural network implementations. The features extracted are useful for both object discrimination (classification) and object representation (pose estimation). We show its use in estimating the class and pose of images of real objects and rendered solid CAD models of machine parts from single views using a feature-space trajectory (FST) neural network classifier. We show more accurate classification and pose estimation results than are achieved by standard principal component analysis (PCA) and Fukunaga-Koontz (FK) feature extraction methods.
A practical method to assess model sensitivity and parameter uncertainty in C cycle models
NASA Astrophysics Data System (ADS)
Delahaies, Sylvain; Roulstone, Ian; Nichols, Nancy
2015-04-01
The carbon cycle combines multiple spatial and temporal scales, from minutes to hours for the chemical processes occurring in plant cells to several hundred of years for the exchange between the atmosphere and the deep ocean and finally to millennia for the formation of fossil fuels. Together with our knowledge of the transformation processes involved in the carbon cycle, many Earth Observation systems are now available to help improving models and predictions using inverse modelling techniques. A generic inverse problem consists in finding a n-dimensional state vector x such that h(x) = y, for a given N-dimensional observation vector y, including random noise, and a given model h. The problem is well posed if the three following conditions hold: 1) there exists a solution, 2) the solution is unique and 3) the solution depends continuously on the input data. If at least one of these conditions is violated the problem is said ill-posed. The inverse problem is often ill-posed, a regularization method is required to replace the original problem with a well posed problem and then a solution strategy amounts to 1) constructing a solution x, 2) assessing the validity of the solution, 3) characterizing its uncertainty. The data assimilation linked ecosystem carbon (DALEC) model is a simple box model simulating the carbon budget allocation for terrestrial ecosystems. Intercomparison experiments have demonstrated the relative merit of various inverse modelling strategies (MCMC, ENKF) to estimate model parameters and initial carbon stocks for DALEC using eddy covariance measurements of net ecosystem exchange of CO2 and leaf area index observations. Most results agreed on the fact that parameters and initial stocks directly related to fast processes were best estimated with narrow confidence intervals, whereas those related to slow processes were poorly estimated with very large uncertainties. While other studies have tried to overcome this difficulty by adding complementary data streams or by considering longer observation windows no systematic analysis has been carried out so far to explain the large differences among results. We consider adjoint based methods to investigate inverse problems using DALEC and various data streams. Using resolution matrices we study the nature of the inverse problems (solution existence, uniqueness and stability) and show how standard regularization techniques affect resolution and stability properties. Instead of using standard prior information as a penalty term in the cost function to regularize the problems we constraint the parameter space using ecological balance conditions and inequality constraints. The efficiency and rapidity of this approach allows us to compute ensembles of solutions to the inverse problems from which we can establish the robustness of the variational method and obtain non Gaussian posterior distributions for the model parameters and initial carbon stocks.
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.
Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions.
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.
3D ocular ultrasound using gaze tracking on the contralateral eye: a feasibility study.
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.
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.
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.
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.
Depth and thermal sensor fusion to enhance 3D thermographic reconstruction.
Cao, Yanpeng; Xu, Baobei; Ye, Zhangyu; Yang, Jiangxin; Cao, Yanlong; Tisse, Christel-Loic; Li, Xin
2018-04-02
Three-dimensional geometrical models with incorporated surface temperature data provide important information for various applications such as medical imaging, energy auditing, and intelligent robots. In this paper we present a robust method for mobile and real-time 3D thermographic reconstruction through depth and thermal sensor fusion. A multimodal imaging device consisting of a thermal camera and a RGB-D sensor is calibrated geometrically and used for data capturing. Based on the underlying principle that temperature information remains robust against illumination and viewpoint changes, we present a Thermal-guided Iterative Closest Point (T-ICP) methodology to facilitate reliable 3D thermal scanning applications. The pose of sensing device is initially estimated using correspondences found through maximizing the thermal consistency between consecutive infrared images. The coarse pose estimate is further refined by finding the motion parameters that minimize a combined geometric and thermographic loss function. Experimental results demonstrate that complimentary information captured by multimodal sensors can be utilized to improve performance of 3D thermographic reconstruction. Through effective fusion of thermal and depth data, the proposed approach generates more accurate 3D thermal models using significantly less scanning data.
Attenuating Stereo Pixel-Locking via Affine Window Adaptation
NASA Technical Reports Server (NTRS)
Stein, Andrew N.; Huertas, Andres; Matthies, Larry H.
2006-01-01
For real-time stereo vision systems, the standard method for estimating sub-pixel stereo disparity given an initial integer disparity map involves fitting parabolas to a matching cost function aggregated over rectangular windows. This results in a phenomenon known as 'pixel-locking,' which produces artificially-peaked histograms of sub-pixel disparity. These peaks correspond to the introduction of erroneous ripples or waves in the 3D reconstruction of truly Rat surfaces. Since stereo vision is a common input modality for autonomous vehicles, these inaccuracies can pose a problem for safe, reliable navigation. This paper proposes a new method for sub-pixel stereo disparity estimation, based on ideas from Lucas-Kanade tracking and optical flow, which substantially reduces the pixel-locking effect. In addition, it has the ability to correct much larger initial disparity errors than previous approaches and is more general as it applies not only to the ground plane.
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.
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
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.
An anti-disturbing real time pose estimation method and system
NASA Astrophysics Data System (ADS)
Zhou, Jian; Zhang, Xiao-hu
2011-08-01
Pose estimation relating two-dimensional (2D) images to three-dimensional (3D) rigid object need some known features to track. In practice, there are many algorithms which perform this task in high accuracy, but all of these algorithms suffer from features lost. This paper investigated the pose estimation when numbers of known features or even all of them were invisible. Firstly, known features were tracked to calculate pose in the current and the next image. Secondly, some unknown but good features to track were automatically detected in the current and the next image. Thirdly, those unknown features which were on the rigid and could match each other in the two images were retained. Because of the motion characteristic of the rigid object, the 3D information of those unknown features on the rigid could be solved by the rigid object's pose at the two moment and their 2D information in the two images except only two case: the first one was that both camera and object have no relative motion and camera parameter such as focus length, principle point, and etc. have no change at the two moment; the second one was that there was no shared scene or no matched feature in the two image. Finally, because those unknown features at the first time were known now, pose estimation could go on in the followed images in spite of the missing of known features in the beginning by repeating the process mentioned above. The robustness of pose estimation by different features detection algorithms such as Kanade-Lucas-Tomasi (KLT) feature, Scale Invariant Feature Transform (SIFT) and Speed Up Robust Feature (SURF) were compared and the compact of the different relative motion between camera and the rigid object were discussed in this paper. Graphic Processing Unit (GPU) parallel computing was also used to extract and to match hundreds of features for real time pose estimation which was hard to work on Central Processing Unit (CPU). Compared with other pose estimation methods, this new method can estimate pose between camera and object when part even all known features are lost, and has a quick response time benefit from GPU parallel computing. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in autonomous navigation and positioning, robots fields at unknown environment. The results of simulation and experiments demonstrate that proposed method could suppress noise effectively, extracted features robustly, and achieve the real time need. Theory analysis and experiment shows the method is reasonable and efficient.
Pose estimation for augmented reality applications using genetic algorithm.
Yu, Ying Kin; Wong, Kin Hong; Chang, Michael Ming Yuen
2005-12-01
This paper describes a genetic algorithm that tackles the pose-estimation problem in computer vision. Our genetic algorithm can find the rotation and translation of an object accurately when the three-dimensional structure of the object is given. In our implementation, each chromosome encodes both the pose and the indexes to the selected point features of the object. Instead of only searching for the pose as in the existing work, our algorithm, at the same time, searches for a set containing the most reliable feature points in the process. This mismatch filtering strategy successfully makes the algorithm more robust under the presence of point mismatches and outliers in the images. Our algorithm has been tested with both synthetic and real data with good results. The accuracy of the recovered pose is compared to the existing algorithms. Our approach outperformed the Lowe's method and the other two genetic algorithms under the presence of point mismatches and outliers. In addition, it has been used to estimate the pose of a real object. It is shown that the proposed method is applicable to augmented reality applications.
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
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
A deep learning approach for pose estimation from volumetric OCT data.
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.
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
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.
Rhythmic Extended Kalman Filter for Gait Rehabilitation Motion Estimation and Segmentation.
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.
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.
Estimating aquatic hazards posed by prescription pharmaceutical residues from municipal wastewater
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...
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.
A Nonrigid Kernel-Based Framework for 2D-3D Pose Estimation and 2D Image Segmentation
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
Localized Dictionaries Based Orientation Field Estimation for Latent Fingerprints.
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.
Jensen, J; Løkke, H; Holmstrup, M; Krogh, P H; Elsgaard, L
2001-08-01
Linear alkylbenzene sulfonates (LAS) can be found in high concentrations in sewage sludge and, hence, may enter the soil compartment as a result of sludge application. Here, LAS may pose a risk for soil-dwelling organisms. In the present probabilistic risk assessment, statistical extrapolation has been used to assess the risk of LAS to soil ecosystems. By use of a log-normal distribution model, the predicted no-effect concentration (PNEC) was estimated for soil fauna, plants, and a combination of these. Due to the heterogeneous endpoints for microorganisms, including functional as well as structural parameters, the use of sensitivity distributions is not considered to be applicable to this group of organisms, and a direct, expert evaluation of toxicity data was used instead. The soil concentration after sludge application was predicted for a number of scenarios and used as the predicted environmental concentration (PEC) in the risk characterization and calculation of risk quotients (RQ = PEC/PNEC). A LAS concentration of 4.6 mg/kg was used as the current best estimate of PNEC in all RQ calculations. Three levels of LAS contamination (530, 2,600, and 16,100 mg/kg), three half-lives (10, 25, and 40 d), and five different sludge loads (2, 4, 6, 8, and 10 t/ha) were included in the risk scenarios. In Denmark, the initial risk ratio would reach 1.5 in a realistic worst-case consideration. For countries not having similar sludge regulations, the estimated risk ratio may initially be considerably higher. However, even in the most extreme scenarios, the level of LAS is expected to be well beyond the estimated PNEC one year after application. The present risk assessment, therefore, concludes that LAS does not pose a significant risk to fauna, plants, and essential functions of agricultural soils as a result of normal sewage sludge amendment. However, risks have been identified in worst-case scenarios.
A Track Initiation Method for the Underwater Target Tracking Environment
NASA Astrophysics Data System (ADS)
Li, Dong-dong; Lin, Yang; Zhang, Yao
2018-04-01
A novel efficient track initiation method is proposed for the harsh underwater target tracking environment (heavy clutter and large measurement errors): track splitting, evaluating, pruning and merging method (TSEPM). Track initiation demands that the method should determine the existence and initial state of a target quickly and correctly. Heavy clutter and large measurement errors certainly pose additional difficulties and challenges, which deteriorate and complicate the track initiation in the harsh underwater target tracking environment. There are three primary shortcomings for the current track initiation methods to initialize a target: (a) they cannot eliminate the turbulences of clutter effectively; (b) there may be a high false alarm probability and low detection probability of a track; (c) they cannot estimate the initial state for a new confirmed track correctly. Based on the multiple hypotheses tracking principle and modified logic-based track initiation method, in order to increase the detection probability of a track, track splitting creates a large number of tracks which include the true track originated from the target. And in order to decrease the false alarm probability, based on the evaluation mechanism, track pruning and track merging are proposed to reduce the false tracks. TSEPM method can deal with the track initiation problems derived from heavy clutter and large measurement errors, determine the target's existence and estimate its initial state with the least squares method. What's more, our method is fully automatic and does not require any kind manual input for initializing and tuning any parameter. Simulation results indicate that our new method improves significantly the performance of the track initiation in the harsh underwater target tracking environment.
78 FR 33393 - Petition Requesting a Ban or Standard on Adult Portable Bed Rails
Federal Register 2010, 2011, 2012, 2013, 2014
2013-06-04
... Standard on Adult Portable Bed Rails AGENCY: Consumer Product Safety Commission. ACTION: Notice. SUMMARY... adult portable bed rails pose an unreasonable risk of injury and initiate related rulemaking under... that adult portable bed rails pose an unreasonable risk of injury and initiate related rulemaking under...
A Bayesian Framework for Human Body Pose Tracking from Depth Image Sequences
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
Curve Set Feature-Based Robust and Fast Pose Estimation Algorithm
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
An evaluation of 3D head pose estimation using the Microsoft Kinect v2.
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.
Orientation estimation of anatomical structures in medical images for object recognition
NASA Astrophysics Data System (ADS)
Bağci, Ulaş; Udupa, Jayaram K.; Chen, Xinjian
2011-03-01
Recognition of anatomical structures is an important step in model based medical image segmentation. It provides pose estimation of objects and information about "where" roughly the objects are in the image and distinguishing them from other object-like entities. In,1 we presented a general method of model-based multi-object recognition to assist in segmentation (delineation) tasks. It exploits the pose relationship that can be encoded, via the concept of ball scale (b-scale), between the binary training objects and their associated grey images. The goal was 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. Unlike position and scale parameters, we observe that orientation parameters require more attention when estimating the pose of the model as even small differences in orientation parameters can lead to inappropriate recognition. Motivated from the non-Euclidean nature of the pose information, we propose in this paper the use of non-Euclidean metrics to estimate orientation of the anatomical structures for more accurate recognition and segmentation. We statistically analyze and evaluate the following metrics for orientation estimation: Euclidean, Log-Euclidean, Root-Euclidean, Procrustes Size-and-Shape, and mean Hermitian metrics. The results show that mean Hermitian and Cholesky decomposition metrics provide more accurate orientation estimates than other Euclidean and non-Euclidean metrics.
New learning based super-resolution: use of DWT and IGMRF prior.
Gajjar, Prakash P; Joshi, Manjunath V
2010-05-01
In this paper, we propose a new learning-based approach for super-resolving an image captured at low spatial resolution. Given the low spatial resolution test image and a database consisting of low and high spatial resolution images, we obtain super-resolution for the test image. We first obtain an initial high-resolution (HR) estimate by learning the high-frequency details from the available database. A new discrete wavelet transform (DWT) based approach is proposed for learning that uses a set of low-resolution (LR) images and their corresponding HR versions. Since the super-resolution is an ill-posed problem, we obtain the final solution using a regularization framework. The LR image is modeled as the aliased and noisy version of the corresponding HR image, and the aliasing matrix entries are estimated using the test image and the initial HR estimate. The prior model for the super-resolved image is chosen as an Inhomogeneous Gaussian Markov random field (IGMRF) and the model parameters are estimated using the same initial HR estimate. A maximum a posteriori (MAP) estimation is used to arrive at the cost function which is minimized using a simple gradient descent approach. We demonstrate the effectiveness of the proposed approach by conducting the experiments on gray scale as well as on color images. The method is compared with the standard interpolation technique and also with existing learning-based approaches. The proposed approach can be used in applications such as wildlife sensor networks, remote surveillance where the memory, the transmission bandwidth, and the camera cost are the main constraints.
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
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.
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.
A combined vision-inertial fusion approach for 6-DoF object pose estimation
NASA Astrophysics Data System (ADS)
Li, Juan; Bernardos, Ana M.; Tarrío, Paula; Casar, José R.
2015-02-01
The estimation of the 3D position and orientation of moving objects (`pose' estimation) is a critical process for many applications in robotics, computer vision or mobile services. Although major research efforts have been carried out to design accurate, fast and robust indoor pose estimation systems, it remains as an open challenge to provide a low-cost, easy to deploy and reliable solution. Addressing this issue, this paper describes a hybrid approach for 6 degrees of freedom (6-DoF) pose estimation that fuses acceleration data and stereo vision to overcome the respective weaknesses of single technology approaches. The system relies on COTS technologies (standard webcams, accelerometers) and printable colored markers. It uses a set of infrastructure cameras, located to have the object to be tracked visible most of the operation time; the target object has to include an embedded accelerometer and be tagged with a fiducial marker. This simple marker has been designed for easy detection and segmentation and it may be adapted to different service scenarios (in shape and colors). Experimental results show that the proposed system provides high accuracy, while satisfactorily dealing with the real-time constraints.
Attribute And-Or Grammar for Joint Parsing of Human Pose, Parts and Attributes.
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.
Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications.
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
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
Geometric Integration of Hybrid Correspondences for RGB-D Unidirectional Tracking
Tang, Shengjun; Chen, Wu; Wang, Weixi; Li, Xiaoming; Li, Wenbin; Huang, Zhengdong; Hu, Han; Guo, Renzhong
2018-01-01
Traditionally, visual-based RGB-D SLAM systems only use correspondences with valid depth values for camera tracking, thus ignoring the regions without 3D information. Due to the strict limitation on measurement distance and view angle, such systems adopt only short-range constraints which may introduce larger drift errors during long-distance unidirectional tracking. In this paper, we propose a novel geometric integration method that makes use of both 2D and 3D correspondences for RGB-D tracking. Our method handles the problem by exploring visual features both when depth information is available and when it is unknown. The system comprises two parts: coarse pose tracking with 3D correspondences, and geometric integration with hybrid correspondences. First, the coarse pose tracking generates the initial camera pose using 3D correspondences with frame-by-frame registration. The initial camera poses are then used as inputs for the geometric integration model, along with 3D correspondences, 2D-3D correspondences and 2D correspondences identified from frame pairs. The initial 3D location of the correspondence is determined in two ways, from depth image and by using the initial poses to triangulate. The model improves the camera poses and decreases drift error during long-distance RGB-D tracking iteratively. Experiments were conducted using data sequences collected by commercial Structure Sensors. The results verify that the geometric integration of hybrid correspondences effectively decreases the drift error and improves mapping accuracy. Furthermore, the model enables a comparative and synergistic use of datasets, including both 2D and 3D features. PMID:29723974
Geometric Integration of Hybrid Correspondences for RGB-D Unidirectional Tracking.
Tang, Shengjun; Chen, Wu; Wang, Weixi; Li, Xiaoming; Darwish, Walid; Li, Wenbin; Huang, Zhengdong; Hu, Han; Guo, Renzhong
2018-05-01
Traditionally, visual-based RGB-D SLAM systems only use correspondences with valid depth values for camera tracking, thus ignoring the regions without 3D information. Due to the strict limitation on measurement distance and view angle, such systems adopt only short-range constraints which may introduce larger drift errors during long-distance unidirectional tracking. In this paper, we propose a novel geometric integration method that makes use of both 2D and 3D correspondences for RGB-D tracking. Our method handles the problem by exploring visual features both when depth information is available and when it is unknown. The system comprises two parts: coarse pose tracking with 3D correspondences, and geometric integration with hybrid correspondences. First, the coarse pose tracking generates the initial camera pose using 3D correspondences with frame-by-frame registration. The initial camera poses are then used as inputs for the geometric integration model, along with 3D correspondences, 2D-3D correspondences and 2D correspondences identified from frame pairs. The initial 3D location of the correspondence is determined in two ways, from depth image and by using the initial poses to triangulate. The model improves the camera poses and decreases drift error during long-distance RGB-D tracking iteratively. Experiments were conducted using data sequences collected by commercial Structure Sensors. The results verify that the geometric integration of hybrid correspondences effectively decreases the drift error and improves mapping accuracy. Furthermore, the model enables a comparative and synergistic use of datasets, including both 2D and 3D features.
Investigation of MM-PBSA rescoring of docking poses.
Thompson, David C; Humblet, Christine; Joseph-McCarthy, Diane
2008-05-01
Target-based virtual screening is increasingly used to generate leads for targets for which high quality three-dimensional (3D) structures are available. To allow large molecular databases to be screened rapidly, a tiered scoring scheme is often employed whereby a simple scoring function is used as a fast filter of the entire database and a more rigorous and time-consuming scoring function is used to rescore the top hits to produce the final list of ranked compounds. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approaches are currently thought to be quite effective at incorporating implicit solvation into the estimation of ligand binding free energies. In this paper, the ability of a high-throughput MM-PBSA rescoring function to discriminate between correct and incorrect docking poses is investigated in detail. Various initial scoring functions are used to generate docked poses for a subset of the CCDC/Astex test set and to dock one set of actives/inactives from the DUD data set. The effectiveness of each of these initial scoring functions is discussed. Overall, the ability of the MM-PBSA rescoring function to (i) regenerate the set of X-ray complexes when docking the bound conformation of the ligand, (ii) regenerate the X-ray complexes when docking conformationally expanded databases for each ligand which include "conformation decoys" of the ligand, and (iii) enrich known actives in a virtual screen for the mineralocorticoid receptor in the presence of "ligand decoys" is assessed. While a pharmacophore-based molecular docking approach, PhDock, is used to carry out the docking, the results are expected to be general to use with any docking method.
NASA Astrophysics Data System (ADS)
Rashid, Ahmar; Khambampati, Anil Kumar; Kim, Bong Seok; Liu, Dong; Kim, Sin; Kim, Kyung Youn
EIT image reconstruction is an ill-posed problem, the spatial resolution of the estimated conductivity distribution is usually poor and the external voltage measurements are subject to variable noise. Therefore, EIT conductivity estimation cannot be used in the raw form to correctly estimate the shape and size of complex shaped regional anomalies. An efficient algorithm employing a shape based estimation scheme is needed. The performance of traditional inverse algorithms, such as the Newton Raphson method, used for this purpose is below par and depends upon the initial guess and the gradient of the cost functional. This paper presents the application of differential evolution (DE) algorithm to estimate complex shaped region boundaries, expressed as coefficients of truncated Fourier series, using EIT. DE is a simple yet powerful population-based, heuristic algorithm with the desired features to solve global optimization problems under realistic conditions. The performance of the algorithm has been tested through numerical simulations, comparing its results with that of the traditional modified Newton Raphson (mNR) method.
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.
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.
NASA Astrophysics Data System (ADS)
Casasent, David P.; Shenoy, Rajesh
1997-10-01
Classification and pose estimation of distorted input objects are considered. The feature space trajectory representation of distorted views of an object is used with a new eigenfeature space. For a distorted input object, the closest trajectory denotes the class of the input and the closest line segment on it denotes its pose. If an input point is too far from a trajectory, it is rejected as clutter. New methods for selecting Fukunaga-Koontz discriminant vectors, the number of dominant eigenvectors per class and for determining training, and test set compatibility are presented.
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
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
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.
Automatic creation of three-dimensional avatars
NASA Astrophysics Data System (ADS)
Villa-Uriol, Maria-Cruz; Sainz, Miguel; Kuester, Falko; Bagherzadeh, Nader
2003-01-01
Highly accurate avatars of humans promise a new level of realism in engineering and entertainment applications, including areas such as computer animated movies, computer game development interactive virtual environments and tele-presence. In order to provide high-quality avatars, new techniques for the automatic acquisition and creation are required. A framework for the capture and construction of arbitrary avatars from image data is presented in this paper. Avatars are automatically reconstructed from multiple static images of a human subject by utilizing image information to reshape a synthetic three-dimensional articulated reference model. A pipeline is presented that combines a set of hardware-accelerated stages into one seamless system. Primary stages in this pipeline include pose estimation, skeleton fitting, body part segmentation, geometry construction and coloring, leading to avatars that can be animated and included into interactive environments. The presented system removes traditional constraints in the initial pose of the captured subject by using silhouette-based modification techniques in combination with a reference model. Results can be obtained in near-real time with very limited user intervention.
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.
Gong, Inna Y.; Schwarz, Ute I.; Crown, Natalie; Dresser, George K.; Lazo-Langner, Alejandro; Zou, GuangYong; Roden, Dan M.; Stein, C. Michael; Rodger, Marc; Wells, Philip S.; Kim, Richard B.; Tirona, Rommel G.
2011-01-01
Variable warfarin response during treatment initiation poses a significant challenge to providing optimal anticoagulation therapy. We investigated the determinants of initial warfarin response in a cohort of 167 patients. During the first nine days of treatment with pharmacogenetics-guided dosing, S-warfarin plasma levels and international normalized ratio were obtained to serve as inputs to a pharmacokinetic-pharmacodynamic (PK-PD) model. Individual PK (S-warfarin clearance) and PD (Imax) parameter values were estimated. Regression analysis demonstrated that CYP2C9 genotype, kidney function, and gender were independent determinants of S-warfarin clearance. The values for Imax were dependent on VKORC1 and CYP4F2 genotypes, vitamin K status (as measured by plasma concentrations of proteins induced by vitamin K absence, PIVKA-II) and weight. Importantly, indication for warfarin was a major independent determinant of Imax during initiation, where PD sensitivity was greater in atrial fibrillation than venous thromboembolism. To demonstrate the utility of the global PK-PD model, we compared the predicted initial anticoagulation responses with previously established warfarin dosing algorithms. These insights and modeling approaches have application to personalized warfarin therapy. PMID:22114699
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cameron, M.K.; Fomel, S.B.; Sethian, J.A.
2009-01-01
In the present work we derive and study a nonlinear elliptic PDE coming from the problem of estimation of sound speed inside the Earth. The physical setting of the PDE allows us to pose only a Cauchy problem, and hence is ill-posed. However we are still able to solve it numerically on a long enough time interval to be of practical use. We used two approaches. The first approach is a finite difference time-marching numerical scheme inspired by the Lax-Friedrichs method. The key features of this scheme is the Lax-Friedrichs averaging and the wide stencil in space. The second approachmore » is a spectral Chebyshev method with truncated series. We show that our schemes work because of (1) the special input corresponding to a positive finite seismic velocity, (2) special initial conditions corresponding to the image rays, (3) the fact that our finite-difference scheme contains small error terms which damp the high harmonics; truncation of the Chebyshev series, and (4) the need to compute the solution only for a short interval of time. We test our numerical scheme on a collection of analytic examples and demonstrate a dramatic improvement in accuracy in the estimation of the sound speed inside the Earth in comparison with the conventional Dix inversion. Our test on the Marmousi example confirms the effectiveness of the proposed approach.« less
NASA Astrophysics Data System (ADS)
Nie, Yao; Zheng, Xiaoxin
2018-07-01
We study the Cauchy problem for the 3D incompressible hyperdissipative Navier–Stokes equations and consider the well-posedness and ill-posedness in critical Fourier-Herz spaces . We prove that if and , the system is locally well-posed for large initial data as well as globally well-posed for small initial data. Also, we obtain the same result for and . More importantly, we show that the system is ill-posed in the sense of norm inflation for and q > 2. The proof relies heavily on particular structure of initial data u 0 that we construct, which makes the first iteration of solution inflate. Specifically, the special structure of u 0 transforms an infinite sum into a finite sum in ‘remainder term’, which permits us to control the remainder.
A multi-camera system for real-time pose estimation
NASA Astrophysics Data System (ADS)
Savakis, Andreas; Erhard, Matthew; Schimmel, James; Hnatow, Justin
2007-04-01
This paper presents a multi-camera system that performs face detection and pose estimation in real-time and may be used for intelligent computing within a visual sensor network for surveillance or human-computer interaction. The system consists of a Scene View Camera (SVC), which operates at a fixed zoom level, and an Object View Camera (OVC), which continuously adjusts its zoom level to match objects of interest. The SVC is set to survey the whole filed of view. Once a region has been identified by the SVC as a potential object of interest, e.g. a face, the OVC zooms in to locate specific features. In this system, face candidate regions are selected based on skin color and face detection is accomplished using a Support Vector Machine classifier. The locations of the eyes and mouth are detected inside the face region using neural network feature detectors. Pose estimation is performed based on a geometrical model, where the head is modeled as a spherical object that rotates upon the vertical axis. The triangle formed by the mouth and eyes defines a vertical plane that intersects the head sphere. By projecting the eyes-mouth triangle onto a two dimensional viewing plane, equations were obtained that describe the change in its angles as the yaw pose angle increases. These equations are then combined and used for efficient pose estimation. The system achieves real-time performance for live video input. Testing results assessing system performance are presented for both still images and video.
An Improved Method of Pose Estimation for Lighthouse Base Station Extension.
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
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
Mathematical Creative Process Wallas Model in Students Problem Posing with Lesson Study Approach
ERIC Educational Resources Information Center
Nuha, Muhammad 'Azmi; Waluya, S. B.; Junaedi, Iwan
2018-01-01
Creative thinking is very important in the modern era so that it should be improved by doing efforts such as making a lesson that train students to pose their own problems. The purposes of this research are (1) to give an initial description of students about mathematical creative thinking level in Problem Posing Model with Lesson Study approach…
Autonomous Vision-Based Tethered-Assisted Rover Docking
NASA Technical Reports Server (NTRS)
Tsai, Dorian; Nesnas, Issa A.D.; Zarzhitsky, Dimitri
2013-01-01
Many intriguing science discoveries on planetary surfaces, such as the seasonal flows on crater walls and skylight entrances to lava tubes, are at sites that are currently inaccessible to state-of-the-art rovers. The in situ exploration of such sites is likely to require a tethered platform both for mechanical support and for providing power and communication. Mother/daughter architectures have been investigated where a mother deploys a tethered daughter into extreme terrains. Deploying and retracting a tethered daughter requires undocking and re-docking of the daughter to the mother, with the latter being the challenging part. In this paper, we describe a vision-based tether-assisted algorithm for the autonomous re-docking of a daughter to its mother following an extreme terrain excursion. The algorithm uses fiducials mounted on the mother to improve the reliability and accuracy of estimating the pose of the mother relative to the daughter. The tether that is anchored by the mother helps the docking process and increases the system's tolerance to pose uncertainties by mechanically aligning the mating parts in the final docking phase. A preliminary version of the algorithm was developed and field-tested on the Axel rover in the JPL Mars Yard. The algorithm achieved an 80% success rate in 40 experiments in both firm and loose soils and starting from up to 6 m away at up to 40 deg radial angle and 20 deg relative heading. The algorithm does not rely on an initial estimate of the relative pose. The preliminary results are promising and help retire the risk associated with the autonomous docking process enabling consideration in future martian and lunar missions.
Structure-From-Motion in 3D Space Using 2D Lidars
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.
Multi-object segmentation using coupled nonparametric shape and relative pose priors
NASA Astrophysics Data System (ADS)
Uzunbas, Mustafa Gökhan; Soldea, Octavian; Çetin, Müjdat; Ünal, Gözde; Erçil, Aytül; Unay, Devrim; Ekin, Ahmet; Firat, Zeynep
2009-02-01
We present a new method for multi-object segmentation in a maximum a posteriori estimation framework. Our method is motivated by the observation that neighboring or coupling objects in images generate configurations and co-dependencies which could potentially aid in segmentation if properly exploited. Our approach employs coupled shape and inter-shape pose priors that are computed using training images in a nonparametric multi-variate kernel density estimation framework. The coupled shape prior is obtained by estimating the joint shape distribution of multiple objects and the inter-shape pose priors are modeled via standard moments. Based on such statistical models, we formulate an optimization problem for segmentation, which we solve by an algorithm based on active contours. Our technique provides significant improvements in the segmentation of weakly contrasted objects in a number of applications. In particular for medical image analysis, we use our method to extract brain Basal Ganglia structures, which are members of a complex multi-object system posing a challenging segmentation problem. We also apply our technique to the problem of handwritten character segmentation. Finally, we use our method to segment cars in urban scenes.
Towards Unmanned Systems for Dismounted Operations in the Canadian Forces
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 Neural-Dynamic Architecture for Concurrent Estimation of Object Pose and Identity
Lomp, Oliver; Faubel, Christian; Schöner, Gregor
2017-01-01
Handling objects or interacting with a human user about objects on a shared tabletop requires that objects be identified after learning from a small number of views and that object pose be estimated. We present a neurally inspired architecture that learns object instances by storing features extracted from a single view of each object. Input features are color and edge histograms from a localized area that is updated during processing. The system finds the best-matching view for the object in a novel input image while concurrently estimating the object’s pose, aligning the learned view with current input. The system is based on neural dynamics, computationally operating in real time, and can handle dynamic scenes directly off live video input. In a scenario with 30 everyday objects, the system achieves recognition rates of 87.2% from a single training view for each object, while also estimating pose quite precisely. We further demonstrate that the system can track moving objects, and that it can segment the visual array, selecting and recognizing one object while suppressing input from another known object in the immediate vicinity. Evaluation on the COIL-100 dataset, in which objects are depicted from different viewing angles, revealed recognition rates of 91.1% on the first 30 objects, each learned from four training views. PMID:28503145
A Simulation Environment for Benchmarking Sensor Fusion-Based Pose Estimators.
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.
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.
Body Parts Dependent Joint Regressors for Human Pose Estimation in Still Images.
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.
Development of a machine vision system for automated structural assembly
NASA Technical Reports Server (NTRS)
Sydow, P. Daniel; Cooper, Eric G.
1992-01-01
Research is being conducted at the LaRC to develop a telerobotic assembly system designed to construct large space truss structures. This research program was initiated within the past several years, and a ground-based test-bed was developed to evaluate and expand the state of the art. Test-bed operations currently use predetermined ('taught') points for truss structural assembly. Total dependence on the use of taught points for joint receptacle capture and strut installation is neither robust nor reliable enough for space operations. Therefore, a machine vision sensor guidance system is being developed to locate and guide the robot to a passive target mounted on the truss joint receptacle. The vision system hardware includes a miniature video camera, passive targets mounted on the joint receptacles, target illumination hardware, and an image processing system. Discrimination of the target from background clutter is accomplished through standard digital processing techniques. Once the target is identified, a pose estimation algorithm is invoked to determine the location, in three-dimensional space, of the target relative to the robots end-effector. Preliminary test results of the vision system in the Automated Structural Assembly Laboratory with a range of lighting and background conditions indicate that it is fully capable of successfully identifying joint receptacle targets throughout the required operational range. Controlled optical bench test results indicate that the system can also provide the pose estimation accuracy to define the target position.
Building a 2.5D Digital Elevation Model from 2D Imagery
NASA Technical Reports Server (NTRS)
Padgett, Curtis W.; Ansar, Adnan I.; Brennan, Shane; Cheng, Yang; Clouse, Daniel S.; Almeida, Eduardo
2013-01-01
When projecting imagery into a georeferenced coordinate frame, one needs to have some model of the geographical region that is being projected to. This model can sometimes be a simple geometrical curve, such as an ellipse or even a plane. However, to obtain accurate projections, one needs to have a more sophisticated model that encodes the undulations in the terrain including things like mountains, valleys, and even manmade structures. The product that is often used for this purpose is a Digital Elevation Model (DEM). The technology presented here generates a high-quality DEM from a collection of 2D images taken from multiple viewpoints, plus pose data for each of the images and a camera model for the sensor. The technology assumes that the images are all of the same region of the environment. The pose data for each image is used as an initial estimate of the geometric relationship between the images, but the pose data is often noisy and not of sufficient quality to build a high-quality DEM. Therefore, the source imagery is passed through a feature-tracking algorithm and multi-plane-homography algorithm, which refine the geometric transforms between images. The images and their refined poses are then passed to a stereo algorithm, which generates dense 3D data for each image in the sequence. The 3D data from each image is then placed into a consistent coordinate frame and passed to a routine that divides the coordinate frame into a number of cells. The 3D points that fall into each cell are collected, and basic statistics are applied to determine the elevation of that cell. The result of this step is a DEM that is in an arbitrary coordinate frame. This DEM is then filtered and smoothed in order to remove small artifacts. The final step in the algorithm is to take the initial DEM and rotate and translate it to be in the world coordinate frame [such as UTM (Universal Transverse Mercator), MGRS (Military Grid Reference System), or geodetic] such that it can be saved in a standard DEM format and used for projection.
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.
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.
Maximal likelihood correspondence estimation for face recognition across pose.
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.
Zielinski, R.A.; Otton, J.K.; Budahn, J.R.
2001-01-01
Radium-bearing barite (radiobarite) is a common constituent of scale and sludge deposits that form in oil-field production equipment. The barite forms as a precipitate from radium-bearing, saline formation water that is pumped to the surface along with oil. Radioactivity levels in some oil-field equipment and in soils contaminated by scale and sludge can be sufficiently high to pose a potential health threat. Accurate determinations of radium isotopes (226Ra+228Ra) in soils are required to establish the level of soil contamination and the volume of soil that may exceed regulatory limits for total radium content. In this study the radium isotopic data are used to provide estimates of the age of formation of the radiobarite contaminant. Age estimates require that highly insoluble radiobarite approximates a chemically closed system from the time of its formation. Age estimates are based on the decay of short-lived 228Ra (half-life=5.76 years) compared to 226Ra (half-life=1600 years). Present activity ratios of 228Ra/226Ra in radiobarite-rich scale or highly contaminated soil are compared to initial ratios at the time of radiobarite precipitation. Initial ratios are estimated by measurements of saline water or recent barite precipitates at the site or by considering a range of probable initial ratios based on reported values in modern oil-field brines. At sites that contain two distinct radiobarite sources of different age, the soils containing mixtures of sources can be identified, and mixing proportions quantified using radium concentration and isotopic data. These uses of radium isotope data provide more description of contamination history and can possibly address liability issues. Copyright ?? 2000 .
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.
Gershoff, Elizabeth T; Sattler, Kierra M P; Ansari, Arya
2018-01-01
Establishing causal links when experiments are not feasible is an important challenge for psychology researchers. The question of whether parents' spanking causes children's externalizing behavior problems poses such a challenge because randomized experiments of spanking are unethical, and correlational studies cannot rule out potential selection factors. This study used propensity score matching based on the lifetime prevalence and recent incidence of spanking in a large and nationally representative sample ( N = 12,112) as well as lagged dependent variables to get as close to causal estimates outside an experiment as possible. Whether children were spanked at the age of 5 years predicted increases in externalizing behavior problems by ages 6 and 8, even after the groups based on spanking prevalence or incidence were matched on a range of sociodemographic, family, and cultural characteristics and children's initial behavior problems. These statistically rigorous methods yield the conclusion that spanking predicts a deterioration of children's externalizing behavior over time.
Factoring attitudes towards armed conflict risk into selection of protected areas for conservation
Hammill, E.; Tulloch, A. I. T.; Possingham, H. P.; Strange, N.; Wilson, K. A.
2016-01-01
The high incidence of armed conflicts in biodiverse regions poses significant challenges in achieving international conservation targets. Because attitudes towards risk vary, we assessed different strategies for protected area planning that reflected alternative attitudes towards the risk of armed conflicts. We find that ignoring conflict risk will deliver the lowest return on investment. Opting to completely avoid conflict-prone areas offers limited improvements and could lead to species receiving no protection. Accounting for conflict by protecting additional areas to offset the impacts of armed conflicts would not only increase the return on investment (an effect that is enhanced when high-risk areas are excluded) but also increase upfront conservation costs. Our results also demonstrate that fine-scale estimations of conflict risk could enhance the cost-effectiveness of investments. We conclude that achieving biodiversity targets in volatile regions will require greater initial investment and benefit from fine-resolution estimates of conflict risk. PMID:27025894
Factoring attitudes towards armed conflict risk into selection of protected areas for conservation.
Hammill, E; Tulloch, A I T; Possingham, H P; Strange, N; Wilson, K A
2016-03-30
The high incidence of armed conflicts in biodiverse regions poses significant challenges in achieving international conservation targets. Because attitudes towards risk vary, we assessed different strategies for protected area planning that reflected alternative attitudes towards the risk of armed conflicts. We find that ignoring conflict risk will deliver the lowest return on investment. Opting to completely avoid conflict-prone areas offers limited improvements and could lead to species receiving no protection. Accounting for conflict by protecting additional areas to offset the impacts of armed conflicts would not only increase the return on investment (an effect that is enhanced when high-risk areas are excluded) but also increase upfront conservation costs. Our results also demonstrate that fine-scale estimations of conflict risk could enhance the cost-effectiveness of investments. We conclude that achieving biodiversity targets in volatile regions will require greater initial investment and benefit from fine-resolution estimates of conflict risk.
Solving Navigational Uncertainty Using Grid Cells on Robots
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
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.
Enhanced RGB-D Mapping Method for Detailed 3D Indoor and Outdoor Modeling
Tang, Shengjun; Zhu, Qing; Chen, Wu; Darwish, Walid; Wu, Bo; Hu, Han; Chen, Min
2016-01-01
RGB-D sensors (sensors with RGB camera and Depth camera) are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks including limited measurement ranges (e.g., within 3 m) and errors in depth measurement increase with distance from the sensor with respect to 3D dense mapping. In this paper, we present a novel approach to geometrically integrate the depth scene and RGB scene to enlarge the measurement distance of RGB-D sensors and enrich the details of model generated from depth images. First, precise calibration for RGB-D Sensors is introduced. In addition to the calibration of internal and external parameters for both, IR camera and RGB camera, the relative pose between RGB camera and IR camera is also calibrated. Second, to ensure poses accuracy of RGB images, a refined false features matches rejection method is introduced by combining the depth information and initial camera poses between frames of the RGB-D sensor. Then, a global optimization model is used to improve the accuracy of the camera pose, decreasing the inconsistencies between the depth frames in advance. In order to eliminate the geometric inconsistencies between RGB scene and depth scene, the scale ambiguity problem encountered during the pose estimation with RGB image sequences can be resolved by integrating the depth and visual information and a robust rigid-transformation recovery method is developed to register RGB scene to depth scene. The benefit of the proposed joint optimization method is firstly evaluated with the publicly available benchmark datasets collected with Kinect. Then, the proposed method is examined by tests with two sets of datasets collected in both outside and inside environments. The experimental results demonstrate the feasibility and robustness of the proposed method. PMID:27690028
Enhanced RGB-D Mapping Method for Detailed 3D Indoor and Outdoor Modeling.
Tang, Shengjun; Zhu, Qing; Chen, Wu; Darwish, Walid; Wu, Bo; Hu, Han; Chen, Min
2016-09-27
RGB-D sensors (sensors with RGB camera and Depth camera) are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks including limited measurement ranges (e.g., within 3 m) and errors in depth measurement increase with distance from the sensor with respect to 3D dense mapping. In this paper, we present a novel approach to geometrically integrate the depth scene and RGB scene to enlarge the measurement distance of RGB-D sensors and enrich the details of model generated from depth images. First, precise calibration for RGB-D Sensors is introduced. In addition to the calibration of internal and external parameters for both, IR camera and RGB camera, the relative pose between RGB camera and IR camera is also calibrated. Second, to ensure poses accuracy of RGB images, a refined false features matches rejection method is introduced by combining the depth information and initial camera poses between frames of the RGB-D sensor. Then, a global optimization model is used to improve the accuracy of the camera pose, decreasing the inconsistencies between the depth frames in advance. In order to eliminate the geometric inconsistencies between RGB scene and depth scene, the scale ambiguity problem encountered during the pose estimation with RGB image sequences can be resolved by integrating the depth and visual information and a robust rigid-transformation recovery method is developed to register RGB scene to depth scene. The benefit of the proposed joint optimization method is firstly evaluated with the publicly available benchmark datasets collected with Kinect. Then, the proposed method is examined by tests with two sets of datasets collected in both outside and inside environments. The experimental results demonstrate the feasibility and robustness of the proposed method.
Robust automatic measurement of 3D scanned models for the human body fat estimation.
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.
Exploring the stability of ligand binding modes to proteins by molecular dynamics simulations.
Liu, Kai; Watanabe, Etsurou; Kokubo, Hironori
2017-02-01
The binding mode prediction is of great importance to structure-based drug design. The discrimination of various binding poses of ligand generated by docking is a great challenge not only to docking score functions but also to the relatively expensive free energy calculation methods. Here we systematically analyzed the stability of various ligand poses under molecular dynamics (MD) simulation. First, a data set of 120 complexes was built based on the typical physicochemical properties of drug-like ligands. Three potential binding poses (one correct pose and two decoys) were selected for each ligand from self-docking in addition to the experimental pose. Then, five independent MD simulations for each pose were performed with different initial velocities for the statistical analysis. Finally, the stabilities of ligand poses under MD were evaluated and compared with the native one from crystal structure. We found that about 94% of the native poses were maintained stable during the simulations, which suggests that MD simulations are accurate enough to judge most experimental binding poses as stable properly. Interestingly, incorrect decoy poses were maintained much less and 38-44% of decoys could be excluded just by performing equilibrium MD simulations, though 56-62% of decoys were stable. The computationally-heavy binding free energy calculation can be performed only for these survived poses.
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.
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
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.
Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.
Makeneni, Spandana; Thieker, David F; Woods, Robert J
2018-03-26
In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody-carbohydrate complexes. The protocol was applied to 10 antibody-carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody-carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.
Measurement of the PPN parameter γ by testing the geometry of near-Earth space
NASA Astrophysics Data System (ADS)
Luo, Jie; Tian, Yuan; Wang, Dian-Hong; Qin, Cheng-Gang; Shao, Cheng-Gang
2016-06-01
The Beyond Einstein Advanced Coherent Optical Network (BEACON) mission was designed to achieve an accuracy of 10^{-9} in measuring the Eddington parameter γ , which is perhaps the most fundamental Parameterized Post-Newtonian parameter. However, this ideal accuracy was just estimated as a ratio of the measurement accuracy of the inter-spacecraft distances to the magnitude of the departure from Euclidean geometry. Based on the BEACON concept, we construct a measurement model to estimate the parameter γ with the least squares method. Influences of the measurement noise and the out-of-plane error on the estimation accuracy are evaluated based on the white noise model. Though the BEACON mission does not require expensive drag-free systems and avoids physical dynamical models of spacecraft, the relatively low accuracy of initial inter-spacecraft distances poses a great challenge, which reduces the estimation accuracy in about two orders of magnitude. Thus the noise requirements may need to be more stringent in the design in order to achieve the target accuracy, which is demonstrated in the work. Considering that, we have given the limits on the power spectral density of both noise sources for the accuracy of 10^{-9}.
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.
A Bayesian inferential approach to quantify the transmission intensity of disease outbreak.
Kadi, Adiveppa S; Avaradi, Shivakumari R
2015-01-01
Emergence of infectious diseases like influenza pandemic (H1N1) 2009 has become great concern, which posed new challenges to the health authorities worldwide. To control these diseases various studies have been developed in the field of mathematical modelling, which is useful tool for understanding the epidemiological dynamics and their dependence on social mixing patterns. We have used Bayesian approach to quantify the disease outbreak through key epidemiological parameter basic reproduction number (R0), using effective contacts, defined as sum of the product of incidence cases and probability of generation time distribution. We have estimated R0 from daily case incidence data for pandemic influenza A/H1N1 2009 in India, for the initial phase. The estimated R0 with 95% credible interval is consistent with several other studies on the same strain. Through sensitivity analysis our study indicates that infectiousness affects the estimate of R0. Basic reproduction number R0 provides the useful information to the public health system to do some effort in controlling the disease by using mitigation strategies like vaccination, quarantine, and so forth.
2008 Preserve America Presidential Awards
Project, New York, New York; Corinth and Alcorn County Mississippi Heritage Tourism Initiative; Lower East and Alcorn County Mississippi Heritage Tourism Initiative were Rosemary Williams, Chairperson, Siege Heritage Tourism Initiative Mrs. Laura Bush poses for a photo with Preserve America Presidential Award
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.
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.
Object recognition and pose estimation of planar objects from range data
NASA Technical Reports Server (NTRS)
Pendleton, Thomas W.; Chien, Chiun Hong; Littlefield, Mark L.; Magee, Michael
1994-01-01
The Extravehicular Activity Helper/Retriever (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, three-dimensional sensing of the operational environment and objects in the environment will therefore be essential. One of the sensors being considered to provide image data for object recognition and pose estimation is a phase-shift laser scanner. The characteristics of the data provided by this scanner have been studied and algorithms have been developed for segmenting range images into planar surfaces, extracting basic features such as surface area, and recognizing the object based on the characteristics of extracted features. Also, an approach has been developed for estimating the spatial orientation and location of the recognized object based on orientations of extracted planes and their intersection points. This paper presents some of the algorithms that have been developed for the purpose of recognizing and estimating the pose of objects as viewed by the laser scanner, and characterizes the desirability and utility of these algorithms within the context of the scanner itself, considering data quality and noise.
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.
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.
Trajectory-based visual localization in underwater surveying missions.
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.
Pose and motion recovery from feature correspondences and a digital terrain map.
Lerner, Ronen; Rivlin, Ehud; Rotstein, Héctor P
2006-09-01
A novel algorithm for pose and motion estimation using corresponding features and a Digital Terrain Map is proposed. Using a Digital Terrain (or Digital Elevation) Map (DTM/DEM) as a global reference enables the elimination of the ambiguity present in vision-based algorithms for motion recovery. As a consequence, the absolute position and orientation of a camera can be recovered with respect to the external reference frame. In order to do this, the DTM is used to formulate a constraint between corresponding features in two consecutive frames. Explicit reconstruction of the 3D world is not required. When considering a number of feature points, the resulting constraints can be solved using nonlinear optimization in terms of position, orientation, and motion. Such a procedure requires an initial guess of these parameters, which can be obtained from dead-reckoning or any other source. The feasibility of the algorithm is established through extensive experimentation. Performance is compared with a state-of-the-art alternative algorithm, which intermediately reconstructs the 3D structure and then registers it to the DTM. A clear advantage for the novel algorithm is demonstrated in variety of scenarios.
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
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.
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.
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.
The Perception of Faces in Different Poses by One-Month-Olds.
ERIC Educational Resources Information Center
Sai, F.; Bushnell, I. W. R.
The ability of 1-month-old infants to recognize their mothers visually was explored with the live faces of mother and stranger presented in three different poses: en face (full face), half-profile, and profile. Subjects were 16 infants with normal Apgar scores at birth who were volunteered by their parents after an initial contact in a maternity…
A new framework for estimating return levels using regional frequency analysis
NASA Astrophysics Data System (ADS)
Winter, Hugo; Bernardara, Pietro; Clegg, Georgina
2017-04-01
We propose a new framework for incorporating more spatial and temporal information into the estimation of extreme return levels. Currently, most studies use extreme value models applied to data from a single site; an approach which is inefficient statistically and leads to return level estimates that are less physically realistic. We aim to highlight the benefits that could be obtained by using methodology based upon regional frequency analysis as opposed to classic single site extreme value analysis. This motivates a shift in thinking, which permits the evaluation of local and regional effects and makes use of the wide variety of data that are now available on high temporal and spatial resolutions. The recent winter storms over the UK during the winters of 2013-14 and 2015-16, which have caused wide-ranging disruption and damaged important infrastructure, provide the main motivation for the current work. One of the most impactful natural hazards is flooding, which is often initiated by extreme precipitation. In this presentation, we focus on extreme rainfall, but shall discuss other meteorological variables alongside potentially damaging hazard combinations. To understand the risks posed by extreme precipitation, we need reliable statistical models which can be used to estimate quantities such as the T-year return level, i.e. the level which is expected to be exceeded once every T-years. Extreme value theory provides the main collection of statistical models that can be used to estimate the risks posed by extreme precipitation events. Broadly, at a single site, a statistical model is fitted to exceedances of a high threshold and the model is used to extrapolate to levels beyond the range of the observed data. However, when we have data at many sites over a spatial domain, fitting a separate model for each separate site makes little sense and it would be better if we could incorporate all this information to improve the reliability of return level estimates. Here, we use the regional frequency analysis approach to define homogeneous regions which are affected by the same storms. Extreme value models are then fitted to the data pooled from across a region. We find that this approach leads to more spatially consistent return level estimates with reduced uncertainty bounds.
Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand
DeLuca, Samuel; Khar, Karen; Meiler, Jens
2015-01-01
RosettaLigand has been successfully used to predict binding poses in protein-small molecule complexes. However, the RosettaLigand docking protocol is comparatively slow in identifying an initial starting pose for the small molecule (ligand) making it unfeasible for use in virtual High Throughput Screening (vHTS). To overcome this limitation, we developed a new sampling approach for placing the ligand in the protein binding site during the initial ‘low-resolution’ docking step. It combines the translational and rotational adjustments to the ligand pose in a single transformation step. The new algorithm is both more accurate and more time-efficient. The docking success rate is improved by 10–15% in a benchmark set of 43 protein/ligand complexes, reducing the number of models that typically need to be generated from 1000 to 150. The average time to generate a model is reduced from 50 seconds to 10 seconds. As a result we observe an effective 30-fold speed increase, making RosettaLigand appropriate for docking medium sized ligand libraries. We demonstrate that this improved initial placement of the ligand is critical for successful prediction of an accurate binding position in the ‘high-resolution’ full atom refinement step. PMID:26207742
Estimation of Full-Body Poses Using Only Five Inertial Sensors: An Eager or Lazy Learning Approach?
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?
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.
Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space
Chen, Min; Hashimoto, Koichi
2017-01-01
Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189
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.
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.
Hsu, Chi-Pin; Lin, Shang-Chih; Shih, Kao-Shang; Huang, Chang-Hung; Lee, Chian-Her
2014-12-01
After total knee replacement, the model-based Roentgen stereophotogrammetric analysis (RSA) technique has been used to monitor the status of prosthetic wear, misalignment, and even failure. However, the overlap of the prosthetic outlines inevitably increases errors in the estimation of prosthetic poses due to the limited amount of available outlines. In the literature, quite a few studies have investigated the problems induced by the overlapped outlines, and manual adjustment is still the mainstream. This study proposes two methods to automate the image processing of overlapped outlines prior to the pose registration of prosthetic models. The outline-separated method defines the intersected points and segments the overlapped outlines. The feature-recognized method uses the point and line features of the remaining outlines to initiate registration. Overlap percentage is defined as the ratio of overlapped to non-overlapped outlines. The simulated images with five overlapping percentages are used to evaluate the robustness and accuracy of the proposed methods. Compared with non-overlapped images, overlapped images reduce the number of outlines available for model-based RSA calculation. The maximum and root mean square errors for a prosthetic outline are 0.35 and 0.04 mm, respectively. The mean translation and rotation errors are 0.11 mm and 0.18°, respectively. The errors of the model-based RSA results are increased when the overlap percentage is beyond about 9%. In conclusion, both outline-separated and feature-recognized methods can be seamlessly integrated to automate the calculation of rough registration. This can significantly increase the clinical practicability of the model-based RSA technique.
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.
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...
Detection of tunnel excavation using fiber optic reflectometry: experimental validation
NASA Astrophysics Data System (ADS)
Linker, Raphael; Klar, Assaf
2013-06-01
Cross-border smuggling tunnels enable unmonitored movement of people and goods, and pose a severe threat to homeland security. In recent years, we have been working on the development of a system based on fiber- optic Brillouin time domain reflectometry (BOTDR) for detecting tunnel excavation. In two previous SPIE publications we have reported the initial development of the system as well as its validation using small-scale experiments. This paper reports, for the first time, results of full-scale experiments and discusses the system performance. The results confirm that distributed measurement of strain profiles in fiber cables buried at shallow depth enable detection of tunnel excavation, and by proper data processing, these measurements enable precise localization of the tunnel, as well as reasonable estimation of its depth.
A Bayesian Inferential Approach to Quantify the Transmission Intensity of Disease Outbreak
Kadi, Adiveppa S.; Avaradi, Shivakumari R.
2015-01-01
Background. Emergence of infectious diseases like influenza pandemic (H1N1) 2009 has become great concern, which posed new challenges to the health authorities worldwide. To control these diseases various studies have been developed in the field of mathematical modelling, which is useful tool for understanding the epidemiological dynamics and their dependence on social mixing patterns. Method. We have used Bayesian approach to quantify the disease outbreak through key epidemiological parameter basic reproduction number (R 0), using effective contacts, defined as sum of the product of incidence cases and probability of generation time distribution. We have estimated R 0 from daily case incidence data for pandemic influenza A/H1N1 2009 in India, for the initial phase. Result. The estimated R 0 with 95% credible interval is consistent with several other studies on the same strain. Through sensitivity analysis our study indicates that infectiousness affects the estimate of R 0. Conclusion. Basic reproduction number R 0 provides the useful information to the public health system to do some effort in controlling the disease by using mitigation strategies like vaccination, quarantine, and so forth. PMID:25784956
Jeremy Fried; Paul Meznarich
2014-01-01
Large wildfires in the United States pose significant challenges to fire management agencies charged with protecting lives, property, and natural resources. A vigorous initial response to a wildfire, a process referred to as "initial attack," can greatly reduce the likelihood of the fire becoming larger and causing substantial damage. Successful...
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.
Pose-Invariant Face Recognition via RGB-D Images.
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.
Aquatic concentrations of chemical analytes compared to ecotoxicity estimates
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
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
Shared sensory estimates for human motion perception and pursuit eye movements.
Mukherjee, Trishna; Battifarano, Matthew; Simoncini, Claudio; Osborne, Leslie C
2015-06-03
Are sensory estimates formed centrally in the brain and then shared between perceptual and motor pathways or is centrally represented sensory activity decoded independently to drive awareness and action? Questions about the brain's information flow pose a challenge because systems-level estimates of environmental signals are only accessible indirectly as behavior. Assessing whether sensory estimates are shared between perceptual and motor circuits requires comparing perceptual reports with motor behavior arising from the same sensory activity. Extrastriate visual cortex both mediates the perception of visual motion and provides the visual inputs for behaviors such as smooth pursuit eye movements. Pursuit has been a valuable testing ground for theories of sensory information processing because the neural circuits and physiological response properties of motion-responsive cortical areas are well studied, sensory estimates of visual motion signals are formed quickly, and the initiation of pursuit is closely coupled to sensory estimates of target motion. Here, we analyzed variability in visually driven smooth pursuit and perceptual reports of target direction and speed in human subjects while we manipulated the signal-to-noise level of motion estimates. Comparable levels of variability throughout viewing time and across conditions provide evidence for shared noise sources in the perception and action pathways arising from a common sensory estimate. We found that conditions that create poor, low-gain pursuit create a discrepancy between the precision of perception and that of pursuit. Differences in pursuit gain arising from differences in optic flow strength in the stimulus reconcile much of the controversy on this topic. Copyright © 2015 the authors 0270-6474/15/358515-16$15.00/0.
Shared Sensory Estimates for Human Motion Perception and Pursuit Eye Movements
Mukherjee, Trishna; Battifarano, Matthew; Simoncini, Claudio
2015-01-01
Are sensory estimates formed centrally in the brain and then shared between perceptual and motor pathways or is centrally represented sensory activity decoded independently to drive awareness and action? Questions about the brain's information flow pose a challenge because systems-level estimates of environmental signals are only accessible indirectly as behavior. Assessing whether sensory estimates are shared between perceptual and motor circuits requires comparing perceptual reports with motor behavior arising from the same sensory activity. Extrastriate visual cortex both mediates the perception of visual motion and provides the visual inputs for behaviors such as smooth pursuit eye movements. Pursuit has been a valuable testing ground for theories of sensory information processing because the neural circuits and physiological response properties of motion-responsive cortical areas are well studied, sensory estimates of visual motion signals are formed quickly, and the initiation of pursuit is closely coupled to sensory estimates of target motion. Here, we analyzed variability in visually driven smooth pursuit and perceptual reports of target direction and speed in human subjects while we manipulated the signal-to-noise level of motion estimates. Comparable levels of variability throughout viewing time and across conditions provide evidence for shared noise sources in the perception and action pathways arising from a common sensory estimate. We found that conditions that create poor, low-gain pursuit create a discrepancy between the precision of perception and that of pursuit. Differences in pursuit gain arising from differences in optic flow strength in the stimulus reconcile much of the controversy on this topic. PMID:26041919
An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation
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
Art critic: Multisignal vision and speech interaction system in a gaming context.
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.
An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation.
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
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.
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.
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)
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...
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.
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.
A Layered Approach for Robust Spatial Virtual Human Pose Reconstruction Using a Still Image
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
Stochastic Integration H∞ Filter for Rapid Transfer Alignment of INS.
Zhou, Dapeng; Guo, Lei
2017-11-18
The performance of an inertial navigation system (INS) operated on a moving base greatly depends on the accuracy of rapid transfer alignment (RTA). However, in practice, the coexistence of large initial attitude errors and uncertain observation noise statistics poses a great challenge for the estimation accuracy of misalignment angles. This study aims to develop a novel robust nonlinear filter, namely the stochastic integration H ∞ filter (SIH ∞ F) for improving both the accuracy and robustness of RTA. In this new nonlinear H ∞ filter, the stochastic spherical-radial integration rule is incorporated with the framework of the derivative-free H ∞ filter for the first time, and the resulting SIH ∞ F simultaneously attenuates the negative effect in estimations caused by significant nonlinearity and large uncertainty. Comparisons between the SIH ∞ F and previously well-known methodologies are carried out by means of numerical simulation and a van test. The results demonstrate that the newly-proposed method outperforms the cubature H ∞ filter. Moreover, the SIH ∞ F inherits the benefit of the traditional stochastic integration filter, but with more robustness in the presence of uncertainty.
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.
AN INFORMATIC APPROACH TO ESTIMATING ECOLOGICAL RISKS POSED BY PHARMACEUTICAL USE
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...
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...
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.
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.
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.
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.
Distribution of Cr, Pb, Cd, Zn, Fe and Mn in Lake Victoria sediments, East Africa
DOE Office of Scientific and Technical Information (OSTI.GOV)
Onyari, J.M.; Wandiga, S.O.
1989-06-01
The presence of many metals at trace or ultra-trace levels in the human environment has received increased global attention. Sediments as a sink for pollutants are widely recognized pollution sources and diagenesis and biochemical transformations within the sediment may mobilize pollutants posing a threat to a wider biological community. The natural (background) concentrations of heavy metals in lake sediments can be estimated either by analysis of surface sediments in non-polluted regions or by analysis of core samples antedating modern pollution. The distribution pattern of heavy metals in tropical freshwater systems has been little studied. The authors found increased concentrations ofmore » lead and other trace metals in Lake Victoria. Thus this study was initiated in order to further investigate the distribution patterns of lead and other metals in Lake Victoria.« less
Jin, Huaiping; Chen, Xiangguang; Yang, Jianwen; Wu, Lei; Wang, Li
2014-11-01
The lack of accurate process models and reliable online sensors for substrate measurements poses significant challenges for controlling substrate feeding accurately, automatically and optimally in fed-batch fermentation industries. It is still a common practice to regulate the feeding rate based upon manual operations. To address this issue, a hybrid intelligent control method is proposed to enable automatic substrate feeding. The resulting control system consists of three modules: a presetting module for providing initial set-points; a predictive module for estimating substrate concentration online based on a new time interval-varying soft sensing algorithm; and a feedback compensator using expert rules. The effectiveness of the proposed approach is demonstrated through its successful applications to the industrial fed-batch chlortetracycline fermentation process. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Álvarez, Gonzalo; Uribe, Eduardo; Díaz, Rosario; Braun, Mauricio; Mariño, Carmen; Blanco, Juan
2011-05-01
In summer 2007, a dinoflagellate preliminarily identified as Protoceratium reticulatum bloomed in Bahía Mejillones, northern Chile. Phytoplankton samples were analyzed in detail by light and scanning electron microscopy revealing the presence of resting cyst and motile cells of P. reticulatum. Oceanographic and phytoplankton data suggest that the bloom was initiated offshore by motile cells and germinated cysts during an upwelling pulse. These cells were advected into the bay when upwelling relaxed and grew without any relevant competitor. Phytoplankton net samples were found to contain yessotoxin as the only toxin in an estimated proportion of 0.2 and 0.4 pg cell - 1 , thus confirming that P. reticulatum is a source of yessotoxin in northern Chilean waters and consequently that it poses a risk for human health and mollusk exploitation in the area.
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.
Study on the initial value for the exterior orientation of the mobile version
NASA Astrophysics Data System (ADS)
Yu, Zhi-jing; Li, Shi-liang
2011-10-01
Single mobile vision coordinate measurement system is in the measurement site using a single camera body and a notebook computer to achieve three-dimensional coordinates. To obtain more accurate approximate values of exterior orientation calculation in the follow-up is very important in the measurement process. The problem is a typical one for the space resection, and now studies on this topic have been widely conducted in research. Single-phase space resection mainly focuses on two aspects: of co-angular constraint based on the method, its representatives are camera co-angular constraint pose estimation algorithm and the cone angle law; the other is a direct linear transformation (DLT). One common drawback for both methods is that the CCD lens distortion is not considered. When the initial value was calculated with the direct linear transformation method, the distribution and abundance of control points is required relatively high, the need that control points can not be distributed in the same plane must be met, and there are at least six non- coplanar control points. However, its usefulness is limited. Initial value will directly influence the convergence and convergence speed of the ways of calculation. This paper will make the nonlinear of the total linear equations linearized by using the total linear equations containing distorted items and Taylor series expansion, calculating the initial value of the camera exterior orientation. Finally, the initial value is proved to be better through experiments.
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.
The Regular Education Initiative: What Do Three Groups of Education Professionals Think?
ERIC Educational Resources Information Center
Davis, Jane C.; Maheady, Larry
1991-01-01
A survey of general education teachers, special education teachers, and building principals in Michigan assessed their agreement with the Regular Education Initiative (REI) goals and methods. Analysis of the 605 responses indicated general agreement with REI goals and procedures. Most educators believed that pragmatic factors posed the greatest…
Despite the Odds: The Contentious Politics of Education Reform
ERIC Educational Resources Information Center
Grindle, Merilee S.
2004-01-01
"Despite the Odds" poses an important question: How can we account for successful policy reform initiatives when the political cards are stacked against change? Theories of politics usually predict that reform initiatives will be unsuccessful when powerful groups are opposed to change and institutions are biased against it. This book,…
Public health adaptation to climate change in Canadian jurisdictions.
Austin, Stephanie E; Ford, James D; Berrang-Ford, Lea; Araos, Malcolm; Parker, Stephen; Fleury, Manon D
2015-01-12
Climate change poses numerous risks to the health of Canadians. Extreme weather events, poor air quality, and food insecurity in northern regions are likely to increase along with the increasing incidence and range of infectious diseases. In this study we identify and characterize Canadian federal, provincial, territorial and municipal adaptation to these health risks based on publically available information. Federal health adaptation initiatives emphasize capacity building and gathering information to address general health, infectious disease and heat-related risks. Provincial and territorial adaptation is varied. Quebec is a leader in climate change adaptation, having a notably higher number of adaptation initiatives reported, addressing almost all risks posed by climate change in the province, and having implemented various adaptation types. Meanwhile, all other Canadian provinces and territories are in the early stages of health adaptation. Based on publically available information, reported adaptation also varies greatly by municipality. The six sampled Canadian regional health authorities (or equivalent) are not reporting any adaptation initiatives. We also find little relationship between the number of initiatives reported in the six sampled municipalities and their provinces, suggesting that municipalities are adapting (or not adapting) autonomously.
Model-based recognition of 3D articulated target using ladar range data.
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.
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
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.
Zou, Yaming; Liao, Yu; Liu, Fengying; Chen, Lei; Shen, Hongcheng; Huang, Shujie; Zheng, Heping; Yang, Bin; Hao, Yuantao
2017-11-01
Syphilis has continuously posed a great challenge to China. However, very little data existed regarding the cost of syphilis. Taking Guangdong Initiative for Comprehensive Control of Syphilis area as the research site, we aimed to comprehensively measure the annual economic burden of syphilis from a societal perspective. Newly diagnosed and follow-up outpatient cases were investigated by questionnaire. Reported tertiary syphilis cases and medical institutions cost were both collected. The direct economic burden was measured by the bottom-up approach, the productivity cost by the human capital method, and the intangible burden by the contingency valuation method. Three hundred five valid early syphilis cases and 13 valid tertiary syphilis cases were collected in the investigation to estimate the personal average cost. The total economic burden of syphilis was US $729,096.85 in Guangdong Initiative for Comprehensive Control of Syphilis sites in the year of 2014, with medical institutions cost accounting for 73.23% of the total. Household average direct cost of early syphilis was US $23.74. Average hospitalization cost of tertiary syphilis was US $2,749.93. Of the cost to medical institutions, screening and testing comprised the largest proportion (26%), followed by intervention and case management (22%) and operational cost (21%). Household average productivity cost of early syphilis was US $61.19. Household intangible cost of syphilis was US $15,810.54. Syphilis caused a substantial economic burden on patients, their families, and society in Guangdong. Household productivity and intangible costs both shared positive relationships with local economic levels. Strengthening the prevention and effective treatment of early syphilis could greatly help to lower the economic burden of syphilis.
NASA Astrophysics Data System (ADS)
Selwa, Edithe; Elisée, Eddy; Zavala, Agustin; Iorga, Bogdan I.
2018-01-01
Our participation to the D3R Grand Challenge 2 involved a protocol in two steps, with an initial analysis of the available structural data from the PDB allowing the selection of the most appropriate combination of docking software and scoring function. Subsequent docking calculations showed that the pose prediction can be carried out with a certain precision, but this is dependent on the specific nature of the ligands. The correct ranking of docking poses is still a problem and cannot be successful in the absence of good pose predictions. Our free energy calculations on two different subsets provided contrasted results, which might have the origin in non-optimal force field parameters associated with the sulfonamide chemical moiety.
A chance constraint estimation approach to optimizing resource management under uncertainty
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.
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.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pettersson, Per, E-mail: per.pettersson@uib.no; Nordström, Jan, E-mail: jan.nordstrom@liu.se; Doostan, Alireza, E-mail: alireza.doostan@colorado.edu
2016-02-01
We present a well-posed stochastic Galerkin formulation of the incompressible Navier–Stokes equations with uncertainty in model parameters or the initial and boundary conditions. The stochastic Galerkin method involves representation of the solution through generalized polynomial chaos expansion and projection of the governing equations onto stochastic basis functions, resulting in an extended system of equations. A relatively low-order generalized polynomial chaos expansion is sufficient to capture the stochastic solution for the problem considered. We derive boundary conditions for the continuous form of the stochastic Galerkin formulation of the velocity and pressure equations. The resulting problem formulation leads to an energy estimatemore » for the divergence. With suitable boundary data on the pressure and velocity, the energy estimate implies zero divergence of the velocity field. Based on the analysis of the continuous equations, we present a semi-discretized system where the spatial derivatives are approximated using finite difference operators with a summation-by-parts property. With a suitable choice of dissipative boundary conditions imposed weakly through penalty terms, the semi-discrete scheme is shown to be stable. Numerical experiments in the laminar flow regime corroborate the theoretical results and we obtain high-order accurate results for the solution variables and the velocity divergence converges to zero as the mesh is refined.« less
Scan-based volume animation driven by locally adaptive articulated registrations.
Rhee, Taehyun; Lewis, J P; Neumann, Ulrich; Nayak, Krishna S
2011-03-01
This paper describes a complete system to create anatomically accurate example-based volume deformation and animation of articulated body regions, starting from multiple in vivo volume scans of a specific individual. In order to solve the correspondence problem across volume scans, a template volume is registered to each sample. The wide range of pose variations is first approximated by volume blend deformation (VBD), providing proper initialization of the articulated subject in different poses. A novel registration method is presented to efficiently reduce the computation cost while avoiding strong local minima inherent in complex articulated body volume registration. The algorithm highly constrains the degrees of freedom and search space involved in the nonlinear optimization, using hierarchical volume structures and locally constrained deformation based on the biharmonic clamped spline. Our registration step establishes a correspondence across scans, allowing a data-driven deformation approach in the volume domain. The results provide an occlusion-free person-specific 3D human body model, asymptotically accurate inner tissue deformations, and realistic volume animation of articulated movements driven by standard joint control estimated from the actual skeleton. Our approach also addresses the practical issues arising in using scans from living subjects. The robustness of our algorithms is tested by their applications on the hand, probably the most complex articulated region in the body, and the knee, a frequent subject area for medical imaging due to injuries. © 2011 IEEE
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.
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
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
From the Adam Smith Institute to the Zapatistas: An Internet Gateway to all Development Knowledge.
ERIC Educational Resources Information Center
Wilks, Alex
2002-01-01
Examines the World Bank Internet initiative, the Development Gateway. Describes the importance of the Bank as a knowledge bank and the threats posed by the Internet to its near monopoly of development thinking. Argues that the initiative reveals biases and misunderstandings in the World Bank's approach to knowledge for development. (CAJ)
NASA Astrophysics Data System (ADS)
Parry, Louise; Neely, Ryan, III; Bennett, Lindsay; Collier, Chris; Dufton, David
2017-04-01
The Scottish Environment Protection Agency (SEPA) has a statutory responsibility to provide flood warning across Scotland. It achieves this through an operational partnership with the UK Met Office wherein meteorological forecasts are applied to a national distributed hydrological model, Grid- to- Grid (G2G), and catchment specific lumped PDM models. Both of these model types rely on observed precipitation input for model development and calibration, and operationally for historical runs to generate initial conditions. Scotland has an average annual precipitation of 1430mm per annum (1971-2000), but the spatial variability in totals is high, predominantly in relation to the topography and prevailing winds, which poses different challenges to both radar and point measurement methods of observation. In addition, the high elevations mean that in winter a significant proportion of precipitation falls as snow. For the operational forecasting models, observed rainfall data is provided in Near Real Time (NRT) from SEPA's network of approximately 260 telemetered TBR gauges and 4 UK Met Office C-band radars. Both data sources have their strengths and weaknesses, particularly in relation to the orography and spatial representativeness, but estimates of rainfall from the two methods can vary greatly. Northern Scotland, particularly near Inverness, is a comparatively sparse part of the radar network. Rainfall totals and distribution in this area are determined by the Northern Western Highlands and Cairngorms mountain ranges, which also have a negative impact on radar observations. In recognition of this issue, the NCAS mobile X-band weather radar (MXWR) was deployed in this area between February and August 2016. This study presents a comparison of rainfall estimates for the Inverness and Moray Firth region generated from the operational radar network, the TBR network, and the MXWR. Quantitative precipitation estimates (QPEs) from both sources of radar data were compared to point estimates of precipitation as well as catchment average estimates generated using different spatial averaging methods, including the operationally applied Thiessen polygons. In addition, the QPEs were applied to operational PDM models to compare the effect on the simulated runoff. The results highlight the hydrological significance of uncertainty in observed rainfall. Recommendations for future investigations are to improve the estimate of radar QPEs through improvement of the correction for orography and the correction for different precipitation types, as well as to analyse the benefits of the UK Met Office radar-raingauge merged product. In addition, we need to quantity the cost-benefit of deploying more radars in Scotland in light of the problems posed by the orography.
Mukherjee, Joyeeta Mitra; Hutton, Brian F; Johnson, Karen L; Pretorius, P Hendrik; King, Michael A
2014-01-01
Motion estimation methods in single photon emission computed tomography (SPECT) can be classified into methods which depend on just the emission data (data-driven), or those that use some other source of information such as an external surrogate. The surrogate-based methods estimate the motion exhibited externally which may not correlate exactly with the movement of organs inside the body. The accuracy of data-driven strategies on the other hand is affected by the type and timing of motion occurrence during acquisition, the source distribution, and various degrading factors such as attenuation, scatter, and system spatial resolution. The goal of this paper is to investigate the performance of two data-driven motion estimation schemes based on the rigid-body registration of projections of motion-transformed source distributions to the acquired projection data for cardiac SPECT studies. Comparison is also made of six intensity based registration metrics to an external surrogate-based method. In the data-driven schemes, a partially reconstructed heart is used as the initial source distribution. The partially-reconstructed heart has inaccuracies due to limited angle artifacts resulting from using only a part of the SPECT projections acquired while the patient maintained the same pose. The performance of different cost functions in quantifying consistency with the SPECT projection data in the data-driven schemes was compared for clinically realistic patient motion occurring as discrete pose changes, one or two times during acquisition. The six intensity-based metrics studied were mean-squared difference (MSD), mutual information (MI), normalized mutual information (NMI), pattern intensity (PI), normalized cross-correlation (NCC) and entropy of the difference (EDI). Quantitative and qualitative analysis of the performance is reported using Monte-Carlo simulations of a realistic heart phantom including degradation factors such as attenuation, scatter and system spatial resolution. Further the visual appearance of motion-corrected images using data-driven motion estimates was compared to that obtained using the external motion-tracking system in patient studies. Pattern intensity and normalized mutual information cost functions were observed to have the best performance in terms of lowest average position error and stability with degradation of image quality of the partial reconstruction in simulations. In all patients, the visual quality of PI-based estimation was either significantly better or comparable to NMI-based estimation. Best visual quality was obtained with PI-based estimation in 1 of the 5 patient studies, and with external-surrogate based correction in 3 out of 5 patients. In the remaining patient study there was little motion and all methods yielded similar visual image quality. PMID:24107647
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.
NASA Astrophysics Data System (ADS)
Dai, A. J.; Chen, Z. Y.; Huang, D. W.; Tong, R. H.; Zhang, J.; Wei, Y. N.; Ma, T. K.; Wang, X. L.; Yang, H. Y.; Gao, H. L.; Pan, Y.; the J-TEXT Team
2018-05-01
A large number of runaway electrons (REs) with energies as high as several tens of mega-electron volt (MeV) may be generated during disruptions on a large-scale tokamak. The kinetic energy carried by REs is eventually deposited on the plasma-facing components, causing damage and posing a threat on the operation of the tokamak. The remaining magnetic energy following a thermal quench is significant on a large-scale tokamak. The conversion of magnetic energy to runaway kinetic energy will increase the threat of runaway electrons on the first wall. The magnetic energy dissipated inside the vacuum vessel (VV) equals the decrease of initial magnetic energy inside the VV plus the magnetic energy flowing into the VV during a disruption. Based on the estimated magnetic energy, the evolution of magnetic-kinetic energy conversion are analyzed through three periods in disruptions with a runaway current plateau.
Mitigation of adverse environmental effects on lunar-based astronomical instruments
NASA Astrophysics Data System (ADS)
Johnson, Charles L.; Dietz, Kurtis L.; Armstrong, T. W.; Colborn, B. L.
The galactic cosmic-ray flux incident on the moon was examined for its potential adverse impact on the performance of the large lunar telescope (LLT) proposed as a part of NASA's Space Exploration Initiative (SEI). Noise produced by the cosmic-ray flux in the charge coupled devices to be used as the primary photodetector in the telescope was estimated. It was calculated that approximately 2.5 m of regolith would provide the shielding necessary to reduce the noise to an acceptable level. Dust is an omnipresent environmental concern for any human-assisted or robotic scientific instruments deployed on the moon. The degree to which dust poses an operational risk to the telescope was examined. Three potential methods for reducing this risk were identified: locating scientific instruments at remote locations; utilizing a prepared, dust-free site for all rocket activities; and covering the optics during high-risk times.
Mitigation of adverse environmental effects on lunar-based astronomical instruments
NASA Astrophysics Data System (ADS)
Johnson, Les; Dietz, Kurtis L.; Armstrong, T. W.; Colborn, B. L.
1994-02-01
The galactic cosmic-ray flux incident on the Moon was examined for its potential adverse impact on the performance of the large lunar telescope (LLT) proposed as a part of NASA's Space Exploration Initiative (SEI). Noise produced by the cosmic-ray flux in the charge coupled devices (CCD's) to be used as the primary photodetector in the telescope was estimated. It was calculated that approximately 2.5 m of regolith would provide the shielding necessary to reduce the noise to an acceptable level. Dust is an omnipresent environmental concern for any human-assisted or robotic scientific instruments deployed on the Moon. The degree to which dust poses an operational risk to the telescope was examined. Three potential methods for reducing this risk were identified: locating scientific instruments at remote locations; utilizing a prepared, dust-free site for all rocket activities; and covering the optics during high-risk times.
Localization of Mobile Robots Using Odometry and an External Vision Sensor
Pizarro, Daniel; Mazo, Manuel; Santiso, Enrique; Marron, Marta; Jimenez, David; Cobreces, Santiago; Losada, Cristina
2010-01-01
This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields. PMID:22319318
Mitigation of adverse environmental effects on lunar-based astronomical instruments
NASA Technical Reports Server (NTRS)
Johnson, Charles L.; Dietz, Kurtis L.; Armstrong, T. W.; Colborn, B. L.
1992-01-01
The galactic cosmic-ray flux incident on the moon was examined for its potential adverse impact on the performance of the large lunar telescope (LLT) proposed as a part of NASA's Space Exploration Initiative (SEI). Noise produced by the cosmic-ray flux in the charge coupled devices to be used as the primary photodetector in the telescope was estimated. It was calculated that approximately 2.5 m of regolith would provide the shielding necessary to reduce the noise to an acceptable level. Dust is an omnipresent environmental concern for any human-assisted or robotic scientific instruments deployed on the moon. The degree to which dust poses an operational risk to the telescope was examined. Three potential methods for reducing this risk were identified: locating scientific instruments at remote locations; utilizing a prepared, dust-free site for all rocket activities; and covering the optics during high-risk times.
Mitigation of adverse environmental effects on lunar-based astronomical instruments
NASA Technical Reports Server (NTRS)
Johnson, Les; Dietz, Kurtis L.; Armstrong, T. W.; Colborn, B. L.
1994-01-01
The galactic cosmic-ray flux incident on the Moon was examined for its potential adverse impact on the performance of the large lunar telescope (LLT) proposed as a part of NASA's Space Exploration Initiative (SEI). Noise produced by the cosmic-ray flux in the charge coupled devices (CCD's) to be used as the primary photodetector in the telescope was estimated. It was calculated that approximately 2.5 m of regolith would provide the shielding necessary to reduce the noise to an acceptable level. Dust is an omnipresent environmental concern for any human-assisted or robotic scientific instruments deployed on the Moon. The degree to which dust poses an operational risk to the telescope was examined. Three potential methods for reducing this risk were identified: locating scientific instruments at remote locations; utilizing a prepared, dust-free site for all rocket activities; and covering the optics during high-risk times.
Addressing the tobacco epidemic in the Philippines: progress since ratification of the WHO FCTC
Antonio, M.; Limpin, M.; Alzona, L.; Trinidad, F.; Dorotheo, U.; Yapchiongco, R.; Garcia, R.; Anden, A.; Alday, J.
2013-01-01
Tobacco use is the leading cause of preventable death, and is estimated to kill more than 5 million persons each year worldwide. Tobacco use and exposure to second-hand smoke pose a major public health problem in the Philippines. Effective tobacco control policies are enshrined in the World Health Organization (WHO) Framework Convention on Tobacco Control (FCTC), a legally binding international treaty that was ratified by the Philippines in 2005. Since 2007, Bloomberg Philanthropies has supported the accelerated reduction of tobacco use in many countries, including the Philippines. Progress in the Philippines is discussed with particular emphasis on the period since ratification of the WHO FCTC, and with particular focus on the grants programme funded by the Bloomberg Initiative. Despite considerable progress, significant challenges are identified that must be addressed in future if the social, health and economic burden from the tobacco epidemic is to be alleviated. PMID:26393010
The public health planners' perfect storm: Hurricane Matthew and Zika virus.
Ahmed, Qanta A; Memish, Ziad A
Hurricane Matthew threatened to be one of the most powerful Hurricanes to hit the United States in a century. Fortunately, it avoided making landfall on Florida, the eye of the Hurricane remaining centered 40 miles off the Florida coast. Even so it has resulted in over $7 Billion USD in damage according to initial estimates with much of the damage ongoing in severe flooding. Response to and recovery from Hurricane Matthew challenged Florida's public health services and resources just as emergency Zika-specific congressional funding to combat Zika outbreaks in Florida had become available. Hurricanes can disrupt the urban environment in a way that increases the likelihood of vector-borne illnesses and their aftermath can severely strain the very infectious disease and infection control academe needed to combat vector-borne outbreaks. This commentary attempts to examine the challenges posed by Hurricane Matthew in Florida's efforts to contain Zika. Copyright © 2016 Elsevier Ltd. All rights reserved.
Localization of mobile robots using odometry and an external vision sensor.
Pizarro, Daniel; Mazo, Manuel; Santiso, Enrique; Marron, Marta; Jimenez, David; Cobreces, Santiago; Losada, Cristina
2010-01-01
This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields.
Gao, Jian; Zhang, Jie; Li, Hong; Li, Lei; Xu, Linghong; Zhang, Yujie; Wang, Zhanshan; Wang, Xuezhong; Zhang, Weiqi; Chen, Yizhen; Cheng, Xi; Zhang, Hao; Peng, Liang; Chai, Fahe; Wei, Yongjie
2018-07-01
Volatile organic compounds (VOCs) can react with atmospheric radicals while being transported after being emitted, resulting in substantial losses. Using only observed VOC mixing ratios to assess VOC pollution, is therefore problematic. The observed mixing ratios and initial mixing ratios taking chemical loss into consideration were performed using data for 90 VOCs in the atmosphere in a typical urban area in Beijing in winter 2013 to gain a more accurate view of VOC pollution. The VOC sources, ambient VOC mixing ratios and compositions, variability and influencing factors, contributions to near-ground-ozone and health risks posed were assessed. Source apportionment should be conducted using initial mixing ratios, but health risks should be assessed using observed mixing ratios. The daytime daily mean initial mixing ratio (72.62ppbv) was 7.72ppbv higher than the daytime daily mean observed mixing ratio (64.90ppbv). Alkenes contributed >70% of the consumed VOCs. The nighttime daily mean observed mixing ratio was 71.66ppbv, 6.76ppbv higher than the daytime mixing ratio. The observed mixing ratio for 66 VOCs was 40.31% higher in Beijing than New York. The OFPs of Ini-D (266.54ppbv) was underestimated 23.41% compared to the OFP of Obs-D (204.14ppbv), improving emission control of ethylene and propene would be an effective way of controlling O 3 . Health risk assessments performed for 28 hazardous VOCs show that benzene, chloroform, 1,2-dichloroethane, and acetaldehyde pose carcinogenic risk and acrolein poses non-carcinogenic risks. Source apportionment results indicated that vehicle exhausts, solvent usage and industrial processes were the main VOC source during the study. Copyright © 2018. Published by Elsevier B.V.
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…
Two cases of cerebral aneurysms in HIV+ children.
Fulmer, B B; Dillard, S C; Musulman, E M; Palmer, C A; Oakes, J
1998-01-01
Two cases of fusiform cerebral aneurysms in human immunodeficiency virus (HIV) positive children are presented. To our knowledge, only 9 patients with this association have been reported. One of our patients represents the first report of a patient with an aneurysm associated with varicella-zoster vasculitis. One patient presented with a subarachnoid hemorrhage, Hunt-Hess grade IV, and posed difficult surgical management. The other patient suffered a cerebral infarct with a resulting hemiparesis. The first patient had a ventriculostomy placed, initially improved, and subsequently died from rebleeding. The second patient improved with medical management. AIDS arteriopathy, and specifically fusiform aneurysms, are being increasingly reported. The various presentations of this surgically challenging entity in light of other AIDS-related syndromes pose difficult management decisions. On occasion, the intracranial aneurysm may be the initial form of presentation as was present in our first patient.
Institutionalizing Blended Learning into Joint Training: A Case Study and Ten Recommendations
2014-12-01
mail.mil pbockelman@mesh.dsci.com ABSTRACT In 2011, the Joint Staff J7 (Joint Training) directorate initiated the Continuum of eLearning project in...Orlando, FL. 14. ABSTRACT In 2011, the Joint Staff J7 (Joint Training) directorate initiated the Continuum of eLearning project in order to integrate...dispersed organizations still poses significant challenges. The Joint Staff J7, Deputy Director for Joint Training initiated the Continuum of eLearning
Retaining Low-Income Residents in the Workforce: Lessons from the Annie E. Casey Jobs Initiative.
ERIC Educational Resources Information Center
Giloth, Bob; Gewirtz, Susan
Annie E. Casey Jobs Initiative sites recognize the challenge that long-term retention poses in today's labor market for low-income residents. They have developed key elements of an operational definition of retention, including the following: no limitation to one job, but only very limited gaps between jobs; and jobs in construction or other…
Public Health Adaptation to Climate Change in Canadian Jurisdictions
Austin, Stephanie E.; Ford, James D.; Berrang-Ford, Lea; Araos, Malcolm; Parker, Stephen; Fleury, Manon D.
2015-01-01
Climate change poses numerous risks to the health of Canadians. Extreme weather events, poor air quality, and food insecurity in northern regions are likely to increase along with the increasing incidence and range of infectious diseases. In this study we identify and characterize Canadian federal, provincial, territorial and municipal adaptation to these health risks based on publically available information. Federal health adaptation initiatives emphasize capacity building and gathering information to address general health, infectious disease and heat-related risks. Provincial and territorial adaptation is varied. Quebec is a leader in climate change adaptation, having a notably higher number of adaptation initiatives reported, addressing almost all risks posed by climate change in the province, and having implemented various adaptation types. Meanwhile, all other Canadian provinces and territories are in the early stages of health adaptation. Based on publically available information, reported adaptation also varies greatly by municipality. The six sampled Canadian regional health authorities (or equivalent) are not reporting any adaptation initiatives. We also find little relationship between the number of initiatives reported in the six sampled municipalities and their provinces, suggesting that municipalities are adapting (or not adapting) autonomously. PMID:25588156
Camera-pose estimation via projective Newton optimization on the manifold.
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.
Storage as a Metric of Catchment Comparison
McNamara, J.P.; Tetzlaff, D.; Bishop, K.; Soulsby, C.; Seyfried, M.; Peters, N.E.; Aulenbach, Brent T.; Hooper, R.
2011-01-01
The volume of water stored within a catchment, and its partitioning among groundwater, soil moisture, snowpack, vegetation, and surface water are the variables that ultimately characterize the state of the hydrologic system. Accordingly, storage may provide useful metrics for catchment comparison. Unfortunately, measuring and predicting the amount of water present in a catchment is seldom done; tracking the dynamics of these stores is even rarer. Storage moderates fluxes and exerts critical controls on a wide range of hydrologic and biologic functions of a catchment. While understanding runoff generation and other processes by which catchments release water will always be central to hydrologic science, it is equally essential to understand how catchments retain water. We have initiated a catchment comparison exercise to begin assessing the value of viewing catchments from the storage perspective. The exercise is based on existing data from five watersheds, no common experimental design, and no integrated modelling efforts. Rather, storage was estimated independently for each site. This briefing presents some initial results of the exercise, poses questions about the definitions and importance of storage and the storage perspective, and suggests future directions for ongoing activities. ?? 2011 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Helmers, Michael; Herrmann, Michael
2018-03-01
We consider a lattice regularization for an ill-posed diffusion equation with a trilinear constitutive law and study the dynamics of phase interfaces in the parabolic scaling limit. Our main result guarantees for a certain class of single-interface initial data that the lattice solutions satisfy asymptotically a free boundary problem with a hysteretic Stefan condition. The key challenge in the proof is to control the microscopic fluctuations that are inevitably produced by the backward diffusion when a particle passes the spinodal region.
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.
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.
Integration and Assessment of Component Health Prognostics in Supervisory Control Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ramuhalli, Pradeep; Bonebrake, Christopher A.; Dib, Gerges
Enhanced risk monitors (ERMs) for active components in advanced reactor concepts use predictive estimates of component failure to update, in real time, predictive safety and economic risk metrics. These metrics have been shown to be capable of use in optimizing maintenance scheduling and managing plant maintenance costs. Integrating this information with plant supervisory control systems increases the potential for making control decisions that utilize real-time information on component conditions. Such decision making would limit the possibility of plant operations that increase the likelihood of degrading the functionality of one or more components while maintaining the overall functionality of the plant.more » ERM uses sensor data for providing real-time information about equipment condition for deriving risk monitors. This information is used to estimate the remaining useful life and probability of failure of these components. By combining this information with plant probabilistic risk assessment models, predictive estimates of risk posed by continued plant operation in the presence of detected degradation may be estimated. In this paper, we describe this methodology in greater detail, and discuss its integration with a prototypic software-based plant supervisory control platform. In order to integrate these two technologies and evaluate the integrated system, software to simulate the sensor data was developed, prognostic models for feedwater valves were developed, and several use cases defined. The full paper will describe these use cases, and the results of the initial evaluation.« less
Regional landfills methane emission inventory in Malaysia.
Abushammala, Mohammed F M; Noor Ezlin Ahmad Basri; Basri, Hassan; Ahmed Hussein El-Shafie; Kadhum, Abdul Amir H
2011-08-01
The decomposition of municipal solid waste (MSW) in landfills under anaerobic conditions produces landfill gas (LFG) containing approximately 50-60% methane (CH(4)) and 30-40% carbon dioxide (CO(2)) by volume. CH(4) has a global warming potential 21 times greater than CO(2); thus, it poses a serious environmental problem. As landfills are the main method for waste disposal in Malaysia, the major aim of this study was to estimate the total CH(4) emissions from landfills in all Malaysian regions and states for the year 2009 using the IPCC, 1996 first-order decay (FOD) model focusing on clean development mechanism (CDM) project applications to initiate emission reductions. Furthermore, the authors attempted to assess, in quantitative terms, the amount of CH(4) that would be emitted from landfills in the period from 1981-2024 using the IPCC 2006 FOD model. The total CH(4) emission using the IPCC 1996 model was estimated to be 318.8 Gg in 2009. The Northern region had the highest CH(4) emission inventory, with 128.8 Gg, whereas the Borneo region had the lowest, with 24.2 Gg. It was estimated that Pulau Penang state produced the highest CH(4) emission, 77.6 Gg, followed by the remaining states with emission values ranging from 38.5 to 1.5 Gg. Based on the IPCC 1996 FOD model, the total Malaysian CH( 4) emission was forecast to be 397.7 Gg by 2020. The IPCC 2006 FOD model estimated a 201 Gg CH(4) emission in 2009, and estimates ranged from 98 Gg in 1981 to 263 Gg in 2024.
The epidemiology of tuberculosis in the Pacific, 2000 to 2013.
Viney, Kerri; Hoy, Damian; Roth, Adam; Kelly, Paul; Harley, David; Sleigh, Adrian
2015-01-01
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. 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. 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). 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.
Caravanos, Jack; Ericson, Bret; Ponce-Canchihuamán, Johny; Hanrahan, David; Block, Meredith; Susilorini, Budi; Fuller, Richard
2013-11-01
Previous studies have evaluated associated health risks and human exposure pathways at mining sites. Others have provided estimates of the scale of the issue based in part on surveys. However, a global census of mining-related hazardous waste sites has been lacking. The Toxic Sites Identification Program (TSIP) implemented by Blacksmith Institute (New York, NY, USA) since 2009 is an ongoing effort to catalogue a wide range of chemically contaminated sites with a potential human health risk (Ericson et al., Environ Monit Assess doi:10.1007/s 10661-012-2665-2, 2012). The TSIP utilizes a rapid assessment instrument, the Initial Site Screening (ISS), to quickly and affordably identify key site criteria including human exposure pathways, estimated populations at risk, and sampling information. The resulting ISS allows for comparison between sites exhibiting different contaminants and pollution sources. This paper explores the results of a subset of ISSs completed at 131 artisanal and small-scale gold mining areas and 275 industrial mining and ore processing sites in 45 countries. The authors show that the ISS captures key data points, allowing for prioritization of sites for further investigation or remedial activity.
Modeling Meteor Flares for Spacecraft Safety
NASA Technical Reports Server (NTRS)
Ehlert, Steven
2017-01-01
NASA's Meteoroid Environment Office (MEO) is tasked with assisting spacecraft operators and engineers in quantifying the threat the meteoroid environment poses to their individual missions. A more complete understanding of the meteoroid environment for this application requires extensive observations. One manner by which the MEO observes meteors is with dedicated video camera systems that operate nightly. Connecting the observational data from these video cameras to the relevant physical properties of the ablating meteoroids, however, is subject to sizable observational and theoretical uncertainties. Arguably the most troublesome theoretical uncertainty in ablation is a model for the structure of meteoroids, as observations clearly show behaviors wholly inconsistent with meteoroids being homogeneous spheres. Further complicating the interpretation of the observations in the context of spacecraft risk is the ubiquitous process of fragmentation and the flares it can produce, which greatly muddles any attempts to estimating initial meteoroid masses. In this talk a method of estimating the mass distribution of fragments in flaring meteors using high resolution video observations will be dis- cussed. Such measurements provide an important step in better understanding of the structure and fragmentation process of the parent meteoroids producing these flares, which in turn may lead to better constraints on meteoroid masses and reduced uncertainties in spacecraft risk.
NASA Technical Reports Server (NTRS)
Voorhies, Coerte V.
1993-01-01
The problem of estimating a steady fluid velocity field near the top of Earth's core which induces the secular variation (SV) indicated by models of the observed geomagnetic field is examined in the source-free mantle/frozen-flux core (SFI/VFFC) approximation. This inverse problem is non-linear because solutions of the forward problem are deterministically chaotic. The SFM/FFC approximation is inexact, and neither the models nor the observations they represent are either complete or perfect. A method is developed for solving the non-linear inverse motional induction problem posed by the hypothesis of (piecewise, statistically) steady core surface flow and the supposition of a complete initial geomagnetic condition. The method features iterative solution of the weighted, linearized least-squares problem and admits optional biases favoring surficially geostrophic flow and/or spatially simple flow. Two types of weights are advanced radial field weights for fitting the evolution of the broad-scale portion of the radial field component near Earth's surface implied by the models, and generalized weights for fitting the evolution of the broad-scale portion of the scalar potential specified by the models.
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.
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
Chowdhury, Sourangsu; Dey, Sagnik
2016-05-01
In India, more than a billion population is at risk of exposure to ambient fine particulate matter (PM2.5) concentration exceeding World Health Organization air quality guideline, posing a serious threat to health. Cause-specific premature death from ambient PM2.5 exposure is poorly known for India. Here we develop a non-linear power law (NLP) function to estimate the relative risk associated with ambient PM2.5 exposure using satellite-based PM2.5 concentration (2001-2010) that is bias-corrected against coincident direct measurements. We show that estimate of annual premature death in India is lower by 14.7% (19.2%) using NLP (integrated exposure risk function, IER) for assumption of uniform baseline mortality across India (as considered in the global burden of disease study) relative to the estimate obtained by adjusting for state-specific baseline mortality using GDP as a proxy. 486,100 (811,000) annual premature death in India is estimated using NLP (IER) risk functions after baseline mortality adjustment. 54.5% of premature death estimated using NLP risk function is attributed to chronic obstructive pulmonary disease (COPD), 24.0% to ischemic heart disease (IHD), 18.5% to stroke and the remaining 3.0% to lung cancer (LC). 44,900 (5900-173,300) less premature death is expected annually, if India achieves its present annual air quality target of 40μgm(-3). Our results identify the worst affected districts in terms of ambient PM2.5 exposure and resulting annual premature death and call for initiation of long-term measures through a systematic framework of pollution and health data archive. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hand Pose Estimation by Fusion of Inertial and Magnetic Sensing Aided by a Permanent Magnet.
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
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
NASA Astrophysics Data System (ADS)
Forbes, Kevin F.; St. Cyr, O. C.
2017-10-01
This paper addresses whether geomagnetic activity challenged the reliability of the electric power system during part of the declining phase of solar cycle 23. Operations by National Grid in England and Wales are examined over the period of 11 March 2003 through 31 March 2005. This paper examines the relationship between measures of geomagnetic activity and a metric of challenged electric power reliability known as the net imbalance volume (NIV). Measured in megawatt hours, NIV represents the sum of all energy deployments initiated by the system operator to balance the electric power system. The relationship between geomagnetic activity and NIV is assessed using a multivariate econometric model. The model was estimated using half-hour settlement data over the period of 11 March 2003 through 31 December 2004. The results indicate that geomagnetic activity had a demonstrable effect on NIV over the sample period. Based on the parameter estimates, out-of-sample predictions of NIV were generated for each half hour over the period of 1 January to 31 March 2005. Consistent with the existence of a causal relationship between geomagnetic activity and the electricity market imbalance, the root-mean-square error of the out-of-sample predictions of NIV is smaller; that is, the predictions are more accurate, when the statistically significant estimated effects of geomagnetic activity are included as drivers in the predictions.
Postprocessing of docked protein-ligand complexes using implicit solvation models.
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.
ERIC Educational Resources Information Center
Korbel, Linda A.
Posing the question, "If you could build a community college for 2010, what would it look like and whom would it serve?" the New Expeditions initiative takes up where the decade-old report by the Commission on the Future of Community Colleges, "Building Communities," left off. The initiative, which sought to remedy the latter report's limited…
Is pretenure interdisciplinary research a career risk?
NASA Astrophysics Data System (ADS)
Fischer, E. V.; Mackey, K. R. M.; Cusack, D. F.; DeSantis, L. R. G.; Hartzell-Nichols, L.; Lutz, J. A.; Melbourne-Thomas, J.; Meyer, R.; Riveros-Iregui, D. A.; Sorte, C. J. B.; Taylor, J. R.; White, S. A.
2012-08-01
Despite initiatives to promote interdisciplinary research, early-career academics continue to perceive professional risks to working at the interface between traditional disciplines. Unexpectedly, the inherent practical challenges of interdisciplinary scholarship, such as new methodologies and lexicons, are not the chief source of the perceived risk. The perception of risk is pervasive across disciplines, and it persists despite efforts to support career development for individuals with common interests [Mitchell and Weiler, 2011]. Suggestions that interdisciplinary work can go unrewarded in academia [Clark et al., 2011] foster a concern that targeting interdisciplinary questions, such as those presented by climate change, will pose problems for acquiring and succeeding in a tenure-track position. If self-preservation limits the questions posed by early-career academics, a perceived career risk is as damaging as a real one to new transdisciplinary initiatives. Thus, institutions should address the source of this perception whether real or specious.
Assessment of the Gaussian Covariance Approximation over an Earth-Asteroid Encounter Period
NASA Technical Reports Server (NTRS)
Mattern, Daniel
2017-01-01
In assessing the risk an asteroid may pose to the Earth, the asteroids state is often predicted for many years, often decades. Only by accounting for the asteroids initial state uncertainty can a measure of the risk be calculated. With the asteroids state uncertainty growing as a function of the initial velocity uncertainty, orbit velocity at the last state update, and the time from the last update to the epoch of interest, the asteroids position uncertainties can grow to many times the size of the Earth when propagated to the encounter risk corridor. This paper examines the merits of propagating the asteroids state covariance as an analytical matrix. The results of this study help to bound the efficacy of applying different metrics for assessing the risk an asteroid poses to the Earth. Additionally, this work identifies a criterion for when different covariance propagation methods are needed to continue predictions after an Earth-encounter period.
Estimating the burden of foodborne diseases in Japan
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
Image-Based Localization Aided Indoor Pedestrian Trajectory Estimation Using Smartphones
Zhou, Yan; Zheng, Xianwei; Chen, Ruizhi; Xiong, Hanjiang; Guo, Sheng
2018-01-01
Accurately determining pedestrian location in indoor environments using consumer smartphones is a significant step in the development of ubiquitous localization services. Many different map-matching methods have been combined with pedestrian dead reckoning (PDR) to achieve low-cost and bias-free pedestrian tracking. However, this works only in areas with dense map constraints and the error accumulates in open areas. In order to achieve reliable localization without map constraints, an improved image-based localization aided pedestrian trajectory estimation method is proposed in this paper. The image-based localization recovers the pose of the camera from the 2D-3D correspondences between the 2D image positions and the 3D points of the scene model, previously reconstructed by a structure-from-motion (SfM) pipeline. This enables us to determine the initial location and eliminate the accumulative error of PDR when an image is successfully registered. However, the image is not always registered since the traditional 2D-to-3D matching rejects more and more correct matches when the scene becomes large. We thus adopt a robust image registration strategy that recovers initially unregistered images by integrating 3D-to-2D search. In the process, the visibility and co-visibility information is adopted to improve the efficiency when searching for the correspondences from both sides. The performance of the proposed method was evaluated through several experiments and the results demonstrate that it can offer highly acceptable pedestrian localization results in long-term tracking, with an error of only 0.56 m, without the need for dedicated infrastructures. PMID:29342123
Calibration of hydrological model with programme PEST
NASA Astrophysics Data System (ADS)
Brilly, Mitja; Vidmar, Andrej; Kryžanowski, Andrej; Bezak, Nejc; Šraj, Mojca
2016-04-01
PEST is tool based on minimization of an objective function related to the root mean square error between the model output and the measurement. We use "singular value decomposition", section of the PEST control file, and Tikhonov regularization method for successfully estimation of model parameters. The PEST sometimes failed if inverse problems were ill-posed, but (SVD) ensures that PEST maintains numerical stability. The choice of the initial guess for the initial parameter values is an important issue in the PEST and need expert knowledge. The flexible nature of the PEST software and its ability to be applied to whole catchments at once give results of calibration performed extremely well across high number of sub catchments. Use of parallel computing version of PEST called BeoPEST was successfully useful to speed up calibration process. BeoPEST employs smart slaves and point-to-point communications to transfer data between the master and slaves computers. The HBV-light model is a simple multi-tank-type model for simulating precipitation-runoff. It is conceptual balance model of catchment hydrology which simulates discharge using rainfall, temperature and estimates of potential evaporation. Version of HBV-light-CLI allows the user to run HBV-light from the command line. Input and results files are in XML form. This allows to easily connecting it with other applications such as pre and post-processing utilities and PEST itself. The procedure was applied on hydrological model of Savinja catchment (1852 km2) and consists of twenty one sub-catchments. Data are temporary processed on hourly basis.
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
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
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...
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.
Dynamic Human Body Modeling Using a Single RGB Camera.
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
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
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
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.
PharmDock: a pharmacophore-based docking program
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
Marginal space learning for efficient detection of 2D/3D anatomical structures in medical images.
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.
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.
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).
Towards Sustainability: A Guide for Colleges.
ERIC Educational Resources Information Center
Khan, Shirley Ali
This guide, which builds on the Further Education Development Agency's environmental, regional, and economic development initiatives, is intended to help further education (FE) colleges throughout the United Kingdom respond to the sustainable development challenges posed by the International Organization for Standardization's quality environmental…
Risks to aquatic organisms posed by human pharmaceutical use
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.
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.
The epidemiology of tuberculosis in the Pacific, 2000 to 2013
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
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
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
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.
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.
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.
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.
Corruption in the Middle East: Challenges Posed for the United States
2004-11-01
American exporters allegedly lost out on foreign deals because they are not allowed, under U.S. law, to pay bribes to foreign officials. For...American companies, the payment of bribes to foreign officials is a criminal act and, of course, the bribes paid cannot be deducted as costs for tax...Cost-reducing (to the briber) or benefit enhancing; • Briber-initiated or bribee -initiated; • Coercive or collusive; centralized or
47 CFR 27.1252 - Involuntary Relocation Procedures.
Code of Federal Regulations, 2011 CFR
2011-10-01
... agreement is reached during the mandatory negotiation period, an AWS licensee may initiate involuntary relocation procedures under the Commission's rules. AWS licensees are obligated to pay to relocate BRS systems to which the AWS system poses an interference problem. Under involuntary relocation, the BRS...
WHICH AIRBORNE CONTAMINANTS POSE THE GREATEST RISK TO WESTERN NATIONAL PARKS (USA)?
The Western Airborne Contaminants Assessment Project (WACAP) was initiated in 2002 by the National Park Service to determine if airborne contaminants where having an impact on remote western ecosystems. Multiple sample media (snow, water, sediment, fish and terrestrial vegetatio...
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)
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
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...
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
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...
Chen, Xinjian; Udupa, Jayaram K.; Alavi, Abass; Torigian, Drew A.
2013-01-01
Image segmentation methods may be classified into two categories: purely image based and model based. Each of these two classes has its own advantages and disadvantages. In this paper, we propose a novel synergistic combination of the image based graph-cut (GC) method with the model based ASM method to arrive at the GC-ASM method for medical image segmentation. A multi-object GC cost function is proposed which effectively integrates the ASM shape information into the GC framework. The proposed method consists of two phases: model building and segmentation. In the model building phase, the ASM model is built and the parameters of the GC are estimated. The segmentation phase consists of two main steps: initialization (recognition) and delineation. For initialization, an automatic method is proposed which estimates the pose (translation, orientation, and scale) of the model, and obtains a rough segmentation result which also provides the shape information for the GC method. For delineation, an iterative GC-ASM algorithm is proposed which performs finer delineation based on the initialization results. The proposed methods are implemented to operate on 2D images and evaluated on clinical chest CT, abdominal CT, and foot MRI data sets. The results show the following: (a) An overall delineation accuracy of TPVF > 96%, FPVF < 0.6% can be achieved via GC-ASM for different objects, modalities, and body regions. (b) GC-ASM improves over ASM in its accuracy and precision to search region. (c) GC-ASM requires far fewer landmarks (about 1/3 of ASM) than ASM. (d) GC-ASM achieves full automation in the segmentation step compared to GC which requires seed specification and improves on the accuracy of GC. (e) One disadvantage of GC-ASM is its increased computational expense owing to the iterative nature of the algorithm. PMID:23585712
Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A
2013-05-01
Image segmentation methods may be classified into two categories: purely image based and model based. Each of these two classes has its own advantages and disadvantages. In this paper, we propose a novel synergistic combination of the image based graph-cut (GC) method with the model based ASM method to arrive at the GC-ASM method for medical image segmentation. A multi-object GC cost function is proposed which effectively integrates the ASM shape information into the GC framework. The proposed method consists of two phases: model building and segmentation. In the model building phase, the ASM model is built and the parameters of the GC are estimated. The segmentation phase consists of two main steps: initialization (recognition) and delineation. For initialization, an automatic method is proposed which estimates the pose (translation, orientation, and scale) of the model, and obtains a rough segmentation result which also provides the shape information for the GC method. For delineation, an iterative GC-ASM algorithm is proposed which performs finer delineation based on the initialization results. The proposed methods are implemented to operate on 2D images and evaluated on clinical chest CT, abdominal CT, and foot MRI data sets. The results show the following: (a) An overall delineation accuracy of TPVF > 96%, FPVF < 0.6% can be achieved via GC-ASM for different objects, modalities, and body regions. (b) GC-ASM improves over ASM in its accuracy and precision to search region. (c) GC-ASM requires far fewer landmarks (about 1/3 of ASM) than ASM. (d) GC-ASM achieves full automation in the segmentation step compared to GC which requires seed specification and improves on the accuracy of GC. (e) One disadvantage of GC-ASM is its increased computational expense owing to the iterative nature of the algorithm.
Aperiodicity Correction for Rotor Tip Vortex Measurements
NASA Technical Reports Server (NTRS)
Ramasamy, Manikandan; Paetzel, Ryan; Bhagwat, Mahendra J.
2011-01-01
The initial roll-up of a tip vortex trailing from a model-scale, hovering rotor was measured using particle image velocimetry. The unique feature of the measurements was that a microscope was attached to the camera to allow much higher spatial resolution than hitherto possible. This also posed some unique challenges. In particular, the existing methodologies to correct for aperiodicity in the tip vortex locations could not be easily extended to the present measurements. The difficulty stemmed from the inability to accurately determine the vortex center, which is a prerequisite for the correction procedure. A new method is proposed for determining the vortex center, as well as the vortex core properties, using a least-squares fit approach. This approach has the obvious advantage that the properties are derived from not just a few points near the vortex core, but from a much larger area of flow measurements. Results clearly demonstrate the advantage in the form of reduced variation in the estimated core properties, and also the self-consistent results obtained using three different aperiodicity correction methods.
Transitioning to Zero Freshwater Withdrawal for Thermoelectric Generation
NASA Astrophysics Data System (ADS)
Macknick, J.; Tidwell, V. C.; Zemlick, K. M.; Sanchez, J.; Woldeyesus, T.
2013-12-01
The electricity sector is the largest withdrawer of freshwater in the United States. The primary demand for water from the electricity sector is for cooling thermoelectric power plants. Droughts and potential changes in water resources resulting from climate change pose important risks to thermoelectric power production in the United States. Power plants can minimize risk in a variety of ways. One method of reducing risk is to move away from dependency on freshwater resources. Here a scoping level analysis is performed to identify the technical tradeoffs and initial cost estimates for retrofitting all existing steam-powered generation to achieve zero freshwater withdrawal. Specifically, the conversion of existing freshwater-cooled plants to dry cooling or a wet cooling system utilizing non-potable water is considered. The least cost alternative is determined for each of the 1,178 freshwater using power plants in the United States. The use of non-potable water resources, such as municipal wastewater and shallow brackish groundwater, is considered based on the availability and proximity of those resources to the power plant, as well as the costs to transport and treat those resources to an acceptable level. The projected increase in levelized cost of electricity due to power plant retrofits ranges roughly from 0.20 to 20/MWh with a median value of 3.53/MWh. With a wholesale price of electricity running about 35/MWh, many retrofits could be accomplished at levels that would add less than 10% to current power plant generation expenses. Such retrofits could alleviate power plant vulnerabilities to thermal discharge limits in times of drought (particularly in the East) and would save 3.2 Mm3/d of freshwater consumption in watersheds with limited water availability (principally in the West). The estimated impact of retrofits on wastewater and brackish water supply is minimal requiring only a fraction of the available resource. Total parasitic energy requirements to achieve zero freshwater withdrawal are estimated at 140 million MWh or roughly 4.5% of the initial production from the retrofitted plants.
Fuel-optimal low-thrust formation reconfiguration via Radau pseudospectral method
NASA Astrophysics Data System (ADS)
Li, Jing
2016-07-01
This paper investigates fuel-optimal low-thrust formation reconfiguration near circular orbit. Based on the Clohessy-Wiltshire equations, first-order necessary optimality conditions are derived from the Pontryagin's maximum principle. The fuel-optimal impulsive solution is utilized to divide the low-thrust trajectory into thrust and coast arcs. By introducing the switching times as optimization variables, the fuel-optimal low-thrust formation reconfiguration is posed as a nonlinear programming problem (NLP) via direct transcription using multiple-phase Radau pseudospectral method (RPM), which is then solved by a sparse nonlinear optimization software SNOPT. To facilitate optimality verification and, if necessary, further refinement of the optimized solution of the NLP, formulas for mass costate estimation and initial costates scaling are presented. Numerical examples are given to show the application of the proposed optimization method. To fix the problem, generic fuel-optimal low-thrust formation reconfiguration can be simplified as reconfiguration without any initial and terminal coast arcs, whose optimal solutions can be efficiently obtained from the multiple-phase RPM at the cost of a slight fuel increment. Finally, influence of the specific impulse and maximum thrust magnitude on the fuel-optimal low-thrust formation reconfiguration is analyzed. Numerical results shown the links and differences between the fuel-optimal impulsive and low-thrust solutions.
A validated non-linear Kelvin-Helmholtz benchmark for numerical hydrodynamics
NASA Astrophysics Data System (ADS)
Lecoanet, D.; McCourt, M.; Quataert, E.; Burns, K. J.; Vasil, G. M.; Oishi, J. S.; Brown, B. P.; Stone, J. M.; O'Leary, R. M.
2016-02-01
The non-linear evolution of the Kelvin-Helmholtz instability is a popular test for code verification. To date, most Kelvin-Helmholtz problems discussed in the literature are ill-posed: they do not converge to any single solution with increasing resolution. This precludes comparisons among different codes and severely limits the utility of the Kelvin-Helmholtz instability as a test problem. The lack of a reference solution has led various authors to assert the accuracy of their simulations based on ad hoc proxies, e.g. the existence of small-scale structures. This paper proposes well-posed two-dimensional Kelvin-Helmholtz problems with smooth initial conditions and explicit diffusion. We show that in many cases numerical errors/noise can seed spurious small-scale structure in Kelvin-Helmholtz problems. We demonstrate convergence to a reference solution using both ATHENA, a Godunov code, and DEDALUS, a pseudo-spectral code. Problems with constant initial density throughout the domain are relatively straightforward for both codes. However, problems with an initial density jump (which are the norm in astrophysical systems) exhibit rich behaviour and are more computationally challenging. In the latter case, ATHENA simulations are prone to an instability of the inner rolled-up vortex; this instability is seeded by grid-scale errors introduced by the algorithm, and disappears as resolution increases. Both ATHENA and DEDALUS exhibit late-time chaos. Inviscid simulations are riddled with extremely vigorous secondary instabilities which induce more mixing than simulations with explicit diffusion. Our results highlight the importance of running well-posed test problems with demonstrated convergence to a reference solution. To facilitate future comparisons, we include as supplementary material the resolved, converged solutions to the Kelvin-Helmholtz problems in this paper in machine-readable form.
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
Huang, Hung-Jin; Chen, Hsin-Yi; Lee, Cheng-Chun
2014-01-01
Apolipoprotein E4 (Apo E4) is the major genetic risk factor in the causation of Alzheimer's disease (AD). In this study we utilize virtual screening of the world's largest traditional Chinese medicine (TCM) database and investigate potential compounds for the inhibition of ApoE4. We present the top three TCM candidates: Solapalmitine, Isodesacetyluvaricin, and Budmunchiamine L5 for further investigation. Dynamics analysis and molecular dynamics (MD) simulation were used to simulate protein-ligand complexes for observing the interactions and protein variations. Budmunchiamine L5 did not have the highest score from virtual screening; however, the dynamics pose is similar to the initial docking pose after MD simulation. Trajectory analysis reveals that Budmunchiamine L5 was stable over all simulation times. The migration distance of Budmunchiamine L5 illustrates that docked ligands are not variable from the initial docked site. Interestingly, Arg158 was observed to form H-bonds with Budmunchiamine L5 in the docking pose and MD snapshot, which indicates that the TCM compounds could stably bind to ApoE4. Our results show that Budmunchiamine L5 has good absorption, blood brain barrier (BBB) penetration, and less toxicity according to absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction and could, therefore, be safely used for developing novel ApoE4 inhibitors. PMID:24967370
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.
Time-Domain Impedance Boundary Conditions for Computational Aeroacoustics
NASA Technical Reports Server (NTRS)
Tam, Christopher K. W.; Auriault, Laurent
1996-01-01
It is an accepted practice in aeroacoustics to characterize the properties of an acoustically treated surface by a quantity known as impedance. Impedance is a complex quantity. As such, it is designed primarily for frequency-domain analysis. Time-domain boundary conditions that are the equivalent of the frequency-domain impedance boundary condition are proposed. Both single frequency and model broadband time-domain impedance boundary conditions are provided. It is shown that the proposed boundary conditions, together with the linearized Euler equations, form well-posed initial boundary value problems. Unlike ill-posed problems, they are free from spurious instabilities that would render time-marching computational solutions impossible.
DOT National Transportation Integrated Search
2016-12-01
Several states have legalized recreational cannabis use, : and more are considering legalization. Increased use of : cannabis among drivers may pose a barrier to achieving : the National Toward Zero Deaths (TZD) initiative. The : transformation of tr...
Non-intrusive head movement analysis of videotaped seizures of epileptic origin.
Mandal, Bappaditya; Eng, How-Lung; Lu, Haiping; Chan, Derrick W S; Ng, Yen-Ling
2012-01-01
In this work we propose a non-intrusive video analytic system for patient's body parts movement analysis in Epilepsy Monitoring Unit. The system utilizes skin color modeling, head/face pose template matching and face detection to analyze and quantify the head movements. Epileptic patients' heads are analyzed holistically to infer seizure and normal random movements. The patient does not require to wear any special clothing, markers or sensors, hence it is totally non-intrusive. The user initializes the person-specific skin color and selects few face/head poses in the initial few frames. The system then tracks the head/face and extracts spatio-temporal features. Support vector machines are then used on these features to classify seizure-like movements from normal random movements. Experiments are performed on numerous long hour video sequences captured in an Epilepsy Monitoring Unit at a local hospital. The results demonstrate the feasibility of the proposed system in pediatric epilepsy monitoring and seizure detection.
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)
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
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.
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.
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.
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
Nonuniform dependence on initial data for compressible gas dynamics: The periodic Cauchy problem
NASA Astrophysics Data System (ADS)
Keyfitz, B. L.; Tığlay, F.
2017-11-01
We start with the classic result that the Cauchy problem for ideal compressible gas dynamics is locally well posed in time in the sense of Hadamard; there is a unique solution that depends continuously on initial data in Sobolev space Hs for s > d / 2 + 1 where d is the space dimension. We prove that the data to solution map for periodic data in two dimensions although continuous is not uniformly continuous.
Recommendations for control of East african sleeping sickness in Uganda.
Kotlyar, Simon
2010-01-01
East African sleeping sickness, caused by Trypanosoma brucei rhodesiense, is prominent in Uganda and poses a serious public health challenge in the region. This publication attempts to provide key components for designing a strategy for a nationwide initiative to provide insecticide-treatment of the animal reservoir to control T. b. rhodesiense. The contents of this article will focus on insecticide-based vector control strategies, monitoring and evaluation framework, and knowledge gaps required for future initiatives.
An Initial Look at DoD’s Activities Toward Climate Change Resiliency: An Annotated Bibliography
2016-02-01
Draft Working Paper An Initial Look at DoD’s Activities Toward Climate Change Resiliency An Annotated Bibliography Susan A. Resetar and Neil Berg...contribute www.rand.org iii Preface The global effects of climate change could have widespread effects and thus pose concerns for all governments...effects and consider possible responses. Many elements of the Department have taken steps to begin dealing with the implications of climate change
Unanticipated potential cancer risk near metal recycling facilities
DOE Office of Scientific and Technical Information (OSTI.GOV)
Raun, Loren, E-mail: raun@rice.edu; Pepple, Karl, E-mail: pepple.karl@epa.gov; Hoyt, Daniel, E-mail: hoyt.daniel@epa.gov
2013-07-15
Metal recycling is an important growing industry. Prior to this study, area sources consisting of metal recycling facilities fell in a category of limited regulatory scrutiny because of assumed low levels of annual emissions. Initiating with community complaints of nuisance from smoke, dust and odor, the Houston Department of Health and Human Services (HDHHS) began a monitoring program outside metal recycler facilities and found metal particulates in outdoor ambient air at levels which could pose a carcinogenic human health risk. In a study of five similar metal recycler facilities which used a torch cutting process, air downwind and outside themore » facility was sampled for eight hours between 6 and 10 times each over 18 months using a mobile laboratory. Ten background locations were also sampled. Iron, manganese, copper, chromium, nickel, lead, cobalt, cadmium and mercury were detected downwind of the metal recyclers at frequencies ranging from 100% of the time for iron to 2% of the time for mercury. Of these metals, chromium, nickel, lead, cobalt, cadmium and mercury were not detected in any sample in the background. Two pairs of samples were analyzed for total chromium and hexavalent chromium to establish a ratio of the fraction of hexavalent chromium in total chromium. This fraction was used to estimate hexavalent chromium at all locations. The carcinogenic risk posed to a residential receptor from metal particulate matter concentrations in the ambient air attributed to the metal recyclers was estimated from each of the five facilities in an effort to rank the importance of this source and inform the need for further investigation. The total risk from these area sources ranged from an increased cancer risk of 1 in 1,000,000 to 6 in 10,000 using the 95th upper confidence limit of the mean of the carcinogenic metal particulate matter concentration, assuming the point of the exposure is the sample location for a residential receptor after accounting for wind direction and the number of shifts that could operate a year. Further study is warranted to better understand the metal air pollution levels in the community and if necessary, to evaluate the feasibility of emission controls and identify operational improvements and best management practices for this industry. This research adds two new aspects to the literature: identification of types and magnitude of metal particulate matter air pollutants associated with a previously unrecognized area source, metal recyclers and their potential risk to health. -- Highlights: • Air monitoring study in response to community complaints found metal contamination. • Metal recyclers found to potentially pose cancer from metal particulates • Chromium, nickel, cobalt and cadmium samples were detected in five metal recyclers. • These metals were not detected in background air samples. • Estimated increased cancer risk ranges from 1 in 1,000,000 to 8 in 10,000.« less
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.
Three-dimensional deformable-model-based localization and recognition of road vehicles.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gisler, Galen R.; Weaver, R. P.; Mader, Charles L.
Kick-em Jenny, in the Eastern Caribbean, is a submerged volcanic cone that has erupted a dozen or more times since its discovery in 1939. The most likely hazard posed by this volcano is to shipping in the immediate vicinity (through volcanic missiles or loss-of-buoyancy), but it is of interest to estimate upper limits on tsunamis that might be produced by a catastrophic explosive eruption. To this end, we have performed two-dimensional simulations of such an event in a geometry resembling that of Kick-em Jenny with our SAGE adaptive mesh Eulerian multifluid compressible hydrocode. We use realistic equations of state formore » air, water, and basalt, and follow the event from the initial explosive eruption, through the generation of a transient water cavity and the propagation of waves away from the site. We find that even for extremely catastrophic explosive eruptions, tsunamis from Kick-em Jenny are unlikely to pose significant danger to nearby islands. For comparison, we have also performed simulations of explosive eruptions at the much larger shield volcano Vailuluu in the Samoan chain, where the greater energy available can produce a more impressive wave. In general, however, we conclude that explosive eruptions do not couple well to water waves. The waves that are produced from such events are turbulent and highly dissipative, and don't propagate well. This is consistent with what we have found previously in simulations of asteroid-impact generated tsunamis. Non-explosive events, however, such as landslides or gas hydrate releases, do couple well to waves, and our simulations of tsunamis generated by subaerial and sub-aqueous landslides demonstrate this.« less
Against Laplacian Reduction of Newtonian Mass to Spatiotemporal Quantities
NASA Astrophysics Data System (ADS)
Martens, Niels C. M.
2018-05-01
Laplace wondered about the minimal choice of initial variables and parameters corresponding to a well-posed initial value problem. Discussions of Laplace's problem in the literature have focused on choosing between spatiotemporal variables relative to absolute space (i.e. substantivalism) or merely relative to other material bodies (i.e. relationalism) and between absolute masses (i.e. absolutism) or merely mass ratios (i.e. comparativism). This paper extends these discussions of Laplace's problem, in the context of Newtonian Gravity, by asking whether mass needs to be included in the initial state at all, or whether a purely spatiotemporal initial state suffices. It is argued that mass indeed needs to be included; removing mass from the initial state drastically reduces the predictive and explanatory power of Newtonian Gravity.
Against Laplacian Reduction of Newtonian Mass to Spatiotemporal Quantities
NASA Astrophysics Data System (ADS)
Martens, Niels C. M.
2018-03-01
Laplace wondered about the minimal choice of initial variables and parameters corresponding to a well-posed initial value problem. Discussions of Laplace's problem in the literature have focused on choosing between spatiotemporal variables relative to absolute space (i.e. substantivalism) or merely relative to other material bodies (i.e. relationalism) and between absolute masses (i.e. absolutism) or merely mass ratios (i.e. comparativism). This paper extends these discussions of Laplace's problem, in the context of Newtonian Gravity, by asking whether mass needs to be included in the initial state at all, or whether a purely spatiotemporal initial state suffices. It is argued that mass indeed needs to be included; removing mass from the initial state drastically reduces the predictive and explanatory power of Newtonian Gravity.
Surgical intervention of complex endo-perio lesions.
Adcock, John E; Bright, David
2007-08-01
Complex endo-perio lesions are infrequent, but pose treatment dilemmas. The lesions are complex with bone loss involving adjacent teeth that are not part of the initial endodontic lesion. The aggressive bone loss is not clearly understood and apparently has some differences from the usual apical periodontitis.
Ask Questions to Encourage Questions Asked
ERIC Educational Resources Information Center
belcastro, sarah-marie
2017-01-01
We delineate some types of structured practice (modeling, requests, feedback, and space-making) that help students learn to pose appropriate questions and to initiate exploration of those questions. Developing skills requires practice, so we suggest ways to embed structured practice into existing class sessions. Including structured practice is…
Attracting Preservice Teachers to Remote Locations
ERIC Educational Resources Information Center
Young, Kenneth D.; Grainger, Peter; James, Dennis
2018-01-01
Teaching in rural/remote regions poses many challenges to teachers and is identified as a priority research area by the state government. Despite initiatives by the Queensland state government and university providers to solve the issue through various incentives designed to attract teachers, the problem remains significant. This research…
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
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...
Using Elicited Choice Probabilities in Hypothetical Elections to Study Decisions to Vote
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
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.
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.
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.
Cauchy problem in spacetimes with closed timelike curves
NASA Astrophysics Data System (ADS)
Friedman, John; Morris, Michael S.; Novikov, Igor D.; Echeverria, Fernando; Klinkhammer, Gunnar; Thorne, Kip S.; Yurtsever, Ulvi
1990-09-01
The laws of physics might permit the existence, in the real Universe, of closed timelike curves (CTC's). Macroscopic CTC's might be a semiclassical consequence of Planck-scale, quantum gravitational, Lorentzian foam, if such foam exists. If CTC's are permitted, then the semiclassical laws of physics (the laws with gravity classical and other fields quantized or classical) should be augmented by a principle of self-consistency, which states that a local solution to the equations of physics can occur in the real Universe only if it can be extended to be part of a global solution, one which is well defined throughout the (nonsingular regions of) classical spacetime. The consequences of this principle are explored for the Cauchy problem of the evolution of a classical, massless scalar field Φ (satisfying □Φ=0) in several model spacetimes with CTC's. In general, self-consistency constrains the initial data for the field Φ. For a family of spacetimes with traversible wormholes, which initially possess no CTC's and then evolve them to the future of a stable Cauchy horizon scrH, self-consistency seems to place no constraints on initial data for Φ that are posed on past null infinity, and none on data posed on spacelike slices which precede scrH. By contrast, initial data posed in the future of scrH, where the CTC's reside, are constrained; but the constraints appear to be mild in the sense that in some neighborhood of every event one is free to specify initial data arbitrarily, with the initial data elsewhere being adjusted to guarantee self-consistent evolution. A spacetime whose self-consistency constraints have this property is defined to be ``benign with respect to the scalar field Φ.'' The question is posed as to whether benign spacetimes in some sense form a generic subset of all spacetimes with CTC's. It is shown that in the set of flat, spatially and temporally closed, 2-dimensional spacetimes the benign ones are not generic. However, it seems likely that every 4-dimensional, asymptotically flat space-time that is stable and has a topology of the form R×(S-one point), where S is a closed 3-manifold, is benign. Wormhole spacetimes are of this type, with S=S1×S2. We suspect that these types of self-consistency behavior of the scalar field Φ are typical for noninteracting (linearly superposing), classical fields. However, interacting classical systems can behave quite differently, as is demonstrated by a study of the motion of a hard-sphere billiard ball in a wormhole spacetime with closed timelike curves: If the ball is classical, then some choices of initial data (some values of the ball's initial position and velocity) give rise to unique, self-consistent motions of the ball; other choices produce two different self-consistent motions; and others might (but we are not yet sure) produce no self-consistent motions whatsoever. By contrast, in a path-integral formulation of the nonrelativistic quantum mechanics of such a billiard ball, there appears to be a unique, self-consistent set of probabilities for the outcomes of all measurements. This paper's conclusion, that CTC's may not be as nasty as people have assumed, is reinforced by the fact that they do not affect Gauss's theorem and thus do not affect the derivation of global conservation laws from differential ones. The standard conservation laws remain valid globally, and in asymptotically flat, wormhole spacetimes they retain a natural, quasilocal interpretation.
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.
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
Vision Assisted Navigation for Miniature Unmanned Aerial Vehicles (MAVs)
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.
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.
NASA Astrophysics Data System (ADS)
Harper, Kathleen A.; Etkina, Eugenia
2002-10-01
As part of weekly reports,1 structured journals in which students answer three standard questions each week, they respond to the prompt, If I were the instructor, what questions would I ask or problems assign to determine if my students understood the material? An initial analysis of the results shows that some student-generated problems indicate fundamental misunderstandings of basic physical concepts. A further investigation explores the relevance of the problems to the week's material, whether the problems are solvable, and the type of problems (conceptual or calculation-based) written. Also, possible links between various characteristics of the problems and conceptual achievement are being explored. The results of this study spark many more questions for further work. A summary of current findings will be presented, along with its relationship to previous work concerning problem posing.2 1Etkina, E. Weekly Reports;A Two-Way Feedback Tool, Science Education, 84, 594-605 (2000). 2Mestre, J.P., Probing Adults Conceptual Understanding and Transfer of Learning Via Problem Posing, Journal of Applied Developmental Psychology, 23, 9-50 (2002).
Modeling in Real Time During the Ebola Response.
Meltzer, Martin I; Santibanez, Scott; Fischer, Leah S; Merlin, Toby L; Adhikari, Bishwa B; Atkins, Charisma Y; Campbell, Caresse; Fung, Isaac Chun-Hai; Gambhir, Manoj; Gift, Thomas; Greening, Bradford; Gu, Weidong; Jacobson, Evin U; Kahn, Emily B; Carias, Cristina; Nerlander, Lina; Rainisch, Gabriel; Shankar, Manjunath; Wong, Karen; Washington, Michael L
2016-07-08
To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html).
NASA Technical Reports Server (NTRS)
Entekhabi, Dara; Bras, Rafael L.; McLaughlin, Dennis B.; Asrar, Ghassem R.; Wei, Ying; Betts, Alan K.; Beven, Keith J.; Duffy, Christopher J.; Dunne, Thomas; Koster, Randall D.;
1998-01-01
An agenda for land-surface hydrology research is proposed to open the debate for more comprehensive prioritization of science and application activities in the hydrologic sciences. A set of science questions are posed and the observational requirements to achieve substantial progress are identified. In this context, the proposal to initiate the 2nd International Hydrologic Decade (IHD) is put forth. The benefits of this initiative for enhanced scientific understanding and improved capability in meeting societal needs are also identified.
A physical approach to the numerical treatment of boundaries in gas dynamics
NASA Technical Reports Server (NTRS)
Moretti, G.
1981-01-01
Two types of boundaries are considered: rigid walls, and artificial (open) boundaries which were arbitrarily drawn somewhere across a wider flow field. A set of partial differential equations (typically, the Euler equations) has an infinite number of solutions, each one defined by a set of initial and boundary conditions. The initial conditions remaining the same, any change in the boundary conditions will produce a new solution. To pose the problem well, a necessary and sufficient number of boundary conditions are prescribed.
Characterizing SHP2 as a Novel Therapeutic Target in Breast Cancer
2012-02-01
50(12), 2339-56. doi:10.1021/bi1014453 Zhang, X., He, Y., Liu, S., Yu, Z., Jiang, Z. X., Yang, Z., Dong, Y., et al. (2010). Salicylic Acid Based...Overall, what we have found so far has been surprising, with the data suggesting that the presence of a -2 acidic residue in the substrate peptide...helped to refine the initial docking poses, with the initial hypothesis being that the pY -1 and -4 position acidic amino acids will bind a pair of
Initial flight qualification and operational maintenance of X-29A flight software
NASA Technical Reports Server (NTRS)
Earls, Michael R.; Sitz, Joel R.
1989-01-01
A discussion is presented of some significant aspects of the initial flight qualification and operational maintenance of the flight control system softward for the X-29A technology demonstrator. Flight qualification and maintenance of complex, embedded flight control system software poses unique problems. The X-29A technology demonstrator aircraft has a digital flight control system which incorporates functions generally considered too complex for analog systems. Organizational responsibilities, software assurance issues, tools, and facilities are discussed.
Adolescents' Perceptions of Alcohol
ERIC Educational Resources Information Center
Roy, Amit; Ikonen, Risto; Keinonen, Tuula; Kumar, Kuldeep
2017-01-01
Purpose: Rising trends in alcohol consumption and early drinking initiation pose serious health risks especially for adolescents. Learner's prior knowledge about alcohol gained from the social surroundings and the media are important sources that can impact the learning outcomes in health education. The purpose of this paper is to map adolescents'…
2011 National Drug Control Strategy. Executive Summary
ERIC Educational Resources Information Center
Office of National Drug Control Policy, 2011
2011-01-01
In May of 2010, President Obama released the Administration's inaugural "National Drug Control Strategy", a comprehensive approach to combat the public health and safety consequences posed by drug use. Now, a year later, the Administration is releasing its update building upon that initial "Strategy". The "Strategy" establishes ambitious goals to…
After Access: Canadian Education and Copyright Reform
ERIC Educational Resources Information Center
Geist, Michael
2006-01-01
With the dramatic growth of the Internet in the 1990s, the Canadian government developed a well-regarded strategy for addressing the emerging issues posed by the "information highway." The strategy featured legal reforms to address privacy and e-commerce, administrative reforms for the government online initiative, and connectivity…
Youth, Terrorism and Education: Britain's Prevent Programme
ERIC Educational Resources Information Center
Thomas, Paul
2016-01-01
Since the 7/7 bombings of July 2005, Britain has experienced a domestic terror threat posed by a small minority of young Muslims. In response, Britain has initiated "Prevent," a preventative counter-terrorism programme. Building on previous, general critiques of Prevent, this article outlines and critically discusses the ways in which…
New Mexico Adolescent Health Risks Survey.
ERIC Educational Resources Information Center
Antle, David
To inform students of health risks (posed by behavior, environment, and genetics) and provide schools with collective risk appraisal information as a basis for planning/evaluating health and wellness initiatives, New Mexico administered the Teen Wellness Check in 1985 to 1,573 ninth-grade students from 7 New Mexico public schools. Subjects were…
ERIC Educational Resources Information Center
Graue, Elizabeth; Ryan, Sharon; Wilinski, Bethany; Northey, Kaitlin; Nocera, Amato
2018-01-01
Background/Context: Early childhood education joined the standards movement in 2002 with the Good Start, Grow Smart initiative (Brown, 2007), with advocates arguing that standards were a tool for creating more continuity and coherence in PreK systems (Bowman, 2006; Kagan 2012). Critics posed concerns about a perceived poor fit between…
ERIC Educational Resources Information Center
Russell, R. Alan
2011-01-01
A question posed by a teacher can often serve as an effective and engaging way to start a class. Sometimes, however, interesting questions arise from comments made by students. The investigation presented in this article arose from a student's very simple question: "Is there a perfect rectangle for folding origami?" The initial investigation was…
ERIC Educational Resources Information Center
Allen, Kasi C.
2013-01-01
In line with the Common Core and Standards for Mathematical Practice that portray a classroom where students are engaged in problem-solving experiences, and where various tools and arguments are employed to grow their strategic thinking, this article is the story of such a student-initiated problem. A seemingly simple question was posed by…
Fiducial Marker Detection and Pose Estimation From LIDAR Range Data
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
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...
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.
A well-posed numerical method to track isolated conformal map singularities in Hele-Shaw flow
NASA Technical Reports Server (NTRS)
Baker, Gregory; Siegel, Michael; Tanveer, Saleh
1995-01-01
We present a new numerical method for calculating an evolving 2D Hele-Shaw interface when surface tension effects are neglected. In the case where the flow is directed from the less viscous fluid into the more viscous fluid, the motion of the interface is ill-posed; small deviations in the initial condition will produce significant changes in the ensuing motion. This situation is disastrous for numerical computation, as small round-off errors can quickly lead to large inaccuracies in the computed solution. Our method of computation is most easily formulated using a conformal map from the fluid domain into a unit disk. The method relies on analytically continuing the initial data and equations of motion into the region exterior to the disk, where the evolution problem becomes well-posed. The equations are then numerically solved in the extended domain. The presence of singularities in the conformal map outside of the disk introduces specific structures along the fluid interface. Our method can explicitly track the location of isolated pole and branch point singularities, allowing us to draw connections between the development of interfacial patterns and the motion of singularities as they approach the unit disk. In particular, we are able to relate physical features such as finger shape, side-branch formation, and competition between fingers to the nature and location of the singularities. The usefulness of this method in studying the formation of topological singularities (self-intersections of the interface) is also pointed out.
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
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
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
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
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.
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
NASA Astrophysics Data System (ADS)
Bona, J. L.; Chen, M.; Saut, J.-C.
2004-05-01
In part I of this work (Bona J L, Chen M and Saut J-C 2002 Boussinesq equations and other systems for small-amplitude long waves in nonlinear dispersive media I: Derivation and the linear theory J. Nonlinear Sci. 12 283-318), a four-parameter family of Boussinesq systems was derived to describe the propagation of surface water waves. Similar systems are expected to arise in other physical settings where the dominant aspects of propagation are a balance between the nonlinear effects of convection and the linear effects of frequency dispersion. In addition to deriving these systems, we determined in part I exactly which of them are linearly well posed in various natural function classes. It was argued that linear well-posedness is a natural necessary requirement for the possible physical relevance of the model in question. In this paper, it is shown that the first-order correct models that are linearly well posed are in fact locally nonlinearly well posed. Moreover, in certain specific cases, global well-posedness is established for physically relevant initial data. In part I, higher-order correct models were also derived. A preliminary analysis of a promising subclass of these models shows them to be well posed.
Human action recognition based on kinematic similarity in real time
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
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.
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.
A Donor-Focused Fundraising Model: An Essential Tool in Community College Foundations' Toolkit
ERIC Educational Resources Information Center
Carter, Linnie S.
2011-01-01
The increased focus on private fundraising poses challenges for community colleges (Jackson & Glass, 2000). A challenge is a lack of fundraising experience within community colleges and their foundations. There now exists a donor-focused fundraising model for community colleges to use to enhance their fundraising initiatives and increase the…
DOT National Transportation Integrated Search
2009-07-01
In 2008, the Federal Motor Carrier Safety Administration (FMCSA) reports that there were about 300 fatalities from bus crashes in the United States. Although bus crashes are relatively rare, they are particularly deadly since many individuals may be ...
22 CFR 303.8 - Requests for records.
Code of Federal Regulations, 2010 CFR
2010-04-01
... treatment could reasonably be expected to pose an imminent threat to the life or physical safety of an... affect public confidence. (2) A request for expedited processing may be made at the time of the initial... Officer shall decide whether to grant the request and shall notify the requester of the decision. If a...
ERIC Educational Resources Information Center
Hourigan, Mairéad; Leavy, Aisling M.
2017-01-01
Teacher knowledge is a critical focus of educational research in light of the potential impact of teacher knowledge on student learning. The dearth of research exploring entry-level preservice teachers' geometric knowledge poses an onerous challenge for mathematics educators in initial teacher education (ITE) when designing experiences that…
ERIC Educational Resources Information Center
Hidalgo, Cecilia
2016-01-01
Interdisciplinarity and knowledge networking are at the core of current global, regional, and national initiatives concerning climate. Both scientifc knowledge and public participation are essential to enhance the capacity of different sectors and governments to respond to challenges posed by climate variability and change. Exchange and bridge…
The Forest Indians in the Present Political Situation of Peru.
ERIC Educational Resources Information Center
Varese, Stefano
The article focuses on tribal minorities (American Indians) of the Peruvian tropical forest from the point of view of the political circumstances and the general administrative conditions of the country. In 1968 the revolutionary military government initiated a series of structural reforms which aimed at transforming Peru. This article poses and…
College Retention Initiatives Meeting the Needs of Millennial Freshman Students
ERIC Educational Resources Information Center
Turner, Patrick; Thompson, Elizabeth
2014-01-01
The qualitative study explored the opinions and perceptions of freshman, sophomores, and freshman students that dropped out of the university to understand the obstacles and enablers that millennial freshmen faced transitioning into a college environment. To understand these factors the study posed the question, how do the participants (i.e.,…
The Evolution of a Community Drug Abuse Program: Families Have a Critical Role.
ERIC Educational Resources Information Center
Hyland, Timothy F.; Schrenker, Robert J.
This description of the Merrillville Substance Abuse Program initially reviews the problems that student drug abuse poses for school administrators. A community needs assessment is described and the evolution of a developmental drug education program is presented. Educational strategies targeted to parents, teachers, and students are discussed,…
USDA-ARS?s Scientific Manuscript database
Climate change poses challenges for northern México and the southern United States, including drought, extreme heat, and flooding. To aid society in preparing for climate- and weather-related risks, partners in the North American Climate Services Partnership have initiated several collaborations. Th...
21 CFR 1401.6 - Expedited process.
Code of Federal Regulations, 2011 CFR
2011-04-01
.... (b) A request for expedited processing may be made at the time of the initial request for records or at a later time. (c) A requester who seeks expedited processing must submit a statement, certified to...) The lack of expedited treatment could reasonably be expected to pose an imminent threat to the life or...
21 CFR 1401.6 - Expedited process.
Code of Federal Regulations, 2010 CFR
2010-04-01
.... (b) A request for expedited processing may be made at the time of the initial request for records or at a later time. (c) A requester who seeks expedited processing must submit a statement, certified to...) The lack of expedited treatment could reasonably be expected to pose an imminent threat to the life or...
Epidemic typhus imported from Algeria.
Niang, M; Brouqui, P; Raoult, D
1999-01-01
We report epidemic typhus in a French patient returning from Algeria. The diagnosis was confirmed by serologic testing and the isolation of Rickettsia prowazekii in blood. Initially the patient was thought to have typhoid fever. Because body lice are prevalent in industrialized regions, the introduction of typhus to pediculosis-endemic areas poses a serious public health risk.
Building Systems for Evaluation of Teachers Poses Challenge
ERIC Educational Resources Information Center
Sawchuk, Stephen
2011-01-01
Rounding the corner on the design of new teacher-evaluation plans, states and districts are beginning to wrestle with the significant technical and logistical hurdles for transforming their blueprints into reality. In the coming months, more states--especially those that won grants through the $4 billion federal Race to the Top initiative--are…
ERIC Educational Resources Information Center
Cohen, Jeremy
2010-01-01
Even in an industry where rapid change is the status quo, it takes a special kind of company to handle the training challenges posed by a major corporate acquisition and massive product rollout. No one has ever accused Verizon of thinking small-scale when it comes to training initiatives, but over the last year, the telecommunications giant…
ERIC Educational Resources Information Center
Duggan, James R.
2014-01-01
The article engages with the opportunities and constraints raised by embedded research during times of rapid and extensive organisational change. Embedded research is an increasingly common approach for funding PhD studentships. The rapid and extensive reforms of the English public sector pose significant and underexplored challenges for embedded…
Hurtado, Carlos; Domínguez, Carmen; Pérez-Babace, Lorea; Cañameras, Núria; Comas, Jordi; Bayona, Josep M
2016-03-15
The widespread distribution of emerging organic contaminants (EOCs) in the water cycle can lead to their incorporation in irrigated crops, posing a potential risk for human consumption. To gain further insight into the processes controlling the uptake of organic microcontaminants, Batavia lettuce (Lactuca sativa) grown under controlled conditions was watered with EOCs (e.g., non-steroidal anti-inflammatories, sulfonamides, β-blockers, phenolic estrogens, anticonvulsants, stimulants, polycyclic musks, biocides) at different concentrations (0-40μgL(-1)). Linear correlations were obtained between the EOC concentrations in the roots and leaves and the watering concentrations for most of the contaminants investigated. However, large differences were found in the root concentration factors ( [Formula: see text] =0.27-733) and leaf translocation concentration factors ( [Formula: see text] =0-3) depending on the persistence of the target contaminants in the rhizosphere and the specific physicochemical properties of each one. With the obtained dataset, a simple predictive model based on a linear regression and the root bioconcentration and translocation factors can be used to estimate the concentration of the target EOCs in leaves based on the dose supplied in the irrigation water or the soil concentration. Finally, enantiomeric fractionation of racemic ibuprofen from the initial spiking mixture suggests that biodegradation mainly occurs in the rhizosphere. Copyright © 2015 Elsevier B.V. All rights reserved.
Miodovnik, Amir; Landrigan, Philip J.
2009-01-01
Background Following a recent report of lead in certain commercial vitamin products, the U.S. Food and Drug Administration (FDA) conducted a nationwide survey to determine the Pb content in 324 multivitamin/mineral products labeled for use by women and children. The FDA compared estimated Pb exposures from each product with safe/tolerable exposure levels, termed provisional total tolerable intake (PTTI) levels, previously developed for at-risk population groups in 1992. Objective We investigated the FDA’s conclusions that Pb concentrations in all vitamin products examined do not pose a hazard to health because they are below the PTTI levels for all groups considered. Discussion For their initial estimations of PTTI levels, the FDA used a blood lead level (BLL) of 10 μg/dL as the threshold for adverse effects in children and in pregnant or lactating women. Studies have repeatedly linked chronic exposure to BLLs < 10 μg/dL with impairments in cognitive function and behavior in young children despite the absence of overt signs of toxicity. The FDA analysis also omitted any consideration of nonfood sources of Pb exposure, which is inconsistent with our current understanding of how most children develop elevated BLLs. Conclusion We feel that based on these oversights, the FDA’s conclusions are unduly reassuring and that reconsideration of their current recommendations appears warranted. PMID:19654907
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.
NASA Astrophysics Data System (ADS)
Winicour, Jeffrey
2017-08-01
An algebraic-hyperbolic method for solving the Hamiltonian and momentum constraints has recently been shown to be well posed for general nonlinear perturbations of the initial data for a Schwarzschild black hole. This is a new approach to solving the constraints of Einstein’s equations which does not involve elliptic equations and has potential importance for the construction of binary black hole data. In order to shed light on the underpinnings of this approach, we consider its application to obtain solutions of the constraints for linearized perturbations of Minkowski space. In that case, we find the surprising result that there are no suitable Cauchy hypersurfaces in Minkowski space for which the linearized algebraic-hyperbolic constraint problem is well posed.
Neumann, M; Cuvillon, L; Breton, E; de Matheli, M
2013-01-01
Recently, a workflow for magnetic resonance (MR) image plane alignment based on tracking in real-time MR images was introduced. The workflow is based on a tracking device composed of 2 resonant micro-coils and a passive marker, and allows for tracking of the passive marker in clinical real-time images and automatic (re-)initialization using the microcoils. As the Kalman filter has proven its benefit as an estimator and predictor, it is well suited for use in tracking applications. In this paper, a Kalman filter is integrated in the previously developed workflow in order to predict position and orientation of the tracking device. Measurement noise covariances of the Kalman filter are dynamically changed in order to take into account that, according to the image plane orientation, only a subset of the 3D pose components is available. The improved tracking performance of the Kalman extended workflow could be quantified in simulation results. Also, a first experiment in the MRI scanner was performed but without quantitative results yet.
Pittalis, Silvia; Fusco, Francesco Maria; Lanini, Simone; Nisii, Carla; Puro, Vincenzo; Lauria, Francesco Nicola; Ippolito, Giuseppe
2009-10-01
Viral haemorrhagic fevers (VHFs) represent a challenge for public health because of their epidemic potential, and their possible use as bioterrorism agents poses particular concern. In 1999 the World Health Organization (WHO) proposed a case definition for VHFs, subsequently adopted by other international institutions with the aim of early detection of initial cases/outbreaks in western countries. We applied this case definition to reports of Ebola and Marburg virus infections to estimate its sensitivity to detect cases of the disease. We analyzed clinical descriptions of 795 reported cases of Ebola haemorrhagic fever: only 58.5% of patients met the proposed case definition. A similar figure was obtained reviewing 169 cases of Marburg diseases, of which only 64.5% were in accordance with the case definition. In conclusion, the WHO case definition for hemorrhagic fevers is too specific and has poor sensitivity both for case finding during Ebola or Marburg outbreaks, and for early detection of suspected cases in western countries. It can lead to a hazardous number of false negatives and its use should be discouraged for early detection of cases.
Zhang, Yong; Zhang, Fan; Zhu, Shuangli; Chen, Li; Yan, Dongmei; Wang, Dongyan; Tang, Ruiyan; Zhu, Hui; Hou, Xiaohui; An, Hongqiu; Zhang, Hong; Xu, Wenbo
2010-02-01
A type 2 vaccine-related poliovirus (strain CHN3024), differing from the Sabin 2 strain by 0.44% in the VP1 coding region was isolated from a patient with vaccine-associated paralytic poliomyelitis. Sequences downstream of nucleotide position 6735 (3D(pol) coding region) were derived from an unidentified sequence; no close match for a potential parent was found, but it could be classified into a non-polio human enteroviruses species C (HEV-C) phylogeny. The virus differed antigenically from the parental Sabin strain, having an amino acid substitution in the neutralizing antigenic site 1. The similarity between CHN3024 and Sabin 2 sequences suggests that the recombination was recent; this is supported by the estimation that the initiating OPV dose was given only 36-75 days before sampling. The patient's clinical manifestations, intratypic differentiation examination, and whole-genome sequencing showed that this recombinant exhibited characteristics of neurovirulent vaccine-derived polioviruses (VDPV), which may, thus, pose a potential threat to a polio-free world.
Wu, Guosheng; Robertson, Daniel H; Brooks, Charles L; Vieth, Michal
2003-10-01
The influence of various factors on the accuracy of protein-ligand docking is examined. The factors investigated include the role of a grid representation of protein-ligand interactions, the initial ligand conformation and orientation, the sampling rate of the energy hyper-surface, and the final minimization. A representative docking method is used to study these factors, namely, CDOCKER, a molecular dynamics (MD) simulated-annealing-based algorithm. A major emphasis in these studies is to compare the relative performance and accuracy of various grid-based approximations to explicit all-atom force field calculations. In these docking studies, the protein is kept rigid while the ligands are treated as fully flexible and a final minimization step is used to refine the docked poses. A docking success rate of 74% is observed when an explicit all-atom representation of the protein (full force field) is used, while a lower accuracy of 66-76% is observed for grid-based methods. All docking experiments considered a 41-member protein-ligand validation set. A significant improvement in accuracy (76 vs. 66%) for the grid-based docking is achieved if the explicit all-atom force field is used in a final minimization step to refine the docking poses. Statistical analysis shows that even lower-accuracy grid-based energy representations can be effectively used when followed with full force field minimization. The results of these grid-based protocols are statistically indistinguishable from the detailed atomic dockings and provide up to a sixfold reduction in computation time. For the test case examined here, improving the docking accuracy did not necessarily enhance the ability to estimate binding affinities using the docked structures. Copyright 2003 Wiley Periodicals, Inc.
The Autoregressive Method: A Method of Approximating and Estimating Positive Functions
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
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
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...
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...
USDA-ARS?s Scientific Manuscript database
There are approximately 55,000 described Acari species, accounting for almost half of all known Arachnida species, but total estimated Acari diversity is reckoned to be far greater. One important source of currently hidden Acari diversity is cryptic speciation, which poses challenges to taxonomists ...
Witoonchart, Peerajak; Chongstitvatana, Prabhas
2017-08-01
In this study, for the first time, we show how to formulate a structured support vector machine (SSVM) as two layers in a convolutional neural network, where the top layer is a loss augmented inference layer and the bottom layer is the normal convolutional layer. We show that a deformable part model can be learned with the proposed structured SVM neural network by backpropagating the error of the deformable part model to the convolutional neural network. The forward propagation calculates the loss augmented inference and the backpropagation calculates the gradient from the loss augmented inference layer to the convolutional layer. Thus, we obtain a new type of convolutional neural network called an Structured SVM convolutional neural network, which we applied to the human pose estimation problem. This new neural network can be used as the final layers in deep learning. Our method jointly learns the structural model parameters and the appearance model parameters. We implemented our method as a new layer in the existing Caffe library. Copyright © 2017 Elsevier Ltd. All rights reserved.
Hybrid Orientation Based Human Limbs Motion Tracking Method
Glonek, Grzegorz; Wojciechowski, Adam
2017-01-01
One of the key technologies that lays behind the human–machine interaction and human motion diagnosis is the limbs motion tracking. To make the limbs tracking efficient, it must be able to estimate a precise and unambiguous position of each tracked human joint and resulting body part pose. In recent years, body pose estimation became very popular and broadly available for home users because of easy access to cheap tracking devices. Their robustness can be improved by different tracking modes data fusion. The paper defines the novel approach—orientation based data fusion—instead of dominating in literature position based approach, for two classes of tracking devices: depth sensors (i.e., Microsoft Kinect) and inertial measurement units (IMU). The detailed analysis of their working characteristics allowed to elaborate a new method that let fuse more precisely limbs orientation data from both devices and compensates their imprecisions. The paper presents the series of performed experiments that verified the method’s accuracy. This novel approach allowed to outperform the precision of position-based joints tracking, the methods dominating in the literature, of up to 18%. PMID:29232832
RGB-D SLAM Based on Extended Bundle Adjustment with 2D and 3D Information
Di, Kaichang; Zhao, Qiang; Wan, Wenhui; Wang, Yexin; Gao, Yunjun
2016-01-01
In the study of SLAM problem using an RGB-D camera, depth information and visual information as two types of primary measurement data are rarely tightly coupled during refinement of camera pose estimation. In this paper, a new method of RGB-D camera SLAM is proposed based on extended bundle adjustment with integrated 2D and 3D information on the basis of a new projection model. First, the geometric relationship between the image plane coordinates and the depth values is constructed through RGB-D camera calibration. Then, 2D and 3D feature points are automatically extracted and matched between consecutive frames to build a continuous image network. Finally, extended bundle adjustment based on the new projection model, which takes both image and depth measurements into consideration, is applied to the image network for high-precision pose estimation. Field experiments show that the proposed method has a notably better performance than the traditional method, and the experimental results demonstrate the effectiveness of the proposed method in improving localization accuracy. PMID:27529256
Automatic Calibration Method for Driver’s Head Orientation in Natural Driving Environment
Fu, Xianping; Guan, Xiao; Peli, Eli; Liu, Hongbo; Luo, Gang
2013-01-01
Gaze tracking is crucial for studying driver’s attention, detecting fatigue, and improving driver assistance systems, but it is difficult in natural driving environments due to nonuniform and highly variable illumination and large head movements. Traditional calibrations that require subjects to follow calibrators are very cumbersome to be implemented in daily driving situations. A new automatic calibration method, based on a single camera for determining the head orientation and which utilizes the side mirrors, the rear-view mirror, the instrument board, and different zones in the windshield as calibration points, is presented in this paper. Supported by a self-learning algorithm, the system tracks the head and categorizes the head pose in 12 gaze zones based on facial features. The particle filter is used to estimate the head pose to obtain an accurate gaze zone by updating the calibration parameters. Experimental results show that, after several hours of driving, the automatic calibration method without driver’s corporation can achieve the same accuracy as a manual calibration method. The mean error of estimated eye gazes was less than 5°in day and night driving. PMID:24639620
Detailed 3D representations for object recognition and modeling.
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.
Realtime Reconstruction of an Animating Human Body from a Single Depth Camera.
Chen, Yin; Cheng, Zhi-Quan; Lai, Chao; Martin, Ralph R; Dang, Gang
2016-08-01
We present a method for realtime reconstruction of an animating human body,which produces a sequence of deforming meshes representing a given performance captured by a single commodity depth camera. We achieve realtime single-view mesh completion by enhancing the parameterized SCAPE model.Our method, which we call Realtime SCAPE, performs full-body reconstruction without the use of markers.In Realtime SCAPE, estimations of body shape parameters and pose parameters, needed for reconstruction, are decoupled. Intrinsic body shape is first precomputed for a given subject, by determining shape parameters with the aid of a body shape database. Subsequently, per-frame pose parameter estimation is performed by means of linear blending skinning (LBS); the problem is decomposed into separately finding skinning weights and transformations. The skinning weights are also determined offline from the body shape database,reducing online reconstruction to simply finding the transformations in LBS. Doing so is formulated as a linear variational problem;carefully designed constraints are used to impose temporal coherence and alleviate artifacts. Experiments demonstrate that our method can produce full-body mesh sequences with high fidelity.
Improving chemical species tomography of turbulent flows using covariance estimation.
Grauer, Samuel J; Hadwin, Paul J; Daun, Kyle J
2017-05-01
Chemical species tomography (CST) experiments can be divided into limited-data and full-rank cases. Both require solving ill-posed inverse problems, and thus the measurement data must be supplemented with prior information to carry out reconstructions. The Bayesian framework formalizes the role of additive information, expressed as the mean and covariance of a joint-normal prior probability density function. We present techniques for estimating the spatial covariance of a flow under limited-data and full-rank conditions. Our results show that incorporating a covariance estimate into CST reconstruction via a Bayesian prior increases the accuracy of instantaneous estimates. Improvements are especially dramatic in real-time limited-data CST, which is directly applicable to many industrially relevant experiments.
Robust kernel representation with statistical local features for face recognition.
Yang, Meng; Zhang, Lei; Shiu, Simon Chi-Keung; Zhang, David
2013-06-01
Factors such as misalignment, pose variation, and occlusion make robust face recognition a difficult problem. It is known that statistical features such as local binary pattern are effective for local feature extraction, whereas the recently proposed sparse or collaborative representation-based classification has shown interesting results in robust face recognition. In this paper, we propose a novel robust kernel representation model with statistical local features (SLF) for robust face recognition. Initially, multipartition max pooling is used to enhance the invariance of SLF to image registration error. Then, a kernel-based representation model is proposed to fully exploit the discrimination information embedded in the SLF, and robust regression is adopted to effectively handle the occlusion in face images. Extensive experiments are conducted on benchmark face databases, including extended Yale B, AR (A. Martinez and R. Benavente), multiple pose, illumination, and expression (multi-PIE), facial recognition technology (FERET), face recognition grand challenge (FRGC), and labeled faces in the wild (LFW), which have different variations of lighting, expression, pose, and occlusions, demonstrating the promising performance of the proposed method.
A well-posed numerical method to track isolated conformal map singularities in Hele-Shaw flow
DOE Office of Scientific and Technical Information (OSTI.GOV)
Baker, G.; Siegel, M.; Tanveer, S.
1995-09-01
We present a new numerical method for calculating an evolving 2D Hele-Shaw interface when surface tension effects are neglected. In the case where the flow is directed from the less viscous fluid into the more viscous fluid, the motion of the interface is ill-posed; small deviations in the initial condition will produce significant changes in the ensuing motion. The situation is disastrous for numerical computation, as small roundoff errors can quickly lead to large inaccuracies in the computed solution. Our method of computation is most easily formulated using a conformal map from the fluid domain into a unit disk. Themore » method relies on analytically continuing the initial data and equations of motion into the region exterior to the disk, where the evolution problem becomes well-posed. The equations are then numerically solved in the extended domain. The presence of singularities in the conformal map outside of the disk introduces specific structures along the fluid interface. Our method can explicitly track the location of isolated pole and branch point singularities, allowing us to draw connections between the development of interfacial patterns and the motion of singularities as they approach the unit disk. In particular, we are able to relate physical features such as finger shape, side-branch formation, and competition between fingers to the nature and location of the singularities. The usefulness of this method in studying the formation of topological singularities (self-intersections of the interface) is also pointed out. 47 refs., 10 figs., 1 tab.« less
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.
Exploring a Structure for Mathematics Lessons That Foster Problem Solving and Reasoning
ERIC Educational Resources Information Center
Sullivan, Peter; Walker, Nadia; Borcek, Chris; Rennie, Mick
2015-01-01
While there is widespread agreement on the importance of incorporating problem solving and reasoning into mathematics classrooms, there is limited specific advice on how this can best happen. This is a report of an aspect of a project that is examining the opportunities and constraints in initiating learning by posing challenging mathematics tasks…
Public Administration: What is It, Why Teach It and Does It Matter?
ERIC Educational Resources Information Center
Fenwick, John; McMillan, Janice
2014-01-01
What is understood by "public administration" in the contemporary UK higher education setting? Is it still being taught and, if so, why? These questions initially appear to be fairly straightforward but any review of the topic quickly poses some rather more tricky areas of enquiry. This article will focus upon three central questions.…
Silence, Words that Wound and Sexual Identity: A Conversation with Applebaum
ERIC Educational Resources Information Center
Jackson, Liz
2008-01-01
In this paper, I continue a conversation initiated by Barbara Applebaum on how to manage irreconcilable difference, harmful language or "words that wound" and various implications of power in the classroom. Referencing emerging works on the nature of speech and silence, classroom power and queer identity, I pose three questions to Applebaum in…
ERIC Educational Resources Information Center
Judith, Kate; Bull, David
2016-01-01
The implementation of open educational resources (OER) at the course level in higher education poses numerous challenges to education practitioners--ranging from discoverability challenges to the lack of knowledge on how to best localize and utilize OER as courseware. Drawing on case studies of OER initiatives globally, the article discusses…
ERIC Educational Resources Information Center
Hunter-Jones, Philippa
2012-01-01
This article explores the changing worldview of a new generation of learners and the threat that this poses to the future of experiential learning (EL). Initially the differing characteristics of three generations of learners, X, Y, and Z, are outlined, along with key educational reforms they have been subject to, particularly in the United…
Equipped for the Future: Tools & Standards for Building & Assessing Quality Adult Literacy Programs.
ERIC Educational Resources Information Center
Spangenberg, Gail; Watson, Sarah
This report presents results from interviews with a sampling of experienced Equipped for the Future (EFF) users. Chapter I provides background and context for this initiative. Chapter II provides facts and figures from the field and presents questions posed and interviewees' views. The questions are as follows: (1) Why did you or your organization…
NASA Astrophysics Data System (ADS)
Seers, T. D.; Hodgetts, D.
2013-12-01
Seers, T. D. & Hodgetts, D. School of Earth, Atmospheric and Environmental Sciences, University of Manchester, UK. M13 9PL. The detection of topological change at the Earth's surface is of considerable scholarly interest, allowing the quantification of the rates of geomorphic processes whilst providing lucid insights into the underlying mechanisms driving landscape evolution. In this regard, the past decade has witnessed the ever increasing proliferation of studies employing multi-temporal topographic data in within the geosciences, bolstered by continuing technical advancements in the acquisition and processing of prerequisite datasets. Provided by workers within the field of Computer Vision, multiview stereo (MVS) dense surface reconstructions, primed by structure-from-motion (SfM) based camera pose estimation represents one such development. Providing a cost effective, operationally efficient data capture medium, the modest requirement of a consumer grade camera for data collection coupled with the minimal user intervention required during post-processing makes SfM-MVS an attractive alternative to terrestrial laser scanners for collecting multi-temporal topographic datasets. However, in similitude to terrestrial scanner derived data, the co-registration of spatially coincident or partially overlapping scans produced by SfM-MVS presents a major technical challenge, particularly in the case of semi non-rigid scenes produced during topographic change detection studies. Moreover, the arbitrary scaling resulting from SfM ambiguity requires that a scale matrix must be estimated during the transformation, introducing further complexity into its formulation. Here, we present a novel, fully unsupervised algorithm which utilises non-linearly weighted image features for the solving the similarity transform (scale, translation rotation) between partially overlapping scans produced by SfM-MVS image processing. With the only initialization condition being partial intersection between input image sets, our method has major advantages over conventional iterative least squares minimization based methods (e.g. Iterative Closest Point variants), acting only on rigid areas of target scenes, being capable of reliably estimating the scaling factor and requiring no incipient estimation of the transformation to initialize (i.e. manual rough alignment). Moreover, because the solution is closed form, convergence is considerably more expedient that most iterative methods. It is hoped that the availability of improved co-registration routines, such as the one presented here, will facilitate the routine collection of multi-temporal topographic datasets by a wider range of geoscience practitioners.
Breast cancer management: quality-of-life and cost considerations.
Radice, Davide; Redaelli, Alberto
2003-01-01
The purpose of this article was to provide a literature-based extensive overview of the quality-of-life and cost issues posed by the management of breast cancer. Incidence and mortality rates vary widely in different countries. Breast cancer accounts approximately for one-fifth of all deaths in women aged 40-50 years. The 1994-1998 incidence rate in the US population was on average 114.3 per 100 000 women. Treatment options include surgery, radiotherapy and drug therapy (cytotoxic and endocrine drugs). All treatment options affect patients' health-related quality of life (HR-QOL) in various ways. The use of cytotoxic agents has a particularly large HR-QOL impact. HR-QOL questionnaires are complex tools, not routinely used in breast cancer trials.Worldwide, around 10 million individuals develop cancer each year; this figure is expected to increase to 15 million in 2020. For all cancers, the total economic burden of this disease worldwide was projected by the authors to be in the range of $US 300-400 billion in 2001 (about $US 100-140 billion as direct costs and the remainder as indirect costs [morbidity and mortality]). According to the National Institute of Health (NIH), the total cost of cancer was estimated at $US 156.7 billion in 2001 in US ($US 56.4 billion as direct costs, $US 15.6 as indirect morbidity costs, and $US 84.7 billion as indirect mortality costs). Based on limited information, in the US, breast cancer can be projected to account for about one-fifth/one-fourth of the total cost of cancer. Breast cancer treatment costs are higher in the US than in other developed countries. Both direct and indirect costs are dependent on disease stage. The per-patient costs for initial care in 1992 were estimated at $US 10 813, for continuing care at $US 1084 and for terminal care at $US 17 886. Stage-specific costs provide information for cost-effectiveness analyses of cancer-control initiatives, such as screening programmes. Economic studies on breast cancer are heterogeneous, and the cost estimates made are not easily generalisable. The cost of treatment for breast cancer in developing countries is < or =5% of that in developed regions.
Cauchemez, Simon; Epperson, Scott; Biggerstaff, Matthew; Swerdlow, David; Finelli, Lyn; Ferguson, Neil M
2013-01-01
Prior to emergence in human populations, zoonoses such as SARS cause occasional infections in human populations exposed to reservoir species. The risk of widespread epidemics in humans can be assessed by monitoring the reproduction number R (average number of persons infected by a human case). However, until now, estimating R required detailed outbreak investigations of human clusters, for which resources and expertise are not always available. Additionally, existing methods do not correct for important selection and under-ascertainment biases. Here, we present simple estimation methods that overcome many of these limitations. Our approach is based on a parsimonious mathematical model of disease transmission and only requires data collected through routine surveillance and standard case investigations. We apply it to assess the transmissibility of swine-origin influenza A H3N2v-M virus in the US, Nipah virus in Malaysia and Bangladesh, and also present a non-zoonotic example (cholera in the Dominican Republic). Estimation is based on two simple summary statistics, the proportion infected by the natural reservoir among detected cases (G) and among the subset of the first detected cases in each cluster (F). If detection of a case does not affect detection of other cases from the same cluster, we find that R can be estimated by 1-G; otherwise R can be estimated by 1-F when the case detection rate is low. In more general cases, bounds on R can still be derived. We have developed a simple approach with limited data requirements that enables robust assessment of the risks posed by emerging zoonoses. We illustrate this by deriving transmissibility estimates for the H3N2v-M virus, an important step in evaluating the possible pandemic threat posed by this virus. Please see later in the article for the Editors' Summary.
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.
Meteoroids and Meteor Storms: A Threat to Spacecraft
NASA Technical Reports Server (NTRS)
Anderson, B. Jeffrey
1999-01-01
Robust system design is the best protection against meteoroid damage. Impacts by small meteoroids are common on satellite surfaces, but impacts by meteoroids large enough to damage well designed systems are very rare. Estimating the threat from the normal meteoroid environment is difficult. Estimates for the occasional "storm" are even more uncertain. Common sense precautions are in order for the 1999 Leonids, but wide-spread catastrophic damage is highly unlikely. Strong Leonid showers are also expected in 2000 and 2001, but these pose much less threat than 1999.
Generation and Repair of AID-initiated DNA Lesions in B Lymphocytes
Chen, Zhangguo; Wang, Jing H.
2014-01-01
Activation-induced deaminase (AID) initiates the secondary antibody diversification process in B lymphocytes. In mammalian B cells, this process includes somatic hypermutation (SHM) and class switch recombination (CSR), both of which require AID. AID induces U:G mismatch lesions in DNA that are subsequently converted into point mutations or DNA double stranded breaks during SHM/CSR. In a physiological context, AID targets immunoglobulin (Ig) loci to mediate SHM/CSR. However, recent studies reveal genome-wide access of AID to numerous non-Ig loci. Thus, AID poses a threat to the genome of B cells if AID-initiated DNA lesions cannot be properly repaired. In this review, we focus on the molecular mechanisms that regulate the specificity of AID targeting and the repair pathways responsible for processing AID-initiated DNA lesions. PMID:24748462
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.
Gorman Ng, Melanie; Milon, Antoine; Vernez, David; Lavoué, Jérôme
2016-04-01
Occupational hygiene practitioners typically assess the risk posed by occupational exposure by comparing exposure measurements to regulatory occupational exposure limits (OELs). In most jurisdictions, OELs are only available for exposure by the inhalation pathway. Skin notations are used to indicate substances for which dermal exposure may lead to health effects. However, these notations are either present or absent and provide no indication of acceptable levels of exposure. Furthermore, the methodology and framework for assigning skin notation differ widely across jurisdictions resulting in inconsistencies in the substances that carry notations. The UPERCUT tool was developed in response to these limitations. It helps occupational health stakeholders to assess the hazard associated with dermal exposure to chemicals. UPERCUT integrates dermal quantitative structure-activity relationships (QSARs) and toxicological data to provide users with a skin hazard index called the dermal hazard ratio (DHR) for the substance and scenario of interest. The DHR is the ratio between the estimated 'received' dose and the 'acceptable' dose. The 'received' dose is estimated using physico-chemical data and information on the exposure scenario provided by the user (body parts exposure and exposure duration), and the 'acceptable' dose is estimated using inhalation OELs and toxicological data. The uncertainty surrounding the DHR is estimated with Monte Carlo simulation. Additional information on the selected substances includes intrinsic skin permeation potential of the substance and the existence of skin notations. UPERCUT is the only available tool that estimates the absorbed dose and compares this to an acceptable dose. In the absence of dermal OELs it provides a systematic and simple approach for screening dermal exposure scenarios for 1686 substances. © The Author 2015. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.
Automated Docking Screens: A Feasibility Study
2009-01-01
Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 Å rmsd 50−60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 Å rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org. PMID:19719084
Automated docking screens: a feasibility study.
Irwin, John J; Shoichet, Brian K; Mysinger, Michael M; Huang, Niu; Colizzi, Francesco; Wassam, Pascal; Cao, Yiqun
2009-09-24
Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 A rmsd 50-60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 A rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org .
NASA Astrophysics Data System (ADS)
Müller, M. S.; Urban, S.; Jutzi, B.
2017-08-01
The number of unmanned aerial vehicles (UAVs) is increasing since low-cost airborne systems are available for a wide range of users. The outdoor navigation of such vehicles is mostly based on global navigation satellite system (GNSS) methods to gain the vehicles trajectory. The drawback of satellite-based navigation are failures caused by occlusions and multi-path interferences. Beside this, local image-based solutions like Simultaneous Localization and Mapping (SLAM) and Visual Odometry (VO) can e.g. be used to support the GNSS solution by closing trajectory gaps but are computationally expensive. However, if the trajectory estimation is interrupted or not available a re-localization is mandatory. In this paper we will provide a novel method for a GNSS-free and fast image-based pose regression in a known area by utilizing a small convolutional neural network (CNN). With on-board processing in mind, we employ a lightweight CNN called SqueezeNet and use transfer learning to adapt the network to pose regression. Our experiments show promising results for GNSS-free and fast localization.
3D face recognition under expressions, occlusions, and pose variations.
Drira, Hassen; Ben Amor, Boulbaba; Srivastava, Anuj; Daoudi, Mohamed; Slama, Rim
2013-09-01
We propose a novel geometric framework for analyzing 3D faces, with the specific goals of comparing, matching, and averaging their shapes. Here we represent facial surfaces by radial curves emanating from the nose tips and use elastic shape analysis of these curves to develop a Riemannian framework for analyzing shapes of full facial surfaces. This representation, along with the elastic Riemannian metric, seems natural for measuring facial deformations and is robust to challenges such as large facial expressions (especially those with open mouths), large pose variations, missing parts, and partial occlusions due to glasses, hair, and so on. This framework is shown to be promising from both--empirical and theoretical--perspectives. In terms of the empirical evaluation, our results match or improve upon the state-of-the-art methods on three prominent databases: FRGCv2, GavabDB, and Bosphorus, each posing a different type of challenge. From a theoretical perspective, this framework allows for formal statistical inferences, such as the estimation of missing facial parts using PCA on tangent spaces and computing average shapes.
NASA Astrophysics Data System (ADS)
Hatt, Charles R.; Speidel, Michael A.; Raval, Amish N.
2014-03-01
We present a novel 2D/ 3D registration algorithm for fusion between transesophageal echocardiography (TEE) and X-ray fluoroscopy (XRF). The TEE probe is modeled as a subset of 3D gradient and intensity point features, which facilitates efficient 3D-to-2D perspective projection. A novel cost-function, based on a combination of intensity and edge features, evaluates the registration cost value without the need for time-consuming generation of digitally reconstructed radiographs (DRRs). Validation experiments were performed with simulations and phantom data. For simulations, in silica XRF images of a TEE probe were generated in a number of different pose configurations using a previously acquired CT image. Random misregistrations were applied and our method was used to recover the TEE probe pose and compare the result to the ground truth. Phantom experiments were performed by attaching fiducial markers externally to a TEE probe, imaging the probe with an interventional cardiac angiographic x-ray system, and comparing the pose estimated from the external markers to that estimated from the TEE probe using our algorithm. Simulations found a 3D target registration error of 1.08(1.92) mm for biplane (monoplane) geometries, while the phantom experiment found a 2D target registration error of 0.69mm. For phantom experiments, we demonstrated a monoplane tracking frame-rate of 1.38 fps. The proposed feature-based registration method is computationally efficient, resulting in near real-time, accurate image based registration between TEE and XRF.
Performance of local optimization in single-plane fluoroscopic analysis for total knee arthroplasty.
Prins, A H; Kaptein, B L; Stoel, B C; Lahaye, D J P; Valstar, E R
2015-11-05
Fluoroscopy-derived joint kinematics plays an important role in the evaluation of knee prostheses. Fluoroscopic analysis requires estimation of the 3D prosthesis pose from its 2D silhouette in the fluoroscopic image, by optimizing a dissimilarity measure. Currently, extensive user-interaction is needed, which makes analysis labor-intensive and operator-dependent. The aim of this study was to review five optimization methods for 3D pose estimation and to assess their performance in finding the correct solution. Two derivative-free optimizers (DHSAnn and IIPM) and three gradient-based optimizers (LevMar, DoNLP2 and IpOpt) were evaluated. For the latter three optimizers two different implementations were evaluated: one with a numerically approximated gradient and one with an analytically derived gradient for computational efficiency. On phantom data, all methods were able to find the 3D pose within 1mm and 1° in more than 85% of cases. IpOpt had the highest success-rate: 97%. On clinical data, the success rates were higher than 85% for the in-plane positions, but not for the rotations. IpOpt was the most expensive method and the application of an analytically derived gradients accelerated the gradient-based methods by a factor 3-4 without any differences in success rate. In conclusion, 85% of the frames can be analyzed automatically in clinical data and only 15% of the frames require manual supervision. The optimal success-rate on phantom data (97% with IpOpt) on phantom data indicates that even less supervision may become feasible. Copyright © 2015 Elsevier Ltd. All rights reserved.
Carbon recovery rates following different wildfire risk mitigation treatments
M. Hurteau; M. North
2010-01-01
Sequestered forest carbon can provide a climate change mitigation benefit, but in dry temperate forests, wildfire poses a reversal risk to carbon offset projects. Reducing wildfire risk requires a reduction in and redistribution of carbon stocks, the benefit of which is only realized when wildfire occurs. To estimate the time needed to recover carbon removed and...
Quantitative metrics for assessing predicted climate change pressure on North American tree species
Kevin M. Potter; William W. Hargrove
2013-01-01
Changing climate may pose a threat to forest tree species, forcing three potential population-level responses: toleration/adaptation, movement to suitable environmental conditions, or local extirpation. Assessments that prioritize and classify tree species for management and conservation activities in the face of climate change will need to incorporate estimates of the...
China: Management and Finance of Higher Education. A World Bank Country Study.
ERIC Educational Resources Information Center
World Bank, Washington, DC.
Key issues in higher education management and finance in China until the end of the century are examined, along with the effect of recent education reform. Attention is directed to: the government's plan for long-term expansion of higher education posed as three alternative targets for enrollment growth; estimated demand for and supply of…
Dispersal of Invasive Forest Insects via Recreational Firewood: A Quantitative Analysis
Frank H. Koch; Denys Yemshanov; Roger D. Magarey; William D. Smith
2012-01-01
Recreational travel is a recognized vector for the spread of invasive species in North America. However, there has been little quantitative analysis of the risks posed by such travel and the associated transport of firewood. In this study, we analyzed the risk of forest insect spread with firewood and estimated related dispersal parameters for application in...
ERIC Educational Resources Information Center
Erwin, T. Dary
Rating scales are a typical method for evaluating a student's performance in outcomes assessment. The analysis of the quality of information from rating scales poses special measurement problems when researchers work with faculty in their development. Generalizability measurement theory offers a set of techniques for estimating errors or…
Lagudi, Antonio; Bianco, Gianfranco; Muzzupappa, Maurizio; Bruno, Fabio
2016-04-14
The integration of underwater 3D data captured by acoustic and optical systems is a promising technique in various applications such as mapping or vehicle navigation. It allows for compensating the drawbacks of the low resolution of acoustic sensors and the limitations of optical sensors in bad visibility conditions. Aligning these data is a challenging problem, as it is hard to make a point-to-point correspondence. This paper presents a multi-sensor registration for the automatic integration of 3D data acquired from a stereovision system and a 3D acoustic camera in close-range acquisition. An appropriate rig has been used in the laboratory tests to determine the relative position between the two sensor frames. The experimental results show that our alignment approach, based on the acquisition of a rig in several poses, can be adopted to estimate the rigid transformation between the two heterogeneous sensors. A first estimation of the unknown geometric transformation is obtained by a registration of the two 3D point clouds, but it ends up to be strongly affected by noise and data dispersion. A robust and optimal estimation is obtained by a statistical processing of the transformations computed for each pose. The effectiveness of the method has been demonstrated in this first experimentation of the proposed 3D opto-acoustic camera.
López, Elena; García, Sergio; Barea, Rafael; Bergasa, Luis M.; Molinos, Eduardo J.; Arroyo, Roberto; Romera, Eduardo; Pardo, Samuel
2017-01-01
One of the main challenges of aerial robots navigation in indoor or GPS-denied environments is position estimation using only the available onboard sensors. This paper presents a Simultaneous Localization and Mapping (SLAM) system that remotely calculates the pose and environment map of different low-cost commercial aerial platforms, whose onboard computing capacity is usually limited. The proposed system adapts to the sensory configuration of the aerial robot, by integrating different state-of-the art SLAM methods based on vision, laser and/or inertial measurements using an Extended Kalman Filter (EKF). To do this, a minimum onboard sensory configuration is supposed, consisting of a monocular camera, an Inertial Measurement Unit (IMU) and an altimeter. It allows to improve the results of well-known monocular visual SLAM methods (LSD-SLAM and ORB-SLAM are tested and compared in this work) by solving scale ambiguity and providing additional information to the EKF. When payload and computational capabilities permit, a 2D laser sensor can be easily incorporated to the SLAM system, obtaining a local 2.5D map and a footprint estimation of the robot position that improves the 6D pose estimation through the EKF. We present some experimental results with two different commercial platforms, and validate the system by applying it to their position control. PMID:28397758
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.
Lagudi, Antonio; Bianco, Gianfranco; Muzzupappa, Maurizio; Bruno, Fabio
2016-01-01
The integration of underwater 3D data captured by acoustic and optical systems is a promising technique in various applications such as mapping or vehicle navigation. It allows for compensating the drawbacks of the low resolution of acoustic sensors and the limitations of optical sensors in bad visibility conditions. Aligning these data is a challenging problem, as it is hard to make a point-to-point correspondence. This paper presents a multi-sensor registration for the automatic integration of 3D data acquired from a stereovision system and a 3D acoustic camera in close-range acquisition. An appropriate rig has been used in the laboratory tests to determine the relative position between the two sensor frames. The experimental results show that our alignment approach, based on the acquisition of a rig in several poses, can be adopted to estimate the rigid transformation between the two heterogeneous sensors. A first estimation of the unknown geometric transformation is obtained by a registration of the two 3D point clouds, but it ends up to be strongly affected by noise and data dispersion. A robust and optimal estimation is obtained by a statistical processing of the transformations computed for each pose. The effectiveness of the method has been demonstrated in this first experimentation of the proposed 3D opto-acoustic camera. PMID:27089344
Model-based tomographic reconstruction of objects containing known components.
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.
Frequency domain surface EMG sensor fusion for estimating finger forces.
Potluri, Chandrasekhar; Kumar, Parmod; Anugolu, Madhavi; Urfer, Alex; Chiu, Steve; Naidu, D; Schoen, Marco P
2010-01-01
Extracting or estimating skeletal hand/finger forces using surface electro myographic (sEMG) signals poses many challenges due to cross-talk, noise, and a temporal and spatially modulated signal characteristics. Normal sEMG measurements are based on single sensor data. In this paper, array sensors are used along with a proposed sensor fusion scheme that result in a simple Multi-Input-Single-Output (MISO) transfer function. Experimental data is used along with system identification to find this MISO system. A Genetic Algorithm (GA) approach is employed to optimize the characteristics of the MISO system. The proposed fusion-based approach is tested experimentally and indicates improvement in finger/hand force estimation.
Benchmarking real-time RGBD odometry for light-duty UAVs
NASA Astrophysics Data System (ADS)
Willis, Andrew R.; Sahawneh, Laith R.; Brink, Kevin M.
2016-06-01
This article describes the theoretical and implementation challenges associated with generating 3D odometry estimates (delta-pose) from RGBD sensor data in real-time to facilitate navigation in cluttered indoor environments. The underlying odometry algorithm applies to general 6DoF motion; however, the computational platforms, trajectories, and scene content are motivated by their intended use on indoor, light-duty UAVs. Discussion outlines the overall software pipeline for sensor processing and details how algorithm choices for the underlying feature detection and correspondence computation impact the real-time performance and accuracy of the estimated odometry and associated covariance. This article also explores the consistency of odometry covariance estimates and the correlation between successive odometry estimates. The analysis is intended to provide users information needed to better leverage RGBD odometry within the constraints of their systems.
Accurate Initial State Estimation in a Monocular Visual–Inertial SLAM System
Chen, Jing; Zhou, Zixiang; Leng, Zhen; Fan, Lei
2018-01-01
The fusion of monocular visual and inertial cues has become popular in robotics, unmanned vehicles and augmented reality fields. Recent results have shown that optimization-based fusion strategies outperform filtering strategies. Robust state estimation is the core capability for optimization-based visual–inertial Simultaneous Localization and Mapping (SLAM) systems. As a result of the nonlinearity of visual–inertial systems, the performance heavily relies on the accuracy of initial values (visual scale, gravity, velocity and Inertial Measurement Unit (IMU) biases). Therefore, this paper aims to propose a more accurate initial state estimation method. On the basis of the known gravity magnitude, we propose an approach to refine the estimated gravity vector by optimizing the two-dimensional (2D) error state on its tangent space, then estimate the accelerometer bias separately, which is difficult to be distinguished under small rotation. Additionally, we propose an automatic termination criterion to determine when the initialization is successful. Once the initial state estimation converges, the initial estimated values are used to launch the nonlinear tightly coupled visual–inertial SLAM system. We have tested our approaches with the public EuRoC dataset. Experimental results show that the proposed methods can achieve good initial state estimation, the gravity refinement approach is able to efficiently speed up the convergence process of the estimated gravity vector, and the termination criterion performs well. PMID:29419751
Drory, Ami; Li, Hongdong; Hartley, Richard
2017-04-11
We present a supervised machine learning approach for markerless estimation of human full-body kinematics for a cyclist from an unconstrained colour image. This approach is motivated by the limitations of existing marker-based approaches restricted by infrastructure, environmental conditions, and obtrusive markers. By using a discriminatively learned mixture-of-parts model, we construct a probabilistic tree representation to model the configuration and appearance of human body joints. During the learning stage, a Structured Support Vector Machine (SSVM) learns body parts appearance and spatial relations. In the testing stage, the learned models are employed to recover body pose via searching in a test image over a pyramid structure. We focus on the movement modality of cycling to demonstrate the efficacy of our approach. In natura estimation of cycling kinematics using images is challenging because of human interaction with a bicycle causing frequent occlusions. We make no assumptions in relation to the kinematic constraints of the model, nor the appearance of the scene. Our technique finds multiple quality hypotheses for the pose. We evaluate the precision of our method on two new datasets using loss functions. Our method achieves a score of 91.1 and 69.3 on mean Probability of Correct Keypoint (PCK) measure and 88.7 and 66.1 on the Average Precision of Keypoints (APK) measure for the frontal and sagittal datasets respectively. We conclude that our method opens new vistas to robust user-interaction free estimation of full body kinematics, a prerequisite to motion analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.
Vortex Lattice UXO Mobility Model for Reef-Type Range Environments
2012-07-01
unexploded ordnance WAA Wide Area Assessment 10...of a given underwater UXO field. By using the upgraded UXO MM to develop an initial Wide Area Assessment (WAA), that subdivides a UXO field into... areas outside of human contact and b) areas where UXO are fully stabilized and pose little risk to humans. Further consideration of the risks presented
Initiating Preservice Education Majors in the Integration of Health Instruction in Middle Schools
ERIC Educational Resources Information Center
Devlin-Scherer, Roberta; Zaccone, Paula R.
2004-01-01
Losses to the workforce and drains on the national economy posed by illnesses, injuries, and environmental hazards dictate that schools operate to prevent, intervene, and help resolve these social and personal health issues. The costs to society for the medical care of children born to addicted and abusive parents, exposure to smoke and pollution,…
ERIC Educational Resources Information Center
Perrault, Evan K.
2018-01-01
Despite improved spam filtering technology, phishing continues to be a prevalent threat for college students. The current study found that approximately 4-in-10 of the students surveyed (N = 462) indicate they do not know what phishing is and the threat it poses. Students also report initially overestimating their confidence to successfully…
Jennifer L. Parke; Fumiaki Funahashi; Clara Weidman; Ebba K. Peterson
2017-01-01
Soilborne Phytophthora spp. can be important for initiating disease through movement of inoculum with surface water to roots or splashing onto foliage. Nursery beds infested with Phytophthora spp. can contaminate container plants set on them, causing disease year after year and posing a risk of additional spread....
Fang, Hua; Zhang, Zhaoyang; Wang, Chanpaul Jin; Daneshmand, Mahmoud; Wang, Chonggang; Wang, Honggang
2015-01-01
Big data create values for business and research, but pose significant challenges in terms of networking, storage, management, analytics and ethics. Multidisciplinary collaborations from engineers, computer scientists, statisticians and social scientists are needed to tackle, discover and understand big data. This survey presents an overview of big data initiatives, technologies and research in industries and academia, and discusses challenges and potential solutions. PMID:26504265
ERIC Educational Resources Information Center
Tisdell, Christopher C.
2017-01-01
Knowing an equation has a unique solution is important from both a modelling and theoretical point of view. For over 70 years, the approach to learning and teaching "well posedness" of initial value problems (IVPs) for second- and higher-order ordinary differential equations has involved transforming the problem and its analysis to a…
Impact of low-frequency sound on historic structures
NASA Astrophysics Data System (ADS)
Sutherland, Louis C.; Horonjeff, Richard D.
2005-09-01
In common usage, the term soundscape usually refers to portions of the sound spectrum audible to human observers, and perhaps more broadly other members of the animal kingdom. There is, however, a soundscape regime at the low end of the frequency spectrum (e.g., 10-25 Hz), which is inaudible to humans, where nonindigenous sound energy may cause noise-induced vibrations in structures. Such low frequency components may be of sufficient magnitude to pose damage risk potential to historic structures and cultural resources. Examples include Anasazi cliff and cave dwellings, and pueblo structures of vega type roof construction. Both are susceptible to noise induced vibration from low-frequency sound pressures that excite resonant frequencies in these structures. The initial damage mechanism is usually fatigue cracking. Many mechanisms are subtle, temporally multiphased, and not initially evident to the naked eye. This paper reviews the types of sources posing the greatest potential threat, their low-frequency spectral characteristics, typical structural responses, and the damage risk mechanisms involved. Measured sound and vibration levels, case history studies, and conditions favorable to damage risk are presented. The paper concludes with recommendations for increasing the damage risk knowledge base to better protect these resources.
The weapon potential of a microbe.
Casadevall, Arturo; Pirofski, Liise-anne
2004-06-01
The designation of a microbe as a potential biological weapon poses the vexing question of how such a decision is made given the many pathogenic microbes that cause disease. Analysis of the properties of microbes that are currently considered biological weapons against humans revealed no obvious relationship to virulence, except that all are pathogenic for humans. Notably, the weapon potential of a microbe rather than its pathogenic properties or virulence appeared to be the major consideration when categorizing certain agents as biological weapons. In an effort to standardize the assessment of the risk that is posed by microbes as biological warfare agents using the basic principles of microbial communicability (defined here as a parameter of transmission) and virulence, a simple formula is proposed for estimating the weapon potential of a microbe.
Food consumption and growth rates of juvenile black carp fed natural and prepared feeds
Hodgins, Nathaniel C.; Schramm, Harold L.; Gerard, Patrick D.
2014-01-01
The introduced mollusciphagic black carp Mylopharyngodon piceus poses a significant threat to native mollusks in temperate waters throughout the northern hemisphere, but consumption rates necessary to estimate the magnitude of impact on mollusks have not been established. We measured food consumption and growth rates for small (77–245 g) and large (466–1,071 g) triploid black carp held individually under laboratory conditions at 20, 25, and 30°C. Daily consumption rates (g food · g wet weight fish−1·d−1·100) of black carp that received prepared feed increased with temperature (small black carp 1.39–1.71; large black carp 1.28–2.10), but temperature-related increases in specific growth rate (100[ln(final weight) - ln(initial weight)]/number of days) only occurred for the large black carp (small black carp −0.02 to 0.19; large black carp 0.16–0.65). Neither daily consumption rates (5.90–6.28) nor specific growth rates (0.05–0.24) differed among temperatures for small black carp fed live snails. The results of these laboratory feeding trials indicate food consumption rates can vary from 289.9 to 349.5 J·g−1·d−1 for 150 g black carp receiving prepared feed, from 268.8 to 441.0 J·g−1·d−1for 800 g black carp receiving prepared feed, and from 84.8 to 90.2 J·g−1·d−1 for 150 g black carp that feed on snails. Applying estimated daily consumption rates to estimated biomass of native mollusks indicates that a relatively low biomass of bla
Pose-free structure from motion using depth from motion constraints.
Zhang, Ji; Boutin, Mireille; Aliaga, Daniel G
2011-10-01
Structure from motion (SFM) is the problem of recovering the geometry of a scene from a stream of images taken from unknown viewpoints. One popular approach to estimate the geometry of a scene is to track scene features on several images and reconstruct their position in 3-D. During this process, the unknown camera pose must also be recovered. Unfortunately, recovering the pose can be an ill-conditioned problem which, in turn, can make the SFM problem difficult to solve accurately. We propose an alternative formulation of the SFM problem with fixed internal camera parameters known a priori. In this formulation, obtained by algebraic variable elimination, the external camera pose parameters do not appear. As a result, the problem is better conditioned in addition to involving much fewer variables. Variable elimination is done in three steps. First, we take the standard SFM equations in projective coordinates and eliminate the camera orientations from the equations. We then further eliminate the camera center positions. Finally, we also eliminate all 3-D point positions coordinates, except for their depths with respect to the camera center, thus obtaining a set of simple polynomial equations of degree two and three. We show that, when there are merely a few points and pictures, these "depth-only equations" can be solved in a global fashion using homotopy methods. We also show that, in general, these same equations can be used to formulate a pose-free cost function to refine SFM solutions in a way that is more accurate than by minimizing the total reprojection error, as done when using the bundle adjustment method. The generalization of our approach to the case of varying internal camera parameters is briefly discussed. © 2011 IEEE
Cost effectiveness of the Oregon quitline "free patch initiative".
Fellows, Jeffrey L; Bush, Terry; McAfee, Tim; Dickerson, John
2007-12-01
We estimated the cost effectiveness of the Oregon tobacco quitline's "free patch initiative" compared to the pre-initiative programme. Using quitline utilisation and cost data from the state, intervention providers and patients, we estimated annual programme use and costs for media promotions and intervention services. We also estimated annual quitline registration calls and the number of quitters and life years saved for the pre-initiative and free patch initiative programmes. Service utilisation and 30-day abstinence at six months were obtained from 959 quitline callers. We compared the cost effectiveness of the free patch initiative (media and intervention costs) to the pre-initiative service offered to insured and uninsured callers. We conducted sensitivity analyses on key programme costs and outcomes by estimating a best case and worst case scenario for each intervention strategy. Compared to the pre-intervention programme, the free patch initiative doubled registered calls, increased quitting fourfold and reduced total costs per quit by $2688. We estimated annual paid media costs were $215 per registered tobacco user for the pre-initiative programme and less than $4 per caller during the free patch initiative. Compared to the pre-initiative programme, incremental quitline promotion and intervention costs for the free patch initiative were $86 (range $22-$353) per life year saved. Compared to the pre-initiative programme, the free patch initiative was a highly cost effective strategy for increasing quitting in the population.
Quantifying cannabis: A field study of marijuana quantity estimation.
Prince, Mark A; Conner, Bradley T; Pearson, Matthew R
2018-06-01
The assessment of marijuana use quantity poses unique challenges. These challenges have limited research efforts on quantity assessments. However, quantity estimates are critical to detecting associations between marijuana use and outcomes. We examined accuracy of marijuana users' estimations of quantities of marijuana they prepared to ingest and predictors of both how much was prepared for a single dose and the degree of (in)accuracy of participants' estimates. We recruited a sample of 128 regular-to-heavy marijuana users for a field study wherein they prepared and estimated quantities of marijuana flower in a joint or a bowl as well as marijuana concentrate using a dab tool. The vast majority of participants overestimated the quantity of marijuana that they used in their preparations. We failed to find robust predictors of estimation accuracy. Self-reported quantity estimates are inaccurate, which has implications for studying the link between quantity and marijuana use outcomes. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
IceVeto: Extended PeV neutrino astronomy in the Southern Hemisphere with IceCube
DOE Office of Scientific and Technical Information (OSTI.GOV)
Auffenberg, Jan; Collaboration: IceCube Collaboration
IceCube, the world's largest high-energy neutrino observatory, built at the South Pole, recently reported evidence of an astrophysical neutrino flux extending to PeV energies in the Southern Hemisphere. This observation raises the question of how the sensitivity in this energy range could be further increased. In the down-going sector, in IceCube's case the Southern Hemisphere, backgrounds from atmospheric muons and neutrinos pose a challenge to the identification of an astrophysical neutrino flux. The IceCube analysis, that led to the evidence for astrophysical neutrinos, is based on an in-ice veto strategy for background rejection. One possibility available to IceCube is themore » concept of an extended surface detector, IceVeto, which could allow the rejection of a large fraction of atmospheric backgrounds, primarily for muons from cosmic ray (CR) air showers as well as from neutrinos in the same air showers. Building on the experience of IceTop/IceCube, possibly the most cost-effective and sensitive way to build IceVeto is as an extension of the IceTop detector, with simple photomultiplier based detector modules for CR air shower detection. Initial simulations and estimates indicate that such a veto detector will significantly increase the sensitivity to an astrophysical flux of ν{sub μ} induced muon tracks in the Southern Hemisphere compared to current analyses. Here we present the motivation and capabilities based on initial simulations. Conceptual ideas for a simplified surface array will be discussed briefly.« less
Cai, Congbo; Chen, Zhong; van Zijl, Peter C.M.
2017-01-01
The reconstruction of MR quantitative susceptibility mapping (QSM) from local phase measurements is an ill posed inverse problem and different regularization strategies incorporating a priori information extracted from magnitude and phase images have been proposed. However, the anatomy observed in magnitude and phase images does not always coincide spatially with that in susceptibility maps, which could give erroneous estimation in the reconstructed susceptibility map. In this paper, we develop a structural feature based collaborative reconstruction (SFCR) method for QSM including both magnitude and susceptibility based information. The SFCR algorithm is composed of two consecutive steps corresponding to complementary reconstruction models, each with a structural feature based l1 norm constraint and a voxel fidelity based l2 norm constraint, which allows both the structure edges and tiny features to be recovered, whereas the noise and artifacts could be reduced. In the M-step, the initial susceptibility map is reconstructed by employing a k-space based compressed sensing model incorporating magnitude prior. In the S-step, the susceptibility map is fitted in spatial domain using weighted constraints derived from the initial susceptibility map from the M-step. Simulations and in vivo human experiments at 7T MRI show that the SFCR method provides high quality susceptibility maps with improved RMSE and MSSIM. Finally, the susceptibility values of deep gray matter are analyzed in multiple head positions, with the supine position most approximate to the gold standard COSMOS result. PMID:27019480
What is the danger of the anomaly zone for empirical phylogenetics?
Huang, Huateng; Knowles, L Lacey
2009-10-01
The increasing number of observations of gene trees with discordant topologies in phylogenetic studies has raised awareness about the problems of incongruence between species trees and gene trees. Moreover, theoretical treatments focusing on the impact of coalescent variance on phylogenetic study have also identified situations where the most probable gene trees are ones that do not match the underlying species tree (i.e., anomalous gene trees [AGTs]). However, although the theoretical proof of the existence of AGTs is alarming, the actual risk that AGTs pose to empirical phylogenetic study is far from clear. Establishing the conditions (i.e., the branch lengths in a species tree) for which AGTs are possible does not address the critical issue of how prevalent they might be. Furthermore, theoretical characterization of the species trees for which AGTs may pose a problem (i.e., the anomaly zone or the species histories for which AGTs are theoretically possible) is based on consideration of just one source of variance that contributes to species tree and gene tree discord-gene lineage coalescence. Yet, empirical data contain another important stochastic component-mutational variance. Estimated gene trees will differ from the underlying gene trees (i.e., the actual genealogy) because of the random process of mutation. Here, we take a simulation approach to investigate the prevalence of AGTs, among estimated gene trees, thereby characterizing the boundaries of the anomaly zone taking into account both coalescent and mutational variances. We also determine the frequency of realized AGTs, which is critical to putting the theoretical work on AGTs into a realistic biological context. Two salient results emerge from this investigation. First, our results show that mutational variance can indeed expand the parameter space (i.e., the relative branch lengths in a species tree) where AGTs might be observed in empirical data. By exploring the underlying cause for the expanded anomaly zone, we identify aspects of empirical data relevant to avoiding the problems that AGTs pose for species tree inference from multilocus data. Second, for the empirical species histories where AGTs are possible, unresolved trees-not AGTs-predominate the pool of estimated gene trees. This result suggests that the risk of AGTs, while they exist in theory, may rarely be realized in practice. By considering the biological realities of both mutational and coalescent variances, the study has refined, and redefined, what the actual challenges are for empirical phylogenetic study of recently diverged taxa that have speciated rapidly-AGTs themselves are unlikely to pose a significant danger to empirical phylogenetic study.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hoegele, W.; Loeschel, R.; Dobler, B.
2011-02-15
Purpose: In this work, a novel stochastic framework for patient positioning based on linac-mounted CB projections is introduced. Based on this formulation, the most probable shifts and rotations of the patient are estimated, incorporating interfractional deformations of patient anatomy and other uncertainties associated with patient setup. Methods: The target position is assumed to be defined by and is stochastically determined from positions of various features such as anatomical landmarks or markers in CB projections, i.e., radiographs acquired with a CB-CT system. The patient positioning problem of finding the target location from CB projections is posed as an inverse problem withmore » prior knowledge and is solved using a Bayesian maximum a posteriori (MAP) approach. The prior knowledge is three-fold and includes the accuracy of an initial patient setup (such as in-room laser and skin marks), the plasticity of the body (relative shifts between target and features), and the feature detection error in CB projections (which may vary depending on specific detection algorithm and feature type). For this purpose, MAP estimators are derived and a procedure of using them in clinical practice is outlined. Furthermore, a rule of thumb is theoretically derived, relating basic parameters of the prior knowledge (initial setup accuracy, plasticity of the body, and number of features) and the parameters of CB data acquisition (number of projections and accuracy of feature detection) to the expected estimation accuracy. Results: MAP estimation can be applied to arbitrary features and detection algorithms. However, to experimentally demonstrate its applicability and to perform the validation of the algorithm, a water-equivalent, deformable phantom with features represented by six 1 mm chrome balls were utilized. These features were detected in the cone beam projections (XVI, Elekta Synergy) by a local threshold method for demonstration purposes only. The accuracy of estimation (strongly varying for different plasticity parameters of the body) agreed with the rule of thumb formula. Moreover, based on this rule of thumb formula, about 20 projections for 6 detectable features seem to be sufficient for a target estimation accuracy of 0.2 cm, even for relatively large feature detection errors with standard deviation of 0.5 cm and spatial displacements of the features with standard deviation of 0.5 cm. Conclusions: The authors have introduced a general MAP-based patient setup algorithm accounting for different sources of uncertainties, which are utilized as the prior knowledge in a transparent way. This new framework can be further utilized for different clinical sites, as well as theoretical developments in the field of patient positioning for radiotherapy.« less
Parameter estimation in plasmonic QED
NASA Astrophysics Data System (ADS)
Jahromi, H. Rangani
2018-03-01
We address the problem of parameter estimation in the presence of plasmonic modes manipulating emitted light via the localized surface plasmons in a plasmonic waveguide at the nanoscale. The emitter that we discuss is the nitrogen vacancy centre (NVC) in diamond modelled as a qubit. Our goal is to estimate the β factor measuring the fraction of emitted energy captured by waveguide surface plasmons. The best strategy to obtain the most accurate estimation of the parameter, in terms of the initial state of the probes and different control parameters, is investigated. In particular, for two-qubit estimation, it is found although we may achieve the best estimation at initial instants by using the maximally entangled initial states, at long times, the optimal estimation occurs when the initial state of the probes is a product one. We also find that decreasing the interqubit distance or increasing the propagation length of the plasmons improve the precision of the estimation. Moreover, decrease of spontaneous emission rate of the NVCs retards the quantum Fisher information (QFI) reduction and therefore the vanishing of the QFI, measuring the precision of the estimation, is delayed. In addition, if the phase parameter of the initial state of the two NVCs is equal to πrad, the best estimation with the two-qubit system is achieved when initially the NVCs are maximally entangled. Besides, the one-qubit estimation has been also analysed in detail. Especially, we show that, using a two-qubit probe, at any arbitrary time, enhances considerably the precision of estimation in comparison with one-qubit estimation.
Bull, R J; Robinson, M; Meier, J R; Stober, J
1982-01-01
Other workers have clearly shown that most, if not all, drinking water in the U.S. contains chemicals that possess mutagenic and/or carcinogenic activity by using bacterial and in vitro methods. In the present work, increased numbers of tumors were observed with samples of organic material isolated from 5 U.S. cities administered as tumor initiators in mouse skin initiation/promotion studies. Only in one case was the result significantly different from control. In studies designed to test whether disinfection practice contributes significantly to the tumor initiating activity found in drinking water mixed results have been obtained. In one experiment, water disinfected by chlorination, ozonation or combined chlorine resulted in a significantly greater number of papillomas when compared to nondisinfected water. In two subsequent experiments, where water was obtained from the Ohio River at different times of the year, no evidence of increased initiating activity was observed with any disinfectant. Analysis of water obtained at the comparable times of the year for total organic halogen, and trihalomethane formation revealed a substantial variation in the formation of these products. Considering the problems such variability poses for estimating risks associated with disinfection by-products, a model system which makes use of commercially obtained humic acid as a substrate for chlorination was investigated using the Ames test. Humic and fulvic acids obtained from two surface waters as well as the commercially obtained humic acid were without activity in TA 1535, TA 1537, TA 1538, TA 98 or TA 100 strains of S. typhimurium. Following treatment with a 0.8 molar ratio of chlorine (based on carbon) significant mutagenic activity was observed with all humic and fulvic acid samples. Comparisons of the specific mutagenic activity of the chlorinated products suggests that the commercial material might provide a useful model for studying health hazards associated with disinfection reactions by-products. PMID:7151763
The Connection Between the Longitudinal Extent of SEP Events and the Properties of Coronal Shocks
NASA Astrophysics Data System (ADS)
Raouafi, N. E.; Lario, D.; Kwon, R. Y.; Riley, P.
2016-12-01
Under the paradigm that the acceleration of solar energetic particles (SEPs) is mainly due to shocks initially driven by coronal mass ejections (CMEs), the observation of a SEP event (generated by a single solar eruption) from distant heliospheric locations poses the question of whether shocks are at the origin of the wide-longitudinal spread of the SEP events. The combination of remote-sensing observations of the corona in extreme ultraviolet (EUV) and white-light (WL) images obtained from multiple vantage points allows us to reconstruct the 3D large-scale structure of the coronal shocks formed around CMEs, and hence estimate the speed of their fronts. On the other hand, coronal magnetohydrodynamic (MHD) simulations allow us to estimate the characteristics of the medium where the shocks propagate and expand. The extent of the shocks and their capability to accelerate SEPs depend on the properties of this medium. We analyze, for the well-studied SEP events of 11 Apr 2013 and 25 Feb 2014 observed by the two STEREO spacecraft and near-Earth observers [Lario et al., 2014, 2016], whether (1) the extent of the shocks as seen in EUV and WL images are determined by the pre-event medium background provided by the MHD simulations, and (2) the properties of the associated shocks at different longitudes are consistent with the thesis that the SEPs observed by the different spacecraft are accelerated and injected by the expanding shocks.
William R. Gould; Debra A. Patla; Rob Daley; Paul Stephen Corn; Blake R. Hossack; Robert Bennetts; Charles R. Peterson
2012-01-01
Monitoring of natural resources is crucial to ecosystem conservation, and yet it can pose many challenges. Annual surveys for amphibian breeding occupancy were conducted in Yellowstone and Grand Teton National Parks over a 4-year period (2006-2009) at two scales: catchments (portions of watersheds) and individual wetland sites. Catchments were selected in a stratified...
ERIC Educational Resources Information Center
Han, Kyung T.; Wells, Craig S.; Sireci, Stephen G.
2012-01-01
Item parameter drift (IPD) occurs when item parameter values change from their original value over time. IPD may pose a serious threat to the fairness and validity of test score interpretations, especially when the goal of the assessment is to measure growth or improvement. In this study, we examined the effect of multidirectional IPD (i.e., some…
Hospital admissions due to norovirus in adult and elderly patients in England.
Haustein, Thomas; Harris, John P; Pebody, Richard; Lopman, Ben A
2009-12-15
Norovirus generally causes a mild illness in the community. However, modeling routine hospital admission statistics, we estimate that approximately 3000 norovirus admissions to English hospitals occur per year, accounting for 0.3% and 0.1% of emergency admissions among elderly and adult patients, respectively, at times of peak activity. These admissions pose a risk for subsequent nosocomial infection outbreaks.
Behavioural Interventions for Self Injurious Behaviour: A Review of Recent Evidence (1998-2008)
ERIC Educational Resources Information Center
Prangnell, Simon J.
2010-01-01
Estimates suggest that up to one quarter of people who have a severe learning disability engage in self injurious behaviour (SIB). SIB poses serious risks, both to the person's physical health and their quality of life. Behavioural approaches have made a contribution to supporting people who engage in SIB, although the last review of these…
Guidance and Control of a Man-Portable Precision Munition Concept
2014-06-01
challenges posed by characteristics of spin-stabilized flight dynamics such as limit cycles, center -of- gravity swerve, instability, and practical...Control Line-of-sight rate and closing velocity estimates are used to form proportional navigation commands in classical guidance schemes...Accelerometers and gyroscopes often supply additional necessary feedback. The accelerometers ensure that the airframe is maneuvering the center of gravity
Piao, Jin-Chun; Kim, Shin-Dug
2017-11-07
Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual-inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual-inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual-inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual-inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.