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
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.
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.
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
Manifolds for pose tracking from monocular video
NASA Astrophysics Data System (ADS)
Basu, Saurav; Poulin, Joshua; Acton, Scott T.
2015-03-01
We formulate a simple human-pose tracking theory from monocular video based on the fundamental relationship between changes in pose and image motion vectors. We investigate the natural embedding of the low-dimensional body pose space into a high-dimensional space of body configurations that behaves locally in a linear manner. The embedded manifold facilitates the decomposition of the image motion vectors into basis motion vector fields of the tangent space to the manifold. This approach benefits from the style invariance of image motion flow vectors, and experiments to validate the fundamental theory show reasonable accuracy (within 4.9 deg of the ground truth).
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.
Human pose tracking from monocular video by traversing an image motion mapped body pose manifold
NASA Astrophysics Data System (ADS)
Basu, Saurav; Poulin, Joshua; Acton, Scott T.
2010-01-01
Tracking human pose from monocular video sequences is a challenging problem due to the large number of independent parameters affecting image appearance and nonlinear relationships between generating parameters and the resultant images. Unlike the current practice of fitting interpolation functions to point correspondences between underlying pose parameters and image appearance, we exploit the relationship between pose parameters and image motion flow vectors in a physically meaningful way. Change in image appearance due to pose change is realized as navigating a low dimensional submanifold of the infinite dimensional Lie group of diffeomorphisms of the two dimensional sphere S2. For small changes in pose, image motion flow vectors lie on the tangent space of the submanifold. Any observed image motion flow vector field is decomposed into the basis motion vector flow fields on the tangent space and combination weights are used to update corresponding pose changes in the different dimensions of the pose parameter space. Image motion flow vectors are largely invariant to style changes in experiments with synthetic and real data where the subjects exhibit variation in appearance and clothing. The experiments demonstrate the robustness of our method (within +/-4° of ground truth) to style variance.
MotionFlow: Visual Abstraction and Aggregation of Sequential Patterns in Human Motion Tracking Data.
Jang, Sujin; Elmqvist, Niklas; Ramani, Karthik
2016-01-01
Pattern analysis of human motions, which is useful in many research areas, requires understanding and comparison of different styles of motion patterns. However, working with human motion tracking data to support such analysis poses great challenges. In this paper, we propose MotionFlow, a visual analytics system that provides an effective overview of various motion patterns based on an interactive flow visualization. This visualization formulates a motion sequence as transitions between static poses, and aggregates these sequences into a tree diagram to construct a set of motion patterns. The system also allows the users to directly reflect the context of data and their perception of pose similarities in generating representative pose states. We provide local and global controls over the partition-based clustering process. To support the users in organizing unstructured motion data into pattern groups, we designed a set of interactions that enables searching for similar motion sequences from the data, detailed exploration of data subsets, and creating and modifying the group of motion patterns. To evaluate the usability of MotionFlow, we conducted a user study with six researchers with expertise in gesture-based interaction design. They used MotionFlow to explore and organize unstructured motion tracking data. Results show that the researchers were able to easily learn how to use MotionFlow, and the system effectively supported their pattern analysis activities, including leveraging their perception and domain knowledge.
Fecal contamination of waters used for recreation, drinking water, and aquaculture is an environmental problem and poses significant human health risks. The problem is often difficult to correct because the source of the contamination cannot be determined with certainty. Run-of...
Fecal contamination of surface waters used for recreation, drinking water and aquaculture are a continuous environmental problem and pose significant human health risks. An alarming amount of the United States rivers/streams (39%), lakes (45%), and estuaries (51%) are not safe f...
MICROBIAL SOURCE TRACKING - 2005
Fecal contamination of surface waters used for recreation, drinking water and aquaculture are a continuous environmental problem and pose significant human health risks. An alarming amount of the United States rivers/streams (39%), lakes (45%), and estuaries (51%) are not safe f...
MICROBIAL SOURCE TRACKING GUIDE
Fecal contamination of surface waters used for recreation, drinking water and aquaculture are a continuous environmental problem and pose significant human health risks. An alarming amount of the United States rivers/streams (39%), lakes (45%), and estuaries (51%) are not safe f...
Fecal contamination of surface waters used for recreation, drinking water and aquaculture are a continuous environmental problem and pose significant human health risks. An alarming amount of the US rivers/streams (39%) lakes (45%), and estuaries (51%) are not safe for fishing an...
MICROBIAL SOURCE TRACKING - 101
Fecal contamination of surface waters used for recreation, drinking water and aquaculture are a continuous environmental problem and pose significant human health risks. Today, a large portion of the United States rivers/streams (39%), lakes (45%), and estuaries (51%) are not saf...
Mosberger, Rafael; Andreasson, Henrik; Lilienthal, Achim J
2014-09-26
This article presents a novel approach for vision-based detection and tracking of humans wearing high-visibility clothing with retro-reflective markers. Addressing industrial applications where heavy vehicles operate in the vicinity of humans, we deploy a customized stereo camera setup with active illumination that allows for efficient detection of the reflective patterns created by the worker's safety garments. After segmenting reflective objects from the image background, the interest regions are described with local image feature descriptors and classified in order to discriminate safety garments from other reflective objects in the scene. In a final step, the trajectories of the detected humans are estimated in 3D space relative to the camera. We evaluate our tracking system in two industrial real-world work environments on several challenging video sequences. The experimental results indicate accurate tracking performance and good robustness towards partial occlusions, body pose variation, and a wide range of different illumination conditions.
Mosberger, Rafael; Andreasson, Henrik; Lilienthal, Achim J.
2014-01-01
This article presents a novel approach for vision-based detection and tracking of humans wearing high-visibility clothing with retro-reflective markers. Addressing industrial applications where heavy vehicles operate in the vicinity of humans, we deploy a customized stereo camera setup with active illumination that allows for efficient detection of the reflective patterns created by the worker's safety garments. After segmenting reflective objects from the image background, the interest regions are described with local image feature descriptors and classified in order to discriminate safety garments from other reflective objects in the scene. In a final step, the trajectories of the detected humans are estimated in 3D space relative to the camera. We evaluate our tracking system in two industrial real-world work environments on several challenging video sequences. The experimental results indicate accurate tracking performance and good robustness towards partial occlusions, body pose variation, and a wide range of different illumination conditions. PMID:25264956
SESSION: EMERGING POLLUTANT ASSESSMENT TECHNIQUES TITLE: BACTERIAL SOURCE TRACKING
Fecal contamination of surface waters used for recreation, drinking water and aquaculture are a continuous environmental problem and pose significant human health risks. An alarming amount of the United States rivers/streams (39%), lakes (45%), and estuaries (51%) are not safe f...
Robust human detection, tracking, and recognition in crowded urban areas
NASA Astrophysics Data System (ADS)
Chen, Hai-Wen; McGurr, Mike
2014-06-01
In this paper, we present algorithms we recently developed to support an automated security surveillance system for very crowded urban areas. In our approach for human detection, the color features are obtained by taking the difference of R, G, B spectrum and converting R, G, B to HSV (Hue, Saturation, Value) space. Morphological patch filtering and regional minimum and maximum segmentation on the extracted features are applied for target detection. The human tracking process approach includes: 1) Color and intensity feature matching track candidate selection; 2) Separate three parallel trackers for color, bright (above mean intensity), and dim (below mean intensity) detections, respectively; 3) Adaptive track gate size selection for reducing false tracking probability; and 4) Forward position prediction based on previous moving speed and direction for continuing tracking even when detections are missed from frame to frame. The Human target recognition is improved with a Super-Resolution Image Enhancement (SRIE) process. This process can improve target resolution by 3-5 times and can simultaneously process many targets that are tracked. Our approach can project tracks from one camera to another camera with a different perspective viewing angle to obtain additional biometric features from different perspective angles, and to continue tracking the same person from the 2nd camera even though the person moved out of the Field of View (FOV) of the 1st camera with `Tracking Relay'. Finally, the multiple cameras at different view poses have been geo-rectified to nadir view plane and geo-registered with Google- Earth (or other GIS) to obtain accurate positions (latitude, longitude, and altitude) of the tracked human for pin-point targeting and for a large area total human motion activity top-view. Preliminary tests of our algorithms indicate than high probability of detection can be achieved for both moving and stationary humans. Our algorithms can simultaneously track more than 100 human targets with averaged tracking period (time length) longer than the performance of the current state-of-the-art.
TRACKING CHLORDANE COMPOSITIONAL AND CHIRAL PROFILES IN SOIL AND VEGETATION. (R828174)
The cycling of chlordane and other persistent organic pollutants through the environment must be comprehensively elucidated to assess adequately the human health risks posed from such contaminants. In this study the compositional and chiral profiles of weathered chlordane resi...
C-arm rotation encoding with accelerometers.
Grzeda, Victor; Fichtinger, Gabor
2010-07-01
Fluoroscopic C-arms are being incorporated in computer-assisted interventions in increasing number. For these applications to work, the relative poses of imaging must be known. To find the pose, tracking methods such as optical cameras, electromagnetic trackers, and radiographic fiducials have been used-all hampered by significant shortcomings. We propose to recover the rotational pose of the C-arm using the angle-sensing ability of accelerometers, by exploiting the capability of the accelerometer to measure tilt angles. By affixing the accelerometer to a C-arm, the accelerometer tracks the C-arm pose during rotations of the C-arm. To demonstrate this concept, a C-arm analogue was constructed with a webcam device affixed to the C-arm model to mimic X-ray imaging. Then, measuring the offset between the accelerometer angle readings to the webcam pose angle, an angle correction equation (ACE) was created to properly tracking the C-arm rotational pose. Several tests were performed on the webcam C-arm model using the ACEs to tracking the primary and secondary angle rotations of the model. We evaluated the capability of linear and polynomial ACEs to tracking the webcam C-arm pose angle for different rotational scenarios. The test results showed that the accelerometer could track the pose of the webcam C-arm model with an accuracy of less than 1.0 degree. The accelerometer was successful in sensing the C-arm's rotation with clinically adequate accuracy in the C-arm webcam model.
On Deming and School Quality: A Conversation with Enid Brown.
ERIC Educational Resources Information Center
Brandt, Ron
1992-01-01
A Deming expert explains that his 14 principles are no recipe but must be combined with the theory of profound knowledge, which poses essential questions and recognizes the importance of human variation, intrinsic motivation, and external rewards. She also debunks grading, formal teacher evaluation, tracking, and decentralized management. (MLH)
A framework for activity detection in wide-area motion imagery
DOE Office of Scientific and Technical Information (OSTI.GOV)
Porter, Reid B; Ruggiero, Christy E; Morrison, Jack D
2009-01-01
Wide-area persistent imaging systems are becoming increasingly cost effective and now large areas of the earth can be imaged at relatively high frame rates (1-2 fps). The efficient exploitation of the large geo-spatial-temporal datasets produced by these systems poses significant technical challenges for image and video analysis and data mining. In recent years there has been significant progress made on stabilization, moving object detection and tracking and automated systems now generate hundreds to thousands of vehicle tracks from raw data, with little human intervention. However, the tracking performance at this scale, is unreliable and average track length is much smallermore » than the average vehicle route. This is a limiting factor for applications which depend heavily on track identity, i.e. tracking vehicles from their points of origin to their final destination. In this paper we propose and investigate a framework for wide-area motion imagery (W AMI) exploitation that minimizes the dependence on track identity. In its current form this framework takes noisy, incomplete moving object detection tracks as input, and produces a small set of activities (e.g. multi-vehicle meetings) as output. The framework can be used to focus and direct human users and additional computation, and suggests a path towards high-level content extraction by learning from the human-in-the-loop.« 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.
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.
Pose-variant facial expression recognition using an embedded image system
NASA Astrophysics Data System (ADS)
Song, Kai-Tai; Han, Meng-Ju; Chang, Shuo-Hung
2008-12-01
In recent years, one of the most attractive research areas in human-robot interaction is automated facial expression recognition. Through recognizing the facial expression, a pet robot can interact with human in a more natural manner. In this study, we focus on the facial pose-variant problem. A novel method is proposed in this paper to recognize pose-variant facial expressions. After locating the face position in an image frame, the active appearance model (AAM) is applied to track facial features. Fourteen feature points are extracted to represent the variation of facial expressions. The distance between feature points are defined as the feature values. These feature values are sent to a support vector machine (SVM) for facial expression determination. The pose-variant facial expression is classified into happiness, neutral, sadness, surprise or anger. Furthermore, in order to evaluate the performance for practical applications, this study also built a low resolution database (160x120 pixels) using a CMOS image sensor. Experimental results show that the recognition rate is 84% with the self-built database.
Face landmark point tracking using LK pyramid optical flow
NASA Astrophysics Data System (ADS)
Zhang, Gang; Tang, Sikan; Li, Jiaquan
2018-04-01
LK pyramid optical flow is an effective method to implement object tracking in a video. It is used for face landmark point tracking in a video in the paper. The landmark points, i.e. outer corner of left eye, inner corner of left eye, inner corner of right eye, outer corner of right eye, tip of a nose, left corner of mouth, right corner of mouth, are considered. It is in the first frame that the landmark points are marked by hand. For subsequent frames, performance of tracking is analyzed. Two kinds of conditions are considered, i.e. single factors such as normalized case, pose variation and slowly moving, expression variation, illumination variation, occlusion, front face and rapidly moving, pose face and rapidly moving, and combination of the factors such as pose and illumination variation, pose and expression variation, pose variation and occlusion, illumination and expression variation, expression variation and occlusion. Global measures and local ones are introduced to evaluate performance of tracking under different factors or combination of the factors. The global measures contain the number of images aligned successfully, average alignment error, the number of images aligned before failure, and the local ones contain the number of images aligned successfully for components of a face, average alignment error for the components. To testify performance of tracking for face landmark points under different cases, tests are carried out for image sequences gathered by us. Results show that the LK pyramid optical flow method can implement face landmark point tracking under normalized case, expression variation, illumination variation which does not affect facial details, pose variation, and that different factors or combination of the factors have different effect on performance of alignment for different landmark points.
Binocular Vision-Based Position and Pose of Hand Detection and Tracking in Space
NASA Astrophysics Data System (ADS)
Jun, Chen; Wenjun, Hou; Qing, Sheng
After the study of image segmentation, CamShift target tracking algorithm and stereo vision model of space, an improved algorithm based of Frames Difference and a new space point positioning model were proposed, a binocular visual motion tracking system was constructed to verify the improved algorithm and the new model. The problem of the spatial location and pose of the hand detection and tracking have been solved.
Robot Tracking of Human Subjects in Field Environments
NASA Technical Reports Server (NTRS)
Graham, Jeffrey; Shillcutt, Kimberly
2003-01-01
Future planetary exploration will involve both humans and robots. Understanding and improving their interaction is a main focus of research in the Intelligent Systems Branch at NASA's Johnson Space Center. By teaming intelligent robots with astronauts on surface extra-vehicular activities (EVAs), safety and productivity can be improved. The EVA Robotic Assistant (ERA) project was established to study the issues of human-robot teams, to develop a testbed robot to assist space-suited humans in exploration tasks, and to experimentally determine the effectiveness of an EVA assistant robot. A companion paper discusses the ERA project in general, its history starting with ASRO (Astronaut-Rover project), and the results of recent field tests in Arizona. This paper focuses on one aspect of the research, robot tracking, in greater detail: the software architecture and algorithms. The ERA robot is capable of moving towards and/or continuously following mobile or stationary targets or sequences of targets. The contributions made by this research include how the low-level pose data is assembled, normalized and communicated, how the tracking algorithm was generalized and implemented, and qualitative performance reports from recent field tests.
NASA Technical Reports Server (NTRS)
Johnson, Nicholas L.
2006-01-01
Since the end of the Apollo program in 1972, human space flight has been restricted to altitudes below 600 km above the Earth s surface with most missions restricted to a ceiling below 400 km. An investigation of the tracked satellite population transiting and influencing the human space flight regime during the past 11 years (equivalent to a full solar cycle) has recently been completed. The overall effects of satellite breakups and solar activity are typically less pronounced in the human space flight regime than other regions of low Earth orbit. As of January 2006 nearly 1500 tracked objects resided in or traversed the human space flight regime, although two-thirds of these objects were in orbits of moderate to high eccentricity, significantly reducing their effect on human space flight safety. During the period investigated, the spatial density of tracked objects in the 350-400 km altitude regime of the International Space Station demonstrated a steady decline, actually decreasing by 50% by the end of the period. On the other hand, the region immediately above 600 km experienced a significant increase in its population density. This regime is important for future risk assessments, since this region represents the reservoir of debris which will influence human space flight safety in the future. The paper seeks to put into sharper perspective the risks posed to human space flight by the tracked satellite population, as well as the influences of solar activity and the effects of compliance with orbital debris mitigation guidelines on human space flight missions. Finally, the methods and successes of characterizing the population of smaller debris at human space flight regimes are addressed.
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%.
Visual Data Mining: An Exploratory Approach to Analyzing Temporal Patterns of Eye Movements
ERIC Educational Resources Information Center
Yu, Chen; Yurovsky, Daniel; Xu, Tian
2012-01-01
Infant eye movements are an important behavioral resource to understand early human development and learning. But the complexity and amount of gaze data recorded from state-of-the-art eye-tracking systems also pose a challenge: how does one make sense of such dense data? Toward this goal, this article describes an interactive approach based on…
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.
Identification of hump highway/rail crossings in Kansas
DOT National Transportation Integrated Search
2003-07-01
Hump crossings or high-profile crossings are a highway/rail intersection (HRI) at which the road surface profile across the rail tracks may pose a risk of a low-clearance vehicle becoming stuck on the tracks. They may also pose a threat to heavy vehi...
Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement
NASA Astrophysics Data System (ADS)
Liu, Dalong; Xu, Lijuan
2018-01-01
In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.
Hybrid markerless tracking of complex articulated motion in golf swings.
Fung, Sim Kwoh; Sundaraj, Kenneth; Ahamed, Nizam Uddin; Kiang, Lam Chee; Nadarajah, Sivadev; Sahayadhas, Arun; Ali, Md Asraf; Islam, Md Anamul; Palaniappan, Rajkumar
2014-04-01
Sports video tracking is a research topic that has attained increasing attention due to its high commercial potential. A number of sports, including tennis, soccer, gymnastics, running, golf, badminton and cricket have been utilised to display the novel ideas in sports motion tracking. The main challenge associated with this research concerns the extraction of a highly complex articulated motion from a video scene. Our research focuses on the development of a markerless human motion tracking system that tracks the major body parts of an athlete straight from a sports broadcast video. We proposed a hybrid tracking method, which consists of a combination of three algorithms (pyramidal Lucas-Kanade optical flow (LK), normalised correlation-based template matching and background subtraction), to track the golfer's head, body, hands, shoulders, knees and feet during a full swing. We then match, track and map the results onto a 2D articulated human stick model to represent the pose of the golfer over time. Our work was tested using two video broadcasts of a golfer, and we obtained satisfactory results. The current outcomes of this research can play an important role in enhancing the performance of a golfer, provide vital information to sports medicine practitioners by providing technically sound guidance on movements and should assist to diminish the risk of golfing injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.
Adaptive relative pose control of spacecraft with model couplings and uncertainties
NASA Astrophysics Data System (ADS)
Sun, Liang; Zheng, Zewei
2018-02-01
The spacecraft pose tracking control problem for an uncertain pursuer approaching to a space target is researched in this paper. After modeling the nonlinearly coupled dynamics for relative translational and rotational motions between two spacecraft, position tracking and attitude synchronization controllers are developed independently by using a robust adaptive control approach. The unknown kinematic couplings, parametric uncertainties, and bounded external disturbances are handled with adaptive updating laws. It is proved via Lyapunov method that the pose tracking errors converge to zero asymptotically. Spacecraft close-range rendezvous and proximity operations are introduced as an example to validate the effectiveness of the proposed control approach.
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.
NASA Astrophysics Data System (ADS)
Chen, Hai-Wen; McGurr, Mike
2016-05-01
We have developed a new way for detection and tracking of human full-body and body-parts with color (intensity) patch morphological segmentation and adaptive thresholding for security surveillance cameras. An adaptive threshold scheme has been developed for dealing with body size changes, illumination condition changes, and cross camera parameter changes. Tests with the PETS 2009 and 2014 datasets show that we can obtain high probability of detection and low probability of false alarm for full-body. Test results indicate that our human full-body detection method can considerably outperform the current state-of-the-art methods in both detection performance and computational complexity. Furthermore, in this paper, we have developed several methods using color features for detection and tracking of human body-parts (arms, legs, torso, and head, etc.). For example, we have developed a human skin color sub-patch segmentation algorithm by first conducting a RGB to YIQ transformation and then applying a Subtractive I/Q image Fusion with morphological operations. With this method, we can reliably detect and track human skin color related body-parts such as face, neck, arms, and legs. Reliable body-parts (e.g. head) detection allows us to continuously track the individual person even in the case that multiple closely spaced persons are merged. Accordingly, we have developed a new algorithm to split a merged detection blob back to individual detections based on the detected head positions. Detected body-parts also allow us to extract important local constellation features of the body-parts positions and angles related to the full-body. These features are useful for human walking gait pattern recognition and human pose (e.g. standing or falling down) estimation for potential abnormal behavior and accidental event detection, as evidenced with our experimental tests. Furthermore, based on the reliable head (face) tacking, we have applied a super-resolution algorithm to enhance the face resolution for improved human face recognition performance.
Technology survey on video face tracking
NASA Astrophysics Data System (ADS)
Zhang, Tong; Gomes, Herman Martins
2014-03-01
With the pervasiveness of monitoring cameras installed in public areas, schools, hospitals, work places and homes, video analytics technologies for interpreting these video contents are becoming increasingly relevant to people's lives. Among such technologies, human face detection and tracking (and face identification in many cases) are particularly useful in various application scenarios. While plenty of research has been conducted on face tracking and many promising approaches have been proposed, there are still significant challenges in recognizing and tracking people in videos with uncontrolled capturing conditions, largely due to pose and illumination variations, as well as occlusions and cluttered background. It is especially complex to track and identify multiple people simultaneously in real time due to the large amount of computation involved. In this paper, we present a survey on literature and software that are published or developed during recent years on the face tracking topic. The survey covers the following topics: 1) mainstream and state-of-the-art face tracking methods, including features used to model the targets and metrics used for tracking; 2) face identification and face clustering from face sequences; and 3) software packages or demonstrations that are available for algorithm development or trial. A number of publically available databases for face tracking are also introduced.
Soft-rigid interaction mechanism towards a lobster-inspired hybrid actuator
NASA Astrophysics Data System (ADS)
Chen, Yaohui; Wan, Fang; Wu, Tong; Song, Chaoyang
2018-01-01
Soft pneumatic actuators (SPAs) are intrinsically light-weight, compliant and therefore ideal to directly interact with humans and be implemented into wearable robotic devices. However, they also pose new challenges in describing and sensing their continuous deformation. In this paper, we propose a hybrid actuator design with bio-inspirations from the lobsters, which can generate reconfigurable bending movements through the internal soft chamber interacting with the external rigid shells. This design with joint and link structures enables us to exactly track its bending configurations that previously posed a significant challenge to soft robots. Analytic models are developed to illustrate the soft-rigid interaction mechanism with experimental validation. A robotic glove using hybrid actuators to assist grasping is assembled to illustrate their potentials in safe human-robot interactions. Considering all the design merits, our work presents a practical approach to the design of next-generation robots capable of achieving both good accuracy and compliance.
Pose tracking for augmented reality applications in outdoor archaeological sites
NASA Astrophysics Data System (ADS)
Younes, Georges; Asmar, Daniel; Elhajj, Imad; Al-Harithy, Howayda
2017-01-01
In recent years, agencies around the world have invested huge amounts of effort toward digitizing many aspects of the world's cultural heritage. Of particular importance is the digitization of outdoor archaeological sites. In the spirit of valorization of this digital information, many groups have developed virtual or augmented reality (AR) computer applications themed around a particular archaeological object. The problem of pose tracking in outdoor AR applications is addressed. Different positional systems are analyzed, resulting in the selection of a monocular camera-based user tracker. The limitations that challenge this technique from map generation, scale, anchoring, to lighting conditions are analyzed and systematically addressed. Finally, as a case study, our pose tracking system is implemented within an AR experience in the Byblos Roman theater in Lebanon.
Robust 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.
Design and implementation of a vision-based hovering and feature tracking algorithm for a quadrotor
NASA Astrophysics Data System (ADS)
Lee, Y. H.; Chahl, J. S.
2016-10-01
This paper demonstrates an approach to the vision-based control of the unmanned quadrotors for hover and object tracking. The algorithms used the Speed Up Robust Features (SURF) algorithm to detect objects. The pose of the object in the image was then calculated in order to pass the pose information to the flight controller. Finally, the flight controller steered the quadrotor to approach the object based on the calculated pose data. The above processes was run using standard onboard resources found in the 3DR Solo quadrotor in an embedded computing environment. The obtained results showed that the algorithm behaved well during its missions, tracking and hovering, although there were significant latencies due to low CPU performance of the onboard image processing system.
Dynamical simulation priors for human motion tracking.
Vondrak, Marek; Sigal, Leonid; Jenkins, Odest Chadwicke
2013-01-01
We propose a simulation-based dynamical motion prior for tracking human motion from video in presence of physical ground-person interactions. Most tracking approaches to date have focused on efficient inference algorithms and/or learning of prior kinematic motion models; however, few can explicitly account for the physical plausibility of recovered motion. Here, we aim to recover physically plausible motion of a single articulated human subject. Toward this end, we propose a full-body 3D physical simulation-based prior that explicitly incorporates a model of human dynamics into the Bayesian filtering framework. We consider the motion of the subject to be generated by a feedback “control loop” in which Newtonian physics approximates the rigid-body motion dynamics of the human and the environment through the application and integration of interaction forces, motor forces, and gravity. Interaction forces prevent physically impossible hypotheses, enable more appropriate reactions to the environment (e.g., ground contacts), and are produced from detected human-environment collisions. Motor forces actuate the body, ensure that proposed pose transitions are physically feasible, and are generated using a motion controller. For efficient inference in the resulting high-dimensional state space, we utilize an exemplar-based control strategy that reduces the effective search space of motor forces. As a result, we are able to recover physically plausible motion of human subjects from monocular and multiview video. We show, both quantitatively and qualitatively, that our approach performs favorably with respect to Bayesian filtering methods with standard motion priors.
Douam, Florian; Hrebikova, Gabriela; Albrecht, Yentli E. Soto; Sellau, Julie; Sharon, Yael; Ding, Qiang; Ploss, Alexander
2017-01-01
Positive-sense RNA viruses pose increasing health and economic concerns worldwide. Our limited understanding of how these viruses interact with their host and how these processes lead to virulence and disease seriously hampers the development of anti-viral strategies. Here, we demonstrate the tracking of (+) and (−) sense viral RNA at single-cell resolution within complex subsets of the human and murine immune system in different mouse models. Our results provide insights into how a prototypic flavivirus, yellow fever virus (YFV-17D), differentially interacts with murine and human hematopoietic cells in these mouse models and how these dynamics influence distinct outcomes of infection. We detect (−) YFV-17D RNA in specific secondary lymphoid compartments and cell subsets not previously recognized as permissive for YFV replication, and we highlight potential virus–host interaction events that could be pivotal in regulating flavivirus virulence and attenuation. PMID:28290449
3-D model-based vehicle tracking.
Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J
2005-10-01
This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.
Optical neural network system for pose determination of spinning satellites
NASA Technical Reports Server (NTRS)
Lee, Andrew; Casasent, David
1990-01-01
An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.
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.
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.
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.
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.
Bellows, Spencer; Smith, Jordan; Mcguire, Peter; Smith, Andrew
2014-01-01
Accurate resuscitation of the critically-ill patient using intravenous fluids and blood products is a challenging, time sensitive task. Ultrasound of the inferior vena cava (IVC) is a non-invasive technique currently used to guide fluid administration, though multiple factors such as variable image quality, time, and operator skill challenge mainstream acceptance. This study represents a first attempt to develop and validate an algorithm capable of automatically tracking and measuring the IVC compared to human operators across a diverse range of image quality. Minimal tracking failures and high levels of agreement between manual and algorithm measurements were demonstrated on good quality videos. Addressing problems such as gaps in the vessel wall and intra-lumen speckle should result in improved performance in average and poor quality videos. Semi-automated measurement of the IVC for the purposes of non-invasive estimation of circulating blood volume poses challenges however is feasible.
User-assisted video segmentation system for visual communication
NASA Astrophysics Data System (ADS)
Wu, Zhengping; Chen, Chun
2002-01-01
Video segmentation plays an important role for efficient storage and transmission in visual communication. In this paper, we introduce a novel video segmentation system using point tracking and contour formation techniques. Inspired by the results from the study of the human visual system, we intend to solve the video segmentation problem into three separate phases: user-assisted feature points selection, feature points' automatic tracking, and contour formation. This splitting relieves the computer of ill-posed automatic segmentation problems, and allows a higher level of flexibility of the method. First, the precise feature points can be found using a combination of user assistance and an eigenvalue-based adjustment. Second, the feature points in the remaining frames are obtained using motion estimation and point refinement. At last, contour formation is used to extract the object, and plus a point insertion process to provide the feature points for next frame's tracking.
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.
Human motion tracking by temporal-spatial local gaussian process experts.
Zhao, Xu; Fu, Yun; Liu, Yuncai
2011-04-01
Human pose estimation via motion tracking systems can be considered as a regression problem within a discriminative framework. It is always a challenging task to model the mapping from observation space to state space because of the high-dimensional characteristic in the multimodal conditional distribution. In order to build the mapping, existing techniques usually involve a large set of training samples in the learning process which are limited in their capability to deal with multimodality. We propose, in this work, a novel online sparse Gaussian Process (GP) regression model to recover 3-D human motion in monocular videos. Particularly, we investigate the fact that for a given test input, its output is mainly determined by the training samples potentially residing in its local neighborhood and defined in the unified input-output space. This leads to a local mixture GP experts system composed of different local GP experts, each of which dominates a mapping behavior with the specific covariance function adapting to a local region. To handle the multimodality, we combine both temporal and spatial information therefore to obtain two categories of local experts. The temporal and spatial experts are integrated into a seamless hybrid system, which is automatically self-initialized and robust for visual tracking of nonlinear human motion. Learning and inference are extremely efficient as all the local experts are defined online within very small neighborhoods. Extensive experiments on two real-world databases, HumanEva and PEAR, demonstrate the effectiveness of our proposed model, which significantly improve the performance of existing models.
The Kinect as an interventional tracking system
NASA Astrophysics Data System (ADS)
Wang, Xiang L.; Stolka, Philipp J.; Boctor, Emad; Hager, Gregory; Choti, Michael
2012-02-01
This work explores the suitability of low-cost sensors for "serious" medical applications, such as tracking of interventional tools in the OR, for simulation, and for education. Although such tracking - i.e. the acquisition of pose data e.g. for ultrasound probes, tissue manipulation tools, needles, but also tissue, bone etc. - is well established, it relies mostly on external devices such as optical or electromagnetic trackers, both of which mandate the use of special markers or sensors attached to each single entity whose pose is to be recorded, and also require their calibration to the tracked entity, i.e. the determination of the geometric relationship between the marker's and the object's intrinsic coordinate frames. The Microsoft Kinect sensor is a recently introduced device for full-body tracking in the gaming market, but it was quickly hacked - due to its wide range of tightly integrated sensors (RGB camera, IR depth and greyscale camera, microphones, accelerometers, and basic actuation) - and used beyond this area. As its field of view and its accuracy are within reasonable usability limits, we describe a medical needle-tracking system for interventional applications based on the Kinect sensor, standard biopsy needles, and no necessary attachments, thus saving both cost and time. Its twin cameras are used as a stereo pair to detect needle-shaped objects, reconstruct their pose in four degrees of freedom, and provide information about the most likely candidate.
The seam visual tracking method for large structures
NASA Astrophysics Data System (ADS)
Bi, Qilin; Jiang, Xiaomin; Liu, Xiaoguang; Cheng, Taobo; Zhu, Yulong
2017-10-01
In this paper, a compact and flexible weld visual tracking method is proposed. Firstly, there was the interference between the visual device and the work-piece to be welded when visual tracking height cannot change. a kind of weld vision system with compact structure and tracking height is researched. Secondly, according to analyze the relative spatial pose between the camera, the laser and the work-piece to be welded and study with the theory of relative geometric imaging, The mathematical model between image feature parameters and three-dimensional trajectory of the assembly gap to be welded is established. Thirdly, the visual imaging parameters of line structured light are optimized by experiment of the weld structure of the weld. Fourth, the interference that line structure light will be scatters at the bright area of metal and the area of surface scratches will be bright is exited in the imaging. These disturbances seriously affect the computational efficiency. The algorithm based on the human eye visual attention mechanism is used to extract the weld characteristics efficiently and stably. Finally, in the experiment, It is verified that the compact and flexible weld tracking method has the tracking accuracy of 0.5mm in the tracking of large structural parts. It is a wide range of industrial application prospects.
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.
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
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.
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
Real Time 3D Facial Movement Tracking Using a Monocular Camera
Dong, Yanchao; Wang, Yanming; Yue, Jiguang; Hu, Zhencheng
2016-01-01
The paper proposes a robust framework for 3D facial movement tracking in real time using a monocular camera. It is designed to estimate the 3D face pose and local facial animation such as eyelid movement and mouth movement. The framework firstly utilizes the Discriminative Shape Regression method to locate the facial feature points on the 2D image and fuses the 2D data with a 3D face model using Extended Kalman Filter to yield 3D facial movement information. An alternating optimizing strategy is adopted to fit to different persons automatically. Experiments show that the proposed framework could track the 3D facial movement across various poses and illumination conditions. Given the real face scale the framework could track the eyelid with an error of 1 mm and mouth with an error of 2 mm. The tracking result is reliable for expression analysis or mental state inference. PMID:27463714
Real Time 3D Facial Movement Tracking Using a Monocular Camera.
Dong, Yanchao; Wang, Yanming; Yue, Jiguang; Hu, Zhencheng
2016-07-25
The paper proposes a robust framework for 3D facial movement tracking in real time using a monocular camera. It is designed to estimate the 3D face pose and local facial animation such as eyelid movement and mouth movement. The framework firstly utilizes the Discriminative Shape Regression method to locate the facial feature points on the 2D image and fuses the 2D data with a 3D face model using Extended Kalman Filter to yield 3D facial movement information. An alternating optimizing strategy is adopted to fit to different persons automatically. Experiments show that the proposed framework could track the 3D facial movement across various poses and illumination conditions. Given the real face scale the framework could track the eyelid with an error of 1 mm and mouth with an error of 2 mm. The tracking result is reliable for expression analysis or mental state inference.
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.
NASA Astrophysics Data System (ADS)
Westfeld, Patrick; Maas, Hans-Gerd; Bringmann, Oliver; Gröllich, Daniel; Schmauder, Martin
2013-11-01
The paper shows techniques for the determination of structured motion parameters from range camera image sequences. The core contribution of the work presented here is the development of an integrated least squares 3D tracking approach based on amplitude and range image sequences to calculate dense 3D motion vector fields. Geometric primitives of a human body model are fitted to time series of range camera point clouds using these vector fields as additional information. Body poses and motion information for individual body parts are derived from the model fit. On the basis of these pose and motion parameters, critical body postures are detected. The primary aim of the study is to automate ergonomic studies for risk assessments regulated by law, identifying harmful movements and awkward body postures in a workplace.
Multiple-Object Tracking in Children: The "Catch the Spies" Task
ERIC Educational Resources Information Center
Trick, L.M.; Jaspers-Fayer, F.; Sethi, N.
2005-01-01
Multiple-object tracking involves simultaneously tracking positions of a number of target-items as they move among distractors. The standard version of the task poses special challenges for children, demanding extended concentration and the ability to distinguish targets from identical-looking distractors, and may thus underestimate children's…
Our self-tracking movement and health literacy: are we really making every moment count?
Vamos, Sandra; Klein, Klaus
2016-08-03
There is a growing movement related to self-tracking in the quest for better health. Why do so many people like to use 'intelligent tools' like shiny sensors or mobile apps to keep an eye on every move? Do they really help us drive sustained healthy behavioral changes? Despite technological advances and product promises, we must remember that technology alone does not facilitate change to optimize health benefits. The purpose of the commentary is to pose the question: How 'health literate' do we have to be to reap the actionable health benefits of self-tracking? Research has revealed the prevalence of limited health literacy across the globe. Health literacy involves a complex set of inter-connected skills, including acting upon health information. This commentary puts attention on health literacy as an essential human tool to better equip people to overcome barriers and use devices to leverage their full potential. © The Author(s) 2016.
Facial recognition in education system
NASA Astrophysics Data System (ADS)
Krithika, L. B.; Venkatesh, K.; Rathore, S.; Kumar, M. Harish
2017-11-01
Human beings exploit emotions comprehensively for conveying messages and their resolution. Emotion detection and face recognition can provide an interface between the individuals and technologies. The most successful applications of recognition analysis are recognition of faces. Many different techniques have been used to recognize the facial expressions and emotion detection handle varying poses. In this paper, we approach an efficient method to recognize the facial expressions to track face points and distances. This can automatically identify observer face movements and face expression in image. This can capture different aspects of emotion and facial expressions.
Human body motion tracking based on quantum-inspired immune cloning algorithm
NASA Astrophysics Data System (ADS)
Han, Hong; Yue, Lichuan; Jiao, Licheng; Wu, Xing
2009-10-01
In a static monocular camera system, to gain a perfect 3D human body posture is a great challenge for Computer Vision technology now. This paper presented human postures recognition from video sequences using the Quantum-Inspired Immune Cloning Algorithm (QICA). The algorithm included three parts. Firstly, prior knowledge of human beings was used, the key joint points of human could be detected automatically from the human contours and skeletons which could be thinning from the contours; And due to the complexity of human movement, a forecasting mechanism of occlusion joint points was addressed to get optimum 2D key joint points of human body; And then pose estimation recovered by optimizing between the 2D projection of 3D human key joint points and 2D detection key joint points using QICA, which recovered the movement of human body perfectly, because this algorithm could acquire not only the global optimal solution, but the local optimal solution.
Sidhu, J. P. S.; Smith, K.; Beale, D. J.; Gyawali, P.; Toze, S.
2015-01-01
Recreational and potable water supplies polluted with human wastewater can pose a direct health risk to humans. Therefore, sensitive detection of human fecal pollution in environmental waters is very important to water quality authorities around the globe. Microbial source tracking (MST) utilizes human fecal markers (HFMs) to detect human wastewater pollution in environmental waters. The concentrations of these markers in raw wastewater are considered important because it is likely that a marker whose concentration is high in wastewater will be more frequently detected in polluted waters. In this study, quantitative PCR (qPCR) assays were used to determine the concentrations of fecal indicator bacteria (FIB) Escherichia coli and Enterococcus spp., HFMs Bacteroides HF183, human adenoviruses (HAdVs), and polyomaviruses (HPyVs) in raw municipal wastewater influent from various climatic zones in Australia. E. coli mean concentrations in pooled human wastewater data sets (from various climatic zones) were the highest (3.2 × 106 gene copies per ml), followed by those of HF183 (8.0 × 105 gene copies per ml) and Enterococcus spp. (3.6 × 105 gene copies per ml). HAdV and HPyV concentrations were 2 to 3 orders of magnitude lower than those of FIB and HF183. Strong positive and negative correlations were observed between the FIB and HFM concentrations within and across wastewater treatment plants (WWTPs). To identify the most sensitive marker of human fecal pollution, environmental water samples were seeded with raw human wastewater. The results from the seeding experiments indicated that Bacteroides HF183 was more sensitive for detecting human fecal pollution than HAdVs and HPyVs. Since the HF183 marker can occasionally be present in nontarget animal fecal samples, it is recommended that HF183 along with a viral marker (HAdVs or HPyVs) be used for tracking human fecal pollution in Australian environmental waters. PMID:26682850
Vision-Aided Inertial Navigation
NASA Technical Reports Server (NTRS)
Roumeliotis, Stergios I. (Inventor); Mourikis, Anastasios I. (Inventor)
2017-01-01
This document discloses, among other things, a system and method for implementing an algorithm to determine pose, velocity, acceleration or other navigation information using feature tracking data. The algorithm has computational complexity that is linear with the number of features tracked.
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
Khan, Zulfiqar Hasan; Gu, Irene Yu-Hua
2013-12-01
This paper proposes a novel Bayesian online learning and tracking scheme for video objects on Grassmann manifolds. Although manifold visual object tracking is promising, large and fast nonplanar (or out-of-plane) pose changes and long-term partial occlusions of deformable objects in video remain a challenge that limits the tracking performance. The proposed method tackles these problems with the main novelties on: 1) online estimation of object appearances on Grassmann manifolds; 2) optimal criterion-based occlusion handling for online updating of object appearances; 3) a nonlinear dynamic model for both the appearance basis matrix and its velocity; and 4) Bayesian formulations, separately for the tracking process and the online learning process, that are realized by employing two particle filters: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in an alternating fashion to mitigate the tracking drift. Experiments using the proposed tracker on videos captured by a single dynamic/static camera have shown robust tracking performance, particularly for scenarios when target objects contain significant nonplanar pose changes and long-term partial occlusions. Comparisons with eight existing state-of-the-art/most relevant manifold/nonmanifold trackers with evaluations have provided further support to the proposed scheme.
B-Mode ultrasound pose recovery via surgical fiducial segmentation and tracking
NASA Astrophysics Data System (ADS)
Asoni, Alessandro; Ketcha, Michael; Kuo, Nathanael; Chen, Lei; Boctor, Emad; Coon, Devin; Prince, Jerry L.
2015-03-01
Ultrasound Doppler imaging may be used to detect blood clots after surgery, a common problem. However, this requires consistent probe positioning over multiple time instances and therefore significant sonographic expertise. Analysis of ultrasound B-mode images of a fiducial implanted at the surgical site offers a landmark to guide a user to the same location repeatedly. We demonstrate that such an implanted fiducial may be successfully detected and tracked to calculate pose and guide a clinician consistently to the site of surgery, potentially reducing the ultrasound experience required for point of care monitoring.
Sidhu, J P S; Ahmed, W; Gernjak, W; Aryal, R; McCarthy, D; Palmer, A; Kolotelo, P; Toze, S
2013-10-01
The concurrence of human sewage contamination in urban stormwater runoff (n=23) from six urban catchments across Australia was assessed by using both microbial source tracking (MST) and chemical source tracking (CST) markers. Out of 23 stormwater samples human adenovirus (HAv), human polyomavirus (HPv) and the sewage-associated markers; Methanobrevibacter smithii nifH and Bacteroides HF183 were detected in 91%, 56%, 43% and 96% of samples, respectively. Similarly, CST markers paracetamol (87%), salicylic acid (78%) acesulfame (96%) and caffeine (91%) were frequently detected. Twenty one samples (91%) were positive for six to eight sewage related MST and CST markers and remaining two samples were positive for five and four markers, respectively. A very good consensus (>91%) observed between the concurrence of the HF183, HAv, acesulfame and caffeine suggests good predictability of the presence of HAv in samples positive for one of the three markers. High prevalence of HAv (91%) also suggests that other enteric viruses may also be present in the stormwater samples which may pose significant health risks. This study underscores the benefits of employing a set of MST and CST markers which could include monitoring for HF183, adenovirus, caffeine and paracetamol to accurately detect human sewage contamination along with credible information on the presence of human enteric viruses, which could be used for more reliable public health risk assessments. Based on the results obtained in this study, it is recommended that some degree of treatment of captured stormwater would be required if it were to be used for non-potable purposes. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.
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.
Managed Relocation of Species: Noah's Ark or Pandora's Box?
NASA Astrophysics Data System (ADS)
Safford, Hugh D.; Hellmann, Jessica J.; McLachlan, Jason; Sax, Dov F.; Schwartz, Mark W.
2009-01-01
Assisted Migration: Evaluating a New Strategy for Species Conservation; Milwaukee, Wisconsin, 1-3 August 2008; The world's human population is growing rapidly. Annually we may now move more earth than natural geological processes, and our dependence on fossil fuels is causing wholesale changes in climate and many ecosystem processes. Although human impacts on the globe have long had major consequences for the Earth's other inhabitants, the current combination of massive habitat change and rapid climate change poses an especially daunting challenge for many species. Rates of anthropogenic global change, from habitat alteration to modifications of the atmosphere, are so high that many species do not possess the capacity to ``track'' these changes through natural dispersal. In addition, ``humanized'' landscapes are now so pervasive in some parts of the globe that natural dispersal corridors have all but completely disappeared.
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.
Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin
2017-11-01
Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.
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.
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.
Real-Time Motion Tracking for Mobile Augmented/Virtual Reality Using Adaptive Visual-Inertial Fusion
Fang, Wei; Zheng, Lianyu; Deng, Huanjun; Zhang, Hongbo
2017-01-01
In mobile augmented/virtual reality (AR/VR), real-time 6-Degree of Freedom (DoF) motion tracking is essential for the registration between virtual scenes and the real world. However, due to the limited computational capacity of mobile terminals today, the latency between consecutive arriving poses would damage the user experience in mobile AR/VR. Thus, a visual-inertial based real-time motion tracking for mobile AR/VR is proposed in this paper. By means of high frequency and passive outputs from the inertial sensor, the real-time performance of arriving poses for mobile AR/VR is achieved. In addition, to alleviate the jitter phenomenon during the visual-inertial fusion, an adaptive filter framework is established to cope with different motion situations automatically, enabling the real-time 6-DoF motion tracking by balancing the jitter and latency. Besides, the robustness of the traditional visual-only based motion tracking is enhanced, giving rise to a better mobile AR/VR performance when motion blur is encountered. Finally, experiments are carried out to demonstrate the proposed method, and the results show that this work is capable of providing a smooth and robust 6-DoF motion tracking for mobile AR/VR in real-time. PMID:28475145
Fang, Wei; Zheng, Lianyu; Deng, Huanjun; Zhang, Hongbo
2017-05-05
In mobile augmented/virtual reality (AR/VR), real-time 6-Degree of Freedom (DoF) motion tracking is essential for the registration between virtual scenes and the real world. However, due to the limited computational capacity of mobile terminals today, the latency between consecutive arriving poses would damage the user experience in mobile AR/VR. Thus, a visual-inertial based real-time motion tracking for mobile AR/VR is proposed in this paper. By means of high frequency and passive outputs from the inertial sensor, the real-time performance of arriving poses for mobile AR/VR is achieved. In addition, to alleviate the jitter phenomenon during the visual-inertial fusion, an adaptive filter framework is established to cope with different motion situations automatically, enabling the real-time 6-DoF motion tracking by balancing the jitter and latency. Besides, the robustness of the traditional visual-only based motion tracking is enhanced, giving rise to a better mobile AR/VR performance when motion blur is encountered. Finally, experiments are carried out to demonstrate the proposed method, and the results show that this work is capable of providing a smooth and robust 6-DoF motion tracking for mobile AR/VR in real-time.
User-assisted visual search and tracking across distributed multi-camera networks
NASA Astrophysics Data System (ADS)
Raja, Yogesh; Gong, Shaogang; Xiang, Tao
2011-11-01
Human CCTV operators face several challenges in their task which can lead to missed events, people or associations, including: (a) data overload in large distributed multi-camera environments; (b) short attention span; (c) limited knowledge of what to look for; and (d) lack of access to non-visual contextual intelligence to aid search. Developing a system to aid human operators and alleviate such burdens requires addressing the problem of automatic re-identification of people across disjoint camera views, a matching task made difficult by factors such as lighting, viewpoint and pose changes and for which absolute scoring approaches are not best suited. Accordingly, we describe a distributed multi-camera tracking (MCT) system to visually aid human operators in associating people and objects effectively over multiple disjoint camera views in a large public space. The system comprises three key novel components: (1) relative measures of ranking rather than absolute scoring to learn the best features for matching; (2) multi-camera behaviour profiling as higher-level knowledge to reduce the search space and increase the chance of finding correct matches; and (3) human-assisted data mining to interactively guide search and in the process recover missing detections and discover previously unknown associations. We provide an extensive evaluation of the greater effectiveness of the system as compared to existing approaches on industry-standard i-LIDS multi-camera data.
Feature extraction algorithm for space targets based on fractal theory
NASA Astrophysics Data System (ADS)
Tian, Balin; Yuan, Jianping; Yue, Xiaokui; Ning, Xin
2007-11-01
In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently. Future space operations can be more economically and reliably executed using machine vision systems, which can meet real time and tracking reliability requirements for image tracking of space surveillance system. Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented. The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC) approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical Morphology. The validity of the proposed method is examined by processing and analyzing images of space targets. The edge extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid method to solve the problems of relative pose for spacecrafts.
NASA Astrophysics Data System (ADS)
Zhang, Haichong K.; Aalamifar, Fereshteh; Boctor, Emad M.
2016-04-01
Synthetic aperture for ultrasound is a technique utilizing a wide aperture in both transmit and receive to enhance the ultrasound image quality. The limitation of synthetic aperture is the maximum available aperture size limit determined by the physical size of ultrasound probe. We propose Synthetic-Tracked Aperture Ultrasound (STRATUS) imaging system to overcome the limitation by extending the beamforming aperture size through ultrasound probe tracking. With a setup involving a robotic arm, the ultrasound probe is moved using the robotic arm, while the positions on a scanning trajectory are tracked in real-time. Data from each pose are synthesized to construct a high resolution image. In previous studies, we have demonstrated the feasibility through phantom experiments. However, various additional factors such as real-time data collection or motion artifacts should be taken into account when the in vivo target becomes the subject. In this work, we build a robot-based STRATUS imaging system with continuous data collection capability considering the practical implementation. A curvilinear array is used instead of a linear array to benefit from its wider capture angle. We scanned human forearms under two scenarios: one submerged the arm in the water tank under 10 cm depth, and the other directly scanned the arm from the surface. The image contrast improved 5.51 dB, and 9.96 dB for the underwater scan and the direct scan, respectively. The result indicates the practical feasibility of STRATUS imaging system, and the technique can be potentially applied to the wide range of human body.
Tracking the Careers of Graduates: A New Agenda for Graduate Schools
ERIC Educational Resources Information Center
Stewart, Debra W.
2013-01-01
As candidates in the 2012 election debated issues raised by the state of the US economy, unemployment statistics and job creation took center stage. The problems under discussion posed (and continue to pose) a particularly clear and pressing challenge to the nation's graduate schools. While the US enjoys a reputation for having the most dynamic…
Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery
Ma, Yalong; Wu, Xinkai; Yu, Guizhen; Xu, Yongzheng; Wang, Yunpeng
2016-01-01
Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-resolution of imagery, platform motion, image instability and the relatively small size of the objects. This research tackles these challenges by proposing a pedestrian detection and tracking system. A two-stage blob-based approach is first developed for pedestrian detection. This approach first extracts pedestrian blobs using the regional gradient feature and geometric constraints filtering and then classifies the detected blobs by using a linear Support Vector Machine (SVM) with a hybrid descriptor, which sophisticatedly combines Histogram of Oriented Gradient (HOG) and Discrete Cosine Transform (DCT) features in order to achieve accurate detection. This research further proposes an approach for pedestrian tracking. This approach employs the feature tracker with the update of detected pedestrian location to track pedestrian objects from the registered videos and extracts the motion trajectory data. The proposed detection and tracking approaches have been evaluated by multiple different datasets, and the results illustrate the effectiveness of the proposed methods. This research is expected to significantly benefit many transportation applications, such as the multimodal traffic performance measure, pedestrian behavior study and pedestrian-vehicle crash analysis. Future work will focus on using fused thermal and visual images to further improve the detection efficiency and effectiveness. PMID:27023564
Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery.
Ma, Yalong; Wu, Xinkai; Yu, Guizhen; Xu, Yongzheng; Wang, Yunpeng
2016-03-26
Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-resolution of imagery, platform motion, image instability and the relatively small size of the objects. This research tackles these challenges by proposing a pedestrian detection and tracking system. A two-stage blob-based approach is first developed for pedestrian detection. This approach first extracts pedestrian blobs using the regional gradient feature and geometric constraints filtering and then classifies the detected blobs by using a linear Support Vector Machine (SVM) with a hybrid descriptor, which sophisticatedly combines Histogram of Oriented Gradient (HOG) and Discrete Cosine Transform (DCT) features in order to achieve accurate detection. This research further proposes an approach for pedestrian tracking. This approach employs the feature tracker with the update of detected pedestrian location to track pedestrian objects from the registered videos and extracts the motion trajectory data. The proposed detection and tracking approaches have been evaluated by multiple different datasets, and the results illustrate the effectiveness of the proposed methods. This research is expected to significantly benefit many transportation applications, such as the multimodal traffic performance measure, pedestrian behavior study and pedestrian-vehicle crash analysis. Future work will focus on using fused thermal and visual images to further improve the detection efficiency and effectiveness.
Adaptive object tracking via both positive and negative models matching
NASA Astrophysics Data System (ADS)
Li, Shaomei; Gao, Chao; Wang, Yawen
2015-03-01
To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as abinary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm can not only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-01-07
... and obtaining input from supply chain partners on attributes and standards for the identification... protecting public health by securing the drug supply chain against the introduction of counterfeit and other... supply chain and protecting consumers from the threats posed by counterfeit drugs. The ability to track...
3-D model-based tracking for UAV indoor localization.
Teulière, Céline; Marchand, Eric; Eck, Laurent
2015-05-01
This paper proposes a novel model-based tracking approach for 3-D localization. One main difficulty of standard model-based approach lies in the presence of low-level ambiguities between different edges. In this paper, given a 3-D model of the edges of the environment, we derive a multiple hypotheses tracker which retrieves the potential poses of the camera from the observations in the image. We also show how these candidate poses can be integrated into a particle filtering framework to guide the particle set toward the peaks of the distribution. Motivated by the UAV indoor localization problem where GPS signal is not available, we validate the algorithm on real image sequences from UAV flights.
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.
Challenges in Requirements Engineering: A Research Agenda for Conceptual Modeling
NASA Astrophysics Data System (ADS)
March, Salvatore T.; Allen, Gove N.
Domains for which information systems are developed deal primarily with social constructions—conceptual objects and attributes created by human intentions and for human purposes. Information systems play an active role in these domains. They document the creation of new conceptual objects, record and ascribe values to their attributes, initiate actions within the domain, track activities performed, and infer conclusions based on the application of rules that govern how the domain is affected when socially-defined and identified causal events occur. Emerging applications of information technologies evaluate such business rules, learn from experience, and adapt to changes in the domain. Conceptual modeling grammars aimed at representing their system requirements must include conceptual objects, socially-defined events, and the rules pertaining to them. We identify challenges to conceptual modeling research and pose an ontology of the artificial as a step toward meeting them.
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.
Point Target Detection in IR Image Sequences using Spatio-Temporal Hypotheses Testing
1999-02-01
incorporate temporal as well as spatial infor- mation, they are often referred to as \\ track before detect " algorithms. The standard approach was to pose the...6, 3]. A drawback of these track - before - detect techniques is that they are very computationally intensive since the entire 3-D space must be ltered
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.
Real-Time 3D Tracking and Reconstruction on Mobile Phones.
Prisacariu, Victor Adrian; Kähler, Olaf; Murray, David W; Reid, Ian D
2015-05-01
We present a novel framework for jointly tracking a camera in 3D and reconstructing the 3D model of an observed object. Due to the region based approach, our formulation can handle untextured objects, partial occlusions, motion blur, dynamic backgrounds and imperfect lighting. Our formulation also allows for a very efficient implementation which achieves real-time performance on a mobile phone, by running the pose estimation and the shape optimisation in parallel. We use a level set based pose estimation but completely avoid the, typically required, explicit computation of a global distance. This leads to tracking rates of more than 100 Hz on a desktop PC and 30 Hz on a mobile phone. Further, we incorporate additional orientation information from the phone's inertial sensor which helps us resolve the tracking ambiguities inherent to region based formulations. The reconstruction step first probabilistically integrates 2D image statistics from selected keyframes into a 3D volume, and then imposes coherency and compactness using a total variational regularisation term. The global optimum of the overall energy function is found using a continuous max-flow algorithm and we show that, similar to tracking, the integration of per voxel posteriors instead of likelihoods improves the precision and accuracy of the reconstruction.
Cryptosporidium source tracking in the Potomac River watershed.
Yang, Wenli; Chen, Plato; Villegas, Eric N; Landy, Ronald B; Kanetsky, Charles; Cama, Vitaliano; Dearen, Theresa; Schultz, Cherie L; Orndorff, Kenneth G; Prelewicz, Gregory J; Brown, Miranda H; Young, Kim Roy; Xiao, Lihua
2008-11-01
To better characterize Cryptosporidium in the Potomac River watershed, a PCR-based genotyping tool was used to analyze 64 base flow and 28 storm flow samples from five sites in the watershed. These sites included two water treatment plant intakes, as well as three upstream sites, each associated with a different type of land use. The uses, including urban wastewater, agricultural (cattle) wastewater, and wildlife, posed different risks in terms of the potential contribution of Cryptosporidium oocysts to the source water. Cryptosporidium was detected in 27 base flow water samples and 23 storm flow water samples. The most frequently detected species was C. andersoni (detected in 41 samples), while 14 other species or genotypes, almost all wildlife associated, were occasionally detected. The two common human-pathogenic species, C. hominis and C. parvum, were not detected. Although C. andersoni was common at all four sites influenced by agriculture, it was largely absent at the urban wastewater site. There were very few positive samples as determined by Environmental Protection Agency method 1623 at any site; only 8 of 90 samples analyzed (9%) were positive for Cryptosporidium as determined by microscopy. The genotyping results suggest that many of the Cryptosporidium oocysts in the water treatment plant source waters were from old calves and adult cattle and might not pose a significant risk to human health.
Temporal and Location Based RFID Event Data Management and Processing
NASA Astrophysics Data System (ADS)
Wang, Fusheng; Liu, Peiya
Advance of sensor and RFID technology provides significant new power for humans to sense, understand and manage the world. RFID provides fast data collection with precise identification of objects with unique IDs without line of sight, thus it can be used for identifying, locating, tracking and monitoring physical objects. Despite these benefits, RFID poses many challenges for data processing and management. RFID data are temporal and history oriented, multi-dimensional, and carrying implicit semantics. Moreover, RFID applications are heterogeneous. RFID data management or data warehouse systems need to support generic and expressive data modeling for tracking and monitoring physical objects, and provide automated data interpretation and processing. We develop a powerful temporal and location oriented data model for modeling and queryingRFID data, and a declarative event and rule based framework for automated complex RFID event processing. The approach is general and can be easily adapted for different RFID-enabled applications, thus significantly reduces the cost of RFID data integration.
Impedance modulation and feedback corrections in tracking targets of variable size and frequency.
Selen, Luc P J; van Dieën, Jaap H; Beek, Peter J
2006-11-01
Humans are able to adjust the accuracy of their movements to the demands posed by the task at hand. The variability in task execution caused by the inherent noisiness of the neuromuscular system can be tuned to task demands by both feedforward (e.g., impedance modulation) and feedback mechanisms. In this experiment, we studied both mechanisms, using mechanical perturbations to estimate stiffness and damping as indices of impedance modulation and submovement scaling as an index of feedback driven corrections. Eight subjects tracked three differently sized targets (0.0135, 0.0270, and 0.0405 rad) moving at three different frequencies (0.20, 0.25, and 0.33 Hz). Movement variability decreased with both decreasing target size and movement frequency, whereas stiffness and damping increased with decreasing target size, independent of movement frequency. These results are consistent with the theory that mechanical impedance acts as a filter of noisy neuromuscular signals but challenge stochastic theories of motor control that do not account for impedance modulation and only partially for feedback control. Submovements during unperturbed cycles were quantified in terms of their gain, i.e., the slope between their duration and amplitude in the speed profile. Submovement gain decreased with decreasing movement frequency and increasing target size. The results were interpreted to imply that submovement gain is related to observed tracking errors and that those tracking errors are expressed in units of target size. We conclude that impedance and submovement gain modulation contribute additively to tracking accuracy.
Feuerstein, Marco; Reichl, Tobias; Vogel, Jakob; Traub, Joerg; Navab, Nassir
2009-06-01
Electromagnetic tracking is currently one of the most promising means of localizing flexible endoscopic instruments such as flexible laparoscopic ultrasound transducers. However, electromagnetic tracking is also susceptible to interference from ferromagnetic material, which distorts the magnetic field and leads to tracking errors. This paper presents new methods for real-time online detection and reduction of dynamic electromagnetic tracking errors when localizing a flexible laparoscopic ultrasound transducer. We use a hybrid tracking setup to combine optical tracking of the transducer shaft and electromagnetic tracking of the flexible transducer tip. A novel approach of modeling the poses of the transducer tip in relation to the transducer shaft allows us to reliably detect and significantly reduce electromagnetic tracking errors. For detecting errors of more than 5 mm, we achieved a sensitivity and specificity of 91% and 93%, respectively. Initial 3-D rms error of 6.91 mm were reduced to 3.15 mm.
Experimental and Theoretical Results in Output Trajectory Redesign for Flexible Structures
NASA Technical Reports Server (NTRS)
Dewey, J. S.; Leang, K.; Devasia, S.
1998-01-01
In this paper we study the optimal redesign of output trajectories for linear invertible systems. This is particularly important for tracking control of flexible structures because the input-state trajectores, that achieve tracking of the required output may cause excessive vibrations in the structure. We pose and solve this problem, in the context of linear systems, as the minimization of a quadratic cost function. The theory is developed and applied to the output tracking of a flexible structure and experimental results are presented.
Hughes, B; Beale, D J; Dennis, P G; Cook, S; Ahmed, W
2017-04-15
Detection of human wastewater contamination in recreational waters is of critical importance to regulators due to the risks posed to public health. To identify such risks, human wastewater-associated microbial source tracking (MST) markers have been developed. At present, however, a greater understanding of the suitability of these markers for the detection of diluted human wastewater in environmental waters is necessary to predict risk. Here, we compared the process limit of detection (PLOD) and process limit of quantification (PLOQ) of six human wastewater-associated MST markers ( Bacteroides HF183 [HF183], Escherichia coli H8 [EC H8], Methanobrevibacter smithii nifH , human adenovirus [HAdV], human polyomavirus [HPyV], and pepper mild mottle virus [PMMoV]) in relation to a fecal indicator bacterium (FIB), Enterococcus sp. 23S rRNA (ENT 23S), and three enteric viruses (human adenovirus serotypes 40/41 [HAdV 40/41], human norovirus [HNoV], and human enterovirus [EV]) in beach water samples seeded with raw and secondary-treated wastewater. Among the six MST markers tested, HF183 was the most sensitive measure of human fecal pollution and was quantifiable up to dilutions of 10 -6 and 10 -4 for beach water samples seeded with raw and secondary-treated wastewater, respectively. Other markers and enteric viruses were detected at various dilutions (10 -1 to 10 -5 ). These MST markers, FIB, and enteric viruses were then quantified in beach water ( n = 12) and sand samples ( n = 12) from South East Queensland (SEQ), Australia, to estimate the levels of human fecal pollution. Of the 12 sites examined, beach water and sand samples from several sites had quantifiable concentrations of HF183 and PMMoV markers. Overall, our results indicate that while HF183 is the most sensitive measure of human fecal pollution, it should be used in conjunction with a conferring viral marker to avoid overestimating the risk of gastrointestinal illness. IMPORTANCE MST is an effective tool to help utilities and regulators improve recreational water quality around the globe. Human fecal pollution poses significant public health risks compared to animal fecal pollution. Several human wastewater-associated markers have been developed and used for MST field studies. However, a head-to-head comparison in terms of their performance to detect diluted human fecal pollution in recreational water is lacking. In this study, we cross-compared the performance of six human wastewater-associated markers in relation to FIB and enteric viruses in beach water samples seeded with raw and secondary-treated wastewater. The results of this study will provide guidance to regulators and utilities on the appropriate application of MST markers for tracking the sources of human fecal pollution in environmental waters and confer human health risks. Copyright © 2017 American Society for Microbiology.
Hughes, B.; Beale, D. J.; Dennis, P. G.; Cook, S.
2017-01-01
ABSTRACT Detection of human wastewater contamination in recreational waters is of critical importance to regulators due to the risks posed to public health. To identify such risks, human wastewater-associated microbial source tracking (MST) markers have been developed. At present, however, a greater understanding of the suitability of these markers for the detection of diluted human wastewater in environmental waters is necessary to predict risk. Here, we compared the process limit of detection (PLOD) and process limit of quantification (PLOQ) of six human wastewater-associated MST markers (Bacteroides HF183 [HF183], Escherichia coli H8 [EC H8], Methanobrevibacter smithii nifH, human adenovirus [HAdV], human polyomavirus [HPyV], and pepper mild mottle virus [PMMoV]) in relation to a fecal indicator bacterium (FIB), Enterococcus sp. 23S rRNA (ENT 23S), and three enteric viruses (human adenovirus serotypes 40/41 [HAdV 40/41], human norovirus [HNoV], and human enterovirus [EV]) in beach water samples seeded with raw and secondary-treated wastewater. Among the six MST markers tested, HF183 was the most sensitive measure of human fecal pollution and was quantifiable up to dilutions of 10−6 and 10−4 for beach water samples seeded with raw and secondary-treated wastewater, respectively. Other markers and enteric viruses were detected at various dilutions (10−1 to 10−5). These MST markers, FIB, and enteric viruses were then quantified in beach water (n = 12) and sand samples (n = 12) from South East Queensland (SEQ), Australia, to estimate the levels of human fecal pollution. Of the 12 sites examined, beach water and sand samples from several sites had quantifiable concentrations of HF183 and PMMoV markers. Overall, our results indicate that while HF183 is the most sensitive measure of human fecal pollution, it should be used in conjunction with a conferring viral marker to avoid overestimating the risk of gastrointestinal illness. IMPORTANCE MST is an effective tool to help utilities and regulators improve recreational water quality around the globe. Human fecal pollution poses significant public health risks compared to animal fecal pollution. Several human wastewater-associated markers have been developed and used for MST field studies. However, a head-to-head comparison in terms of their performance to detect diluted human fecal pollution in recreational water is lacking. In this study, we cross-compared the performance of six human wastewater-associated markers in relation to FIB and enteric viruses in beach water samples seeded with raw and secondary-treated wastewater. The results of this study will provide guidance to regulators and utilities on the appropriate application of MST markers for tracking the sources of human fecal pollution in environmental waters and confer human health risks. PMID:28159789
Working and Learning with Knowledge in the Lobes of a Humanoid's Mind
NASA Technical Reports Server (NTRS)
Ambrose, Robert; Savely, Robert; Bluethmann, William; Kortenkamp, David
2003-01-01
Humanoid class robots must have sufficient dexterity to assist people and work in an environment designed for human comfort and productivity. This dexterity, in particular the ability to use tools, requires a cognitive understanding of self and the world that exceeds contemporary robotics. Our hypothesis is that the sense-think-act paradigm that has proven so successful for autonomous robots is missing one or more key elements that will be needed for humanoids to meet their full potential as autonomous human assistants. This key ingredient is knowledge. The presented work includes experiments conducted on the Robonaut system, a NASA and the Defense Advanced research Projects Agency (DARPA) joint project, and includes collaborative efforts with a DARPA Mobile Autonomous Robot Software technical program team of researchers at NASA, MIT, USC, NRL, UMass and Vanderbilt. The paper reports on results in the areas of human-robot interaction (human tracking, gesture recognition, natural language, supervised control), perception (stereo vision, object identification, object pose estimation), autonomous grasping (tactile sensing, grasp reflex, grasp stability) and learning (human instruction, task level sequences, and sensorimotor association).
Human silhouette matching based on moment invariants
NASA Astrophysics Data System (ADS)
Sun, Yong-Chao; Qiu, Xian-Jie; Xia, Shi-Hong; Wang, Zhao-Qi
2005-07-01
This paper aims to apply the method of silhouette matching based on moment invariants to infer the human motion parameters from video sequences of single monocular uncalibrated camera. Currently, there are two ways of tracking human motion: Marker and Markerless. While a hybrid framework is introduced in this paper to recover the input video contents. A standard 3D motion database is built up by marker technique in advance. Given a video sequences, human silhouettes are extracted as well as the viewpoint information of the camera which would be utilized to project the standard 3D motion database onto the 2D one. Therefore, the video recovery problem is formulated as a matching issue of finding the most similar body pose in standard 2D library with the one in video image. The framework is applied to the special trampoline sport where we can obtain the complicated human motion parameters in the single camera video sequences, and a lot of experiments are demonstrated that this approach is feasible in the field of monocular video-based 3D motion reconstruction.
Recognition of human activity characteristics based on state transitions modeling technique
NASA Astrophysics Data System (ADS)
Elangovan, Vinayak; Shirkhodaie, Amir
2012-06-01
Human Activity Discovery & Recognition (HADR) is a complex, diverse and challenging task but yet an active area of ongoing research in the Department of Defense. By detecting, tracking, and characterizing cohesive Human interactional activity patterns, potential threats can be identified which can significantly improve situation awareness, particularly, in Persistent Surveillance Systems (PSS). Understanding the nature of such dynamic activities, inevitably involves interpretation of a collection of spatiotemporally correlated activities with respect to a known context. In this paper, we present a State Transition model for recognizing the characteristics of human activities with a link to a prior contextbased ontology. Modeling the state transitions between successive evidential events determines the activities' temperament. The proposed state transition model poses six categories of state transitions including: Human state transitions of Object handling, Visibility, Entity-entity relation, Human Postures, Human Kinematics and Distance to Target. The proposed state transition model generates semantic annotations describing the human interactional activities via a technique called Casual Event State Inference (CESI). The proposed approach uses a low cost kinect depth camera for indoor and normal optical camera for outdoor monitoring activities. Experimental results are presented here to demonstrate the effectiveness and efficiency of the proposed technique.
Lineage tracing of genome-edited alleles reveals high fidelity axolotl limb regeneration.
Flowers, Grant Parker; Sanor, Lucas D; Crews, Craig M
2017-09-16
Salamanders are unparalleled among tetrapods in their ability to regenerate many structures, including entire limbs, and the study of this ability may provide insights into human regenerative therapies. The complex structure of the limb poses challenges to the investigation of the cellular and molecular basis of its regeneration. Using CRISPR/Cas, we genetically labelled unique cell lineages within the developing axolotl embryo and tracked the frequency of each lineage within amputated and fully regenerated limbs. This allowed us, for the first time, to assess the contributions of multiple low frequency cell lineages to the regenerating limb at once. Our comparisons reveal that regenerated limbs are high fidelity replicas of the originals even after repeated amputations.
NASA Astrophysics Data System (ADS)
Engelhardt, Sandy; Kolb, Silvio; De Simone, Raffaele; Karck, Matthias; Meinzer, Hans-Peter; Wolf, Ivo
2016-03-01
Mitral valve annuloplasty describes a surgical procedure where an artificial prosthesis is sutured onto the anatomical structure of the mitral annulus to re-establish the valve's functionality. Choosing an appropriate commercially available ring size and shape is a difficult decision the surgeon has to make intraoperatively according to his experience. In our augmented-reality framework, digitalized ring models are superimposed onto endoscopic image streams without using any additional hardware. To place the ring model on the proper position within the endoscopic image plane, a pose estimation is performed that depends on the localization of sutures placed by the surgeon around the leaflet origins and punctured through the stiffer structure of the annulus. In this work, the tissue penetration points are tracked by the real-time capable Lucas Kanade optical flow algorithm. The accuracy and robustness of this tracking algorithm is investigated with respect to the question whether outliers influence the subsequent pose estimation. Our results suggest that optical flow is very stable for a variety of different endoscopic scenes and tracking errors do not affect the position of the superimposed virtual objects in the scene, making this approach a viable candidate for annuloplasty augmented reality-enhanced decision support.
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.
Hawaiian lavas: a window into mantle dynamics
NASA Astrophysics Data System (ADS)
Jones, Tim; Davies, Rhodri; Campbell, Ian
2017-04-01
The emergence of double track volcanism at Hawaii has traditionally posed two problems: (i) the physical emergence of two parallel chains of volcanoes at around 3 Ma, named the Loa and Kea tracks after the largest volcanoes in their sequence, and (ii) the systematic geochemical differences between the erupted lavas along each track. In this study, we dissolve this distinction by providing a geodynamical explanation for the physical emergence of double track volcanism at 3 Ma and use numerical models of the Hawaiian plume to illustrate how this process naturally leads to each volcanic track sampling distinct mantle compositions, which accounts for much of the geochemical characteristics of the Loa and Kea trends.
Gorham, T J; Lee, J
2016-05-01
Canada geese (Branta canadensis) faeces have been shown to contain pathogenic protozoa and bacteria in numerous studies over the past 15 years. Further, increases in both the Canada geese populations and their ideal habitat requirements in the United States (US) translate to a greater presence of these human pathogens in public areas, such as recreational freshwater beaches. Combining these factors, the potential health risk posed by Canada geese faeces at freshwater beaches presents an emerging public health issue that warrants further study. Here, literature concerning human pathogens in Canada geese faeces is reviewed and the potential impacts these pathogens may have on human health are discussed. Pathogens of potential concern include Campylobacter jejuni, Salmonella Typhimurium, Listeria monocytogenes, Helicobacter canadensis, Arcobacter spp., Enterohemorragic Escherichia coli pathogenic strains, Chlamydia psitacci, Cryptosporidium parvum and Giardia lamblia. Scenarios presenting potential exposure to pathogens eluted from faeces include bathers swimming in lakes, children playing with wet and dry sand impacted by geese droppings and other common recreational activities associated with public beaches. Recent recreational water-associated disease outbreaks in the US support the plausibility for some of these pathogens, including Cryptosporidium spp. and C. jejuni, to cause human illness in this setting. In view of these findings and the uncertainties associated with the real health risk posed by Canada geese faecal pathogens to users of freshwater lakes, it is recommended that beach managers use microbial source tracking and conduct a quantitative microbial risk assessment to analyse the local impact of Canada geese on microbial water quality during their decision-making process in beach and watershed management. © 2015 Blackwell Verlag GmbH.
NASA Technical Reports Server (NTRS)
Adams, Robert B.; LaPointe, Michael; Wilks, Rod; Allen, Brian
2009-01-01
This poster reviews the planning and design for an integrated architecture for characterization, mitigation, scientific evaluation and resource utilization of near earth objects. This includes tracks to observe and characterize the nature of the threat posed by a NEO, and deflect if a significant threat is posed. The observation stack can also be used for a more complete scientific analysis of the NEO.
Gesture-controlled interfaces for self-service machines and other applications
NASA Technical Reports Server (NTRS)
Cohen, Charles J. (Inventor); Jacobus, Charles J. (Inventor); Paul, George (Inventor); Beach, Glenn (Inventor); Foulk, Gene (Inventor); Obermark, Jay (Inventor); Cavell, Brook (Inventor)
2004-01-01
A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines.
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.
NASA Astrophysics Data System (ADS)
House, Rachael; Lasso, Andras; Harish, Vinyas; Baum, Zachary; Fichtinger, Gabor
2017-03-01
PURPOSE: Optical pose tracking of medical instruments is often used in image-guided interventions. Unfortunately, compared to commonly used computing devices, optical trackers tend to be large, heavy, and expensive devices. Compact 3D vision systems, such as Intel RealSense cameras can capture 3D pose information at several magnitudes lower cost, size, and weight. We propose to use Intel SR300 device for applications where it is not practical or feasible to use conventional trackers and limited range and tracking accuracy is acceptable. We also put forward a vertebral level localization application utilizing the SR300 to reduce risk of wrong-level surgery. METHODS: The SR300 was utilized as an object tracker by extending the PLUS toolkit to support data collection from RealSense cameras. Accuracy of the camera was tested by comparing to a high-accuracy optical tracker. CT images of a lumbar spine phantom were obtained and used to create a 3D model in 3D Slicer. The SR300 was used to obtain a surface model of the phantom. Markers were attached to the phantom and a pointer and tracked using Intel RealSense SDK's built-in object tracking feature. 3D Slicer was used to align CT image with phantom using landmark registration and display the CT image overlaid on the optical image. RESULTS: Accuracy of the camera yielded a median position error of 3.3mm (95th percentile 6.7mm) and orientation error of 1.6° (95th percentile 4.3°) in a 20x16x10cm workspace, constantly maintaining proper marker orientation. The model and surface correctly aligned demonstrating the vertebral level localization application. CONCLUSION: The SR300 may be usable for pose tracking in medical procedures where limited accuracy is acceptable. Initial results suggest the SR300 is suitable for vertebral level localization.
40 CFR 159.188 - Failure of performance information.
Code of Federal Regulations, 2014 CFR
2014-07-01
... for control of animals that pose a risk to human health, including any of the public health pesticides... Information § 159.188 Failure of performance information. (a) Microorganisms that pose a risk to human health... pesticide to perform as claimed involved the use against microorganisms which may pose a risk to human...
40 CFR 159.188 - Failure of performance information.
Code of Federal Regulations, 2011 CFR
2011-07-01
... for control of animals that pose a risk to human health, including any of the public health pesticides... Information § 159.188 Failure of performance information. (a) Microorganisms that pose a risk to human health... pesticide to perform as claimed involved the use against microorganisms which may pose a risk to human...
40 CFR 159.188 - Failure of performance information.
Code of Federal Regulations, 2012 CFR
2012-07-01
... for control of animals that pose a risk to human health, including any of the public health pesticides... Information § 159.188 Failure of performance information. (a) Microorganisms that pose a risk to human health... pesticide to perform as claimed involved the use against microorganisms which may pose a risk to human...
40 CFR 159.188 - Failure of performance information.
Code of Federal Regulations, 2013 CFR
2013-07-01
... for control of animals that pose a risk to human health, including any of the public health pesticides... Information § 159.188 Failure of performance information. (a) Microorganisms that pose a risk to human health... pesticide to perform as claimed involved the use against microorganisms which may pose a risk to human...
40 CFR 159.188 - Failure of performance information.
Code of Federal Regulations, 2010 CFR
2010-07-01
... for control of animals that pose a risk to human health, including any of the public health pesticides... Information § 159.188 Failure of performance information. (a) Microorganisms that pose a risk to human health... pesticide to perform as claimed involved the use against microorganisms which may pose a risk to human...
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.
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
Experimental and Theoretical Results in Output-Trajectory Redesign for Flexible Structures
NASA Technical Reports Server (NTRS)
Dewey, J. S.; Devasia, Santosh
1996-01-01
In this paper we study the optimal redesign of output trajectory for linear invertible systems. This is particularly important for tracking control of flexible structures because the input-state trajectories that achieve the required output may cause excessive vibrations in the structure. A trade-off is then required between tracking and vibrations reduction. We pose and solve this problem as the minimization of a quadratic cost function. The theory is developed and applied to the output tracking of a flexible structure and experimental results are presented.
Human tracking over camera networks: a review
NASA Astrophysics Data System (ADS)
Hou, Li; Wan, Wanggen; Hwang, Jenq-Neng; Muhammad, Rizwan; Yang, Mingyang; Han, Kang
2017-12-01
In recent years, automated human tracking over camera networks is getting essential for video surveillance. The tasks of tracking human over camera networks are not only inherently challenging due to changing human appearance, but also have enormous potentials for a wide range of practical applications, ranging from security surveillance to retail and health care. This review paper surveys the most widely used techniques and recent advances for human tracking over camera networks. Two important functional modules for the human tracking over camera networks are addressed, including human tracking within a camera and human tracking across non-overlapping cameras. The core techniques of human tracking within a camera are discussed based on two aspects, i.e., generative trackers and discriminative trackers. The core techniques of human tracking across non-overlapping cameras are then discussed based on the aspects of human re-identification, camera-link model-based tracking and graph model-based tracking. Our survey aims to address existing problems, challenges, and future research directions based on the analyses of the current progress made toward human tracking techniques over camera networks.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-11-17
... control pest microorganisms that pose a threat to human health and whose presence cannot readily be... control pest microorganisms that pose a threat to human health and whose presence cannot readily be... of prions (that poses a threat to human health), an applicant or registrant would be required by...
Gilbert, Marius; Newman, Scott H.; Takekawa, John Y.; Loth, Leo; Biradar, Chandrashekhar; Prosser, Diann J.; Balachandran, Sivananinthaperumal; Rao, Mandava Venkata Subba; Mundkur, Taej; Yan, Baoping; Xing, Zhi; Hou, Yuansheng; Batbayar, Nyambayar; Tseveenmayadag, Natsagdorj; Hogerwerf, Lenny; Slingenbergh, Jan; Xiao, Xiangming
2010-01-01
Highly pathogenic avian influenza (HPAI) H5N1 virus persists in Asia, posing a threat to poultry, wild birds, and humans. Previous work in Southeast Asia demonstrated that HPAI H5N1 risk is related to domestic ducks and people. Other studies discussed the role of migratory birds in the long distance spread of HPAI H5N1. However, the interplay between local persistence and long-distance dispersal has never been studied. We expand previous geospatial risk analysis to include South and Southeast Asia, and integrate the analysis with migration data of satellite-tracked wild waterfowl along the Central Asia flyway. We find that the population of domestic duck is the main factor delineating areas at risk of HPAI H5N1 spread in domestic poultry in South Asia, and that other risk factors, such as human population and chicken density, are associated with HPAI H5N1 risk within those areas. We also find that satellite tracked birds (Ruddy Shelduck and two Bar-headed Geese) reveal a direct spatio-temporal link between the HPAI H5N1 hot-spots identified in India and Bangladesh through our risk model, and the wild bird outbreaks in May,June,July 2009 in China(Qinghai Lake), Mongolia, and Russia. This suggests that the continental-scale dynamics of HPAI H5N1 are structured as a number of persistence areas delineated by domestic ducks, connected by rare transmission through migratory waterfowl.
Control of a HexaPOD treatment couch for robot-assisted radiotherapy.
Hermann, Christian; Ma, Lei; Wilbert, Jürgen; Baier, Kurt; Schilling, Klaus
2012-10-01
Moving tumors, for example in the vicinity of the lungs, pose a challenging problem in radiotherapy, as healthy tissue should not be irradiated. Apart from gating approaches, one standard method is to irradiate the complete volume within which a tumor moves plus a safety margin containing a considerable volume of healthy tissue. This work deals with a system for tumor motion compensation using the HexaPOD® robotic treatment couch (Medical Intelligence GmbH, Schwabmünchen, Germany). The HexaPOD, carrying the patient during treatment, is instructed to perform translational movements such that the tumor motion, from the beams-eye view of the linear accelerator, is eliminated. The dynamics of the HexaPOD are characterized by time delays, saturations, and other non-linearities that make the design of control a challenging task. The focus of this work lies on two control methods for the HexaPOD that can be used for reference tracking. The first method uses a model predictive controller based on a model gained through system identification methods, and the second method uses a position control scheme useful for reference tracking. We compared the tracking performance of both methods in various experiments with real hardware using ideal reference trajectories, prerecorded patient trajectories, and human volunteers whose breathing motion was compensated by the system.
The image-interpretation-workstation of the future: lessons learned
NASA Astrophysics Data System (ADS)
Maier, S.; van de Camp, F.; Hafermann, J.; Wagner, B.; Peinsipp-Byma, E.; Beyerer, J.
2017-05-01
In recent years, professionally used workstations got increasingly complex and multi-monitor systems are more and more common. Novel interaction techniques like gesture recognition were developed but used mostly for entertainment and gaming purposes. These human computer interfaces are not yet widely used in professional environments where they could greatly improve the user experience. To approach this problem, we combined existing tools in our imageinterpretation-workstation of the future, a multi-monitor workplace comprised of four screens. Each screen is dedicated to a special task in the image interpreting process: a geo-information system to geo-reference the images and provide a spatial reference for the user, an interactive recognition support tool, an annotation tool and a reporting tool. To further support the complex task of image interpreting, self-developed interaction systems for head-pose estimation and hand tracking were used in addition to more common technologies like touchscreens, face identification and speech recognition. A set of experiments were conducted to evaluate the usability of the different interaction systems. Two typical extensive tasks of image interpreting were devised and approved by military personal. They were then tested with a current setup of an image interpreting workstation using only keyboard and mouse against our image-interpretationworkstation of the future. To get a more detailed look at the usefulness of the interaction techniques in a multi-monitorsetup, the hand tracking, head pose estimation and the face recognition were further evaluated using tests inspired by everyday tasks. The results of the evaluation and the discussion are presented in this paper.
Cryptosporidium Source Tracking in the Potomac River Watershed▿
Yang, Wenli; Chen, Plato; Villegas, Eric N.; Landy, Ronald B.; Kanetsky, Charles; Cama, Vitaliano; Dearen, Theresa; Schultz, Cherie L.; Orndorff, Kenneth G.; Prelewicz, Gregory J.; Brown, Miranda H.; Young, Kim Roy; Xiao, Lihua
2008-01-01
To better characterize Cryptosporidium in the Potomac River watershed, a PCR-based genotyping tool was used to analyze 64 base flow and 28 storm flow samples from five sites in the watershed. These sites included two water treatment plant intakes, as well as three upstream sites, each associated with a different type of land use. The uses, including urban wastewater, agricultural (cattle) wastewater, and wildlife, posed different risks in terms of the potential contribution of Cryptosporidium oocysts to the source water. Cryptosporidium was detected in 27 base flow water samples and 23 storm flow water samples. The most frequently detected species was C. andersoni (detected in 41 samples), while 14 other species or genotypes, almost all wildlife associated, were occasionally detected. The two common human-pathogenic species, C. hominis and C. parvum, were not detected. Although C. andersoni was common at all four sites influenced by agriculture, it was largely absent at the urban wastewater site. There were very few positive samples as determined by Environmental Protection Agency method 1623 at any site; only 8 of 90 samples analyzed (9%) were positive for Cryptosporidium as determined by microscopy. The genotyping results suggest that many of the Cryptosporidium oocysts in the water treatment plant source waters were from old calves and adult cattle and might not pose a significant risk to human health. PMID:18776033
Severe Weather Guide - Mediterranean Ports. 4. Augusta Bay
1988-03-01
the year. The track o-f strong extratropical storms has moved northward and poses little tiireat to Augusta Bay. Sea breezes are daily occurrences...as temperatures, begin to moderate. Extratropi cal systems begin to transit Europe as the storm track moves southward in advance of the winter...SUB-GROUP 18. SUBJECT TERMS {Continue on reverse if necessary and identify by block number) Storm haven Mediterranean meteorology Augusta Bay
Real-time Awake Animal Motion Tracking System for SPECT Imaging
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goddard Jr, James Samuel; Baba, Justin S; Lee, Seung Joon
Enhancements have been made in the development of a real-time optical pose measurement and tracking system that provides 3D position and orientation data for a single photon emission computed tomography (SPECT) imaging system for awake, unanesthetized, unrestrained small animals. Three optical cameras with infrared (IR) illumination view the head movements of an animal enclosed in a transparent burrow. Markers placed on the head provide landmark points for image segmentation. Strobed IR LED s are synchronized to the cameras and illuminate the markers to prevent motion blur for each set of images. The system using the three cameras automatically segments themore » markers, detects missing data, rejects false reflections, performs trinocular marker correspondence, and calculates the 3D pose of the animal s head. Improvements have been made in methods for segmentation, tracking, and 3D calculation to give higher speed and more accurate measurements during a scan. The optical hardware has been installed within a Siemens MicroCAT II small animal scanner at Johns Hopkins without requiring functional changes to the scanner operation. The system has undergone testing using both phantoms and live mice and has been characterized in terms of speed, accuracy, robustness, and reliability. Experimental data showing these motion tracking results are given.« less
Multithreaded hybrid feature tracking for markerless augmented reality.
Lee, Taehee; Höllerer, Tobias
2009-01-01
We describe a novel markerless camera tracking approach and user interaction methodology for augmented reality (AR) on unprepared tabletop environments. We propose a real-time system architecture that combines two types of feature tracking. Distinctive image features of the scene are detected and tracked frame-to-frame by computing optical flow. In order to achieve real-time performance, multiple operations are processed in a synchronized multi-threaded manner: capturing a video frame, tracking features using optical flow, detecting distinctive invariant features, and rendering an output frame. We also introduce user interaction methodology for establishing a global coordinate system and for placing virtual objects in the AR environment by tracking a user's outstretched hand and estimating a camera pose relative to it. We evaluate the speed and accuracy of our hybrid feature tracking approach, and demonstrate a proof-of-concept application for enabling AR in unprepared tabletop environments, using bare hands for interaction.
Chen, Yuantao; Xu, Weihong; Kuang, Fangjun; Gao, Shangbing
2013-01-01
The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking's accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM). Furthermore, the paper's algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target's saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.
Remote Viewer for Maritime Robotics Software
NASA Technical Reports Server (NTRS)
Kuwata, Yoshiaki; Wolf, Michael; Huntsberger, Terrance L.; Howard, Andrew B.
2013-01-01
This software is a viewer program for maritime robotics software that provides a 3D visualization of the boat pose, its position history, ENC (Electrical Nautical Chart) information, camera images, map overlay, and detected tracks.
Pose estimation and tracking of non-cooperative rocket bodies using Time-of-Flight cameras
NASA Astrophysics Data System (ADS)
Gómez Martínez, Harvey; Giorgi, Gabriele; Eissfeller, Bernd
2017-10-01
This paper presents a methodology for estimating the position and orientation of a rocket body in orbit - the target - undergoing a roto-translational motion, with respect to a chaser spacecraft, whose task is to match the target dynamics for a safe rendezvous. During the rendezvous maneuver the chaser employs a Time-of-Flight camera that acquires a point cloud of 3D coordinates mapping the sensed target surface. Once the system identifies the target, it initializes the chaser-to-target relative position and orientation. After initialization, a tracking procedure enables the system to sense the evolution of the target's pose between frames. The proposed algorithm is evaluated using simulated point clouds, generated with a CAD model of the Cosmos-3M upper stage and the PMD CamCube 3.0 camera specifications.
An interactive framework for acquiring vision models of 3-D objects from 2-D images.
Motai, Yuichi; Kak, Avinash
2004-02-01
This paper presents a human-computer interaction (HCI) framework for building vision models of three-dimensional (3-D) objects from their two-dimensional (2-D) images. Our framework is based on two guiding principles of HCI: 1) provide the human with as much visual assistance as possible to help the human make a correct input; and 2) verify each input provided by the human for its consistency with the inputs previously provided. For example, when stereo correspondence information is elicited from a human, his/her job is facilitated by superimposing epipolar lines on the images. Although that reduces the possibility of error in the human marked correspondences, such errors are not entirely eliminated because there can be multiple candidate points close together for complex objects. For another example, when pose-to-pose correspondence is sought from a human, his/her job is made easier by allowing the human to rotate the partial model constructed in the previous pose in relation to the partial model for the current pose. While this facility reduces the incidence of human-supplied pose-to-pose correspondence errors, such errors cannot be eliminated entirely because of confusion created when multiple candidate features exist close together. Each input provided by the human is therefore checked against the previous inputs by invoking situation-specific constraints. Different types of constraints (and different human-computer interaction protocols) are needed for the extraction of polygonal features and for the extraction of curved features. We will show results on both polygonal objects and object containing curved features.
Infrared measurement and composite tracking algorithm for air-breathing hypersonic vehicles
NASA Astrophysics Data System (ADS)
Zhang, Zhao; Gao, Changsheng; Jing, Wuxing
2018-03-01
Air-breathing hypersonic vehicles have capabilities of hypersonic speed and strong maneuvering, and thus pose a significant challenge to conventional tracking methodologies. To achieve desirable tracking performance for hypersonic targets, this paper investigates the problems related to measurement model design and tracking model mismatching. First, owing to the severe aerothermal effect of hypersonic motion, an infrared measurement model in near space is designed and analyzed based on target infrared radiation and an atmospheric model. Second, using information from infrared sensors, a composite tracking algorithm is proposed via a combination of the interactive multiple models (IMM) algorithm, fitting dynamics model, and strong tracking filter. During the procedure, the IMMs algorithm generates tracking data to establish a fitting dynamics model of the target. Then, the strong tracking unscented Kalman filter is employed to estimate the target states for suppressing the impact of target maneuvers. Simulations are performed to verify the feasibility of the presented composite tracking algorithm. The results demonstrate that the designed infrared measurement model effectively and continuously observes hypersonic vehicles, and the proposed composite tracking algorithm accurately and stably tracks these targets.
Hardy, Jean; Veinot, Tiffany C; Yan, Xiang; Berrocal, Veronica J; Clarke, Philippa; Goodspeed, Robert; Gomez-Lopez, Iris N; Romero, Daniel; Vydiswaran, V G Vinod
2018-03-01
Research regarding place and health has undergone a revolution due to the availability of consumer-focused location-tracking devices that reveal fine-grained details of human mobility. Such research requires that participants accept such devices enough to use them in their daily lives. There is a need for a theoretically grounded understanding of acceptance of different location-tracking technology options, and its research implications. Guided by an extended Unified Theory of Acceptance and Use of Technology (UTAUT), we conducted a 28-day field study comparing 21 chronically ill people's acceptance of two leading, consumer-focused location-tracking technologies deployed for research purposes: (1) a location-enabled smartphone, and (2) a GPS watch/activity tracker. Participants used both, and completed two surveys and qualitative interviews. Findings revealed that all participants exerted effort to facilitate data capture, such as by incorporating devices into daily routines and developing workarounds to keep devices functioning. Nevertheless, the smartphone was perceived to be significantly easier and posed fewer usability challenges for participants than the watch. Older participants found the watch significantly more difficult to use. For both devices, effort expectancy was significantly associated with future willingness to participate in research although prosocial motivations overcame some concerns. Social influence, performance expectancy and use behavior were significantly associated with intentions to use the devices in participants' personal lives. Data gathered via the smartphone was significantly more complete than data gathered via the watch, primarily due to usability challenges. To make longer-term participation in location tracking research a reality, and to achieve complete data capture, researchers must minimize the effort involved in participation; this requires usable devices. For long-term location-tracking studies using similar devices, findings indicate that only smartphone-based tracking is up to the challenge. Copyright © 2018 Elsevier Inc. All rights reserved.
Virtual rigid body: a new optical tracking paradigm in image-guided interventions
NASA Astrophysics Data System (ADS)
Cheng, Alexis; Lee, David S.; Deshmukh, Nishikant; Boctor, Emad M.
2015-03-01
Tracking technology is often necessary for image-guided surgical interventions. Optical tracking is one the options, but it suffers from line of sight and workspace limitations. Optical tracking is accomplished by attaching a rigid body marker, having a pattern for pose detection, onto a tool or device. A larger rigid body results in more accurate tracking, but at the same time large size limits its usage in a crowded surgical workspace. This work presents a prototype of a novel optical tracking method using a virtual rigid body (VRB). We define the VRB as a 3D rigid body marker in the form of pattern on a surface generated from a light source. Its pose can be recovered by observing the projected pattern with a stereo-camera system. The rigid body's size is no longer physically limited as we can manufacture small size light sources. Conventional optical tracking also requires line of sight to the rigid body. VRB overcomes these limitations by detecting a pattern projected onto the surface. We can project the pattern onto a region of interest, allowing the pattern to always be in the view of the optical tracker. This helps to decrease the occurrence of occlusions. This manuscript describes the method and results compared with conventional optical tracking in an experiment setup using known motions. The experiments are done using an optical tracker and a linear-stage, resulting in targeting errors of 0.38mm+/-0.28mm with our method compared to 0.23mm+/-0.22mm with conventional optical markers. Another experiment that replaced the linear stage with a robot arm resulted in rotational errors of 0.50+/-0.31° and 2.68+/-2.20° and the translation errors of 0.18+/-0.10 mm and 0.03+/-0.02 mm respectively.
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
Sustainable High-Potential Career Development: A Resource-Based View.
ERIC Educational Resources Information Center
Iles, Paul
1997-01-01
In the current economic climate, fast-track career models pose problems for individuals and organizations. An alternative model uses a resource-based view of the company and principles of sustainable development borrowed from environmentalism. (SK)
An experimental comparison of online object-tracking algorithms
NASA Astrophysics Data System (ADS)
Wang, Qing; Chen, Feng; Xu, Wenli; Yang, Ming-Hsuan
2011-09-01
This paper reviews and evaluates several state-of-the-art online object tracking algorithms. Notwithstanding decades of efforts, object tracking remains a challenging problem due to factors such as illumination, pose, scale, deformation, motion blur, noise, and occlusion. To account for appearance change, most recent tracking algorithms focus on robust object representations and effective state prediction. In this paper, we analyze the components of each tracking method and identify their key roles in dealing with specific challenges, thereby shedding light on how to choose and design algorithms for different situations. We compare state-of-the-art online tracking methods including the IVT,1 VRT,2 FragT,3 BoostT,4 SemiT,5 BeSemiT,6 L1T,7 MILT,8 VTD9 and TLD10 algorithms on numerous challenging sequences, and evaluate them with different performance metrics. The qualitative and quantitative comparative results demonstrate the strength and weakness of these algorithms.
Robust control of dielectric elastomer diaphragm actuator for human pulse signal tracking
NASA Astrophysics Data System (ADS)
Ye, Zhihang; Chen, Zheng; Asmatulu, Ramazan; Chan, Hoyin
2017-08-01
Human pulse signal tracking is an emerging technology that is needed in traditional Chinese medicine. However, soft actuation with multi-frequency tracking capability is needed for tracking human pulse signal. Dielectric elastomer (DE) is one type of soft actuating that has great potential in human pulse signal tracking. In this paper, a DE diaphragm actuator was designed and fabricated to track human pulse pressure signal. A physics-based and control-oriented model has been developed to capture the dynamic behavior of DE diaphragm actuator. Using the physical model, an H-infinity robust control was designed for the actuator to reject high-frequency sensing noises and disturbances. The robust control was then implemented in real-time to track a multi-frequency signal, which verified the tracking capability and robustness of the control system. In the human pulse signal tracking test, a human pulse signal was measured at the City University of Hong Kong and then was tracked using DE actuator at Wichita State University in the US. Experimental results have verified that the DE actuator with its robust control is capable of tracking human pulse signal.
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.
Situation exploration in a persistent surveillance system with multidimensional data
NASA Astrophysics Data System (ADS)
Habibi, Mohammad S.
2013-03-01
There is an emerging need for fusing hard and soft sensor data in an efficient surveillance system to provide accurate estimation of situation awareness. These mostly abstract, multi-dimensional and multi-sensor data pose a great challenge to the user in performing analysis of multi-threaded events efficiently and cohesively. To address this concern an interactive Visual Analytics (VA) application is developed for rapid assessment and evaluation of different hypotheses based on context-sensitive ontology spawn from taxonomies describing human/human and human/vehicle/object interactions. A methodology is described here for generating relevant ontology in a Persistent Surveillance System (PSS) and demonstrates how they can be utilized in the context of PSS to track and identify group activities pertaining to potential threats. The proposed VA system allows for visual analysis of raw data as well as metadata that have spatiotemporal representation and content-based implications. Additionally in this paper, a technique for rapid search of tagged information contingent to ranking and confidence is explained for analysis of multi-dimensional data. Lastly the issue of uncertainty associated with processing and interpretation of heterogeneous data is also addressed.
Human-like object tracking and gaze estimation with PKD android
Wijayasinghe, Indika B.; Miller, Haylie L.; Das, Sumit K; Bugnariu, Nicoleta L.; Popa, Dan O.
2018-01-01
As the use of robots increases for tasks that require human-robot interactions, it is vital that robots exhibit and understand human-like cues for effective communication. In this paper, we describe the implementation of object tracking capability on Philip K. Dick (PKD) android and a gaze tracking algorithm, both of which further robot capabilities with regard to human communication. PKD's ability to track objects with human-like head postures is achieved with visual feedback from a Kinect system and an eye camera. The goal of object tracking with human-like gestures is twofold : to facilitate better human-robot interactions and to enable PKD as a human gaze emulator for future studies. The gaze tracking system employs a mobile eye tracking system (ETG; SensoMotoric Instruments) and a motion capture system (Cortex; Motion Analysis Corp.) for tracking the head orientations. Objects to be tracked are displayed by a virtual reality system, the Computer Assisted Rehabilitation Environment (CAREN; MotekForce Link). The gaze tracking algorithm converts eye tracking data and head orientations to gaze information facilitating two objectives: to evaluate the performance of the object tracking system for PKD and to use the gaze information to predict the intentions of the user, enabling the robot to understand physical cues by humans. PMID:29416193
Human-like object tracking and gaze estimation with PKD android
NASA Astrophysics Data System (ADS)
Wijayasinghe, Indika B.; Miller, Haylie L.; Das, Sumit K.; Bugnariu, Nicoleta L.; Popa, Dan O.
2016-05-01
As the use of robots increases for tasks that require human-robot interactions, it is vital that robots exhibit and understand human-like cues for effective communication. In this paper, we describe the implementation of object tracking capability on Philip K. Dick (PKD) android and a gaze tracking algorithm, both of which further robot capabilities with regard to human communication. PKD's ability to track objects with human-like head postures is achieved with visual feedback from a Kinect system and an eye camera. The goal of object tracking with human-like gestures is twofold: to facilitate better human-robot interactions and to enable PKD as a human gaze emulator for future studies. The gaze tracking system employs a mobile eye tracking system (ETG; SensoMotoric Instruments) and a motion capture system (Cortex; Motion Analysis Corp.) for tracking the head orientations. Objects to be tracked are displayed by a virtual reality system, the Computer Assisted Rehabilitation Environment (CAREN; MotekForce Link). The gaze tracking algorithm converts eye tracking data and head orientations to gaze information facilitating two objectives: to evaluate the performance of the object tracking system for PKD and to use the gaze information to predict the intentions of the user, enabling the robot to understand physical cues by humans.
Dodds, Peter Sheridan; Mitchell, Lewis; Reagan, Andrew J.; ...
2016-05-11
Instabilities and long term shifts in seasons, whether induced by natural drivers or human activities, pose great disruptive threats to ecological, agricultural, and social systems. Here, we propose, measure, and explore two fundamental markers of location-sensitive seasonal variations: the Summer and Winter Teletherms—the on-average annual dates of the hottest and coldest days of the year. We analyze daily temperature extremes recorded at 1218 stations across the contiguous United States from 1853–2012, and observe large regional variation with the Summer Teletherm falling up to 90 days after the Summer Solstice, and 50 days for the Winter Teletherm after the Winter Solstice.more » We show that Teletherm temporal dynamics are substantive with clear and in some cases dramatic shifts reflective of system bifurcations. We also compare recorded daily temperature extremes with output from two regional climate models finding considerable though relatively unbiased error. In conclusion, our work demonstrates that Teletherms are an intuitive, powerful, and statistically sound measure of local climate change, and that they pose detailed, stringent challenges for future theoretical and computational models.« less
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
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.
Human-tracking strategies for a six-legged rescue robot based on distance and view
NASA Astrophysics Data System (ADS)
Pan, Yang; Gao, Feng; Qi, Chenkun; Chai, Xun
2016-03-01
Human tracking is an important issue for intelligent robotic control and can be used in many scenarios, such as robotic services and human-robot cooperation. Most of current human-tracking methods are targeted for mobile/tracked robots, but few of them can be used for legged robots. Two novel human-tracking strategies, view priority strategy and distance priority strategy, are proposed specially for legged robots, which enable them to track humans in various complex terrains. View priority strategy focuses on keeping humans in its view angle arrange with priority, while its counterpart, distance priority strategy, focuses on keeping human at a reasonable distance with priority. To evaluate these strategies, two indexes(average and minimum tracking capability) are defined. With the help of these indexes, the view priority strategy shows advantages compared with distance priority strategy. The optimization is done in terms of these indexes, which let the robot has maximum tracking capability. The simulation results show that the robot can track humans with different curves like square, circular, sine and screw paths. Two novel control strategies are proposed which specially concerning legged robot characteristics to solve human tracking problems more efficiently in rescue circumstances.
NASA Astrophysics Data System (ADS)
Kryuchkov, B. I.; Usov, V. M.; Chertopolokhov, V. A.; Ronzhin, A. L.; Karpov, A. A.
2017-05-01
Extravehicular activity (EVA) on the lunar surface, necessary for the future exploration of the Moon, involves extensive use of robots. One of the factors of safe EVA is a proper interaction between cosmonauts and robots in extreme environments. This requires a simple and natural man-machine interface, e.g. multimodal contactless interface based on recognition of gestures and cosmonaut's poses. When travelling in the "Follow Me" mode (master/slave), a robot uses onboard tools for tracking cosmonaut's position and movements, and on the basis of these data builds its itinerary. The interaction in the system "cosmonaut-robot" on the lunar surface is significantly different from that on the Earth surface. For example, a man, dressed in a space suit, has limited fine motor skills. In addition, EVA is quite tiring for the cosmonauts, and a tired human being less accurately performs movements and often makes mistakes. All this leads to new requirements for the convenient use of the man-machine interface designed for EVA. To improve the reliability and stability of human-robot communication it is necessary to provide options for duplicating commands at the task stages and gesture recognition. New tools and techniques for space missions must be examined at the first stage of works in laboratory conditions, and then in field tests (proof tests at the site of application). The article analyzes the methods of detection and tracking of movements and gesture recognition of the cosmonaut during EVA, which can be used for the design of human-machine interface. A scenario for testing these methods by constructing a virtual environment simulating EVA on the lunar surface is proposed. Simulation involves environment visualization and modeling of the use of the "vision" of the robot to track a moving cosmonaut dressed in a spacesuit.
Association of phenylbutazone usage with horses bought for slaughter: a public health risk.
Dodman, Nicholas; Blondeau, Nicolas; Marini, Ann M
2010-05-01
Sixty-seven million pounds of horsemeat derived from American horses were sent abroad for human consumption last year. Horses are not raised as food animals in the United States, and mechanisms to ensure the removal of horses treated with banned substances from the food chain are inadequate at best. Phenylbutazone (PBZ) is the most commonly used non-steroidal anti-inflammatory drug (NSAID) in equine practice. Thoroughbred (TB) race horses like other horse breeds are slaughtered for human consumption. Phenylbutazone is banned for use in any animal intended for human consumption because it causes serious and lethal idiosyncratic adverse effects in humans. The number of horses that have received phenylbutazone prior to being sent to slaughter for human consumption is unknown but its presence in some is highly likely. We identified eighteen TB race horses that were given PBZ on race day and sent for intended slaughter by matching their registered name to their race track drug record over a five year period. Sixteen rescued TB race horses were given PBZ on race day. Thus, PBZ residues may be present in some horsemeat derived from American horses. The permissive allowance of such horsemeat used for human consumption poses a serious public health risk. Published by Elsevier Ltd.
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.
Real-time skeleton tracking for embedded systems
NASA Astrophysics Data System (ADS)
Coleca, Foti; Klement, Sascha; Martinetz, Thomas; Barth, Erhardt
2013-03-01
Touch-free gesture technology is beginning to become more popular with consumers and may have a significant future impact on interfaces for digital photography. However, almost every commercial software framework for gesture and pose detection is aimed at either desktop PCs or high-powered GPUs, making mobile implementations for gesture recognition an attractive area for research and development. In this paper we present an algorithm for hand skeleton tracking and gesture recognition that runs on an ARM-based platform (Pandaboard ES, OMAP 4460 architecture). The algorithm uses self-organizing maps to fit a given topology (skeleton) into a 3D point cloud. This is a novel way of approaching the problem of pose recognition as it does not employ complex optimization techniques or data-based learning. After an initial background segmentation step, the algorithm is ran in parallel with heuristics, which detect and correct artifacts arising from insufficient or erroneous input data. We then optimize the algorithm for the ARM platform using fixed-point computation and the NEON SIMD architecture the OMAP4460 provides. We tested the algorithm with two different depth-sensing devices (Microsoft Kinect, PMD Camboard). For both input devices we were able to accurately track the skeleton at the native framerate of the cameras.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Weon, Chijun; Hyun Nam, Woo; Lee, Duhgoon
Purpose: Registration between 2D ultrasound (US) and 3D preoperative magnetic resonance (MR) (or computed tomography, CT) images has been studied recently for US-guided intervention. However, the existing techniques have some limits, either in the registration speed or the performance. The purpose of this work is to develop a real-time and fully automatic registration system between two intermodal images of the liver, and subsequently an indirect lesion positioning/tracking algorithm based on the registration result, for image-guided interventions. Methods: The proposed position tracking system consists of three stages. In the preoperative stage, the authors acquire several 3D preoperative MR (or CT) imagesmore » at different respiratory phases. Based on the transformations obtained from nonrigid registration of the acquired 3D images, they then generate a 4D preoperative image along the respiratory phase. In the intraoperative preparatory stage, they properly attach a 3D US transducer to the patient’s body and fix its pose using a holding mechanism. They then acquire a couple of respiratory-controlled 3D US images. Via the rigid registration of these US images to the 3D preoperative images in the 4D image, the pose information of the fixed-pose 3D US transducer is determined with respect to the preoperative image coordinates. As feature(s) to use for the rigid registration, they may choose either internal liver vessels or the inferior vena cava. Since the latter is especially useful in patients with a diffuse liver disease, the authors newly propose using it. In the intraoperative real-time stage, they acquire 2D US images in real-time from the fixed-pose transducer. For each US image, they select candidates for its corresponding 2D preoperative slice from the 4D preoperative MR (or CT) image, based on the predetermined pose information of the transducer. The correct corresponding image is then found among those candidates via real-time 2D registration based on a gradient-based similarity measure. Finally, if needed, they obtain the position information of the liver lesion using the 3D preoperative image to which the registered 2D preoperative slice belongs. Results: The proposed method was applied to 23 clinical datasets and quantitative evaluations were conducted. With the exception of one clinical dataset that included US images of extremely low quality, 22 datasets of various liver status were successfully applied in the evaluation. Experimental results showed that the registration error between the anatomical features of US and preoperative MR images is less than 3 mm on average. The lesion tracking error was also found to be less than 5 mm at maximum. Conclusions: A new system has been proposed for real-time registration between 2D US and successive multiple 3D preoperative MR/CT images of the liver and was applied for indirect lesion tracking for image-guided intervention. The system is fully automatic and robust even with images that had low quality due to patient status. Through visual examinations and quantitative evaluations, it was verified that the proposed system can provide high lesion tracking accuracy as well as high registration accuracy, at performance levels which were acceptable for various clinical applications.« less
Zhou, Junbo; Gong, Jian; Ding, Chun; Chen, Guiqin
2015-08-01
Ovarian cancer is one of the most malignant types of cancer of the female human reproductive track, posing a severe threat to the health of the female population. Numerous previous studies have demonstrated that microRNA (miR)-145 is downregulated in ovarian cancer, and that quercetin can inhibit the growth of cancer cells via regulating the expression of miRs. Therefore, the present study investigated the effect of quercetin on the expression of miR-145 in SKOV-3 and A2780 human ovarian cancer cell lines. The results revealed that the expression levels of cleaved caspase-3 in the SKOV-3 and A2780 cells were significantly increased following treatment to induce overexpression of miR-145 compared with treatment with quercetin alone (P<0.01). However, the expression of cleaved caspase-3 in the anti-miR-145 (miR-145 inhibitor) group of cells was markedly decreased compared with that in the miR-145 overexpression group (P<0.01). Taken together, the results suggested that treatment with quercetin induced the apoptosis of human ovarian carcinoma cells through activation of the extrinsic death receptor mediated and intrinsic mitochondrial apoptotic pathways.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brandt, C.C.; Benson, S.B.; Beeler, D.A.
The Clinch River Remedial Investigation (CRRI) is designed to address the transport, fate, and distribution of waterborne contaminants (radionuclides, metals, and organic compounds) released from the US Department of Energy`s (DOE`s) Oak Ridge Reservation (ORR) and to assess potential risks to human health and the environment associated with these contaminants. The remedial investigation is entering Phase 2, which has the following items as its objectives: define the nature and extent of the contamination in areas downstream from the DOE ORR, evaluate the human health and ecological risks posed by these contaminants, and perform preliminary identification and evaluation of potential remediationmore » alternatives. This plan describes the requirements, responsibilities, and roles of personnel during sampling, analysis, and data review for the Clinch River Environmental Restoration Program (CR-ERP). The purpose of the plan is to formalize the process for obtaining analytical services, tracking sampling and analysis documentation, and assessing the overall quality of the CR-ERP data collection program to ensure that it will provide the necessary building blocks for the program decision-making process.« less
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.
Fast Markerless Tracking for Augmented Reality in Planar Environment
NASA Astrophysics Data System (ADS)
Basori, Ahmad Hoirul; Afif, Fadhil Noer; Almazyad, Abdulaziz S.; AbuJabal, Hamza Ali S.; Rehman, Amjad; Alkawaz, Mohammed Hazim
2015-12-01
Markerless tracking for augmented reality should not only be accurate but also fast enough to provide a seamless synchronization between real and virtual beings. Current reported methods showed that a vision-based tracking is accurate but requires high computational power. This paper proposes a real-time hybrid-based method for tracking unknown environments in markerless augmented reality. The proposed method provides collaboration of vision-based approach with accelerometers and gyroscopes sensors as camera pose predictor. To align the augmentation relative to camera motion, the tracking method is done by substituting feature-based camera estimation with combination of inertial sensors with complementary filter to provide more dynamic response. The proposed method managed to track unknown environment with faster processing time compared to available feature-based approaches. Moreover, the proposed method can sustain its estimation in a situation where feature-based tracking loses its track. The collaboration of sensor tracking managed to perform the task for about 22.97 FPS, up to five times faster than feature-based tracking method used as comparison. Therefore, the proposed method can be used to track unknown environments without depending on amount of features on scene, while requiring lower computational cost.
Going wild: what a global small-animal tracking system could do for experimental biologists.
Wikelski, Martin; Kays, Roland W; Kasdin, N Jeremy; Thorup, Kasper; Smith, James A; Swenson, George W
2007-01-01
Tracking animals over large temporal and spatial scales has revealed invaluable and spectacular biological information, particularly when the paths and fates of individuals can be monitored on a global scale. However, only large animals (greater than approximately 300 g) currently can be followed globally because of power and size constraints on the tracking devices. And yet the vast majority of animals is small. Tracking small animals is important because they are often part of evolutionary and ecological experiments, they provide important ecosystem services and they are of conservation concern or pose harm to human health. Here, we propose a small-animal satellite tracking system that would enable the global monitoring of animals down to the size of the smallest birds, mammals (bats), marine life and eventually large insects. To create the scientific framework necessary for such a global project, we formed the ICARUS initiative (www.IcarusInitiative.org), the International Cooperation for Animal Research Using Space. ICARUS also highlights how small-animal tracking could address some of the ;Grand Challenges in Environmental Sciences' identified by the US National Academy of Sciences, such as the spread of infectious diseases or the relationship between biological diversity and ecosystem functioning. Small-animal tracking would allow the quantitative assessment of dispersal and migration in natural populations and thus help solve enigmas regarding population dynamics, extinctions and invasions. Experimental biologists may find a global small-animal tracking system helpful in testing, validating and expanding laboratory-derived discoveries in wild, natural populations. We suggest that the relatively modest investment into a global small-animal tracking system will pay off by providing unprecedented insights into both basic and applied nature. Tracking small animals over large spatial and temporal scales could prove to be one of the most powerful techniques of the early 21st century, offering potential solutions to a wide range of biological and societal questions that date back two millennia to the Greek philosopher Aristotle's enigma about songbird migration. Several of the more recent Grand Challenges in Environmental Sciences, such as the regulation and functional consequences of biological diversity or the surveillance of the population ecology of zoonotic hosts, pathogens or vectors, could also be addressed by a global small-animal tracking system. Our discussion is intended to contribute to an emerging groundswell of scientific support to make such a new technological system happen.
2017-06-21
military facilities and firing ranges, may pose a risk to the environment10 and humans ’ health .13 As such, it may require a remediation plan for the...fire ranges. Nitroaromatic and nitramine compounds such as explosives are carcinogenic and mutagenic so they pose threat to human health and the...detonations. It is crucial to understand their fate and transport in subsurface environments as they can pose a significant hazard to humans and
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.
Hu, Yuanan; Cheng, Hefa; Tao, Shu
2017-10-01
Driven by the growing demand for food products of animal origin, industrial livestock and poultry production has become increasingly popular and is on the track of becoming an important source of environmental pollution in China. Although concentrated animal feeding operations (CAFOs) have higher production efficiency and profitability with less resource consumption compared to the traditional family-based and "free range" farming, they bring significant environmental pollution concerns and pose public health risks. Gaseous pollutants and bioaerosols are emitted directly from CAFOs, which have health implications on animal producers and neighboring communities. A range of pollutants are excreted with the animal waste, including nutrients, pathogens, natural and synthetic hormones, veterinary antimicrobials, and heavy metals, which can enter local farmland soils, surface water, and groundwater, during the storage and disposal of animal waste, and pose direct and indirect human health risks. The extensive use of antimicrobials in CAFOs also contributes to the global public health concern of antimicrobial resistance (AMR). Efforts on treating the large volumes of manure generated in CAFOs should be enhanced (e.g., by biogas digesters and integrated farm systems) to minimize their impacts on the environment and human health. Furthermore, the use of veterinary drugs and feed additives in industrial livestock and poultry farming should be controlled, which will not only make the animal food products much safer to the consumers, but also render the manure more benign for treatment and disposal on farmlands. While improving the sustainability of animal farming, China also needs to promote healthy food consumption, which not only improves public health from avoiding high-meat diets, but also slows down the expansion of industrial animal farming, and thus reduces the associated environmental and public health risks. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Trube, Matthew J.; Hyslop, Andrew M.; Carignan, Craig R.; Easley, Joseph W.
2012-01-01
A hardware-in-the-loop ground system was developed for simulating a robotic servicer spacecraft tracking a target satellite at short range. A relative navigation sensor package "Argon" is mounted on the end-effector of a Fanuc 430 manipulator, which functions as the base platform of the robotic spacecraft servicer. Machine vision algorithms estimate the pose of the target spacecraft, mounted on a Rotopod R-2000 platform, relay the solution to a simulation of the servicer spacecraft running in "Freespace", which performs guidance, navigation and control functions, integrates dynamics, and issues motion commands to a Fanuc platform controller so that it tracks the simulated servicer spacecraft. Results will be reviewed for several satellite motion scenarios at different ranges. Key words: robotics, satellite, servicing, guidance, navigation, tracking, control, docking.
On Inertial Body Tracking in the Presence of Model Calibration Errors
Miezal, Markus; Taetz, Bertram; Bleser, Gabriele
2016-01-01
In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments—the IMU-to-segment calibrations, subsequently called I2S calibrations—to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and segment length errors in the tested ranges. Errors in the I2S orientations were, however, linearly propagated into the estimated segment orientations. In the absence of magnetic disturbances, severe model calibration errors and fast motion changes, the newly developed IMU centered EKF-based method yielded comparable results with lower computational complexity. PMID:27455266
Modifications and integration of the electronic tracking board in a pediatric emergency department.
Dexheimer, Judith W; Kennebeck, Stephanie
2013-07-01
Electronic health records (EHRs) are used for data storage; provider, laboratory, and patient communication; clinical decision support; procedure and medication orders; and decision support alerts. Clinical decision support is part of any EHR and is designed to help providers make better decisions. The emergency department (ED) poses a unique environment to the use of EHRs and clinical decision support. Used effectively, computerized tracking boards can help improve flow, communication, and the dissemination of pertinent visit information between providers and other departments in a busy ED. We discuss the unique modifications and decisions made in the implementation of an EHR and computerized tracking board in a pediatric ED. We discuss the changing views based on provider roles, customization to the user interface including the layout and colors, decision support, tracking board best practices collected from other institutions and colleagues, and a case study of using reminders on the electronic tracking board to drive pain reassessments.
Precise Orbit Determination for LEO Spacecraft Using GNSS Tracking Data from Multiple Antennas
NASA Technical Reports Server (NTRS)
Kuang, Da; Bertiger, William; Desai, Shailen; Haines, Bruce
2010-01-01
To support various applications, certain Earth-orbiting spacecrafts (e.g., SRTM, COSMIC) use multiple GNSS antennas to provide tracking data for precise orbit determination (POD). POD using GNSS tracking data from multiple antennas poses some special technical issues compared to the typical single-antenna approach. In this paper, we investigate some of these issues using both real and simulated data. Recommendations are provided for POD with multiple GNSS antennas and for antenna configuration design. The observability of satellite position with multiple antennas data is compared against single antenna case. The impact of differential clock (line biases) and line-of-sight (up, along-track, and cross-track) on kinematic and reduced-dynamic POD is evaluated. The accuracy of monitoring the stability of the spacecraft structure by simultaneously performing POD of the spacecraft and relative positioning of the multiple antennas is also investigated.
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.
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.
Human action recognition based on spatial-temporal descriptors using key poses
NASA Astrophysics Data System (ADS)
Hu, Shuo; Chen, Yuxin; Wang, Huaibao; Zuo, Yaqing
2014-11-01
Human action recognition is an important area of pattern recognition today due to its direct application and need in various occasions like surveillance and virtual reality. In this paper, a simple and effective human action recognition method is presented based on the key poses of human silhouette and the spatio-temporal feature. Firstly, the contour points of human silhouette have been gotten, and the key poses are learned by means of K-means clustering based on the Euclidean distance between each contour point and the centre point of the human silhouette, and then the type of each action is labeled for further match. Secondly, we obtain the trajectories of centre point of each frame, and create a spatio-temporal feature value represented by W to describe the motion direction and speed of each action. The value W contains the information of location and temporal order of each point on the trajectories. Finally, the matching stage is performed by comparing the key poses and W between training sequences and test sequences, the nearest neighbor sequences is found and its label supplied the final result. Experiments on the public available Weizmann datasets show the proposed method can improve accuracy by distinguishing amphibious poses and increase suitability for real-time applications by reducing the computational cost.
75 FR 39450 - Terpene Constituents of the Extract of Chenopodium ambrosioides
Federal Register 2010, 2011, 2012, 2013, 2014
2010-07-09
... exposures resulting from exposure to residues from this pesticidal extract. C. Biochemical Pesticide Human... that this active ingredient poses no significant human health risk with regard to food use. a. The...) factors in calculating a dose level that poses no appreciable risk. Health risks to humans, including...
Automatic Intra-Operative Stitching of Non-Overlapping Cone-Beam CT Acquisitions
Fotouhi, Javad; Fuerst, Bernhard; Unberath, Mathias; Reichenstein, Stefan; Lee, Sing Chun; Johnson, Alex A.; Osgood, Greg M.; Armand, Mehran; Navab, Nassir
2018-01-01
Purpose Cone-Beam Computed Tomography (CBCT) is one of the primary imaging modalities in radiation therapy, dentistry, and orthopedic interventions. While CBCT provides crucial intraoperative information, it is bounded by a limited imaging volume, resulting in reduced effectiveness. This paper introduces an approach allowing real-time intraoperative stitching of overlapping and non-overlapping CBCT volumes to enable 3D measurements on large anatomical structures. Methods A CBCT-capable mobile C-arm is augmented with a Red-Green-Blue-Depth (RGBD) camera. An off-line co-calibration of the two imaging modalities results in co-registered video, infrared, and X-ray views of the surgical scene. Then, automatic stitching of multiple small, non-overlapping CBCT volumes is possible by recovering the relative motion of the C-arm with respect to the patient based on the camera observations. We propose three methods to recover the relative pose: RGB-based tracking of visual markers that are placed near the surgical site, RGBD-based simultaneous localization and mapping (SLAM) of the surgical scene which incorporates both color and depth information for pose estimation, and surface tracking of the patient using only depth data provided by the RGBD sensor. Results On an animal cadaver, we show stitching errors as low as 0.33 mm, 0.91 mm, and 1.72mm when the visual marker, RGBD SLAM, and surface data are used for tracking, respectively. Conclusions The proposed method overcomes one of the major limitations of CBCT C-arm systems by integrating vision-based tracking and expanding the imaging volume without any intraoperative use of calibration grids or external tracking systems. We believe this solution to be most appropriate for 3D intraoperative verification of several orthopedic procedures. PMID:29569728
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.
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.
Epidemiology. Tracking the human fallout from 'mad cow disease'.
Balter, M
2000-09-01
A task force here has been studying cases of variant Creutzfeldt-Jakob disease (vCJD), an incurable malady of the brain and nervous system that has been linked to eating beef or other products from cattle infected with bovine spongiform encephalopathy or "mad cow disease." The team's goal is to find out just how the patients got infected and how many of them there may ultimately be. The number of confirmed or probable vCJD cases in the United Kingdom is still relatively small--a total of 80 as Science went to press--and recent estimates of the number of potential cases are lower than was once feared. Yet the task force's own recent results show that the incidence of vCJD is rising, and researchers remain determined to try to solve the riddles posed by vCJD.
Computer vision for RGB-D sensors: Kinect and its applications.
Shao, Ling; Han, Jungong; Xu, Dong; Shotton, Jamie
2013-10-01
Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use as an off-the-shelf technology. This special issue is specifically dedicated to new algorithms and/or new applications based on the Kinect (or similar RGB-D) sensors. In total, we received over ninety submissions from more than twenty countries all around the world. The submissions cover a wide range of areas including object and scene classification, 3-D pose estimation, visual tracking, data fusion, human action/activity recognition, 3-D reconstruction, mobile robotics, and so on. After two rounds of review by at least two (mostly three) expert reviewers for each paper, the Guest Editors have selected twelve high-quality papers to be included in this highly popular special issue. The papers that comprise this issue are briefly summarized.
Tracking the visual focus of attention for a varying number of wandering people.
Smith, Kevin; Ba, Sileye O; Odobez, Jean-Marc; Gatica-Perez, Daniel
2008-07-01
We define and address the problem of finding the visual focus of attention for a varying number of wandering people (VFOA-W), determining where the people's movement is unconstrained. VFOA-W estimation is a new and important problem with mplications for behavior understanding and cognitive science, as well as real-world applications. One such application, which we present in this article, monitors the attention passers-by pay to an outdoor advertisement. Our approach to the VFOA-W problem proposes a multi-person tracking solution based on a dynamic Bayesian network that simultaneously infers the (variable) number of people in a scene, their body locations, their head locations, and their head pose. For efficient inference in the resulting large variable-dimensional state-space we propose a Reversible Jump Markov Chain Monte Carlo (RJMCMC) sampling scheme, as well as a novel global observation model which determines the number of people in the scene and localizes them. We propose a Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM)-based VFOA-W model which use head pose and location information to determine people's focus state. Our models are evaluated for tracking performance and ability to recognize people looking at an outdoor advertisement, with results indicating good performance on sequences where a moderate number of people pass in front of an advertisement.
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.
Simultaneous localization and calibration for electromagnetic tracking systems.
Sadjadi, Hossein; Hashtrudi-Zaad, Keyvan; Fichtinger, Gabor
2016-06-01
In clinical environments, field distortion can cause significant electromagnetic tracking errors. Therefore, dynamic calibration of electromagnetic tracking systems is essential to compensate for measurement errors. It is proposed to integrate the motion model of the tracked instrument with redundant EM sensor observations and to apply a simultaneous localization and mapping algorithm in order to accurately estimate the pose of the instrument and create a map of the field distortion in real-time. Experiments were conducted in the presence of ferromagnetic and electrically-conductive field distorting objects and results compared with those of a conventional sensor fusion approach. The proposed method reduced the tracking error from 3.94±1.61 mm to 1.82±0.62 mm in the presence of steel, and from 0.31±0.22 mm to 0.11±0.14 mm in the presence of aluminum. With reduced tracking error and independence from external tracking devices or pre-operative calibrations, the approach is promising for reliable EM navigation in various clinical procedures. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
van der Kruk, E; Schwab, A L; van der Helm, F C T; Veeger, H E J
2018-03-01
In gait studies body pose reconstruction (BPR) techniques have been widely explored, but no previous protocols have been developed for speed skating, while the peculiarities of the skating posture and technique do not automatically allow for the transfer of the results of those explorations to kinematic skating data. The aim of this paper is to determine the best procedure for body pose reconstruction and inverse dynamics of speed skating, and to what extend this choice influences the estimation of joint power. The results show that an eight body segment model together with a global optimization method with revolute joint in the knee and in the lumbosacral joint, while keeping the other joints spherical, would be the most realistic model to use for the inverse kinematics in speed skating. To determine joint power, this method should be combined with a least-square error method for the inverse dynamics. Reporting on the BPR technique and the inverse dynamic method is crucial to enable comparison between studies. Our data showed an underestimation of up to 74% in mean joint power when no optimization procedure was applied for BPR and an underestimation of up to 31% in mean joint power when a bottom-up inverse dynamics method was chosen instead of a least square error approach. Although these results are aimed at speed skating, reporting on the BPR procedure and the inverse dynamics method, together with setting a golden standard should be common practice in all human movement research to allow comparison between studies. Copyright © 2018 Elsevier Ltd. All rights reserved.
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.
Close-Range Tracking of Underwater Vehicles Using Light Beacons
Bosch, Josep; Gracias, Nuno; Ridao, Pere; Istenič, Klemen; Ribas, David
2016-01-01
This paper presents a new tracking system for autonomous underwater vehicles (AUVs) navigating in a close formation, based on computer vision and the use of active light markers. While acoustic localization can be very effective from medium to long distances, it is not so advantageous in short distances when the safety of the vehicles requires higher accuracy and update rates. The proposed system allows the estimation of the pose of a target vehicle at short ranges, with high accuracy and execution speed. To extend the field of view, an omnidirectional camera is used. This camera provides a full coverage of the lower hemisphere and enables the concurrent tracking of multiple vehicles in different positions. The system was evaluated in real sea conditions by tracking vehicles in mapping missions, where it demonstrated robust operation during extended periods of time. PMID:27023547
Close-Range Tracking of Underwater Vehicles Using Light Beacons.
Bosch, Josep; Gracias, Nuno; Ridao, Pere; Istenič, Klemen; Ribas, David
2016-03-25
This paper presents a new tracking system for autonomous underwater vehicles (AUVs) navigating in a close formation, based on computer vision and the use of active light markers. While acoustic localization can be very effective from medium to long distances, it is not so advantageous in short distances when the safety of the vehicles requires higher accuracy and update rates. The proposed system allows the estimation of the pose of a target vehicle at short ranges, with high accuracy and execution speed. To extend the field of view, an omnidirectional camera is used. This camera provides a full coverage of the lower hemisphere and enables the concurrent tracking of multiple vehicles in different positions. The system was evaluated in real sea conditions by tracking vehicles in mapping missions, where it demonstrated robust operation during extended periods of time.
Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion
Filippeschi, Alessandro; Schmitz, Norbert; Miezal, Markus; Bleser, Gabriele; Ruffaldi, Emanuele; Stricker, Didier
2017-01-01
Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error). PMID:28587178
Mathematics and Sports. Mathematical World. Volume 3.
ERIC Educational Resources Information Center
Sadovskii, L. E.; Sadovskii, A. L.
This volume contains some examples of mathematical applications in sports. Sports discussed include tennis, figure skating, gymnastics, track and field, soccer, skiing, hockey, and swimming. Problems and situations are posed and answers with thorough explanations are provided. Chapters include: (1) Mathematics and Sports; (2) What Is Applied…
Affordability Approaches for Human Space Exploration
NASA Technical Reports Server (NTRS)
Holladay, Jon; Smith, David Alan
2012-01-01
The design and development of historical NASA Programs (Apollo, Shuttle and International Space Station), have been based on pre-agreed missions which included specific pre-defined destinations (e.g., the Moon and low Earth orbit). Due to more constrained budget profiles, and the desire to have a more flexible architecture for Mission capture as it is affordable, NASA is working toward a set of Programs that are capability based, rather than mission and/or destination specific. This means designing for a performance capability that can be applied to a specific human exploration mission/destination later (sometime years later). This approach does support developing systems to flatter budgets over time, however, it also poses the challenge of how to accomplish this effectively while maintaining a trained workforce, extensive manufacturing, test and launch facilities, and ensuring mission success ranging from Low Earth Orbit to asteroid destinations. NASA Marshall Space Flight Center (MSFC) in support of Exploration Systems Directorate (ESD) in Washington, DC has been developing approaches to track affordability across multiple Programs. The first step is to ensure a common definition of affordability: the discipline to bear cost in meeting a budget with margin over the life of the program. The second step is to infuse responsibility and accountability for affordability into all levels of the implementing organization since affordability is no single person s job; it is everyone s job. The third step is to use existing data to identify common affordability elements organized by configuration (vehicle/facility), cost, schedule, and risk. The fourth step is to analyze and trend this affordability data using an affordability dashboard to provide status, measures, and trends for ESD and Program level of affordability tracking. This paper will provide examples of how regular application of this approach supports affordable and therefore sustainable human space exploration architecture.
Maintaining clinical tissue archives and supporting human research: challenges and solutions.
Giannini, Caterina; Oelkers, Michael M; Edwards, William D; Aubry, Marie Christine; Muncil, Maureen M; Mohamud, Koshin H; Sandleback, Sara G; Nowak, John M; Bridgeman, Andrew; Brown, Marie E; Cheville, John C
2011-03-01
The increasing number of requests for use of clinically archived tissue in translational research poses unique challenges. Conflicts may arise between pathologists who are responsible for overseeing and preserving the tissues and investigators who need these materials for research purposes. To evaluate the status of our institution's Tissue Registry Archive and to develop updated written policies and procedures to support a new modern and robust tracking system with features of a library loan system. An observational study was performed. We found the existing process for managing loans of tissue (slides and paraffin blocks) to be insufficient for the complexity and volume of this task. After extensive customization, a new tracking system was implemented in January 2008. Analysis of the first year of the system's use (2008) showed that of the 206,330 slides and 51,416 blocks loaned out in 2008, 92% and 94%, respectively, were returned by the due date. These rates were markedly improved from those before the new system: 61% and 47%, respectively, in 2005. Material permanently "lost" in 2008 represented only 0.02% of slides and 0.05% of blocks, none of which was the only diagnostic material for the case. With expanding needs for archived tissues for clinical care and growing demands for translational research, it is essential that pathology departments at institutions with large tissue-based research endeavors have a tracking and management system in place to meet clinical, educational, and research needs, as well as legal requirements.
Multispectral embedding-based deep neural network for three-dimensional human pose recovery
NASA Astrophysics Data System (ADS)
Yu, Jialin; Sun, Jifeng
2018-01-01
Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.
Advanced human machine interaction for an image interpretation workstation
NASA Astrophysics Data System (ADS)
Maier, S.; Martin, M.; van de Camp, F.; Peinsipp-Byma, E.; Beyerer, J.
2016-05-01
In recent years, many new interaction technologies have been developed that enhance the usability of computer systems and allow for novel types of interaction. The areas of application for these technologies have mostly been in gaming and entertainment. However, in professional environments, there are especially demanding tasks that would greatly benefit from improved human machine interfaces as well as an overall improved user experience. We, therefore, envisioned and built an image-interpretation-workstation of the future, a multi-monitor workplace comprised of four screens. Each screen is dedicated to a complex software product such as a geo-information system to provide geographic context, an image annotation tool, software to generate standardized reports and a tool to aid in the identification of objects. Using self-developed systems for hand tracking, pointing gestures and head pose estimation in addition to touchscreens, face identification, and speech recognition systems we created a novel approach to this complex task. For example, head pose information is used to save the position of the mouse cursor on the currently focused screen and to restore it as soon as the same screen is focused again while hand gestures allow for intuitive manipulation of 3d objects in mid-air. While the primary focus is on the task of image interpretation, all of the technologies involved provide generic ways of efficiently interacting with a multi-screen setup and could be utilized in other fields as well. In preliminary experiments, we received promising feedback from users in the military and started to tailor the functionality to their needs
Tracking and characterizing the head motion of unanaesthetized rats in positron emission tomography
Kyme, Andre; Meikle, Steven; Baldock, Clive; Fulton, Roger
2012-01-01
Positron emission tomography (PET) is an important in vivo molecular imaging technique for translational research. Imaging unanaesthetized rats using motion-compensated PET avoids the confounding impact of anaesthetic drugs and enables animals to be imaged during normal or evoked behaviour. However, there is little published data on the nature of rat head motion to inform the design of suitable marker-based motion-tracking set-ups for brain imaging—specifically, set-ups that afford close to uninterrupted tracking. We performed a systematic study of rat head motion parameters for unanaesthetized tube-bound and freely moving rats with a view to designing suitable motion-tracking set-ups in each case. For tube-bound rats, using a single appropriately placed binocular tracker, uninterrupted tracking was possible greater than 95 per cent of the time. For freely moving rats, simulations and measurements of a live subject indicated that two opposed binocular trackers are sufficient (less than 10% interruption to tracking) for a wide variety of behaviour types. We conclude that reliable tracking of head pose can be achieved with marker-based optical-motion-tracking systems for both tube-bound and freely moving rats undergoing PET studies without sedation. PMID:22718992
Towards Kilo-Hertz 6-DoF Visual Tracking Using an Egocentric Cluster of Rolling Shutter Cameras.
Bapat, Akash; Dunn, Enrique; Frahm, Jan-Michael
2016-11-01
To maintain a reliable registration of the virtual world with the real world, augmented reality (AR) applications require highly accurate, low-latency tracking of the device. In this paper, we propose a novel method for performing this fast 6-DOF head pose tracking using a cluster of rolling shutter cameras. The key idea is that a rolling shutter camera works by capturing the rows of an image in rapid succession, essentially acting as a high-frequency 1D image sensor. By integrating multiple rolling shutter cameras on the AR device, our tracker is able to perform 6-DOF markerless tracking in a static indoor environment with minimal latency. Compared to state-of-the-art tracking systems, this tracking approach performs at significantly higher frequency, and it works in generalized environments. To demonstrate the feasibility of our system, we present thorough evaluations on synthetically generated data with tracking frequencies reaching 56.7 kHz. We further validate the method's accuracy on real-world images collected from a prototype of our tracking system against ground truth data using standard commodity GoPro cameras capturing at 120 Hz frame rate.
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.
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.
Exploiting target amplitude information to improve multi-target tracking
NASA Astrophysics Data System (ADS)
Ehrman, Lisa M.; Blair, W. Dale
2006-05-01
Closely-spaced (but resolved) targets pose a challenge for measurement-to-track data association algorithms. Since the Mahalanobis distances between measurements collected on closely-spaced targets and tracks are similar, several elements of the corresponding kinematic measurement-to-track cost matrix are also similar. Lacking any other information on which to base assignments, it is not surprising that data association algorithms make mistakes. One ad hoc approach for mitigating this problem is to multiply the kinematic measurement-to-track likelihoods by amplitude likelihoods. However, this can actually be detrimental to the measurement-to-track association process. With that in mind, this paper pursues a rigorous treatment of the hypothesis probabilities for kinematic measurements and features. Three simple scenarios are used to demonstrate the impact of basing data association decisions on these hypothesis probabilities for Rayleigh, fixed-amplitude, and Rician targets. The first scenario assumes that the tracker carries two tracks but only one measurement is collected. This provides insight into more complex scenarios in which there are fewer measurements than tracks. The second scenario includes two measurements and one track. This extends naturally to the case with more measurements than tracks. Two measurements and two tracks are present in the third scenario, which provides insight into the performance of this method when the number of measurements equals the number of tracks. In all cases, basing data association decisions on the hypothesis probabilities leads to good results.
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.
Macrobend optical sensing for pose measurement in soft robot arms
NASA Astrophysics Data System (ADS)
Sareh, Sina; Noh, Yohan; Li, Min; Ranzani, Tommaso; Liu, Hongbin; Althoefer, Kaspar
2015-12-01
This paper introduces a pose-sensing system for soft robot arms integrating a set of macrobend stretch sensors. The macrobend sensory design in this study consists of optical fibres and is based on the notion that bending an optical fibre modulates the intensity of the light transmitted through the fibre. This sensing method is capable of measuring bending, elongation and compression in soft continuum robots and is also applicable to wearable sensing technologies, e.g. pose sensing in the wrist joint of a human hand. In our arrangement, applied to a cylindrical soft robot arm, the optical fibres for macrobend sensing originate from the base, extend to the tip of the arm, and then loop back to the base. The connectors that link the fibres to the necessary opto-electronics are all placed at the base of the arm, resulting in a simplified overall design. The ability of this custom macrobend stretch sensor to flexibly adapt its configuration allows preserving the inherent softness and compliance of the robot which it is installed on. The macrobend sensing system is immune to electrical noise and magnetic fields, is safe (because no electricity is needed at the sensing site), and is suitable for modular implementation in multi-link soft continuum robotic arms. The measurable light outputs of the proposed stretch sensor vary due to bend-induced light attenuation (macrobend loss), which is a function of the fibre bend radius as well as the number of repeated turns. The experimental study conducted as part of this research revealed that the chosen bend radius has a far greater impact on the measured light intensity values than the number of turns (if greater than five). Taking into account that the bend radius is the only significantly influencing design parameter, the macrobend stretch sensors were developed to create a practical solution to the pose sensing in soft continuum robot arms. Henceforward, the proposed sensing design was benchmarked against an electromagnetic tracking system (NDI Aurora) for validation.
NASA Astrophysics Data System (ADS)
Lu, Qun; Yu, Li; Zhang, Dan; Zhang, Xuebo
2018-01-01
This paper presentsa global adaptive controller that simultaneously solves tracking and regulation for wheeled mobile robots with unknown depth and uncalibrated camera-to-robot extrinsic parameters. The rotational angle and the scaled translation between the current camera frame and the reference camera frame, as well as the ones between the desired camera frame and the reference camera frame can be calculated in real time by using the pose estimation techniques. A transformed system is first obtained, for which an adaptive controller is then designed to accomplish both tracking and regulation tasks, and the controller synthesis is based on Lyapunov's direct method. Finally, the effectiveness of the proposed method is illustrated by a simulation study.
Staley, Zachery R; Grabuski, Josey; Sverko, Ed; Edge, Thomas A
2016-11-01
Storm water runoff is a major source of pollution, and understanding the components of storm water discharge is essential to remediation efforts and proper assessment of risks to human and ecosystem health. In this study, culturable Escherichia coli and ampicillin-resistant E. coli levels were quantified and microbial source tracking (MST) markers (including markers for general Bacteroidales spp., human, ruminant/cow, gull, and dog) were detected in storm water outfalls and sites along the Humber River in Toronto, Ontario, Canada, and enumerated via endpoint PCR and quantitative PCR (qPCR). Additionally, chemical source tracking (CST) markers specific for human wastewater (caffeine, carbamazepine, codeine, cotinine, acetaminophen, and acesulfame) were quantified. Human and gull fecal sources were detected at all sites, although concentrations of the human fecal marker were higher, particularly in outfalls (mean outfall concentrations of 4.22 log 10 copies, expressed as copy numbers [CN]/100 milliliters for human and 0.46 log 10 CN/100 milliliters for gull). Higher concentrations of caffeine, acetaminophen, acesulfame, E. coli, and the human fecal marker were indicative of greater raw sewage contamination at several sites (maximum concentrations of 34,800 ng/liter, 5,120 ng/liter, 9,720 ng/liter, 5.26 log 10 CFU/100 ml, and 7.65 log 10 CN/100 ml, respectively). These results indicate pervasive sewage contamination at storm water outfalls and throughout the Humber River, with multiple lines of evidence identifying Black Creek and two storm water outfalls with prominent sewage cross-connection problems requiring remediation. Limited data are available on specific sources of pollution in storm water, though our results indicate the value of using both MST and CST methodologies to more reliably assess sewage contamination in impacted watersheds. Storm water runoff is one of the most prominent non-point sources of biological and chemical contaminants which can potentially degrade water quality and pose risks to human and ecosystem health. Therefore, identifying fecal contamination in storm water runoff and outfalls is essential for remediation efforts to reduce risks to public health. This study employed multiple methods of identifying levels and sources of fecal contamination in both river and storm water outfall sites, evaluating the efficacy of using culture-based enumeration of E. coli, molecular methods of determining the source(s) of contamination, and CST markers as indicators of fecal contamination. The results identified pervasive human sewage contamination in storm water outfalls and throughout an urban watershed and highlight the utility of using both MST and CST to identify raw sewage contamination. © Crown copyright 2016.
Grabuski, Josey; Sverko, Ed; Edge, Thomas A.
2016-01-01
ABSTRACT Storm water runoff is a major source of pollution, and understanding the components of storm water discharge is essential to remediation efforts and proper assessment of risks to human and ecosystem health. In this study, culturable Escherichia coli and ampicillin-resistant E. coli levels were quantified and microbial source tracking (MST) markers (including markers for general Bacteroidales spp., human, ruminant/cow, gull, and dog) were detected in storm water outfalls and sites along the Humber River in Toronto, Ontario, Canada, and enumerated via endpoint PCR and quantitative PCR (qPCR). Additionally, chemical source tracking (CST) markers specific for human wastewater (caffeine, carbamazepine, codeine, cotinine, acetaminophen, and acesulfame) were quantified. Human and gull fecal sources were detected at all sites, although concentrations of the human fecal marker were higher, particularly in outfalls (mean outfall concentrations of 4.22 log10 copies, expressed as copy numbers [CN]/100 milliliters for human and 0.46 log10 CN/100 milliliters for gull). Higher concentrations of caffeine, acetaminophen, acesulfame, E. coli, and the human fecal marker were indicative of greater raw sewage contamination at several sites (maximum concentrations of 34,800 ng/liter, 5,120 ng/liter, 9,720 ng/liter, 5.26 log10 CFU/100 ml, and 7.65 log10 CN/100 ml, respectively). These results indicate pervasive sewage contamination at storm water outfalls and throughout the Humber River, with multiple lines of evidence identifying Black Creek and two storm water outfalls with prominent sewage cross-connection problems requiring remediation. Limited data are available on specific sources of pollution in storm water, though our results indicate the value of using both MST and CST methodologies to more reliably assess sewage contamination in impacted watersheds. IMPORTANCE Storm water runoff is one of the most prominent non-point sources of biological and chemical contaminants which can potentially degrade water quality and pose risks to human and ecosystem health. Therefore, identifying fecal contamination in storm water runoff and outfalls is essential for remediation efforts to reduce risks to public health. This study employed multiple methods of identifying levels and sources of fecal contamination in both river and storm water outfall sites, evaluating the efficacy of using culture-based enumeration of E. coli, molecular methods of determining the source(s) of contamination, and CST markers as indicators of fecal contamination. The results identified pervasive human sewage contamination in storm water outfalls and throughout an urban watershed and highlight the utility of using both MST and CST to identify raw sewage contamination. PMID:27542934
Real-time depth camera tracking with geometrically stable weight algorithm
NASA Astrophysics Data System (ADS)
Fu, Xingyin; Zhu, Feng; Qi, Feng; Wang, Mingming
2017-03-01
We present an approach for real-time camera tracking with depth stream. Existing methods are prone to drift in sceneries without sufficient geometric information. First, we propose a new weight method for an iterative closest point algorithm commonly used in real-time dense mapping and tracking systems. By detecting uncertainty in pose and increasing weight of points that constrain unstable transformations, our system achieves accurate and robust trajectory estimation results. Our pipeline can be fully parallelized with GPU and incorporated into the current real-time depth camera tracking system seamlessly. Second, we compare the state-of-the-art weight algorithms and propose a weight degradation algorithm according to the measurement characteristics of a consumer depth camera. Third, we use Nvidia Kepler Shuffle instructions during warp and block reduction to improve the efficiency of our system. Results on the public TUM RGB-D database benchmark demonstrate that our camera tracking system achieves state-of-the-art results both in accuracy and efficiency.
Tracking dynamic team activity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tambe, M.
1996-12-31
AI researchers are striving to build complex multi-agent worlds with intended applications ranging from the RoboCup robotic soccer tournaments, to interactive virtual theatre, to large-scale real-world battlefield simulations. Agent tracking - monitoring other agent`s actions and inferring their higher-level goals and intentions - is a central requirement in such worlds. While previous work has mostly focused on tracking individual agents, this paper goes beyond by focusing on agent teams. Team tracking poses the challenge of tracking a team`s joint goals and plans. Dynamic, real-time environments add to the challenge, as ambiguities have to be resolved in real-time. The central hypothesismore » underlying the present work is that an explicit team-oriented perspective enables effective team tracking. This hypothesis is instantiated using the model tracing technology employed in tracking individual agents. Thus, to track team activities, team models are put to service. Team models are a concrete application of the joint intentions framework and enable an agent to track team activities, regardless of the agent`s being a collaborative participant or a non-participant in the team. To facilitate real-time ambiguity resolution with team models: (i) aspects of tracking are cast as constraint satisfaction problems to exploit constraint propagation techniques; and (ii) a cost minimality criterion is applied to constrain tracking search. Empirical results from two separate tasks in real-world, dynamic environments one collaborative and one competitive - are provided.« less
Track structure in biological models.
Curtis, S B
1986-01-01
High-energy heavy ions in the galactic cosmic radiation (HZE particles) may pose a special risk during long term manned space flights outside the sheltering confines of the earth's geomagnetic field. These particles are highly ionizing, and they and their nuclear secondaries can penetrate many centimeters of body tissue. The three dimensional patterns of ionizations they create as they lose energy are referred to as their track structure. Several models of biological action on mammalian cells attempt to treat track structure or related quantities in their formulation. The methods by which they do this are reviewed. The proximity function is introduced in connection with the theory of Dual Radiation Action (DRA). The ion-gamma kill (IGK) model introduces the radial energy-density distribution, which is a smooth function characterizing both the magnitude and extension of a charged particle track. The lethal, potentially lethal (LPL) model introduces lambda, the mean distance between relevant ion clusters or biochemical species along the track. Since very localized energy depositions (within approximately 10 nm) are emphasized, the proximity function as defined in the DRA model is not of utility in characterizing track structure in the LPL formulation.
FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras.
Xu, Lan; Liu, Yebin; Cheng, Wei; Guo, Kaiwen; Zhou, Guyue; Dai, Qionghai; Fang, Lu
2017-07-18
Aiming at automatic, convenient and non-instrusive motion capture, this paper presents a new generation markerless motion capture technique, the FlyCap system, to capture surface motions of moving characters using multiple autonomous flying cameras (autonomous unmanned aerial vehicles(UAVs) each integrated with an RGBD video camera). During data capture, three cooperative flying cameras automatically track and follow the moving target who performs large-scale motions in a wide space. We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera. We leverage the using of visual-odometry information provided by the UAV platform, and formulate the surface tracking problem in a non-linear objective function that can be linearized and effectively minimized through a Gaussian-Newton method. Quantitative and qualitative experimental results demonstrate the plausible surface and motion reconstruction results.
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.
Experiences from the anatomy track in the ontology alignment evaluation initiative.
Dragisic, Zlatan; Ivanova, Valentina; Li, Huanyu; Lambrix, Patrick
2017-12-04
One of the longest running tracks in the Ontology Alignment Evaluation Initiative is the Anatomy track which focuses on aligning two anatomy ontologies. The Anatomy track was started in 2005. In 2005 and 2006 the task in this track was to align the Foundational Model of Anatomy and the OpenGalen Anatomy Model. Since 2007 the ontologies used in the track are the Adult Mouse Anatomy and a part of the NCI Thesaurus. Since 2015 the data in the Anatomy track is also used in the Interactive track of the Ontology Alignment Evaluation Initiative. In this paper we focus on the Anatomy track in the years 2007-2016 and the Anatomy part of the Interactive track in 2015-2016. We describe the data set and the changes it went through during the years as well as the challenges it poses for ontology alignment systems. Further, we give an overview of all systems that participated in the track and the techniques they have used. We discuss the performance results of the systems and summarize the general trends. About 50 systems have participated in the Anatomy track. Many different techniques were used. The most popular matching techniques are string-based strategies and structure-based techniques. Many systems also use auxiliary information. The quality of the alignment has increased for the best performing systems since the beginning of the track and more and more systems check the coherence of the proposed alignment and implement a repair strategy. Further, interacting with an oracle is beneficial.
A distributed database view of network tracking systems
NASA Astrophysics Data System (ADS)
Yosinski, Jason; Paffenroth, Randy
2008-04-01
In distributed tracking systems, multiple non-collocated trackers cooperate to fuse local sensor data into a global track picture. Generating this global track picture at a central location is fairly straightforward, but the single point of failure and excessive bandwidth requirements introduced by centralized processing motivate the development of decentralized methods. In many decentralized tracking systems, trackers communicate with their peers via a lossy, bandwidth-limited network in which dropped, delayed, and out of order packets are typical. Oftentimes the decentralized tracking problem is viewed as a local tracking problem with a networking twist; we believe this view can underestimate the network complexities to be overcome. Indeed, a subsequent 'oversight' layer is often introduced to detect and handle track inconsistencies arising from a lack of robustness to network conditions. We instead pose the decentralized tracking problem as a distributed database problem, enabling us to draw inspiration from the vast extant literature on distributed databases. Using the two-phase commit algorithm, a well known technique for resolving transactions across a lossy network, we describe several ways in which one may build a distributed multiple hypothesis tracking system from the ground up to be robust to typical network intricacies. We pay particular attention to the dissimilar challenges presented by network track initiation vs. maintenance and suggest a hybrid system that balances speed and robustness by utilizing two-phase commit for only track initiation transactions. Finally, we present simulation results contrasting the performance of such a system with that of more traditional decentralized tracking implementations.
Sensing Human Activity: GPS Tracking
van der Spek, Stefan; van Schaick, Jeroen; de Bois, Peter; de Haan, Remco
2009-01-01
The enhancement of GPS technology enables the use of GPS devices not only as navigation and orientation tools, but also as instruments used to capture travelled routes: as sensors that measure activity on a city scale or the regional scale. TU Delft developed a process and database architecture for collecting data on pedestrian movement in three European city centres, Norwich, Rouen and Koblenz, and in another experiment for collecting activity data of 13 families in Almere (The Netherlands) for one week. The question posed in this paper is: what is the value of GPS as ‘sensor technology’ measuring activities of people? The conclusion is that GPS offers a widely useable instrument to collect invaluable spatial-temporal data on different scales and in different settings adding new layers of knowledge to urban studies, but the use of GPS-technology and deployment of GPS-devices still offers significant challenges for future research. PMID:22574061
Learning gestures for customizable human-computer interaction in the operating room.
Schwarz, Loren Arthur; Bigdelou, Ali; Navab, Nassir
2011-01-01
Interaction with computer-based medical devices in the operating room is often challenging for surgeons due to sterility requirements and the complexity of interventional procedures. Typical solutions, such as delegating the interaction task to an assistant, can be inefficient. We propose a method for gesture-based interaction in the operating room that surgeons can customize to personal requirements and interventional workflow. Given training examples for each desired gesture, our system learns low-dimensional manifold models that enable recognizing gestures and tracking particular poses for fine-grained control. By capturing the surgeon's movements with a few wireless body-worn inertial sensors, we avoid issues of camera-based systems, such as sensitivity to illumination and occlusions. Using a component-based framework implementation, our method can easily be connected to different medical devices. Our experiments show that the approach is able to robustly recognize learned gestures and to distinguish these from other movements.
Eichhorn, Klaus Wolfgang; Westphal, Ralf; Rilk, Markus; Last, Carsten; Bootz, Friedrich; Wahl, Friedrich; Jakob, Mark; Send, Thorsten
2017-10-01
Having one hand occupied with the endoscope is the major disadvantage for the surgeon when it comes to functional endoscopic sinus surgery (FESS). Only the other hand is free to use the surgical instruments. Tiredness or frequent instrument changes can thus lead to shaky endoscopic images. We collected the pose data (position and orientation) of the rigid 0° endoscope and all the instruments used in 16 FESS procedures with manual endoscope guidance as well as robot-assisted endoscope guidance. In combination with the DICOM CT data, we tracked the endoscope poses and workspaces using self-developed tracking markers. All surgeries were performed once with the robot and once with the surgeon holding the endoscope. Looking at the durations required, we observed a decrease in the operating time because one surgeon doing all the procedures and so a learning curve occurred what we expected. The visual inspection of the specimens showed no damages to any of the structures outside the paranasal sinuses. Robot-assisted endoscope guidance in sinus surgery is possible. Further CT data, however, are desirable for the surgical analysis of a tracker-based navigation within the anatomic borders. Our marker-based tracking of the endoscope as well as the instruments makes an automated endoscope guidance feasible. On the subjective side, we see that RASS brings a relief for the surgeon.
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.
16 CFR 260.10 - Non-toxic claims.
Code of Federal Regulations, 2013 CFR
2013-01-01
... pose any risk to humans or the environment, including household pets. If the cleaning product poses no... implication, that a product, package, or service is non-toxic. Non-toxic claims should be clearly and... product, package, or service is non-toxic both for humans and for the environment generally. Therefore...
16 CFR 260.10 - Non-toxic claims.
Code of Federal Regulations, 2014 CFR
2014-01-01
... pose any risk to humans or the environment, including household pets. If the cleaning product poses no... implication, that a product, package, or service is non-toxic. Non-toxic claims should be clearly and... product, package, or service is non-toxic both for humans and for the environment generally. Therefore...
Handling Discourse: Gestures, Reference Tracking, and Communication Strategies in Early L2
ERIC Educational Resources Information Center
Gullberg, Marianne
2006-01-01
The production of cohesive discourse, especially maintained reference, poses problems for early second language L2 speakers. This paper considers a communicative account of overexplicit L2 discourse by focusing on the interdependence between spoken and gestural cohesion, the latter being expressed by anchoring of referents in gesture space.…
ERIC Educational Resources Information Center
Kibble, Bob
2015-01-01
When Bob Kibble told an eight-year-old girl that he teaches teachers, she asked him, "So, who teaches you?" The question stopped him in his tracks, and has probably been the question that has made him think more than any other question. Kibble poses the following questions to those who are teachers or teachers of teachers whose…
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
Multimodal Deep Autoencoder for Human Pose Recovery.
Hong, Chaoqun; Yu, Jun; Wan, Jian; Tao, Dacheng; Wang, Meng
2015-12-01
Video-based human pose recovery is usually conducted by retrieving relevant poses using image features. In the retrieving process, the mapping between 2D images and 3D poses is assumed to be linear in most of the traditional methods. However, their relationships are inherently non-linear, which limits recovery performance of these methods. In this paper, we propose a novel pose recovery method using non-linear mapping with multi-layered deep neural network. It is based on feature extraction with multimodal fusion and back-propagation deep learning. In multimodal fusion, we construct hypergraph Laplacian with low-rank representation. In this way, we obtain a unified feature description by standard eigen-decomposition of the hypergraph Laplacian matrix. In back-propagation deep learning, we learn a non-linear mapping from 2D images to 3D poses with parameter fine-tuning. The experimental results on three data sets show that the recovery error has been reduced by 20%-25%, which demonstrates the effectiveness of the proposed method.
This asset includes the EPA Federal Agency Hazardous Waste Compliance Docket (Docket), which is required by Section 120(c) of the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA). The Docket contains information reported to EPA by federal facilities that manage hazardous waste or from which hazardous substances, pollutants or contaminants have been or may be released. The Docket serves three major purposes:1. To identify all federal facilities that must be evaluated through the site assessment process to determine whether they pose a risk to human health and the environment sufficient to warrant inclusion on the National Priorities List (NPL); 2. To compile and maintain the information submitted to EPA on such facilities under the provisions listed in section 120(c) of CERCLA; and3. To provide a mechanism to make the information available to the public.The docket includes facilities which have provided information to EPA through documents such as reports under a Federal agency environmental restoration program, regardless of the absence of section 103 reporting. E-Docket is an internal business management tool that will improve the tracking and record keeping of information about facilities that have been identified as potential Docket sites. The functionality of the system is basic record tracking, and it will contain a list of draft proposed facilities which can be sorted based on Agency ownership, region, or status (Draft Propose
NASA Technical Reports Server (NTRS)
Saha, Janapriya; Cucinotta, Francis A.; Wang, Minli
2013-01-01
High LET radiation from GCR (Galactic Cosmic Rays) consisting mainly of high charge and energy (HZE) nuclei and secondary protons and neutrons, and secondaries from protons in SPE (Solar Particle Event) pose a major health risk to astronauts due to induction of DNA damage and oxidative stress. Experiments with high energy particles mimicking the space environment for estimation of radiation risk are being performed at NASA Space Radiation Laboratory at BNL. Experiments with low energy particles comparing to high energy particles of similar LET are of interest for investigation of the role of track structure on biological effects. For this purpose, we report results utilizing the Tandem Van de Graaff accelerator at BNL. The primary objective of our studies is to elucidate the influence of high vs low energy deposition on track structure, delta ray contribution and resulting biological responses. These low energy ions are of special relevance as these energies may occur following absorption through the spacecraft and shielding materials in human tissues and nuclear fragments produced in tissues by high energy protons and neutrons. This study will help to verify the efficiency of these low energy particles and better understand how various cell types respond to them.
Tracking and recognition face in videos with incremental local sparse representation model
NASA Astrophysics Data System (ADS)
Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang
2013-10-01
This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.
Towards an IMU Evaluation Framework for Human Body Tracking.
Venek, Verena; Kremser, Wolfgang; Schneider, Cornelia
2018-01-01
Existing full-body tracking systems, which use Inertial Measurement Units (IMUs) as sensing unit, require expert knowledge for setup and data collection. Thus, the daily application for human body tracking is difficult. In particular, in the field of active and assisted living (AAL), tracking human movements would enable novel insights not only into the quantity but also into the quality of human movement, for example by monitoring functional training. While the current market offers a wide range of products with vastly different properties, literature lacks guidelines for choosing IMUs for body tracking applications. Therefore, this paper introduces developments towards an IMU evaluation framework for human body tracking which compares IMUs against five requirement areas that consider device features and data quality. The data quality is assessed by conducting a static and a dynamic error analysis. In a first application to four IMUs of different component consumption, the IMU evaluation framework convinced as promising tool for IMU selection.
NASA Astrophysics Data System (ADS)
Yang, Juqing; Wang, Dayong; Fan, Baixing; Dong, Dengfeng; Zhou, Weihu
2017-03-01
In-situ intelligent manufacturing for large-volume equipment requires industrial robots with absolute high-accuracy positioning and orientation steering control. Conventional robots mainly employ an offline calibration technology to identify and compensate key robotic parameters. However, the dynamic and static parameters of a robot change nonlinearly. It is not possible to acquire a robot's actual parameters and control the absolute pose of the robot with a high accuracy within a large workspace by offline calibration in real-time. This study proposes a real-time online absolute pose steering control method for an industrial robot based on six degrees of freedom laser tracking measurement, which adopts comprehensive compensation and correction of differential movement variables. First, the pose steering control system and robot kinematics error model are constructed, and then the pose error compensation mechanism and algorithm are introduced in detail. By accurately achieving the position and orientation of the robot end-tool, mapping the computed Jacobian matrix of the joint variable and correcting the joint variable, the real-time online absolute pose compensation for an industrial robot is accurately implemented in simulations and experimental tests. The average positioning error is 0.048 mm and orientation accuracy is better than 0.01 deg. The results demonstrate that the proposed method is feasible, and the online absolute accuracy of a robot is sufficiently enhanced.
Optical flow and driver's kinematics analysis for state of alert sensing.
Jiménez-Pinto, Javier; Torres-Torriti, Miguel
2013-03-28
Road accident statistics from different countries show that a significant number of accidents occur due to driver's fatigue and lack of awareness to traffic conditions. In particular, about 60% of the accidents in which long haul truck and bus drivers are involved are attributed to drowsiness and fatigue. It is thus fundamental to improve non-invasive systems for sensing a driver's state of alert. One of the main challenges to correctly resolve the state of alert is measuring the percentage of eyelid closure over time (PERCLOS), despite the driver's head and body movements. In this paper, we propose a technique that involves optical flow and driver's kinematics analysis to improve the robustness of the driver's alert state measurement under pose changes using a single camera with near-infrared illumination. The proposed approach infers and keeps track of the driver's pose in 3D space in order to ensure that eyes can be located correctly, even after periods of partial occlusion, for example, when the driver stares away from the camera. Our experiments show the effectiveness of the approach with a correct eyes detection rate of 99.41%, on average. The results obtained with the proposed approach in an experiment involving fifteen persons under different levels of sleep deprivation also confirm the discriminability of the fatigue levels. In addition to the measurement of fatigue and drowsiness, the pose tracking capability of the proposed approach has potential applications in distraction assessment and alerting of machine operators.
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.
Optical Flow and Driver's Kinematics Analysis for State of Alert Sensing
Jiménez-Pinto, Javier; Torres-Torriti, Miguel
2013-01-01
Road accident statistics from different countries show that a significant number of accidents occur due to driver's fatigue and lack of awareness to traffic conditions. In particular, about 60% of the accidents in which long haul truck and bus drivers are involved are attributed to drowsiness and fatigue. It is thus fundamental to improve non-invasive systems for sensing a driver's state of alert. One of the main challenges to correctly resolve the state of alert is measuring the percentage of eyelid closure over time (PERCLOS), despite the driver's head and body movements. In this paper, we propose a technique that involves optical flow and driver's kinematics analysis to improve the robustness of the driver's alert state measurement under pose changes using a single camera with near-infrared illumination. The proposed approach infers and keeps track of the driver's pose in 3D space in order to ensure that eyes can be located correctly, even after periods of partial occlusion, for example, when the driver stares away from the camera. Our experiments show the effectiveness of the approach with a correct eyes detection rate of 99.41%, on average. The results obtained with the proposed approach in an experiment involving fifteen persons under different levels of sleep deprivation also confirm the discriminability of the fatigue levels. In addition to the measurement of fatigue and drowsiness, the pose tracking capability of the proposed approach has potential applications in distraction assessment and alerting of machine operators. PMID:23539029
GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome.
Simovski, Boris; Vodák, Daniel; Gundersen, Sveinung; Domanska, Diana; Azab, Abdulrahman; Holden, Lars; Holden, Marit; Grytten, Ivar; Rand, Knut; Drabløs, Finn; Johansen, Morten; Mora, Antonio; Lund-Andersen, Christin; Fromm, Bastian; Eskeland, Ragnhild; Gabrielsen, Odd Stokke; Ferkingstad, Egil; Nakken, Sigve; Bengtsen, Mads; Nederbragt, Alexander Johan; Thorarensen, Hildur Sif; Akse, Johannes Andreas; Glad, Ingrid; Hovig, Eivind; Sandve, Geir Kjetil
2017-07-01
Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation. We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered. Through a combination of streamlined data acquisition, interoperable representation of dataset collections, and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no. © The Author 2017. Published by Oxford University Press.
Evaluation of a video-based head motion tracking system for dedicated brain PET
NASA Astrophysics Data System (ADS)
Anishchenko, S.; Beylin, D.; Stepanov, P.; Stepanov, A.; Weinberg, I. N.; Schaeffer, S.; Zavarzin, V.; Shaposhnikov, D.; Smith, M. F.
2015-03-01
Unintentional head motion during Positron Emission Tomography (PET) data acquisition can degrade PET image quality and lead to artifacts. Poor patient compliance, head tremor, and coughing are examples of movement sources. Head motion due to patient non-compliance can be an issue with the rise of amyloid brain PET in dementia patients. To preserve PET image resolution and quantitative accuracy, head motion can be tracked and corrected in the image reconstruction algorithm. While fiducial markers can be used, a contactless approach is preferable. A video-based head motion tracking system for a dedicated portable brain PET scanner was developed. Four wide-angle cameras organized in two stereo pairs are used for capturing video of the patient's head during the PET data acquisition. Facial points are automatically tracked and used to determine the six degree of freedom head pose as a function of time. The presented work evaluated the newly designed tracking system using a head phantom and a moving American College of Radiology (ACR) phantom. The mean video-tracking error was 0.99±0.90 mm relative to the magnetic tracking device used as ground truth. Qualitative evaluation with the ACR phantom shows the advantage of the motion tracking application. The developed system is able to perform tracking with accuracy close to millimeter and can help to preserve resolution of brain PET images in presence of movements.
Evolution of circadian rhythms: from bacteria to human.
Bhadra, Utpal; Thakkar, Nirav; Das, Paromita; Pal Bhadra, Manika
2017-07-01
The human body persists in its rhythm as per its initial time zone, and transition always occur according to solar movements around the earth over 24 h. While traveling across different latitudes and longitudes, at the pace exceeding the earth's movement, the changes in the external cues exceed the level of toleration of the body's biological clock. This poses an alteration in our physiological activities of sleep-wake pattern, mental alertness, organ movement, and eating habits, causing them to temporarily lose the track of time. This is further re-synchronized with the physiological cues of the destination over time. The mechanism of resetting of the clocks with varying time zones and cues occur in organisms from bacteria to humans. It is the result of the evolution of different pathways and molecular mechanisms over the time. There has been evolution of numerous comprehensive mechanisms using various research tools to get a deeper insight into the rapid turnover of molecular mechanisms in various species. This review reports insights into the evolution of the circadian mechanism and its evolutionary shift which is vital and plays a major role in assisting different organisms to adapt in different zones and controls their internal biological clocks with changing external cues. Copyright © 2017 Elsevier B.V. All rights reserved.
STS-49 Endeavour, Orbiter Vehicle (OV) 105, Planning Team in MCC Bldg 30 FCR
NASA Technical Reports Server (NTRS)
1992-01-01
STS-49 Endeavour, Orbiter Vehicle (OV) 105, Planning Team with Flight Director (FD) James M. Heflin, Jr (front right next to ship model) poses in JSC's Mission Control Center (MCC) Bldg 30 Flight Control Room (FCR). The group stands in front of visual displays projecting STS-49 data and ground track map.
Efficient place and route enablement of 5-tracks standard-cells through EUV compatible N5 ruleset
NASA Astrophysics Data System (ADS)
Matti, L.; Gerousis, V.; Berekovic, M.; Debacker, P.; Sherazi, S. M. Y.; Milojevic, D.; Baert, R.; Ryckaert, J.; Kim, Ryoung-han; Verkest, Diederik; Raghavan, P.
2018-03-01
In imec predictive N5 technology platform (poly pitch 42nm, metal pitch 32nm), enabling cell height reduction from 6 to 5 tracks constitutes an interesting opportunity to reduce area of digital IP-blocks without increasing wafer cost. From a physical point of view, the two main challenges of reducing the number of tracks are posed by the increased difficulty of completing inter-cell connections in standard cell design, and by increased pin density that makes more challenging for the router to maintain high placement densities. Both these issues can potentially result into cell and chip area enlargement, thus mitigating or canceling the benefits of moving to 5-Tracks. In this study this side effect was avoided through a careful Design-Technology Co-Optimization approach (DTCO) [1], where a set of design arcs was used in conjunction with an EUV compatible ruleset that allowed efficient 5-Tracks standard cell design, resulting in final area gains up to 17% that were validated through a commercial state-of-the-art Place and Route (P&R) flow.
A restraint-free small animal SPECT imaging system with motion tracking
DOE Office of Scientific and Technical Information (OSTI.GOV)
Weisenberger, A.G.; Gleason, S.S.; Goddard, J.
2005-06-01
We report on an approach toward the development of a high-resolution single photon emission computed tomography (SPECT) system to image the biodistribution of radiolabeled tracers such as Tc-99m and I-125 in unrestrained/unanesthetized mice. An infrared (IR)-based position tracking apparatus has been developed and integrated into a SPECT gantry. The tracking system is designed to measure the spatial position of a mouse's head at a rate of 10-15 frames per second with submillimeter accuracy. The high-resolution, gamma imaging detectors are based on pixellated NaI(Tl) crystal scintillator arrays, position-sensitive photomultiplier tubes, and novel readout circuitry requiring fewer analog-digital converter (ADC) channels whilemore » retaining high spatial resolution. Two SPECT gamma camera detector heads based upon position-sensitive photomultiplier tubes have been built and installed onto the gantry. The IR landmark-based pose measurement and tracking system is under development to provide animal position data during a SPECT scan. The animal position and orientation data acquired by the tracking system will be used for motion correction during the tomographic image reconstruction.« less
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.
ADRC for spacecraft attitude and position synchronization in libration point orbits
NASA Astrophysics Data System (ADS)
Gao, Chen; Yuan, Jianping; Zhao, Yakun
2018-04-01
This paper addresses the problem of spacecraft attitude and position synchronization in libration point orbits between a leader and a follower. Using dual quaternion, the dimensionless relative coupled dynamical model is derived considering computation efficiency and accuracy. Then a model-independent dimensionless cascade pose-feedback active disturbance rejection controller is designed to spacecraft attitude and position tracking control problems considering parameter uncertainties and external disturbances. Numerical simulations for the final approach phase in spacecraft rendezvous and docking and formation flying are done, and the results show high-precision tracking errors and satisfactory convergent rates under bounded control torque and force which validate the proposed approach.
Reconstruction software of the silicon tracker of DAMPE mission
NASA Astrophysics Data System (ADS)
Tykhonov, A.; Gallo, V.; Wu, X.; Zimmer, S.
2017-10-01
DAMPE is a satellite-borne experiment aimed to probe astroparticle physics in the GeV-TeV energy range. The Silicon tracker (STK) is one of the key components of DAMPE, which allows the reconstruction of trajectories (tracks) of detected particles. The non-negligible amount of material in the tracker poses a challenge to its reconstruction and alignment. In this paper we describe methods to address this challenge. We present the track reconstruction algorithm and give insight into the alignment algorithm. We also present our CAD-to-GDML converter, an in-house tool for implementing detector geometry in the software from the CAD drawings of the detector.
Vemuri, Anant Suraj; Nicolau, Stephane A; Ayache, Nicholas; Marescaux, Jacques; Soler, Luc
2013-01-01
The screening of oesophageal adenocarcinoma involves obtaining biopsies at different regions along the oesophagus. The localization and tracking of these biopsy sites inter-operatively poses a significant challenge for providing targeted treatments. This paper presents a novel framework for providing a guided navigation to the gastro-intestinal specialist for accurate re-positioning of the endoscope at previously targeted sites. Firstly, we explain our approach for the application of electromagnetic tracking in acheiving this objective. Then, we show on three in-vivo porcine interventions that our system can provide accurate guidance information, which was qualitatively evaluated by five experts.
Human image tracking technique applied to remote collaborative environments
NASA Astrophysics Data System (ADS)
Nagashima, Yoshio; Suzuki, Gen
1993-10-01
To support various kinds of collaborations over long distances by using visual telecommunication, it is necessary to transmit visual information related to the participants and topical materials. When people collaborate in the same workspace, they use visual cues such as facial expressions and eye movement. The realization of coexistence in a collaborative workspace requires the support of these visual cues. Therefore, it is important that the facial images be large enough to be useful. During collaborations, especially dynamic collaborative activities such as equipment operation or lectures, the participants often move within the workspace. When the people move frequently or over a wide area, the necessity for automatic human tracking increases. Using the movement area of the human being or the resolution of the extracted area, we have developed a memory tracking method and a camera tracking method for automatic human tracking. Experimental results using a real-time tracking system show that the extracted area fairly moves according to the movement of the human head.
NASA Astrophysics Data System (ADS)
Xue, Yuan; Cheng, Teng; Xu, Xiaohai; Gao, Zeren; Li, Qianqian; Liu, Xiaojing; Wang, Xing; Song, Rui; Ju, Xiangyang; Zhang, Qingchuan
2017-01-01
This paper presents a system for positioning markers and tracking the pose of a rigid object with 6 degrees of freedom in real-time using 3D digital image correlation, with two examples for medical imaging applications. Traditional DIC method was improved to meet the requirements of the real-time by simplifying the computations of integral pixel search. Experiments were carried out and the results indicated that the new method improved the computational efficiency by about 4-10 times in comparison with the traditional DIC method. The system was aimed for orthognathic surgery navigation in order to track the maxilla segment after LeFort I osteotomy. Experiments showed noise for the static point was at the level of 10-3 mm and the measurement accuracy was 0.009 mm. The system was demonstrated on skin surface shape evaluation of a hand for finger stretching exercises, which indicated a great potential on tracking muscle and skin movements.
NASA Astrophysics Data System (ADS)
Roth, Eatai; Howell, Darrin; Beckwith, Cydney; Burden, Samuel A.
2017-05-01
Humans, interacting with cyber-physical systems (CPS), formulate beliefs about the system's dynamics. It is natural to expect that human operators, tasked with teleoperation, use these beliefs to control the remote robot. For tracking tasks in the resulting human-cyber-physical system (HCPS), theory suggests that human operators can achieve exponential tracking (in stable systems) without state estimation provided they possess an accurate model of the system's dynamics. This internalized inverse model, however, renders a portion of the system state unobservable to the human operator—the zero dynamics. Prior work shows humans can track through observable linear dynamics, thus we focus on nonlinear dynamics rendered unobservable through tracking control. We propose experiments to assess the human operator's ability to learn and invert such models, and distinguish this behavior from that achieved by pure feedback control.
The Genomic HyperBrowser: an analysis web server for genome-scale data
Sandve, Geir K.; Gundersen, Sveinung; Johansen, Morten; Glad, Ingrid K.; Gunathasan, Krishanthi; Holden, Lars; Holden, Marit; Liestøl, Knut; Nygård, Ståle; Nygaard, Vegard; Paulsen, Jonas; Rydbeck, Halfdan; Trengereid, Kai; Clancy, Trevor; Drabløs, Finn; Ferkingstad, Egil; Kalaš, Matúš; Lien, Tonje; Rye, Morten B.; Frigessi, Arnoldo; Hovig, Eivind
2013-01-01
The immense increase in availability of genomic scale datasets, such as those provided by the ENCODE and Roadmap Epigenomics projects, presents unprecedented opportunities for individual researchers to pose novel falsifiable biological questions. With this opportunity, however, researchers are faced with the challenge of how to best analyze and interpret their genome-scale datasets. A powerful way of representing genome-scale data is as feature-specific coordinates relative to reference genome assemblies, i.e. as genomic tracks. The Genomic HyperBrowser (http://hyperbrowser.uio.no) is an open-ended web server for the analysis of genomic track data. Through the provision of several highly customizable components for processing and statistical analysis of genomic tracks, the HyperBrowser opens for a range of genomic investigations, related to, e.g., gene regulation, disease association or epigenetic modifications of the genome. PMID:23632163
The Genomic HyperBrowser: an analysis web server for genome-scale data.
Sandve, Geir K; Gundersen, Sveinung; Johansen, Morten; Glad, Ingrid K; Gunathasan, Krishanthi; Holden, Lars; Holden, Marit; Liestøl, Knut; Nygård, Ståle; Nygaard, Vegard; Paulsen, Jonas; Rydbeck, Halfdan; Trengereid, Kai; Clancy, Trevor; Drabløs, Finn; Ferkingstad, Egil; Kalas, Matús; Lien, Tonje; Rye, Morten B; Frigessi, Arnoldo; Hovig, Eivind
2013-07-01
The immense increase in availability of genomic scale datasets, such as those provided by the ENCODE and Roadmap Epigenomics projects, presents unprecedented opportunities for individual researchers to pose novel falsifiable biological questions. With this opportunity, however, researchers are faced with the challenge of how to best analyze and interpret their genome-scale datasets. A powerful way of representing genome-scale data is as feature-specific coordinates relative to reference genome assemblies, i.e. as genomic tracks. The Genomic HyperBrowser (http://hyperbrowser.uio.no) is an open-ended web server for the analysis of genomic track data. Through the provision of several highly customizable components for processing and statistical analysis of genomic tracks, the HyperBrowser opens for a range of genomic investigations, related to, e.g., gene regulation, disease association or epigenetic modifications of the genome.
Human movement tracking based on Kalman filter
NASA Astrophysics Data System (ADS)
Zhang, Yi; Luo, Yuan
2006-11-01
During the rehabilitation process of the post-stroke patients is conducted, their movements need to be localized and learned so that incorrect movement can be instantly modified or tuned. Therefore, tracking these movement becomes vital and necessary for the rehabilitative course. In the technologies of human movement tracking, the position prediction of human movement is very important. In this paper, we first analyze the configuration of the human movement system and choice of sensors. Then, The Kalman filter algorithm and its modified algorithm are proposed and to be used to predict the position of human movement. In the end, on the basis of analyzing the performance of the method, it is clear that the method described can be used to the system of human movement tracking.
An Empirical Human Controller Model for Preview Tracking Tasks.
van der El, Kasper; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus Rene M; Mulder, Max
2016-11-01
Real-life tracking tasks often show preview information to the human controller about the future track to follow. The effect of preview on manual control behavior is still relatively unknown. This paper proposes a generic operator model for preview tracking, empirically derived from experimental measurements. Conditions included pursuit tracking, i.e., without preview information, and tracking with 1 s of preview. Controlled element dynamics varied between gain, single integrator, and double integrator. The model is derived in the frequency domain, after application of a black-box system identification method based on Fourier coefficients. Parameter estimates are obtained to assess the validity of the model in both the time domain and frequency domain. Measured behavior in all evaluated conditions can be captured with the commonly used quasi-linear operator model for compensatory tracking, extended with two viewpoints of the previewed target. The derived model provides new insights into how human operators use preview information in tracking tasks.
Analyzing Ocean Tracks: A model for student engagement in authentic scientific practices using data
NASA Astrophysics Data System (ADS)
Krumhansl, K.; Krumhansl, R.; Brown, C.; DeLisi, J.; Kochevar, R.; Sickler, J.; Busey, A.; Mueller-Northcott, J.; Block, B.
2013-12-01
The collection of large quantities of scientific data has not only transformed science, but holds the potential to transform teaching and learning by engaging students in authentic scientific work. Furthermore, it has become imperative in a data-rich world that students gain competency in working with and interpreting data. The Next Generation Science Standards reflect both the opportunity and need for greater integration of data in science education, and emphasize that both scientific knowledge and practice are essential elements of science learning. The process of enabling access by novice learners to data collected and used by experts poses significant challenges, however, recent research has demonstrated that barriers to student learning with data can be overcome by the careful design of data access and analysis tools that are specifically tailored to students. A group of educators at Education Development Center, Inc. (EDC) and scientists at Stanford University's Hopkins Marine Station are collaborating to develop and test a model for student engagement with scientific data using a web-based platform. This model, called Ocean Tracks: Investigating Marine Migrations in a Changing Ocean, provides students with the ability to plot and analyze tracks of migrating marine animals collected through the Tagging of Pacific Predators program. The interface and associated curriculum support students in identifying relationships between animal behavior and physical oceanographic variables (e.g. SST, chlorophyll, currents), making linkages between the living world and climate. Students are also supported in investigating possible sources of human impact to important biodiversity hotspots in the Pacific Ocean. The first round of classroom testing revealed that students were able to easily access and display data on the interface, and collect measurements from the animal tracks and oceanographic data layers. They were able to link multiple types of data to draw powerful inferences about how marine animal behavior is influenced by the ocean environment, and propose strategies to protect marine animals in the context of a changing ocean. Classroom testing also revealed the importance of providing students with real-world context to their learning, and the opportunity to directly compare their scientific investigations of data with those of scientists in the field. Our results also identified that student engagement was enhanced when they developed a direct personal connection to their scientific investigations by linking human activities to changes occurring in the natural world, and visualizing these changes using authentic data. This presentation will review the design elements of the Ocean Tracks interface and associated curriculum, our successes and challenges in supporting students in data based learning, and discuss specific linkages to the NGSS.
Ann Hutchinson (as subject), Dr. Joan Vernikos (R), Dee O'Hara (L), J. Evans and E. Lowe pose for
NASA Technical Reports Server (NTRS)
1993-01-01
Ann Hutchinson (as subject), Dr. Joan Vernikos (R), Dee O'Hara (L), J. Evans and E. Lowe pose for pictures in the NASA Magazine aritcle 'How it Feels to be a Human Test Subject' as they prepare for a bed rest study to simulate the efects of microgravity on the human body.
Meisner, Matthew H; Harmon, Jason P; Ives, Anthony R
2011-02-01
Cannibalism, where one species feeds on individuals of its own species, and intraguild predation (IGP), where a predator feeds on other predatory species, can both pose significant threats to natural enemies and interfere with their biological control of pests. Behavioral mechanisms to avoid these threats, however, could help maintain superior pest control. Here, we ask whether larvae of Coccinella septempunctata (Coleoptera: Coccinellidae) and Harmonia axyridis (Coleoptera: Coccinellidae) respond to larval tracks deposited by the other and whether this behavioral response reduces the threat of cannibalism and IGP. In petri dish experiments, we show that both H. axyridis and C. septempunctata avoid foraging in areas with conspecific larval tracks. Using a method of preventing larvae from depositing tracks, we then demonstrate that the frequency of cannibalism is greater for both species when larvae are prevented from depositing tracks compared with when the tracks are deposited. For multi-species interactions we show in petri dish experiments that C. septempunctata avoids H. axyridis larval tracks but H. axyridis does not avoid C. septempunctata larval tracks, demonstrating an asymmetry in response to larval tracks that parallels the asymmetry in aggressiveness between these species as intraguild predators. On single plants, we show that the presence of H. axyridis larval tracks reduces the risk of IGP by H. axyridis on C. septempunctata. Our study suggests that larval tracks can be used in more ways than previously described, in this case by changing coccinellid larval behavior in a way that reduces cannibalism and IGP. © 2011 Entomological Society of America
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.
Model-Based Reinforcement of Kinect Depth Data for Human Motion Capture Applications
Calderita, Luis Vicente; Bandera, Juan Pedro; Bustos, Pablo; Skiadopoulos, Andreas
2013-01-01
Motion capture systems have recently experienced a strong evolution. New cheap depth sensors and open source frameworks, such as OpenNI, allow for perceiving human motion on-line without using invasive systems. However, these proposals do not evaluate the validity of the obtained poses. This paper addresses this issue using a model-based pose generator to complement the OpenNI human tracker. The proposed system enforces kinematics constraints, eliminates odd poses and filters sensor noise, while learning the real dimensions of the performer's body. The system is composed by a PrimeSense sensor, an OpenNI tracker and a kinematics-based filter and has been extensively tested. Experiments show that the proposed system improves pure OpenNI results at a very low computational cost. PMID:23845933
Video-Based Eye Tracking to Detect the Attention Shift: A Computer Classroom Context-Aware System
ERIC Educational Resources Information Center
Kuo, Yung-Lung; Lee, Jiann-Shu; Hsieh, Min-Chai
2014-01-01
Eye and head movements evoked in response to obvious visual attention shifts. However, there has been little progress on the causes of absent-mindedness so far. The paper proposes an attention awareness system that captures the conditions regarding the interaction of eye gaze and head pose under various attentional switching in computer classroom.…
Mobile Robot Pose Tracking for Performance Analysis
2002-08-01
of Applanix POS LV 420 Intertial Navigation Unit (HMMWV Test Vehicle). GPS Outage Duration (minutes)POS LV 420-RT (using DGPS) 0 min 1 min 3 min 5...0.02 0.02 0.02 True Heading (deg) 0.02 0.02 0.02 0.04 0.06 0.10 0.20 Table 3: Performance of Applanix LV 420 with post-processing (HMMWV Test Vehicle
A computer simulation approach to measurement of human control strategy
NASA Technical Reports Server (NTRS)
Green, J.; Davenport, E. L.; Engler, H. F.; Sears, W. E., III
1982-01-01
Human control strategy is measured through use of a psychologically-based computer simulation which reflects a broader theory of control behavior. The simulation is called the human operator performance emulator, or HOPE. HOPE was designed to emulate control learning in a one-dimensional preview tracking task and to measure control strategy in that setting. When given a numerical representation of a track and information about current position in relation to that track, HOPE generates positions for a stick controlling the cursor to be moved along the track. In other words, HOPE generates control stick behavior corresponding to that which might be used by a person learning preview tracking.
Li, Li-Guan; Yin, Xiaole; Zhang, Tong
2018-05-24
Antimicrobial resistance (AMR) has been a worldwide public health concern. Current widespread AMR pollution has posed a big challenge in accurately disentangling source-sink relationship, which has been further confounded by point and non-point sources, as well as endogenous and exogenous cross-reactivity under complicated environmental conditions. Because of insufficient capability in identifying source-sink relationship within a quantitative framework, traditional antibiotic resistance gene (ARG) signatures-based source-tracking methods would hardly be a practical solution. By combining broad-spectrum ARG profiling with machine-learning classification SourceTracker, here we present a novel way to address the question in the era of high-throughput sequencing. Its potential in extensive application was firstly validated by 656 global-scale samples covering diverse environmental types (e.g., human/animal gut, wastewater, soil, ocean) and broad geographical regions (e.g., China, USA, Europe, Peru). Its potential and limitations in source prediction as well as effect of parameter adjustment were then rigorously evaluated by artificial configurations with representative source proportions. When applying SourceTracker in region-specific analysis, excellent performance was achieved by ARG profiles in two sample types with obvious different source compositions, i.e., influent and effluent of wastewater treatment plant. Two environmental metagenomic datasets of anthropogenic interference gradient further supported its potential in practical application. To complement general-profile-based source tracking in distinguishing continuous gradient pollution, a few generalist and specialist indicator ARGs across ecotypes were identified in this study. We demonstrated for the first time that the developed source-tracking platform when coupling with proper experiment design and efficient metagenomic analysis tools will have significant implications for assessing AMR pollution. Following predicted source contribution status, risk ranking of different sources in ARG dissemination will be possible, thereby paving the way for establishing priority in mitigating ARG spread and designing effective control strategies.
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
Human performance evaluation in dual-axis critical task tracking
NASA Technical Reports Server (NTRS)
Ritchie, M. L.; Nataraj, N. S.
1975-01-01
A dual axis tracking using a multiloop critical task was set up to evaluate human performance. The effects of control stick variation and display formats are evaluated. A secondary loading was used to measure the degradation in tracking performance.
Multilayer Joint Gait-Pose Manifolds for Human Gait Motion Modeling.
Ding, Meng; Fan, Guolian
2015-11-01
We present new multilayer joint gait-pose manifolds (multilayer JGPMs) for complex human gait motion modeling, where three latent variables are defined jointly in a low-dimensional manifold to represent a variety of body configurations. Specifically, the pose variable (along the pose manifold) denotes a specific stage in a walking cycle; the gait variable (along the gait manifold) represents different walking styles; and the linear scale variable characterizes the maximum stride in a walking cycle. We discuss two kinds of topological priors for coupling the pose and gait manifolds, i.e., cylindrical and toroidal, to examine their effectiveness and suitability for motion modeling. We resort to a topologically-constrained Gaussian process (GP) latent variable model to learn the multilayer JGPMs where two new techniques are introduced to facilitate model learning under limited training data. First is training data diversification that creates a set of simulated motion data with different strides. Second is the topology-aware local learning to speed up model learning by taking advantage of the local topological structure. The experimental results on the Carnegie Mellon University motion capture data demonstrate the advantages of our proposed multilayer models over several existing GP-based motion models in terms of the overall performance of human gait motion modeling.
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.
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.
Recognition of complex human behaviours using 3D imaging for intelligent surveillance applications
NASA Astrophysics Data System (ADS)
Yao, Bo; Lepley, Jason J.; Peall, Robert; Butler, Michael; Hagras, Hani
2016-10-01
We introduce a system that exploits 3-D imaging technology as an enabler for the robust recognition of the human form. We combine this with pose and feature recognition capabilities from which we can recognise high-level human behaviours. We propose a hierarchical methodology for the recognition of complex human behaviours, based on the identification of a set of atomic behaviours, individual and sequential poses (e.g. standing, sitting, walking, drinking and eating) that provides a framework from which we adopt time-based machine learning techniques to recognise complex behaviour patterns.
[Highly contagious diseases with human-to-human transmission].
Rybka, Aleš; Szanyi, Juraj; Kapla, Jaroslav; Plíšek, Stanislav
2012-12-01
Highly contagious diseases are caused by various biological agents that pose a risk to individuals and may have a potential for public health impact. They result in high mortality and morbidity rates, might cause public panic and therefore require special measures. The pathogens that can be easily disseminated or transmitted from person to person are the riskiest for clinicians (Ebola virus, Marburg virus, Lassa virus, Crimean-Congo hemorrhagic fever virus, Variola major, SARS virus and Yersinia pestis). Human-to-human transmission has not been confirmed for the other biological agents and therefore they pose a very low risk for population.
Hand-Eye Calibration in Visually-Guided Robot Grinding.
Li, Wen-Long; Xie, He; Zhang, Gang; Yan, Si-Jie; Yin, Zhou-Ping
2016-11-01
Visually-guided robot grinding is a novel and promising automation technique for blade manufacturing. One common problem encountered in robot grinding is hand-eye calibration, which establishes the pose relationship between the end effector (hand) and the scanning sensor (eye). This paper proposes a new calibration approach for robot belt grinding. The main contribution of this paper is its consideration of both joint parameter errors and pose parameter errors in a hand-eye calibration equation. The objective function of the hand-eye calibration is built and solved, from which 30 compensated values (corresponding to 24 joint parameters and six pose parameters) are easily calculated in a closed solution. The proposed approach is economic and simple because only a criterion sphere is used to calculate the calibration parameters, avoiding the need for an expensive and complicated tracking process using a laser tracker. The effectiveness of this method is verified using a calibration experiment and a blade grinding experiment. The code used in this approach is attached in the Appendix.
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.
Reproducibility of apatite fission-track length data and thermal history reconstruction
NASA Astrophysics Data System (ADS)
Ketcham, Richard A.; Donelick, Raymond A.; Balestrieri, Maria Laura; Zattin, Massimiliano
2009-07-01
The ability to derive detailed thermal history information from apatite fission-track analysis is predicated on the reliability of track length measurements. However, insufficient attention has been given to whether and how these measurements should be standardized. In conjunction with a fission-track workshop we conducted an experiment in which 11 volunteers measured ~ 50 track lengths on one or two samples. One mount contained Durango apatite with unannealed induced tracks, and one contained apatite from a crystalline rock containing spontaneous tracks with a broad length distribution caused by partial resetting. Results for both mounts showed scatter indicative of differences in measurement technique among the individual analysts. The effects of this variability on thermal history inversion were tested using the HeFTy computer program to model the spontaneous track measurements. A cooling-only scenario and a reheating scenario more consistent with the sample's geological history were posed. When a uniform initial length value from the literature was used, results among analysts were very inconsistent in both scenarios, although normalizing for track angle by projecting all lengths to a c-axis parallel crystallographic orientation improved some aspects of congruency. When the induced track measurement was used as the basis for thermal history inversion congruency among analysts, and agreement with inversions based on data previously collected, was significantly improved. Further improvement was obtained by using c-axis projection. Differences among inversions that persisted could be traced to differential sampling of long- and short-track populations among analysts. The results of this study, while demonstrating the robustness of apatite fission-track thermal history inversion, nevertheless point to the necessity for a standardized length calibration schema that accounts for analyst variation.
SU-G-JeP3-03: Effect of Robot Pose On Beam Blocking for Ultrasound Guided SBRT of the Prostate
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gerlach, S; Schlaefer, A; Kuhlemann, I
Purpose: Ultrasound presents a fast, volumetric image modality for real-time tracking of abdominal organ motion. How-ever, ultrasound transducer placement during radiation therapy is challenging. Recently, approaches using robotic arms for intra-treatment ultrasound imaging have been proposed. Good and reliable imaging requires placing the transducer close to the PTV. We studied the effect of a seven degrees of freedom robot on the fea-sible beam directions. Methods: For five CyberKnife prostate treatment plans we established viewports for the transducer, i.e., points on the patient surface with a soft tissue view towards the PTV. Choosing a feasible transducer pose and using the kinematicmore » redundancy of the KUKA LBR iiwa robot, we considered three robot poses. Poses 1 to 3 had the elbow point anterior, superior, and inferior, respectively. For each pose and each beam starting point, the pro-jections of robot and PTV were computed. We added a 20 mm margin accounting for organ / beam motion. The number of nodes for which the PTV was partially of fully blocked were established. Moreover, the cumula-tive overlap for each of the poses and the minimum overlap over all poses were computed. Results: The fully and partially blocked nodes ranged from 12% to 20% and 13% to 27%, respectively. Typically, pose 3 caused the fewest blocked nodes. The cumulative overlap ranged from 19% to 29%. Taking the minimum overlap, i.e., considering moving the robot’s elbow while maintaining the transducer pose, the cumulative over-lap was reduced to 16% to 18% and was 3% to 6% lower than for the best individual pose. Conclusion: Our results indicate that it is possible to identify feasible ultrasound transducer poses and to use the kinematic redundancy of a 7 DOF robot to minimize the impact of the imaging subsystem on the feasible beam directions for ultrasound guided and motion compensated SBRT. Research partially funded by DFG grants ER 817/1-1 and SCHL 1844/3-1.« less
Diocou, S; Volpe, A; Jauregui-Osoro, M; Boudjemeline, M; Chuamsaamarkkee, K; Man, F; Blower, P J; Ng, T; Mullen, G E D; Fruhwirth, G O
2017-04-19
Cancer cell metastasis is responsible for most cancer deaths. Non-invasive in vivo cancer cell tracking in spontaneously metastasizing tumor models still poses a challenge requiring highest sensitivity and excellent contrast. The goal of this study was to evaluate if the recently introduced PET radiotracer [ 18 F]tetrafluoroborate ([ 18 F]BF 4 - ) is useful for sensitive and specific metastasis detection in an orthotopic xenograft breast cancer model expressing the human sodium iodide symporter (NIS) as a reporter. In vivo imaging was complemented by ex vivo fluorescence microscopy and γ-counting of harvested tissues. Radionuclide imaging with [ 18 F]BF 4 - (PET/CT) was compared to the conventional tracer [ 123 I]iodide (sequential SPECT/CT). We found that [ 18 F]BF 4 - was superior due to better pharmacokinetics, i.e. faster tumor uptake and faster and more complete clearance from circulation. [ 18 F]BF 4 - -PET was also highly specific as in all detected tissues cancer cell presence was confirmed microscopically. Undetected comparable tissues were similarly found to be free of metastasis. Metastasis detection by routine metabolic imaging with [ 18 F]FDG-PET failed due to low standard uptake values and low contrast caused by adjacent metabolically active organs in this model. [ 18 F]BF 4 - -PET combined with NIS expressing disease models is particularly useful whenever preclinical in vivo cell tracking is of interest.
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeVolpi, A.; Palm, R.
CFE poses a number of verification challenges that could be met in part by an accurate and low-cost means of aiding in accountability of treaty-limited equipment. Although the treaty as signed does not explicitly call for the use of tags, there is a provision for recording serial numbers'' and placing special marks'' on equipment subject to reduction. There are approximately 150,000 residual items to be tracked for CFE-I, about half for each alliance of state parties. These highly mobile items are subject to complex treaty limitations: deployment limits and zones, ceilings subceilings, holdings and allowances. There are controls and requirementsmore » for storage, conversion, and reduction. In addition, there are national security concerns regarding modernization and mobilization capability. As written into the treaty, a heavy reliance has been placed on human inspectors for CFE verification. Inspectors will mostly make visual observations and photographs as the means of monitoring compliance; these observations can be recorded by handwriting or keyed into a laptop computer. CFE is now less a treaty between two alliances than a treaty among 22 state parties, with inspection data an reports to be shared with each party in the official languages designated by CSCE. One of the potential roles for bar-coded tags would be to provide a universal, exchangable, computer-compatible language for tracking TLE. 10 figs.« less
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.
Real-time tracking of objects for a KC-135 microgravity experiment
NASA Technical Reports Server (NTRS)
Littlefield, Mark L.
1994-01-01
The design of a visual tracking system for use on the Extra-Vehicular Activity Helper/Retriever (EVAHR) is discussed. EVAHR is an autonomous robot designed to perform numerous tasks in an orbital microgravity environment. Since the ability to grasp a freely translating and rotating object is vital to the robot's mission, the EVAHR must analyze range image generated by the primary sensor. This allows EVAHR to locate and focus its sensors so that an accurate set of object poses can be determined and a grasp strategy planned. To test the visual tracking system being developed, a mathematical simulation was used to model the space station environment and maintain dynamics on the EVAHR and any other free floating objects. A second phase of the investigation consists of a series of experiments carried out aboard a KC-135 aircraft flying a parabolic trajectory to simulate microgravity.
Intelligence-aided multitarget tracking for urban operations - a case study: counter terrorism
NASA Astrophysics Data System (ADS)
Sathyan, T.; Bharadwaj, K.; Sinha, A.; Kirubarajan, T.
2006-05-01
In this paper, we present a framework for tracking multiple mobile targets in an urban environment based on data from multiple sources of information, and for evaluating the threat these targets pose to assets of interest (AOI). The motivating scenario is one where we have to track many targets, each with different (unknown) destinations and/or intents. The tracking algorithm is aided by information about the urban environment (e.g., road maps, buildings, hideouts), and strategic and intelligence data. The tracking algorithm needs to be dynamic in that it has to handle a time-varying number of targets and the ever-changing urban environment depending on the locations of the moving objects and AOI. Our solution uses the variable structure interacting multiple model (VS-IMM) estimator, which has been shown to be effective in tracking targets based on road map information. Intelligence information is represented as target class information and incorporated through a combined likelihood calculation within the VS-IMM estimator. In addition, we develop a model to calculate the probability that a particular target can attack a given AOI. This model for the calculation of the probability of attack is based on the target kinematic and class information. Simulation results are presented to demonstrate the operation of the proposed framework on a representative scenario.
Heuer, Sabine; Hallowell, Brooke
2015-01-01
Numerous authors report that people with aphasia have greater difficulty allocating attention than people without neurological disorders. Studying how attention deficits contribute to language deficits is important. However, existing methods for indexing attention allocation in people with aphasia pose serious methodological challenges. Eye-tracking methods have great potential to address such challenges. We developed and assessed the validity of a new dual-task method incorporating eye tracking to assess attention allocation. Twenty-six adults with aphasia and 33 control participants completed auditory sentence comprehension and visual search tasks. To test whether the new method validly indexes well-documented patterns in attention allocation, demands were manipulated by varying task complexity in single- and dual-task conditions. Differences in attention allocation were indexed via eye-tracking measures. For all participants significant increases in attention allocation demands were observed from single- to dual-task conditions and from simple to complex stimuli. Individuals with aphasia had greater difficulty allocating attention with greater task demands. Relationships between eye-tracking indices of comprehension during single and dual tasks and standardized testing were examined. Results support the validity of the novel eye-tracking method for assessing attention allocation in people with and without aphasia. Clinical and research implications are discussed. PMID:25913549
Maximum power point tracker for photovoltaic power plants
NASA Astrophysics Data System (ADS)
Arcidiacono, V.; Corsi, S.; Lambri, L.
The paper describes two different closed-loop control criteria for the maximum power point tracking of the voltage-current characteristic of a photovoltaic generator. The two criteria are discussed and compared, inter alia, with regard to the setting-up problems that they pose. Although a detailed analysis is not embarked upon, the paper also provides some quantitative information on the energy advantages obtained by using electronic maximum power point tracking systems, as compared with the situation in which the point of operation of the photovoltaic generator is not controlled at all. Lastly, the paper presents two high-efficiency MPPT converters for experimental photovoltaic plants of the stand-alone and the grid-interconnected type.
Incorporating Target Priorities in the Sensor Tasking Reward Function
NASA Astrophysics Data System (ADS)
Gehly, S.; Bennett, J.
2016-09-01
Orbital debris tracking poses many challenges, most fundamentally the need to track a large number of objects from a limited number of sensors. The use of information theoretic sensor allocation provides a means to efficiently collect data on the multitarget system. An additional need of the community is the ability to specify target priorities, driven both by user needs and environmental factors such as collision warnings. This research develops a method to incorporate target priorities in the sensor tasking reward function, allowing for several applications in different tasking modes such as catalog maintenance, calibration, and collision monitoring. A set of numerical studies is included to demonstrate the functionality of the method.
Brown, Alisa; Uneri, Ali; Silva, Tharindu De; Manbachi, Amir; Siewerdsen, Jeffrey H
2018-04-01
Dynamic reference frames (DRFs) are a common component of modern surgical tracking systems; however, the limited number of commercially available DRFs poses a constraint in developing systems, especially for research and education. This work presents the design and validation of a large, open-source library of DRFs compatible with passive, single-face tracking systems, such as Polaris stereoscopic infrared trackers (NDI, Waterloo, Ontario). An algorithm was developed to create new DRF designs consistent with intra- and intertool design constraints and convert to computer-aided design (CAD) files suitable for three-dimensional printing. A library of 10 such groups, each with 6 to 10 DRFs, was produced and tracking performance was validated in comparison to a standard commercially available reference, including pivot calibration, fiducial registration error (FRE), and target registration error (TRE). Pivot tests showed calibration error [Formula: see text], indistinguishable from the reference. FRE was [Formula: see text], and TRE in a CT head phantom was [Formula: see text], both equivalent to the reference. The library of DRFs offers a useful resource for surgical navigation research and could be extended to other tracking systems and alternative design constraints.
2017-06-01
implement human following on a mobile robot in an indoor environment . B. FUTURE WORK Future work that could be conducted in the realm of this thesis...FEASIBILITY OF CONDUCTING HUMAN TRACKING AND FOLLOWING IN AN INDOOR ENVIRONMENT USING A MICROSOFT KINECT AND THE ROBOT OPERATING SYSTEM by...FEASIBILITY OF CONDUCTING HUMAN TRACKING AND FOLLOWING IN AN INDOOR ENVIRONMENT USING A MICROSOFT KINECT AND THE ROBOT OPERATING SYSTEM 5. FUNDING NUMBERS
Nanoparticle-Cell Interaction: A Cell Mechanics Perspective.
Septiadi, Dedy; Crippa, Federica; Moore, Thomas Lee; Rothen-Rutishauser, Barbara; Petri-Fink, Alke
2018-05-01
Progress in the field of nanoparticles has enabled the rapid development of multiple products and technologies; however, some nanoparticles can pose both a threat to the environment and human health. To enable their safe implementation, a comprehensive knowledge of nanoparticles and their biological interactions is needed. In vitro and in vivo toxicity tests have been considered the gold standard to evaluate nanoparticle safety, but it is becoming necessary to understand the impact of nanosystems on cell mechanics. Here, the interaction between particles and cells, from the point of view of cell mechanics (i.e., bionanomechanics), is highlighted and put in perspective. Specifically, the ability of intracellular and extracellular nanoparticles to impair cell adhesion, cytoskeletal organization, stiffness, and migration are discussed. Furthermore, the development of cutting-edge, nanotechnology-driven tools based on the use of particles allowing the determination of cell mechanics is emphasized. These include traction force microscopy, colloidal probe atomic force microscopy, optical tweezers, magnetic manipulation, and particle tracking microrheology. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
The development of automated behavior analysis software
NASA Astrophysics Data System (ADS)
Jaana, Yuki; Prima, Oky Dicky A.; Imabuchi, Takashi; Ito, Hisayoshi; Hosogoe, Kumiko
2015-03-01
The measurement of behavior for participants in a conversation scene involves verbal and nonverbal communications. The measurement validity may vary depending on the observers caused by some aspects such as human error, poorly designed measurement systems, and inadequate observer training. Although some systems have been introduced in previous studies to automatically measure the behaviors, these systems prevent participants to talk in a natural way. In this study, we propose a software application program to automatically analyze behaviors of the participants including utterances, facial expressions (happy or neutral), head nods, and poses using only a single omnidirectional camera. The camera is small enough to be embedded into a table to allow participants to have spontaneous conversation. The proposed software utilizes facial feature tracking based on constrained local model to observe the changes of the facial features captured by the camera, and the Japanese female facial expression database to recognize expressions. Our experiment results show that there are significant correlations between measurements observed by the observers and by the software.
Origin of marine debris is related to disposable packs of ultra-processed food.
Andrades, Ryan; Martins, Agnaldo S; Fardim, Lorena M; Ferreira, Juliana S; Santos, Robson G
2016-08-15
Marine debris is currently distributed worldwide, and the discard and contamination pose hazards to human and wildlife health. One of the gaps in debris science is tracking the source of debris to better evaluate and avoid the pathway of debris from the source to marine environment. For this, we evaluated three beaches of different urbanization levels and environmental influences; a low urbanized beach, a highly urbanized beach and a non-urbanized estuary-associated beach, in order to determine the sources and original use of debris. Plastic was the major material found on beaches, and the urbanized beach recorded the highest debris densities. Marine debris was primarily from land-based sources, and the debris recorded in all beaches was mainly assigned as food-related items. Our results highlight the major presence of disposable and short-lived products comprising the majority of debris that enters the ocean and draw attention to the unsustainable lifestyle of current society. Copyright © 2016 Elsevier Ltd. All rights reserved.
Reactions of migrating birds to lights and aircraft.
Larkin, R P; Torre-Bueno, J R; Griffin, D R; Walcott, C
1975-01-01
Midair collsions between birds and aircraft pose a hazard for both. While observing migrating birds with a tracking radar, we find that birds often react, by taking evasive maneuvers, at distances of 200-300 m to both searchlight beams and the approach of a small airplane with its landing lights on. Appropriately arranged lights on aircraft should decrease the hazard of collisions with birds. Images PMID:1056007
Superfund Record of Decision (EPA Region 1): Salem Acres Site, Salem, MA, March 1993
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
This decision document represents the selected remedial action for the Salem Acres Site in Salem, Massachusetts. The remedial action for the Salem Acres Site, as described in this ROD, addresses the principal threats to the human health and the environment posed by exposure of humans to contaminated soils from the Salem Acres Site. This remedy addresses all principal threats to human health and the environment posed by the sources of contamination at the Site resulting from dermal absorption and incidental ingestion of contaminants in surficial soils.
1989-11-01
and/or spill sites on Department of Defense (DoD) installations, and " Control hazards to human health, welfare, and the environment that may have...Investigations do not indicate harmful levels of contamination and do not pose a significant threat to human health or the environment. The site does not warrant...Feasibility Study - Investigation confirms the presence of contamination that may pose a threat to human health and/or the environment, and some sort of
The Evolution of a Connectionist Model of Situated Human Language Understanding
NASA Astrophysics Data System (ADS)
Mayberry, Marshall R.; Crocker, Matthew W.
The Adaptive Mechanisms in Human Language Processing (ALPHA) project features both experimental and computational tracks designed to complement each other in the investigation of the cognitive mechanisms that underlie situated human utterance processing. The models developed in the computational track replicate results obtained in the experimental track and, in turn, suggest further experiments by virtue of behavior that arises as a by-product of their operation.
2016-10-01
ARL-TR-7846 ● OCT 2016 US Army Research Laboratory Application of Hybrid Along-Track Interferometry/ Displaced Phase Center...Research Laboratory Application of Hybrid Along-Track Interferometry/ Displaced Phase Center Antenna Method for Moving Human Target Detection...TYPE Technical Report 3. DATES COVERED (From - To) 2015–2016 4. TITLE AND SUBTITLE Application of Hybrid Along-Track Interferometry/ Displaced
Validating an artificial intelligence human proximity operations system with test cases
NASA Astrophysics Data System (ADS)
Huber, Justin; Straub, Jeremy
2013-05-01
An artificial intelligence-controlled robot (AICR) operating in close proximity to humans poses risk to these humans. Validating the performance of an AICR is an ill posed problem, due to the complexity introduced by the erratic (noncomputer) actors. In order to prove the AICR's usefulness, test cases must be generated to simulate the actions of these actors. This paper discusses AICR's performance validation in the context of a common human activity, moving through a crowded corridor, using test cases created by an AI use case producer. This test is a two-dimensional simplification relevant to autonomous UAV navigation in the national airspace.
Markerless motion estimation for motion-compensated clinical brain imaging
NASA Astrophysics Data System (ADS)
Kyme, Andre Z.; Se, Stephen; Meikle, Steven R.; Fulton, Roger R.
2018-05-01
Motion-compensated brain imaging can dramatically reduce the artifacts and quantitative degradation associated with voluntary and involuntary subject head motion during positron emission tomography (PET), single photon emission computed tomography (SPECT) and computed tomography (CT). However, motion-compensated imaging protocols are not in widespread clinical use for these modalities. A key reason for this seems to be the lack of a practical motion tracking technology that allows for smooth and reliable integration of motion-compensated imaging protocols in the clinical setting. We seek to address this problem by investigating the feasibility of a highly versatile optical motion tracking method for PET, SPECT and CT geometries. The method requires no attached markers, relying exclusively on the detection and matching of distinctive facial features. We studied the accuracy of this method in 16 volunteers in a mock imaging scenario by comparing the estimated motion with an accurate marker-based method used in applications such as image guided surgery. A range of techniques to optimize performance of the method were also studied. Our results show that the markerless motion tracking method is highly accurate (<2 mm discrepancy against a benchmarking system) on an ethnically diverse range of subjects and, moreover, exhibits lower jitter and estimation of motion over a greater range than some marker-based methods. Our optimization tests indicate that the basic pose estimation algorithm is very robust but generally benefits from rudimentary background masking. Further marginal gains in accuracy can be achieved by accounting for non-rigid motion of features. Efficiency gains can be achieved by capping the number of features used for pose estimation provided that these features adequately sample the range of head motion encountered in the study. These proof-of-principle data suggest that markerless motion tracking is amenable to motion-compensated brain imaging and holds good promise for a practical implementation in clinical PET, SPECT and CT systems.
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.
Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments.
Ionescu, Catalin; Papava, Dragos; Olaru, Vlad; Sminchisescu, Cristian
2014-07-01
We introduce a new dataset, Human3.6M, of 3.6 Million accurate 3D Human poses, acquired by recording the performance of 5 female and 6 male subjects, under 4 different viewpoints, for training realistic human sensing systems and for evaluating the next generation of human pose estimation models and algorithms. Besides increasing the size of the datasets in the current state-of-the-art by several orders of magnitude, we also aim to complement such datasets with a diverse set of motions and poses encountered as part of typical human activities (taking photos, talking on the phone, posing, greeting, eating, etc.), with additional synchronized image, human motion capture, and time of flight (depth) data, and with accurate 3D body scans of all the subject actors involved. We also provide controlled mixed reality evaluation scenarios where 3D human models are animated using motion capture and inserted using correct 3D geometry, in complex real environments, viewed with moving cameras, and under occlusion. Finally, we provide a set of large-scale statistical models and detailed evaluation baselines for the dataset illustrating its diversity and the scope for improvement by future work in the research community. Our experiments show that our best large-scale model can leverage our full training set to obtain a 20% improvement in performance compared to a training set of the scale of the largest existing public dataset for this problem. Yet the potential for improvement by leveraging higher capacity, more complex models with our large dataset, is substantially vaster and should stimulate future research. The dataset together with code for the associated large-scale learning models, features, visualization tools, as well as the evaluation server, is available online at http://vision.imar.ro/human3.6m.
Amiri, Shahram; Wilson, David R; Masri, Bassam A; Sharma, Gulshan; Anglin, Carolyn
2011-06-03
Determining the 3D pose of the patella after total knee arthroplasty is challenging. The commonly used single-plane fluoroscopy is prone to large errors in the clinically relevant mediolateral direction. A conventional fixed bi-planar setup is limited in the minimum angular distance between the imaging planes necessary for visualizing the patellar component, and requires a highly flexible setup to adjust for the subject-specific geometries. As an alternative solution, this study investigated the use of a novel multi-planar imaging setup that consists of a C-arm tracked by an external optoelectric tracking system, to acquire calibrated radiographs from multiple orientations. To determine the accuracies, a knee prosthesis was implanted on artificial bones and imaged in simulated 'Supine' and 'Weightbearing' configurations. The results were compared with measures from a coordinate measuring machine as the ground-truth reference. The weightbearing configuration was the preferred imaging direction with RMS errors of 0.48 mm and 1.32 ° for mediolateral shift and tilt of the patella, respectively, the two most clinically relevant measures. The 'imaging accuracies' of the system, defined as the accuracies in 3D reconstruction of a cylindrical ball bearing phantom (so as to avoid the influence of the shape and orientation of the imaging object), showed an order of magnitude (11.5 times) reduction in the out-of-plane RMS errors in comparison to single-plane fluoroscopy. With this new method, complete 3D pose of the patellofemoral and tibiofemoral joints during quasi-static activities can be determined with a many-fold (up to 8 times) (3.4mm) improvement in the out-of-plane accuracies compared to a conventional single-plane fluoroscopy setup. Copyright © 2011 Elsevier Ltd. All rights reserved.
STS-49 Endeavour, Orbiter Vehicle (OV) 105, Planning Team in MCC Bldg 30 FCR
1992-05-15
S92-36606 (20 May 1992) --- STS-49 Endeavour, Orbiter Vehicle (OV) 105, Planning Team with Flight Director (FD) James M. Heflin, Jr. (front right next to ship model) poses in Johnson Space Center?s (JSC) Mission Control Center (MCC) Bldg 30 Flight Control Room (FCR). The group stands in front of visual displays projecting STS-49 data and ground track map.
Understanding Satellite Characterization Knowledge Gained from Radiometric Data
2011-09-01
observation model, the time - resolved pose of a satellite can be estimated autonomously through each pass from non- resolved radiometry. The benefits of...and we assume the satellite can achieve both the set attitude and the necessary maneuver to change its orientation from one time -step to the next...Observation Model The UKF observation model uses the Time domain Analysis Simulation for Advanced Tracking (TASAT) software to provide high-fidelity satellite
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kovesdi, C.; Spielman, Z.; LeBlanc, K.
An important element of human factors engineering (HFE) pertains to measurement and evaluation (M&E). The role of HFE-M&E should be integrated throughout the entire control room modernization (CRM) process and be used for human-system performance evaluation and diagnostic purposes with resolving potential human engineering deficiencies (HEDs) and other human machine interface (HMI) design issues. NUREG-0711 describes how HFE in CRM should employ a hierarchical set of measures, particularly during integrated system validation (ISV), including plant performance, personnel task performance, situation awareness, cognitive workload, and anthropometric/ physiological factors. Historically, subjective measures have been primarily used since they are easier to collectmore » and do not require specialized equipment. However, there are pitfalls with relying solely on subjective measures in M&E such that negatively impact reliability, sensitivity, and objectivity. As part of comprehensively capturing a diverse set of measures that strengthen findings and inferences made of the benefits from emerging technologies like advanced displays, this paper discusses the value of using eye tracking as an objective method that can be used in M&E. A brief description of eye tracking technology and relevant eye tracking measures is provided. Additionally, technical considerations and the unique challenges with using eye tracking in full-scaled simulations are addressed. Finally, this paper shares preliminary findings regarding the use of a wearable eye tracking system in a full-scale simulator study. These findings should help guide future full-scale simulator studies using eye tracking as a methodology to evaluate human-system performance.« less
Study on robot motion control for intelligent welding processes based on the laser tracking sensor
NASA Astrophysics Data System (ADS)
Zhang, Bin; Wang, Qian; Tang, Chen; Wang, Ju
2017-06-01
A robot motion control method is presented for intelligent welding processes of complex spatial free-form curve seams based on the laser tracking sensor. First, calculate the tip position of the welding torch according to the velocity of the torch and the seam trajectory detected by the sensor. Then, search the optimal pose of the torch under constraints using genetic algorithms. As a result, the intersection point of the weld seam and the laser plane of the sensor is within the detectable range of the sensor. Meanwhile, the angle between the axis of the welding torch and the tangent of the weld seam meets the requirements. The feasibility of the control method is proved by simulation.
Big Data Provenance: Challenges, State of the Art and Opportunities.
Wang, Jianwu; Crawl, Daniel; Purawat, Shweta; Nguyen, Mai; Altintas, Ilkay
2015-01-01
Ability to track provenance is a key feature of scientific workflows to support data lineage and reproducibility. The challenges that are introduced by the volume, variety and velocity of Big Data, also pose related challenges for provenance and quality of Big Data, defined as veracity. The increasing size and variety of distributed Big Data provenance information bring new technical challenges and opportunities throughout the provenance lifecycle including recording, querying, sharing and utilization. This paper discusses the challenges and opportunities of Big Data provenance related to the veracity of the datasets themselves and the provenance of the analytical processes that analyze these datasets. It also explains our current efforts towards tracking and utilizing Big Data provenance using workflows as a programming model to analyze Big Data.
Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan
2014-10-01
It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.
A real-time tracking system for monitoring shipments of hazardous materials
NASA Astrophysics Data System (ADS)
Womble, Phillip; Paschal, Jon; Hopper, Lindsay; Pinson, Dudley; Schultz, Frederick; Whitfield Humphrey, Melinda
2007-04-01
Due to the ever increasing use of radioactive materials in day to day living from the treatment of cancer patients and irradiation of food for preservation to industrial radiography to check for defects in the welding of pipelines and buildings there is a growing concern over the tracking and monitoring of these sources in transit prior to use as well as the waste produced by such use. The prevention of lost sealed sources is important in reducing the environmental and health risk posed by direct exposure, co-mingling in the metal recycling stream, use in contaminated consumer products, and use in terrorist activities. Northwest Nuclear, LLC (NWN) and the Applied Physics Institute (API) at Western Kentucky University have developed a tracking technology using active radio frequency identification (RFID) tags. This system provides location information by measuring the time of arrival of packets from a set of RFID tags to a set of location receivers. The system can track and graphically display the location on maps, drawings or photographs of tagged items on any 802.11- compliant device (PDAs, laptops, computers, WiFi telephones) situated both outside and inside structures. This location information would be vital for tracking the location of high level radiological sources while in transit. RFID technology would reduce the number of lost sources by tracking them from origination to destination. Special tags which indicate tampering or sudden movement have also been developed.
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.
A hierarchical framework for air traffic control
NASA Astrophysics Data System (ADS)
Roy, Kaushik
Air travel in recent years has been plagued by record delays, with over $8 billion in direct operating costs being attributed to 100 million flight delay minutes in 2007. Major contributing factors to delay include weather, congestion, and aging infrastructure; the Next Generation Air Transportation System (NextGen) aims to alleviate these delays through an upgrade of the air traffic control system. Changes to large-scale networked systems such as air traffic control are complicated by the need for coordinated solutions over disparate temporal and spatial scales. Individual air traffic controllers must ensure aircraft maintain safe separation locally with a time horizon of seconds to minutes, whereas regional plans are formulated to efficiently route flows of aircraft around weather and congestion on the order of every hour. More efficient control algorithms that provide a coordinated solution are required to safely handle a larger number of aircraft in a fixed amount of airspace. Improved estimation algorithms are also needed to provide accurate aircraft state information and situational awareness for human controllers. A hierarchical framework is developed to simultaneously solve the sometimes conflicting goals of regional efficiency and local safety. Careful attention is given in defining the interactions between the layers of this hierarchy. In this way, solutions to individual air traffic problems can be targeted and implemented as needed. First, the regional traffic flow management problem is posed as an optimization problem and shown to be NP-Hard. Approximation methods based on aggregate flow models are developed to enable real-time implementation of algorithms that reduce the impact of congestion and adverse weather. Second, the local trajectory design problem is solved using a novel slot-based sector model. This model is used to analyze sector capacity under varying traffic patterns, providing a more comprehensive understanding of how increased automation in NextGen will affect the overall performance of air traffic control. The dissertation also provides solutions to several key estimation problems that support corresponding control tasks. Throughout the development of these estimation algorithms, aircraft motion is modeled using hybrid systems, which encapsulate both the discrete flight mode of an aircraft and the evolution of continuous states such as position and velocity. The target-tracking problem is posed as one of hybrid state estimation, and two new algorithms are developed to exploit structure specific to aircraft motion, especially near airports. First, discrete mode evolution is modeled using state-dependent transitions, in which the likelihood of changing flight modes is dependent on aircraft state. Second, an estimator is designed for systems with limited mode changes, including arrival aircraft. Improved target tracking facilitates increased safety in collision avoidance and trajectory design problems. A multiple-target tracking and identity management algorithm is developed to improve situational awareness for controllers about multiple maneuvering targets in a congested region. Finally, tracking algorithms are extended to predict aircraft landing times; estimated time of arrival prediction is one example of important decision support information for air traffic control.
Liu, Yu Y; Shen, Ya X; Liu, Cheng; Liu, Hao F
2017-04-16
The present study aims to investigate the influence of human activity on heavy metals in a typical arid urban area of China and assess human health risks posed by heavy metals in PM 1 (particles <1.0 μm in diameter) for different people. In this paper, Changji (Xinjiang, China) was selected as the study area, and samples were collected from March 2014 to March 2015. A total 14 elements in PM 1 were quantified using ICP-MS. An enrichment factor (EF) was used to assess the influence of human activity on the contamination of these metals. The results indicated that Mn was not enriched; Co, Cu, Cr, Ni, Tl, and V were slightly enriched; Mo, Pb, and Sb were moderately enriched; and Ag, As, and Cd were strongly enriched. To assess the health risks associated with inhaling PM 1 , the risk assessment code and loss in life expectancy based on the individual metals were calculated. The results showed that the elements Ag, Cu, Mo, Pb, Sb, Tl, and V in PM 1 posed low levels of non-carcinogenic risks, but these metals may still pose risks to certain susceptible populations. In addition, the results also showed that As, Co, and Cr posed an appreciable carcinogenic risk, while Cd and Ni posed low levels of carcinogenic risk. The total predicted loss of life expectancy caused by the three metals As, Co, and Ni was 63.67 d for the elderly, 30.95 d for adult males, 26.62 d for adult females, and 48.22 d for children. Therefore, the safety of the elderly and children exposed to PM 1 should be given more attention than the safety of adults. The results from this study demonstrate that the health risks posed by heavy metals in PM 1 in Changji, Xinjiang, China should be examined.
Canaries in a coal-mine? What the killings of journalists tell us about future repression
Carey, Sabine C
2017-01-01
An independent press that is free from government censorship is regarded as instrumental to ensuring human rights protection. Yet governments across the globe often target journalists when their reports seem to offend them or contradict their policies. Can the government’s infringements of the rights of journalists tell us anything about its wider human rights agenda? The killing of a journalist is a sign of deteriorating respect for human rights. If a government orders the killing of a journalist, it is willing to use extreme measures to eliminate the threat posed by the uncontrolled flow of information. If non-state actors murder journalists, it reflects insecurity, which can lead to a backlash by the government, again triggering state-sponsored repression. To test the argument whether the killing of journalists is a precursor to increasing repression, we introduce a new global dataset on killings of journalists between 2002 and 2013 that uses three different sources that track such events across the world. The new data show that mostly local journalists are targeted and that in most cases the perpetrators remain unconfirmed. Particularly in countries with limited repression, human rights conditions are likely to deteriorate in the two years following the killing of a journalist. When journalists are killed, human rights conditions are unlikely to improve where standard models of human rights would expect an improvement. Our research underlines the importance of taking the treatment of journalists seriously, not only because failure to do so endangers their lives and limits our understanding of events on the ground, but also because their physical safety is an important precursor of more repression in the future. PMID:28546646
Track monitoring from the dynamic response of a passing train: A sparse approach
NASA Astrophysics Data System (ADS)
Lederman, George; Chen, Siheng; Garrett, James H.; Kovačević, Jelena; Noh, Hae Young; Bielak, Jacobo
2017-06-01
Collecting vibration data from revenue service trains could be a low-cost way to more frequently monitor railroad tracks, yet operational variability makes robust analysis a challenge. We propose a novel analysis technique for track monitoring that exploits the sparsity inherent in train-vibration data. This sparsity is based on the observation that large vertical train vibrations typically involve the excitation of the train's fundamental mode due to track joints, switchgear, or other discrete hardware. Rather than try to model the entire rail profile, in this study we examine a sparse approach to solving an inverse problem where (1) the roughness is constrained to a discrete and limited set of "bumps"; and (2) the train system is idealized as a simple damped oscillator that models the train's vibration in the fundamental mode. We use an expectation maximization (EM) approach to iteratively solve for the track profile and the train system properties, using orthogonal matching pursuit (OMP) to find the sparse approximation within each step. By enforcing sparsity, the inverse problem is well posed and the train's position can be found relative to the sparse bumps, thus reducing the uncertainty in the GPS data. We validate the sparse approach on two sections of track monitored from an operational train over a 16 month period of time, one where track changes did not occur during this period and another where changes did occur. We show that this approach can not only detect when track changes occur, but also offers insight into the type of such changes.
Sun, Liang; Huo, Wei; Jiao, Zongxia
2017-03-01
This paper studies relative pose control for a rigid spacecraft with parametric uncertainties approaching to an unknown tumbling target in disturbed space environment. State feedback controllers for relative translation and relative rotation are designed in an adaptive nonlinear robust control framework. The element-wise and norm-wise adaptive laws are utilized to compensate the parametric uncertainties of chaser and target spacecraft, respectively. External disturbances acting on two spacecraft are treated as a lumped and bounded perturbation input for system. To achieve the prescribed disturbance attenuation performance index, feedback gains of controllers are designed by solving linear matrix inequality problems so that lumped disturbance attenuation with respect to the controlled output is ensured in the L 2 -gain sense. Moreover, in the absence of lumped disturbance input, asymptotical convergence of relative pose are proved by using the Lyapunov method. Numerical simulations are performed to show that position tracking and attitude synchronization are accomplished in spite of the presence of couplings and uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Canessa, Andrea; Gibaldi, Agostino; Chessa, Manuela; Fato, Marco; Solari, Fabio; Sabatini, Silvio P.
2017-01-01
Binocular stereopsis is the ability of a visual system, belonging to a live being or a machine, to interpret the different visual information deriving from two eyes/cameras for depth perception. From this perspective, the ground-truth information about three-dimensional visual space, which is hardly available, is an ideal tool both for evaluating human performance and for benchmarking machine vision algorithms. In the present work, we implemented a rendering methodology in which the camera pose mimics realistic eye pose for a fixating observer, thus including convergent eye geometry and cyclotorsion. The virtual environment we developed relies on highly accurate 3D virtual models, and its full controllability allows us to obtain the stereoscopic pairs together with the ground-truth depth and camera pose information. We thus created a stereoscopic dataset: GENUA PESTO—GENoa hUman Active fixation database: PEripersonal space STereoscopic images and grOund truth disparity. The dataset aims to provide a unified framework useful for a number of problems relevant to human and computer vision, from scene exploration and eye movement studies to 3D scene reconstruction. PMID:28350382
Automated tracking and classification of the settlement behaviour of barnacle cyprids
Aldred, Nick; Clare, Anthony S.
2017-01-01
A focus on the development of nontoxic coatings to control marine biofouling has led to increasing interest in the settlement behaviour of fouling organisms. Barnacles pose a significant fouling challenge and accordingly the behaviour of their settlement-stage cypris larva (cyprid) has attracted much attention, yet remains poorly understood. Tracking technologies have been developed that quantify cyprid movement, but none have successfully automated data acquisition over the prolonged periods necessary to capture and identify the full repertoire of behaviours, from alighting on a surface to permanent attachment. Here we outline a new tracking system and a novel classification system for identifying and quantifying the exploratory behaviour of cyprids. The combined system enables, for the first time, tracking of multiple larvae, simultaneously, over long periods (hours), followed by automatic classification of typical cyprid behaviours into swimming, wide search, close search and inspection events. The system has been evaluated by comparing settlement behaviour in the light and dark (infrared illumination) and tracking one of a group of 25 cyprids from the water column to settlement over the course of 5 h. Having removed a significant technical barrier to progress in the field, it is anticipated that the system will accelerate our understanding of the process of surface selection and settlement by barnacles. PMID:28356538
NASA Astrophysics Data System (ADS)
Cousquer, Yohann; Pryet, Alexandre; Atteia, Olivier; Ferré, Ty P. A.; Delbart, Célestine; Valois, Rémi; Dupuy, Alain
2018-03-01
The inverse problem of groundwater models is often ill-posed and model parameters are likely to be poorly constrained. Identifiability is improved if diverse data types are used for parameter estimation. However, some models, including detailed solute transport models, are further limited by prohibitive computation times. This often precludes the use of concentration data for parameter estimation, even if those data are available. In the case of surface water-groundwater (SW-GW) models, concentration data can provide SW-GW mixing ratios, which efficiently constrain the estimate of exchange flow, but are rarely used. We propose to reduce computational limits by simulating SW-GW exchange at a sink (well or drain) based on particle tracking under steady state flow conditions. Particle tracking is used to simulate advective transport. A comparison between the particle tracking surrogate model and an advective-dispersive model shows that dispersion can often be neglected when the mixing ratio is computed for a sink, allowing for use of the particle tracking surrogate model. The surrogate model was implemented to solve the inverse problem for a real SW-GW transport problem with heads and concentrations combined in a weighted hybrid objective function. The resulting inversion showed markedly reduced uncertainty in the transmissivity field compared to calibration on head data alone.
3D laser traking of a particle in 3DFM
NASA Astrophysics Data System (ADS)
Desai, Kalpit; Welch, Gregory; Bishop, Gary; Taylor, Russell; Superfine, Richard
2003-11-01
The principal goal of 3D tracking in our home-built 3D Magnetic Force Microscope is to monitor movement of the particle with respect to laser beam waist and keep the particle at the center of laser beam. The sensory element is a Quadrant Photo Diode (QPD) which captures scattering of light caused by particle motion with bandwidth up to 40 KHz. XYZ translation stage is the driver element which moves particle back in the center of the laser with accuracy of couple of nanometers and with bandwidth up to 300 Hz. Since our particles vary in size, composition and shape, instead of using a priori model we use standard system identification techniques to have optimal approximation to the relationship between particle motion and QPD response. We have developed position feedback control system software that is capable of 3-dimensional tracking of beads that are attached to cilia on living cells which are beating at up to 15Hz. We have also modeled the control system of instrument to simulate performance of 3D particle tracking for different experimental conditions. Given operational level of nanometers, noise poses a great challenge for the tracking system. We propose to use stochastic control theory approaches to increase robustness of tracking.
Temporal dynamics of Puumala hantavirus infection in cyclic populations of bank voles.
Voutilainen, Liina; Kallio, Eva R; Niemimaa, Jukka; Vapalahti, Olli; Henttonen, Heikki
2016-02-18
Understanding the dynamics of zoonotic pathogens in their reservoir host populations is a prerequisite for predicting and preventing human disease epidemics. The human infection risk of Puumala hantavirus (PUUV) is highest in northern Europe, where populations of the rodent host (bank vole, Myodes glareolus) undergo cyclic fluctuations. We conducted a 7-year capture-mark-recapture study to monitor seasonal and multiannual patterns of the PUUV infection rate in bank vole populations exhibiting a 3-year density cycle. Infected bank voles were most abundant in mid-winter months during years of increasing or peak host density. Prevalence of PUUV infection in bank voles exhibited a regular, seasonal pattern reflecting the annual population turnover and accumulation of infections within each year cohort. In autumn, the PUUV transmission rate tracked increasing host abundance, suggesting a density-dependent transmission. However, prevalence of PUUV infection was similar during the increase and peak years of the density cycle despite a twofold difference in host density. This may result from the high proportion of individuals carrying maternal antibodies constraining transmission during the cycle peak years. Our exceptionally intensive and long-term dataset provides a solid basis on which to develop models to predict the dynamic public health threat posed by PUUV in northern Europe.
Pavement Sealcoat, PAHs, and the Environment
NASA Astrophysics Data System (ADS)
Van Metre, P. C.; Mahler, B. J.
2011-12-01
Recent research by the USGS has identified coal-tar-based pavement sealants as a major source of polycyclic aromatic hydrocarbons (PAHs) to the environment. Coal-tar-based sealcoat is commonly used to coat parking lots and driveways and is typically is 20-35 percent coal tar pitch, a known human carcinogen. Several PAHs are suspected mutagens, carcinogens, and (or) teratogens. In the central and eastern U.S. where the coal-tar-based sealants dominate use, sum-PAH concentration in dust particles from sealcoated pavement is about 1,000 times higher than in the western U.S. where the asphalt-based formulation is prevalent. Source apportionment modeling indicates that particles from sealcoated pavement are contributing the majority of the PAHs to recent lake sediment in 35 U.S. urban lakes and are the primary cause of upward trends in PAHs in many of these lakes. Mobile particles from parking lots with coal-tar-based sealcoat are tracked indoors, resulting in elevated PAH concentrations in house dust. In a recently completed study, volatilization fluxes of PAHs from sealcoated pavement were estimated to be about 60 times fluxes from unsealed pavement. Using a wide variety of methods, the author and colleagues have shown that coal-tar-based sealcoat is a major source of PAHs to the urban environment and might pose risks to aquatic life and human health.
Yang, Shuai; Zhang, Xinlei; Diao, Lihong; Guo, Feifei; Wang, Dan; Liu, Zhongyang; Li, Honglei; Zheng, Junjie; Pan, Jingshan; Nice, Edouard C; Li, Dong; He, Fuchu
2015-09-04
The Chromosome-centric Human Proteome Project (C-HPP) aims to catalog genome-encoded proteins using a chromosome-by-chromosome strategy. As the C-HPP proceeds, the increasing requirement for data-intensive analysis of the MS/MS data poses a challenge to the proteomic community, especially small laboratories lacking computational infrastructure. To address this challenge, we have updated the previous CAPER browser into a higher version, CAPER 3.0, which is a scalable cloud-based system for data-intensive analysis of C-HPP data sets. CAPER 3.0 uses cloud computing technology to facilitate MS/MS-based peptide identification. In particular, it can use both public and private cloud, facilitating the analysis of C-HPP data sets. CAPER 3.0 provides a graphical user interface (GUI) to help users transfer data, configure jobs, track progress, and visualize the results comprehensively. These features enable users without programming expertise to easily conduct data-intensive analysis using CAPER 3.0. Here, we illustrate the usage of CAPER 3.0 with four specific mass spectral data-intensive problems: detecting novel peptides, identifying single amino acid variants (SAVs) derived from known missense mutations, identifying sample-specific SAVs, and identifying exon-skipping events. CAPER 3.0 is available at http://prodigy.bprc.ac.cn/caper3.
Modeling human tracking error in several different anti-tank systems
NASA Technical Reports Server (NTRS)
Kleinman, D. L.
1981-01-01
An optimal control model for generating time histories of human tracking errors in antitank systems is outlined. Monte Carlo simulations of human operator responses for three Army antitank systems are compared. System/manipulator dependent data comparisons reflecting human operator limitations in perceiving displayed quantities and executing intended control motions are presented. Motor noise parameters are also discussed.
Human health risk assessment of heavy metals in urban stormwater.
Ma, Yukun; Egodawatta, Prasanna; McGree, James; Liu, An; Goonetilleke, Ashantha
2016-07-01
Toxic chemical pollutants such as heavy metals (HMs) are commonly present in urban stormwater. These pollutants can pose a significant risk to human health and hence a significant barrier for urban stormwater reuse. The primary aim of this study was to develop an approach for quantitatively assessing the risk to human health due to the presence of HMs in stormwater. This approach will lead to informed decision making in relation to risk management of urban stormwater reuse, enabling efficient implementation of appropriate treatment strategies. In this study, risks to human health from heavy metals were assessed as hazard index (HI) and quantified as a function of traffic and land use related parameters. Traffic and land use are the primary factors influencing heavy metal loads in the urban environment. The risks posed by heavy metals associated with total solids and fine solids (<150μm) were considered to represent the maximum and minimum risk levels, respectively. The study outcomes confirmed that Cr, Mn and Pb pose the highest risks, although these elements are generally present in low concentrations. The study also found that even though the presence of a single heavy metal does not pose a significant risk, the presence of multiple heavy metals could be detrimental to human health. These findings suggest that stormwater guidelines should consider the combined risk from multiple heavy metals rather than the threshold concentration of an individual species. Furthermore, it was found that risk to human health from heavy metals in stormwater is significantly influenced by traffic volume and the risk associated with stormwater from industrial areas is generally higher than that from commercial and residential areas. Copyright © 2016 Elsevier B.V. All rights reserved.
The rarity of "unusual" [corrected] dispositions of victim bodies: staging and posing.
Keppel, Robert D; Weis, Joseph G
2004-11-01
The act of leaving a victim's body in an unusual position is a conscious criminal action by an offender to thwart an investigation, shock the finder and investigators of the crime scene, or give perverted pleasure to the killer. The unusual position concepts of posing and staging a murder victim have been documented thoroughly and have been accepted by the courts as a definable phenomenon. One staging case and one posing case are outlined and reveal characteristics of those homicides. From the Washington State Attorney General's Homicide Investigation and Tracking System's database on murder covering the years 1981-2000 (a total of 5,224 cases), the relative frequency of unusual body dispositions is revealed as a very rare occurrence. Only 1.3% of victims are left in an unusual position, with 0.3% being posed and 0.1% being staged. The characteristics of these types of murders also set them apart: compared to all other murders, in staged murders the victims and killers are, on average, older. All victims and offenders in the staged murders are white, with victims being disproportionately white in murders with any kind of unusual body disposition. Likewise, females stand out as victims when the body is posed, staged, or left in other unusual positions. Whereas posed bodies are more likely to include sexual assault, often in serial murders, there is no evidence of either in the staged cases. Lastly, when a body is left in an unusual position, binding is more likely, as well as the use of more "hands on" means of killing the victim, such as stabbing or cutting weapons, bludgeons, ligatures, or hands and feet.
Tu, Hongwei; Fan, Chengji; Chen, Xiaohui; Liu, Jiaxian; Wang, Bin; Huang, Zhibin; Zhang, Yiyue; Meng, Xiaojing; Zou, Fei
2017-08-01
The synaptic adhesion protein Neurexin 2a (Nrxn2a) plays a key role in neuronal development and is associated with cognitive functioning and locomotor behavior. Although low-level metal exposure poses a potential risk to the human nervous system, especially during the developmental stages, little is known about the effects of metal exposures on nrxn2a expression during embryonic development. We therefore exposed wild-type zebrafish embryos/larvae to cadmium (CdCl 2 ), manganese (MnCl 2 ), and lead ([CH 3 COO] 2 Pb), to determine their effect on mortality, malformation, and hatching rate. Concentrations of these metals in zebrafish were detected by inductively coupled plasma mass spectrometry analysis. Locomotor activity of zebrafish larvae was analyzed using a video-track tracking system. Expression of nrxn2a was assessed by in situ hybridization and quantitative polymerase chain reaction. The results showed that mortality, malformation, and bioaccumulation increased as the exposure dosages and duration increased. Developmental exposure to these metals significantly reduced larval swim distance and velocity. The nrxn2aa and nrxn2ab genes were expressed in the central nervous system and downregulated by almost all of the 3 metals, especially Pb. These data demonstrate that exposure to metals downregulates nrxn2a in the zebrafish model system, and this is likely linked to concurrent developmental processes. Environ Toxicol Chem 2017;36:2147-2154. © 2017 SETAC. © 2017 SETAC.
Finger tracking for hand-held device interface using profile-matching stereo vision
NASA Astrophysics Data System (ADS)
Chang, Yung-Ping; Lee, Dah-Jye; Moore, Jason; Desai, Alok; Tippetts, Beau
2013-01-01
Hundreds of millions of people use hand-held devices frequently and control them by touching the screen with their fingers. If this method of operation is being used by people who are driving, the probability of deaths and accidents occurring substantially increases. With a non-contact control interface, people do not need to touch the screen. As a result, people will not need to pay as much attention to their phones and thus drive more safely than they would otherwise. This interface can be achieved with real-time stereovision. A novel Intensity Profile Shape-Matching Algorithm is able to obtain 3-D information from a pair of stereo images in real time. While this algorithm does have a trade-off between accuracy and processing speed, the result of this algorithm proves the accuracy is sufficient for the practical use of recognizing human poses and finger movement tracking. By choosing an interval of disparity, an object at a certain distance range can be segmented. In other words, we detect the object by its distance to the cameras. The advantage of this profile shape-matching algorithm is that detection of correspondences relies on the shape of profile and not on intensity values, which are subjected to lighting variations. Based on the resulting 3-D information, the movement of fingers in space from a specific distance can be determined. Finger location and movement can then be analyzed for non-contact control of hand-held devices.
NASA Technical Reports Server (NTRS)
Reale, O.; Lau, W.K.; Susskind, J.; Brin, E.; Liu, E.; Riishojgaard, L. P.; Rosenburg, R.; Fuentes, M.
2009-01-01
Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. Moreover, the automated analyses of cyclones over the northern Indian Ocean, produced by operational global data assimilation systems (DASs), are generally of inferior quality than in other basins. In this work it is shown that the assimilation of Atmospheric Infrared Sounder (AIRS) temperature retrievals under partial cloudy conditions can significantly impact the representation of the cyclone Nargis (which caused devastating loss of life in Myanmar in May 2008) in a global DAS. Forecasts produced from these improved analyses by a global model produce substantially smaller track errors. The impact of the assimilation of clear-sky radiances on the same DAS and forecasting system is positive, but smaller than the one obtained by ingestion of AIRS retrievals, possibly due to poorer coverage.
Passive Markers for Tracking Surgical Instruments in Real-Time 3-D Ultrasound Imaging
Stoll, Jeffrey; Ren, Hongliang; Dupont, Pierre E.
2013-01-01
A family of passive echogenic markers is presented by which the position and orientation of a surgical instrument can be determined in a 3-D ultrasound volume, using simple image processing. Markers are attached near the distal end of the instrument so that they appear in the ultrasound volume along with the instrument tip. They are detected and measured within the ultrasound image, thus requiring no external tracking device. This approach facilitates imaging instruments and tissue simultaneously in ultrasound-guided interventions. Marker-based estimates of instrument pose can be used in augmented reality displays or for image-based servoing. Design principles for marker shapes are presented that ensure imaging system and measurement uniqueness constraints are met. An error analysis is included that can be used to guide marker design and which also establishes a lower bound on measurement uncertainty. Finally, examples of marker measurement and tracking algorithms are presented along with experimental validation of the concepts. PMID:22042148
PROBLEM OF FORMING IN A MAN-OPERATOR A HABIT OF TRACKING A MOVING TARGET,
Cybernetics stimulated the large-scale use of the method of functional analogy which makes it possible to compare technical and human activity systems...interesting and highly efficient human activity because of the psychological control factor involved in its operation. The human tracking system is
Human body segmentation via data-driven graph cut.
Li, Shifeng; Lu, Huchuan; Shao, Xingqing
2014-11-01
Human body segmentation is a challenging and important problem in computer vision. Existing methods usually entail a time-consuming training phase for prior knowledge learning with complex shape matching for body segmentation. In this paper, we propose a data-driven method that integrates top-down body pose information and bottom-up low-level visual cues for segmenting humans in static images within the graph cut framework. The key idea of our approach is first to exploit human kinematics to search for body part candidates via dynamic programming for high-level evidence. Then, by using the body parts classifiers, obtaining bottom-up cues of human body distribution for low-level evidence. All the evidence collected from top-down and bottom-up procedures are integrated in a graph cut framework for human body segmentation. Qualitative and quantitative experiment results demonstrate the merits of the proposed method in segmenting human bodies with arbitrary poses from cluttered backgrounds.
Localization Methods for a Mobile Robot in Urban Environments
2004-10-04
Columbia University, Department of Computer Science, 2001. [30] R. Brown and P. Hwang , Introduction to random signals and applied Kalman filtering, 3rd...sensor. An extended Kalman filter integrates the sensor data and keeps track of the uncertainty associated with it. The second method is based on...errors+ compass/GPS errors corrected odometry pose odometry error estimates zk zk h(x)~ h(x)~ Kalman Filter zk Fig. 4. A diagram of the extended
Right Whale Diving and Foraging Behavior in the Southwestern Gulf of Maine
2011-09-30
atop a relatively simple food chain consisting only of phytoplankton, copepods , and whales that can serve as a convenient model to study trophic...oceanographic processes that promote the thin, aggregated layers of copepods upon which the whales feed, and (3) to assess the risks posed to right whales... copepods remained at the surface during the day (Baumgartner et al. 2011). We hypothesize that right whales faithfully track these changes in
2011-12-02
construction and validation of predictive computer models such as those used in Time-domain Analysis Simulation for Advanced Tracking (TASAT), a...characterization data, successful construction and validation of predictive computer models was accomplished. And an investigation in pose determination from...currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YYYY) 2. REPORT TYPE 3. DATES
Tracking Enrolments and Graduations in Humanities Education in South Africa: Are We in Crisis?
ERIC Educational Resources Information Center
Yu, K.; Pillay, V.
2011-01-01
In this article we respond to the perceived crisis in humanities education in South Africa which posits firstly that large numbers of students are leaving this field and that secondly, the value of a humanities education has declined. To do this we track the enrolments and graduation rates in humanities at both undergraduate and postgraduate…
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.
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.
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.
Canine scent detection and microbial source tracking of human waste contamination in storm drains.
Van De Werfhorst, Laurie C; Murray, Jill L S; Reynolds, Scott; Reynolds, Karen; Holden, Patricia A
2014-06-01
Human fecal contamination of surface waters and drains is difficult to diagnose. DNA-based and chemical analyses of water samples can be used to specifically quantify human waste contamination, but their expense precludes routine use. We evaluated canine scent tracking, using two dogs trained to respond to the scent of municipal wastewater, as a field approach for surveying human fecal contamination. Fecal indicator bacteria, as well as DNA-based and chemical markers of human waste, were analyzed in waters sampled from canine scent-evaluated sites (urban storm drains and creeks). In the field, the dogs responded positively (70% and 100%) at sites for which sampled waters were then confirmed as contaminated with human waste. When both dogs indicated a negative response, human waste markers were absent. Overall, canine scent tracking appears useful for prioritizing sampling sites for which DNA-based and similarly expensive assays can confirm and quantify human waste contamination.
Meiotic drive-based strategy to minimize mycotoxins in corn
USDA-ARS?s Scientific Manuscript database
Some fungi pose a dual threat to corn production by causing disease (seedling, root, stalk or ear rots) and by producing mycotoxins that pose health risks to humans and domestic animals. For example, the fungus Fusarium verticillioides can cause stalk and ear rot of corn and produce fumonisins, a fa...
Trifocal Tensor-Based Adaptive Visual Trajectory Tracking Control of Mobile Robots.
Chen, Jian; Jia, Bingxi; Zhang, Kaixiang
2017-11-01
In this paper, a trifocal tensor-based approach is proposed for the visual trajectory tracking task of a nonholonomic mobile robot equipped with a roughly installed monocular camera. The desired trajectory is expressed by a set of prerecorded images, and the robot is regulated to track the desired trajectory using visual feedback. Trifocal tensor is exploited to obtain the orientation and scaled position information used in the control system, and it works for general scenes owing to the generality of trifocal tensor. In the previous works, the start, current, and final images are required to share enough visual information to estimate the trifocal tensor. However, this requirement can be easily violated for perspective cameras with limited field of view. In this paper, key frame strategy is proposed to loosen this requirement, extending the workspace of the visual servo system. Considering the unknown depth and extrinsic parameters (installing position of the camera), an adaptive controller is developed based on Lyapunov methods. The proposed control strategy works for almost all practical circumstances, including both trajectory tracking and pose regulation tasks. Simulations are made based on the virtual experimentation platform (V-REP) to evaluate the effectiveness of the proposed approach.
Inter- and Intra-Chromosomal Aberrations in Human Cells Exposed in vitro to Space-like Radiations
NASA Technical Reports Server (NTRS)
Hada, Megumi; Cucinotta, F. A.; Gonda, S. R.; Wu, H.
2005-01-01
Energetic heavy ions pose a great health risk to astronauts in extended ISS and future exploration missions. High-LET heavy ions are particularly effective in causing various biological effects, including cell inactivation, genetic mutations and cancer induction. Most of these biological endpoints are closely related to chromosomal damage, which can be utilized as a biomarker for radiation insults. Previously, we had studied chromosome aberrations in human lymphocytes and fibroblasts induced by both low- and high-LET radiation using FISH and multicolor fluorescence in situ hybridization (mFISH) techniques. In this study, we exposed human cells in vitro to gamma rays and energetic particles of varying types and energies and dose rates, and analyzed chromosomal damages using the multicolor banding in situ hybridization (mBAND) procedure. Confluent human epithelial cells and lymphocytes were exposed to energetic heavy ions at NASA Space Radiation Laboratory (NSRL) at the Brookhaven National Laboratory (Upton, NY) or Cs-137 gamma radiation source at the Baylor College (Houston, TX). After colcemid and Calyculin A treatment, cells were fixed and painted with XCyte3 mBAND kit (MetaSystems) and chromosome aberrations were analyzed with mBAND analysis system (MetaSystems). With this technique, individually painted chromosomal bands on one chromosome allowed the identification of interchromosomal aberrations (translocation to unpainted chromosomes) and intrachromosomal aberrations (inversions and deletions within a single painted chromosome). The possible relationship between the frequency of inter- and intra-chromosomal exchanges and the track structure of radiation is discussed. The work was supported by the NASA Space Radiation Health Program.
Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process
NASA Astrophysics Data System (ADS)
Nakanishi, W.; Fuse, T.; Ishikawa, T.
2015-05-01
This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.
Appearance-based multimodal human tracking and identification for healthcare in the digital home.
Yang, Mau-Tsuen; Huang, Shen-Yen
2014-08-05
There is an urgent need for intelligent home surveillance systems to provide home security, monitor health conditions, and detect emergencies of family members. One of the fundamental problems to realize the power of these intelligent services is how to detect, track, and identify people at home. Compared to RFID tags that need to be worn all the time, vision-based sensors provide a natural and nonintrusive solution. Observing that body appearance and body build, as well as face, provide valuable cues for human identification, we model and record multi-view faces, full-body colors and shapes of family members in an appearance database by using two Kinects located at a home's entrance. Then the Kinects and another set of color cameras installed in other parts of the house are used to detect, track, and identify people by matching the captured color images with the registered templates in the appearance database. People are detected and tracked by multisensor fusion (Kinects and color cameras) using a Kalman filter that can handle duplicate or partial measurements. People are identified by multimodal fusion (face, body appearance, and silhouette) using a track-based majority voting. Moreover, the appearance-based human detection, tracking, and identification modules can cooperate seamlessly and benefit from each other. Experimental results show the effectiveness of the human tracking across multiple sensors and human identification considering the information of multi-view faces, full-body clothes, and silhouettes. The proposed home surveillance system can be applied to domestic applications in digital home security and intelligent healthcare.
Appearance-Based Multimodal Human Tracking and Identification for Healthcare in the Digital Home
Yang, Mau-Tsuen; Huang, Shen-Yen
2014-01-01
There is an urgent need for intelligent home surveillance systems to provide home security, monitor health conditions, and detect emergencies of family members. One of the fundamental problems to realize the power of these intelligent services is how to detect, track, and identify people at home. Compared to RFID tags that need to be worn all the time, vision-based sensors provide a natural and nonintrusive solution. Observing that body appearance and body build, as well as face, provide valuable cues for human identification, we model and record multi-view faces, full-body colors and shapes of family members in an appearance database by using two Kinects located at a home's entrance. Then the Kinects and another set of color cameras installed in other parts of the house are used to detect, track, and identify people by matching the captured color images with the registered templates in the appearance database. People are detected and tracked by multisensor fusion (Kinects and color cameras) using a Kalman filter that can handle duplicate or partial measurements. People are identified by multimodal fusion (face, body appearance, and silhouette) using a track-based majority voting. Moreover, the appearance-based human detection, tracking, and identification modules can cooperate seamlessly and benefit from each other. Experimental results show the effectiveness of the human tracking across multiple sensors and human identification considering the information of multi-view faces, full-body clothes, and silhouettes. The proposed home surveillance system can be applied to domestic applications in digital home security and intelligent healthcare. PMID:25098207
NASA Technical Reports Server (NTRS)
Agarwal, G. C.; Osafo-Charles, F.; Oneill, W. D.; Gottlieb, G. L.
1982-01-01
Time series analysis is applied to model human operator dynamics in pursuit and compensatory tracking modes. The normalized residual criterion is used as a one-step analytical tool to encompass the processes of identification, estimation, and diagnostic checking. A parameter constraining technique is introduced to develop more reliable models of human operator dynamics. The human operator is adequately modeled by a second order dynamic system both in pursuit and compensatory tracking modes. In comparing the data sampling rates, 100 msec between samples is adequate and is shown to provide better results than 200 msec sampling. The residual power spectrum and eigenvalue analysis show that the human operator is not a generator of periodic characteristics.
Optimal Configuration of Human Motion Tracking Systems: A Systems Engineering Approach
NASA Technical Reports Server (NTRS)
Henderson, Steve
2005-01-01
Human motion tracking systems represent a crucial technology in the area of modeling and simulation. These systems, which allow engineers to capture human motion for study or replication in virtual environments, have broad applications in several research disciplines including human engineering, robotics, and psychology. These systems are based on several sensing paradigms, including electro-magnetic, infrared, and visual recognition. Each of these paradigms requires specialized environments and hardware configurations to optimize performance of the human motion tracking system. Ideally, these systems are used in a laboratory or other facility that was designed to accommodate the particular sensing technology. For example, electromagnetic systems are highly vulnerable to interference from metallic objects, and should be used in a specialized lab free of metal components.
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.
Improvement of Hand Movement on Visual Target Tracking by Assistant Force of Model-Based Compensator
NASA Astrophysics Data System (ADS)
Ide, Junko; Sugi, Takenao; Nakamura, Masatoshi; Shibasaki, Hiroshi
Human motor control is achieved by the appropriate motor commands generating from the central nerve system. A test of visual target tracking is one of the effective methods for analyzing the human motor functions. We have previously examined a possibility for improving the hand movement on visual target tracking by additional assistant force through a simulation study. In this study, a method for compensating the human hand movement on visual target tracking by adding an assistant force was proposed. Effectiveness of the compensation method was investigated through the experiment for four healthy adults. The proposed compensator precisely improved the reaction time, the position error and the variability of the velocity of the human hand. The model-based compensator proposed in this study is constructed by using the measurement data on visual target tracking for each subject. The properties of the hand movement for different subjects can be reflected in the structure of the compensator. Therefore, the proposed method has possibility to adjust the individual properties of patients with various movement disorders caused from brain dysfunctions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dowla, Farid U.
Subsurface sensors that employ radioisotopes, such 241Am-Be and 137Cs, for reservoir characterization must be tracked for safety and security reasons. Other radiological sources are also widely used in medicine. The radiological source containers, in both applications, are small, mobile and used widely worldwide. The nuclear sources pose radiological dispersal device (RDD) security risks. Security concerns with the industrial use of radionuclide sources is in fact quite high as it is estimated that each year hundreds of sealed sources go missing, either lost or stolen. Risk mitigation efforts include enhanced regulations, source-use guidelines, research and development on electronic tracking of sources.more » This report summarizes the major elements of the requirements and operational concepts of nuclear sources with the goal of developing automated electronic tagging and locating systems.« less
A Matter of Millimeters: Defining the Processes for Critical Clearances on Curiosity
NASA Technical Reports Server (NTRS)
Florow, Brandon
2013-01-01
The Mars Science Laboratory (MSL) mission presents an immense packaging problem in that it takes a rover the size of a car with a sky crane landing system and packs it tightly into a spacecraft. This creates many areas of close and critical clearances. Critical Clearances are defined as hardware-to-hardware or hardware-to-envelope clearances which fall below a pre-established location dependent threshold and pose a risk of hardware to hardware contact during events such as launch, entry, landing, and operations. Close Clearances, on the other hand, are defined as any clearance value that is chosen to be tracked but is larger than the critical clearance threshold for its region. Close clearances may be tracked for various reasons including uncertainty in design, large expected dynamic motion, etc.
Big Data Provenance: Challenges, State of the Art and Opportunities
Wang, Jianwu; Crawl, Daniel; Purawat, Shweta; Nguyen, Mai; Altintas, Ilkay
2017-01-01
Ability to track provenance is a key feature of scientific workflows to support data lineage and reproducibility. The challenges that are introduced by the volume, variety and velocity of Big Data, also pose related challenges for provenance and quality of Big Data, defined as veracity. The increasing size and variety of distributed Big Data provenance information bring new technical challenges and opportunities throughout the provenance lifecycle including recording, querying, sharing and utilization. This paper discusses the challenges and opportunities of Big Data provenance related to the veracity of the datasets themselves and the provenance of the analytical processes that analyze these datasets. It also explains our current efforts towards tracking and utilizing Big Data provenance using workflows as a programming model to analyze Big Data. PMID:29399671
Seslija, Petar; Teeter, Matthew G; Yuan, Xunhua; Naudie, Douglas D R; Bourne, Robert B; Macdonald, Steven J; Peters, Terry M; Holdsworth, David W
2012-10-01
The ability to accurately measure joint kinematics is an important tool in studying both normal joint function and pathologies associated with injury and disease. The purpose of this study is to evaluate the efficacy, accuracy, precision, and clinical safety of measuring 3D joint motion using a conventional flat-panel radiography system prior to its application in an in vivo study. An automated, image-based tracking algorithm was implemented to measure the three-dimensional pose of a sparse object from a two-dimensional radiographic projection. The algorithm was tested to determine its efficiency and failure rate, defined as the number of image frames where automated tracking failed, or required user intervention. The accuracy and precision of measuring three-dimensional motion were assessed using a robotic controlled, tibiofemoral knee phantom programmed to mimic a subject with a total knee replacement performing a stair ascent activity. Accuracy was assessed by comparing the measurements of the single-plane radiographic tracking technique to those of an optical tracking system, and quantified by the measurement discrepancy between the two systems using the Bland-Altman technique. Precision was assessed through a series of repeated measurements of the tibiofemoral kinematics, and was quantified using the across-trial deviations of the repeated kinematic measurements. The safety of the imaging procedure was assessed by measuring the effective dose of ionizing radiation associated with the x-ray exposures, and analyzing its relative risk to a human subject. The automated tracking algorithm displayed a failure rate of 2% and achieved an average computational throughput of 8 image frames/s. Mean differences between the radiographic and optical measurements for translations and rotations were less than 0.08 mm and 0.07° in-plane, and 0.24 mm and 0.6° out-of-plane. The repeatability of kinematics measurements performed using the radiographic tracking technique was better than ±0.09 mm and 0.12° in-plane, and ±0.70 mm and ±0.07° out-of-plane. The effective dose associated with the imaging protocol used was 15 μSv for 10 s of radiographic cine acquisition. This study demonstrates the ability to accurately measure knee-joint kinematics using a single-plane radiographic measurement technique. The measurement technique can be easily implemented at most clinical centers equipped with a modern-day radiographic x-ray system. The dose of ionizing radiation associated with the image acquisition represents a minimal risk to any subjects undergoing the examination.
Electrical Activity in Martian Dust Storms
NASA Astrophysics Data System (ADS)
Majid, W.; Arabshahi, S.; Kocz, J.
2016-12-01
Dust storms on Mars are predicted to be capable of producing electrostatic fields and discharges, even larger than those in dust storms on Earth. Such electrical activity poses serious risks to any Human exploration of the planet and the lack of sufficient data to characterize any such activity has been identified by NASA's MEPAG as a key human safety knowledge gap. There are three key elements in the characterization of Martian electrostatic discharges: dependence on Martian environmental conditions, frequency of occurrence, and the strength of the generated electric fields. We will describe a recently deployed detection engine using NASA's Deep Space Network (DSN) to carry out a long term monitoring campaign to search for and characterize the entire Mars hemisphere for powerful discharges during routine tracking of spacecraft at Mars on an entirely non-interfering basis. The resulting knowledge of Mars electrical activity would allow NASA to plan risk mitigation measures to ensure human safety during Mars exploration. In addition, these measurements will also allow us to place limits on presence of oxidants such as H2O2 that may be produced by such discharges, providing another measurement point for models describing Martian atmospheric chemistry and habitability. Because of the continuous Mars telecommunication needs of NASA's Mars-based assets, the DSN is the only instrument in the world that combines long term, high cadence, observing opportunities with large sensitive telescopes, making it a unique asset worldwide in searching for and characterizing electrostatic activity at Mars from the ground.
Gelsleichter, James; Szabo, Nancy J
2013-07-01
The presence of human pharmaceuticals in sewage-impacted ecosystems is a growing concern that poses health risks to aquatic wildlife. Despite this, few studies have investigated the uptake of active pharmaceutical ingredients (APIs) in aquatic organisms. In this study, the uptake of 9 APIs from human drugs was examined and compared in neonate bull sharks (Carcharhinus leucas) residing in pristine (Myakka River) and wastewater-impacted (Caloosahatchee River) tributaries of Florida's Charlotte Harbor estuary. The synthetic estrogen used in human contraceptives (17α-ethynylestradiol) and 6 of the selective serotonin/norepinephrine reuptake inhibitors (citalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, venlafaxine) used in human antidepressants were observed at detectable and, in some cases, quantifiable levels in plasma of Caloosahatchee River sharks. Comparatively, only venlafaxine was detected in the plasma of a single Myakka River shark at a level below the limit of quantitation. These results suggest that sharks residing in wastewater-impacted habitats accumulate APIs, a factor that may pose special risks to C. leucas since it is one of few shark species to regularly occupy freshwater systems. Further research is needed to determine if the low levels of API uptake observed in Caloosahatchee River bull sharks pose health risks to these animals. Copyright © 2013 Elsevier B.V. All rights reserved.
Online Object Tracking, Learning and Parsing with And-Or Graphs.
Wu, Tianfu; Lu, Yang; Zhu, Song-Chun
2017-12-01
This paper presents a method, called AOGTracker, for simultaneously tracking, learning and parsing (TLP) of unknown objects in video sequences with a hierarchical and compositional And-Or graph (AOG) representation. The TLP method is formulated in the Bayesian framework with a spatial and a temporal dynamic programming (DP) algorithms inferring object bounding boxes on-the-fly. During online learning, the AOG is discriminatively learned using latent SVM [1] to account for appearance (e.g., lighting and partial occlusion) and structural (e.g., different poses and viewpoints) variations of a tracked object, as well as distractors (e.g., similar objects) in background. Three key issues in online inference and learning are addressed: (i) maintaining purity of positive and negative examples collected online, (ii) controling model complexity in latent structure learning, and (iii) identifying critical moments to re-learn the structure of AOG based on its intrackability. The intrackability measures uncertainty of an AOG based on its score maps in a frame. In experiments, our AOGTracker is tested on two popular tracking benchmarks with the same parameter setting: the TB-100/50/CVPR2013 benchmarks , [3] , and the VOT benchmarks [4] -VOT 2013, 2014, 2015 and TIR2015 (thermal imagery tracking). In the former, our AOGTracker outperforms state-of-the-art tracking algorithms including two trackers based on deep convolutional network [5] , [6] . In the latter, our AOGTracker outperforms all other trackers in VOT2013 and is comparable to the state-of-the-art methods in VOT2014, 2015 and TIR2015.
Ma, Yukun; Liu, An; Egodawatta, Prasanna; McGree, James; Goonetilleke, Ashantha
2017-01-01
Among the numerous pollutants present in urban road dust, polycyclic aromatic hydrocarbons (PAHs) are among the most toxic chemical pollutants and can pose cancer risk to humans. The primary aim of the study was to develop a quantitative model to assess the cancer risk from PAHs in urban road dust based on traffic and land use factors and thereby to characterise the risk posed by PAHs in fine (<150μm) and coarse (>150μm) particles. The risk posed by PAHs was quantified as incremental lifetime cancer risk (ILCR), which was modelled as a function of traffic volume and percentages of different urban land uses. The study outcomes highlighted the fact that cancer risk from PAHs in urban road dust is primarily influenced by PAHs associated with fine solids. Heavy PAHs with 5 to 6 benzene rings, especially dibenzo[a,h]anthracene (D[a]A) and benzo[a]pyrene (B[a]P) in the mixture contribute most to the risk. The quantitative model developed based on traffic and land use factors will contribute to informed decision making in relation to the management of risk posed by PAHs in urban road dust. Copyright © 2016 Elsevier B.V. All rights reserved.
Laser induced mortality of Anopheles stephensi mosquitoes
NASA Astrophysics Data System (ADS)
Keller, Matthew D.; Leahy, David J.; Norton, Bryan J.; Johanson, Threeric; Mullen, Emma R.; Marvit, Maclen; Makagon, Arty
2016-02-01
Small, flying insects continue to pose great risks to both human health and agricultural production throughout the world, so there remains a compelling need to develop new vector and pest control approaches. Here, we examined the use of short (<25 ms) laser pulses to kill or disable anesthetized female Anopheles stephensi mosquitoes, which were chosen as a representative species. The mortality of mosquitoes exposed to laser pulses of various wavelength, power, pulse duration, and spot size combinations was assessed 24 hours after exposure. For otherwise comparable conditions, green and far-infrared wavelengths were found to be more effective than near- and mid-infrared wavelengths. Pulses with larger laser spot sizes required lower lethal energy densities, or fluence, but more pulse energy than for smaller spot sizes with greater fluence. Pulse duration had to be reduced by several orders of magnitude to significantly lower the lethal pulse energy or fluence required. These results identified the most promising candidates for the lethal laser component in a system being designed to identify, track, and shoot down flying insects in the wild.
Discrimination of Complex Human Behavior by Pigeons (Columba livia) and Humans
Qadri, Muhammad A. J.; Sayde, Justin M.; Cook, Robert G.
2014-01-01
The cognitive and neural mechanisms for recognizing and categorizing behavior are not well understood in non-human animals. In the current experiments, pigeons and humans learned to categorize two non-repeating, complex human behaviors (“martial arts” vs. “Indian dance”). Using multiple video exemplars of a digital human model, pigeons discriminated these behaviors in a go/no-go task and humans in a choice task. Experiment 1 found that pigeons already experienced with discriminating the locomotive actions of digital animals acquired the discrimination more rapidly when action information was available than when only pose information was available. Experiments 2 and 3 found this same dynamic superiority effect with naïve pigeons and human participants. Both species used the same combination of immediately available static pose information and more slowly perceived dynamic action cues to discriminate the behavioral categories. Theories based on generalized visual mechanisms, as opposed to embodied, species-specific action networks, offer a parsimonious account of how these different animals recognize behavior across and within species. PMID:25379777
Mining the Quantified Self: Personal Knowledge Discovery as a Challenge for Data Science.
Fawcett, Tom
2015-12-01
The last several years have seen an explosion of interest in wearable computing, personal tracking devices, and the so-called quantified self (QS) movement. Quantified self involves ordinary people recording and analyzing numerous aspects of their lives to understand and improve themselves. This is now a mainstream phenomenon, attracting a great deal of attention, participation, and funding. As more people are attracted to the movement, companies are offering various new platforms (hardware and software) that allow ever more aspects of daily life to be tracked. Nearly every aspect of the QS ecosystem is advancing rapidly, except for analytic capabilities, which remain surprisingly primitive. With increasing numbers of qualified self participants collecting ever greater amounts and types of data, many people literally have more data than they know what to do with. This article reviews the opportunities and challenges posed by the QS movement. Data science provides well-tested techniques for knowledge discovery. But making these useful for the QS domain poses unique challenges that derive from the characteristics of the data collected as well as the specific types of actionable insights that people want from the data. Using a small sample of QS time series data containing information about personal health we provide a formulation of the QS problem that connects data to the decisions of interest to the user.
Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah
2015-01-01
The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.
Human health problems associated with current agricultural food production.
Bhat, Ramesh V
2008-01-01
Scientific and technological developments in the agricultural sectors in the recent past has resulted in increased food production and at the same time led to certain public health concerns. Unseasonal rains at the time of harvest and improper post harvest technology often results in agricultural commodities being contaminated with certain fungi and results in the production of mycotoxins. Consumption of such commodities has resulted in human disease outbreaks. Naturally occurring toxins, inherently present in foods and either consumed as such or mixed up with grains, had been responsible for disease outbreaks. Other possible causes of health concern include the application of various agrochemicals such as pesticides and the use of antibiotics in aquaculture and veterinary practices. Foodborne pathogens entering the food chain during both traditional and organic agriculture pose a challenge to public health. Modern biotechnology, producing genetically modified foods, if not regulated appropriately could pose dangers to human health. Use of various integrated food management systems like the Hazard Analysis and critical control system approach for risk prevention, monitoring and control of food hazards are being emphasized with globalization to minimise the danger posed to human health from improper agricultural practices.
ERIC Educational Resources Information Center
Finkel, Ed
2016-01-01
Does America needs more welders and fewer philosophers? Community college humanities professors and administrators say it benefits all students, whether liberal arts or career track, to take courses in philosophy, history, political science, language arts, and other liberal arts subjects. And they're developing innovative humanities curricula to…
Bed Bug Epidemic: A Challenge to Public Health
ERIC Educational Resources Information Center
Ratnapradipa, Dhitinut; Ritzel, Dale O.; Haramis, Linn D.; Bliss, Kadi R.
2011-01-01
In recent years, reported cases of bed bug infestations in the U.S. and throughout the world have escalated dramatically, posing a global public health problem. Although bed bugs are not known to transmit disease to humans, they pose both direct and indirect public health challenges in terms of health effects, treatment, cost, and resource…
SMEs and their E-Commerce: Implications for Training in Wellington, New Zealand
ERIC Educational Resources Information Center
Beal, Tim; Abdullah, Moha Asri
2005-01-01
One of the greatest challenges facing traditional small and medium-sized enterprises (SMEs) throughout the world is that posed by the Internet. While the Internet offers great potential to SMEs, from improving and cheapening production processes through to reaching global customers, it also poses great problems. SMEs' resources, human and…
The Role of Visual Working Memory in Attentive Tracking of Unique Objects
ERIC Educational Resources Information Center
Makovski, Tal; Jiang, Yuhong V.
2009-01-01
When tracking moving objects in space humans usually attend to the objects' spatial locations and update this information over time. To what extent do surface features assist attentive tracking? In this study we asked participants to track identical or uniquely colored objects. Tracking was enhanced when objects were unique in color. The benefit…
Measuring Human Performance in Simulated Nuclear Power Plant Control Rooms Using Eye Tracking
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kovesdi, Casey Robert; Rice, Brandon Charles; Bower, Gordon Ross
Control room modernization will be an important part of life extension for the existing light water reactor fleet. As part of modernization efforts, personnel will need to gain a full understanding of how control room technologies affect performance of human operators. Recent advances in technology enables the use of eye tracking technology to continuously measure an operator’s eye movement, which correlates with a variety of human performance constructs such as situation awareness and workload. This report describes eye tracking metrics in the context of how they will be used in nuclear power plant control room simulator studies.
NASA Technical Reports Server (NTRS)
Uhlemann, H.; Geiser, G.
1975-01-01
Multivariable manual compensatory tracking experiments were carried out in order to determine typical strategies of the human operator and conditions for improvement of his performance if one of the visual displays of the tracking errors is supplemented by an auditory feedback. Because the tracking error of the system which is only visually displayed is found to decrease, but not in general that of the auditorally supported system, it was concluded that the auditory feedback unloads the visual system of the operator who can then concentrate on the remaining exclusively visual displays.
Cassidy, Jessica M; Carey, James R; Lu, Chiahao; Krach, Linda E; Feyma, Tim; Durfee, William K; Gillick, Bernadette T
2015-12-01
This study analyzed the relationship between electrophysiological responses to transcranial magnetic stimulation (TMS), finger tracking accuracy, and volume of neural substrate in children with congenital hemiparesis. Nineteen participants demonstrating an ipsilesional motor-evoked potential (MEP) were compared with eleven participants showing an absent ipsilesional MEP response. Comparisons of finger tracking accuracy from the affected and less affected hands and ipsilesional/contralesional (I/C) volume ratio for the primary motor cortex (M1) and posterior limb of internal capsule (PLIC) were done using two-sample t-tests. Participants showing an ipsilesional MEP response demonstrated superior tracking performance from the less affected hand (p=0.016) and significantly higher I/C volume ratios for M1 (p=0.028) and PLIC (p=0.005) compared to participants without an ipsilesional MEP response. Group differences in finger tracking accuracy from the affected hand were not significant. These results highlight differentiating factors amongst children with congenital hemiparesis showing contrasting MEP responses: less affected hand performance and preserved M1 and PLIC volume. Along with MEP status, these factors pose important clinical implications in pediatric stroke rehabilitation. These findings may also reflect competitive developmental processes associated with the preservation of affected hand function at the expense of some function in the less affected hand. Copyright © 2015 Elsevier Ltd. All rights reserved.
A versatile pitch tracking algorithm: from human speech to killer whale vocalizations.
Shapiro, Ari Daniel; Wang, Chao
2009-07-01
In this article, a pitch tracking algorithm [named discrete logarithmic Fourier transformation-pitch detection algorithm (DLFT-PDA)], originally designed for human telephone speech, was modified for killer whale vocalizations. The multiple frequency components of some of these vocalizations demand a spectral (rather than temporal) approach to pitch tracking. The DLFT-PDA algorithm derives reliable estimations of pitch and the temporal change of pitch from the harmonic structure of the vocal signal. Scores from both estimations are combined in a dynamic programming search to find a smooth pitch track. The algorithm is capable of tracking killer whale calls that contain simultaneous low and high frequency components and compares favorably across most signal to noise ratio ranges to the peak-picking and sidewinder algorithms that have been used for tracking killer whale vocalizations previously.
Development of a Sunspot Tracking System
NASA Technical Reports Server (NTRS)
Taylor, Jaime R.
1998-01-01
Large solar flares produce a significant amount of energetic particles which pose a hazard for human activity in space. In the hope of understanding flare mechanisms and thus better predicting solar flares, NASA's Marshall Space Flight Center (MSFC) developed an experimental vector magnetograph (EXVM) polarimeter to measure the Sun's magnetic field. The EXVM will be used to perform ground-based solar observations and will provide a proof of concept for the design of a similar instrument for the Japanese Solar-B space mission. The EXVM typically operates for a period of several minutes. During this time there is image motion due to atmospheric fluctuation and telescope wind loading. To optimize the EXVM performance an image motion compensation device (sunspot tracker) is needed. The sunspot tracker consists of two parts, an image motion determination system and an image deflection system. For image motion determination a CCD or CID camera is used to digitize an image, than an algorithm is applied to determine the motion. This motion or error signal is sent to the image deflection system which moves the image back to its original location. Both of these systems are under development. Two algorithms are available for sunspot tracking which require the use of only one row and one column of image data. To implement these algorithms, two identical independent systems are being developed, one system for each axis of motion. Two CID cameras have been purchased; the data from each camera will be used to determine image motion for each direction. The error signal generated by the tracking algorithm will be sent to an image deflection system consisting of an actuator and a mirror constrained to move about one axis. Magnetostrictive actuators were chosen to move the mirror over piezoelectrics due to their larger driving force and larger range of motion. The actuator and mirror mounts are currently under development.
Takahashi, Hajime; Ohshima, Chihiro; Nakagawa, Miku; Thanatsang, Krittaporn; Phraephaisarn, Chirapiphat; Chaturongkasumrit, Yuphakhun; Keeratipibul, Suwimon; Kuda, Takashi; Kimura, Bon
2014-01-01
Listeria innocua is an important hygiene indicator bacterium in food industries because it behaves similar to Listeria monocytogenes, which is pathogenic to humans. PFGE is often used to characterize bacterial strains and to track contamination source. However, because PFGE is an expensive, complicated, time-consuming protocol, and poses difficulty in data sharing, development of a new typing method is necessary. MLVA is a technique that identifies bacterial strains on the basis of the number of tandem repeats present in the genome varies depending on the strains. MLVA has gained attention due to its high reproducibility and ease of data sharing. In this study, we developed a MLVA protocol to assess L. innocua and evaluated it by tracking the contamination source of L. innocua in an actual food manufacturing factory by typing the bacterial strains isolated from the factory. Three VNTR regions of the L. innocua genome were chosen for use in the MLVA. The number of repeat units in each VNTR region was calculated based on the results of PCR product analysis using capillary electrophoresis (CE). The calculated number of repetitions was compared with the results of the gene sequence analysis to demonstrate the accuracy of the CE repeat number analysis. The developed technique was evaluated using 60 L. innocua strains isolated from a food factory. These 60 strains were classified into 11 patterns using MLVA. Many of the strains were classified into ST-6, revealing that this MLVA strain type can contaminate each manufacturing process in the factory. The MLVA protocol developed in this study for L. innocua allowed rapid and easy analysis through the use of CE. This technique was found to be very useful in hygiene control in factories because it allowed us to track contamination sources and provided information regarding whether the bacteria were present in the factories.
Efficient Model Posing and Morphing Software
2014-04-01
disclosure of contents or reconstruction of this document. Air Force Research Laboratory 711th Human Performance Wing Human ...Command, Air Force Research Laboratory 711th Human Performance Wing, Human Effectiveness Directorate, Bioeffects Division, Radio Frequency...13. SUPPLEMENTARY NOTES 14. ABSTRACT The absorption of electromagnetic energy within human tissue depends upon anatomical posture and body
NASA Astrophysics Data System (ADS)
Fradera, Xavier; Verras, Andreas; Hu, Yuan; Wang, Deping; Wang, Hongwu; Fells, James I.; Armacost, Kira A.; Crespo, Alejandro; Sherborne, Brad; Wang, Huijun; Peng, Zhengwei; Gao, Ying-Duo
2018-01-01
We describe the performance of multiple pose prediction methods for the D3R 2016 Grand Challenge. The pose prediction challenge includes 36 ligands, which represent 4 chemotypes and some miscellaneous structures against the FXR ligand binding domain. In this study we use a mix of fully automated methods as well as human-guided methods with considerations of both the challenge data and publicly available data. The methods include ensemble docking, colony entropy pose prediction, target selection by molecular similarity, molecular dynamics guided pose refinement, and pose selection by visual inspection. We evaluated the success of our predictions by method, chemotype, and relevance of publicly available data. For the overall data set, ensemble docking, visual inspection, and molecular dynamics guided pose prediction performed the best with overall mean RMSDs of 2.4, 2.2, and 2.2 Å respectively. For several individual challenge molecules, the best performing method is evaluated in light of that particular ligand. We also describe the protein, ligand, and public information data preparations that are typical of our binding mode prediction workflow.
Feathered Detectives: Real-Time GPS Tracking of Scavenging Gulls Pinpoints Illegal Waste Dumping.
Navarro, Joan; Grémillet, David; Afán, Isabel; Ramírez, Francisco; Bouten, Willem; Forero, Manuela G
2016-01-01
Urban waste impacts human and environmental health, and waste management has become one of the major challenges of humanity. Concurrently with new directives due to manage this human by-product, illegal dumping has become one of the most lucrative activities of organized crime. Beyond economic fraud, illegal waste disposal strongly enhances uncontrolled dissemination of human pathogens, pollutants and invasive species. Here, we demonstrate the potential of novel real-time GPS tracking of scavenging species to detect environmental crime. Specifically, we were able to detect illegal activities at an officially closed dump, which was visited recurrently by 5 of 19 GPS-tracked yellow-legged gulls (Larus michahellis). In comparison with conventional land-based surveys, GPS tracking allows a much wider and cost-efficient spatiotemporal coverage, even of the most hazardous sites, while GPS data accessibility through the internet enables rapid intervention. Our results suggest that multi-species guilds of feathered detectives equipped with GPS and cameras could help fight illegal dumping at continental scales. We encourage further experimental studies, to infer waste detection thresholds in gulls and other scavenging species exploiting human waste dumps.
Feathered Detectives: Real-Time GPS Tracking of Scavenging Gulls Pinpoints Illegal Waste Dumping
Grémillet, David; Afán, Isabel; Ramírez, Francisco; Bouten, Willem; Forero, Manuela G.
2016-01-01
Urban waste impacts human and environmental health, and waste management has become one of the major challenges of humanity. Concurrently with new directives due to manage this human by-product, illegal dumping has become one of the most lucrative activities of organized crime. Beyond economic fraud, illegal waste disposal strongly enhances uncontrolled dissemination of human pathogens, pollutants and invasive species. Here, we demonstrate the potential of novel real-time GPS tracking of scavenging species to detect environmental crime. Specifically, we were able to detect illegal activities at an officially closed dump, which was visited recurrently by 5 of 19 GPS-tracked yellow-legged gulls (Larus michahellis). In comparison with conventional land-based surveys, GPS tracking allows a much wider and cost-efficient spatiotemporal coverage, even of the most hazardous sites, while GPS data accessibility through the internet enables rapid intervention. Our results suggest that multi-species guilds of feathered detectives equipped with GPS and cameras could help fight illegal dumping at continental scales. We encourage further experimental studies, to infer waste detection thresholds in gulls and other scavenging species exploiting human waste dumps. PMID:27448048
21 CFR 872.2060 - Jaw tracking device.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Jaw tracking device. 872.2060 Section 872.2060 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES DENTAL DEVICES Diagnostic Devices § 872.2060 Jaw tracking device. (a) Jaw tracking device...
21 CFR 872.2060 - Jaw tracking device.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Jaw tracking device. 872.2060 Section 872.2060 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES DENTAL DEVICES Diagnostic Devices § 872.2060 Jaw tracking device. (a) Jaw tracking device...
21 CFR 872.2060 - Jaw tracking device.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Jaw tracking device. 872.2060 Section 872.2060 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES DENTAL DEVICES Diagnostic Devices § 872.2060 Jaw tracking device. (a) Jaw tracking device...
21 CFR 872.2060 - Jaw tracking device.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Jaw tracking device. 872.2060 Section 872.2060 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES DENTAL DEVICES Diagnostic Devices § 872.2060 Jaw tracking device. (a) Jaw tracking device...
Tracking the rise of stem cell tourism.
Ryan, Kirsten A; Sanders, Amanda N; Wang, Dong D; Levine, Aaron D
2010-01-01
Driven by hype surrounding stem cell research, a number of clinics around the world currently offer 'stem cell therapies' to patients. These unproven interventions have attracted policy interest owing to the risks they may pose to patients and to the progress of legitimate translational stem cell research, yet remarkably little data exists about the patients who undergo these unproven therapies or their experiences. We sought to characterize this patient population. We developed a comprehensive data set of blogs written by patients (or their caretakers) about their experiences with unproven stem cell therapies. Analyzing these data suggests that unproven stem cell therapies are increasing rapidly in popularity and are attracting a wide range of patients--both young and old and with a diverse collection of medical conditions. These results should help clinicians advise individual patients and help policymakers devise strategies to mitigate the risks these treatments pose.
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.
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
Calibration-free gaze tracking for automatic measurement of visual acuity in human infants.
Xiong, Chunshui; Huang, Lei; Liu, Changping
2014-01-01
Most existing vision-based methods for gaze tracking need a tedious calibration process. In this process, subjects are required to fixate on a specific point or several specific points in space. However, it is hard to cooperate, especially for children and human infants. In this paper, a new calibration-free gaze tracking system and method is presented for automatic measurement of visual acuity in human infants. As far as I know, it is the first time to apply the vision-based gaze tracking in the measurement of visual acuity. Firstly, a polynomial of pupil center-cornea reflections (PCCR) vector is presented to be used as the gaze feature. Then, Gaussian mixture models (GMM) is employed for gaze behavior classification, which is trained offline using labeled data from subjects with healthy eyes. Experimental results on several subjects show that the proposed method is accurate, robust and sufficient for the application of measurement of visual acuity in human infants.
NASA Astrophysics Data System (ADS)
Zheng, Dan; Jiao, Haifeng; Zhong, Huiying; Qiu, Jishi; Yan, Xiaojun; Duan, Qingyuan; Chai, Liyue
2017-06-01
The composition of chlorophenols in marine organisms from the southern coast of Hangzhou Bay, China, was analyzed and the health risks posed to humans assessed. A total of 19 chlorophenols from 16 types of marine organism were analyzed across nine survey sections in Hangzhou Bay. The chlorophenols were analyzed by gas chromatography-mass spectrometry using a DB-5MS quartz capillary column. The concentrations of monochlorophenol, dichlorophenol, trichlorophenol, tetrachlorophenol, and pentachlorophenol ranged from below the detection limit (ND) to 132 μg/kg, ND-51.0 μg/kg, ND-42.5 μg/kg, ND-69.0 μg/kg, and ND-9.06 μg/kg, respectively. Additionally, concentration differences between each type of chlorophenol were not signifi cant (P>0.05). However, signifi cant differences were found between monochlorophenol (F=8.13, P<0.01) and total chlorophenol (F=5.19, P<0.01) concentrations. As the noncarcinogenic risk indices were <0.1 (10-5-10-2) for all of the organisms, no high risk was posed by 2-chlorophenol, 2,4-dichlorophenol, 2,4,6-trichlorophenol, 2,4,5-trichlorophenol, 2,3,4,6-tetrachlorophenol, and pentachlorophenol to humans consuming marine organisms from the study area. Furthermore, the carcinogenic risks posed by 2,4,6-trichlorophenol and pentachlorophenol were lower than limits set by the International Commission on Radiological Protection and the US Environmental Protection Agency. However, the noncarcinogenic and carcinogenic risks posed by chlorophenols in marine organisms from four of the survey sections (Sizaopu, Niluoshan, Longshan Town and Xinhong zha) were higher than the other survey sections.
Political impediments to a tobacco endgame
Rabe, Barry George
2013-01-01
Any serious consideration of exploring a tobacco endgame in the USA must build upon the enviable track record of reducing tobacco use through a mixture of federal and state policies. This foundation may pose particular challenges in approaching an endgame, including questions of national political feasibility, public support, limitations of sub-federal experimentation and recruitment of future political champions. Advocates must demonstrate a compelling need for a dramatic expansion beyond existing efforts, amid competition from alternative issues and little apparent public appetite for such an initiative. PMID:23591512
The CZCS geolocation algorithms
NASA Technical Reports Server (NTRS)
Wilson, W. H.; Smith, R. C.; Nolten, J. W.
1981-01-01
The Coastal Zone Color Scanner (CZCS) on board the Nimbus 7 satellite was designed to measure surface radiance upwelled from the ocean in 6 spectral bands. The CZCS spectrometer obtains its information from a rotating mirror and is timed to collect data when the mirror views the Earth surface between ca. 40 degrees to the left and right of the subsatellite track. Each scan is divided into 1968 picture elements, pixels, of 0.04 degrees scan each. In order to avoid direct reflected Sun glint, the rotating mirror shaft can be tilted so that scans across the subsatellite track up to 20 degrees forward or aft of the point directed beneath the satellite. The CZCS is the first satellite borne instrument to have this tilted scan capability and therefore poses some new problems in locating the Earth surface position of viewed pixels.
Quantitation of Cellular Dynamics in Growing Arabidopsis Roots with Light Sheet Microscopy
Birnbaum, Kenneth D.; Leibler, Stanislas
2011-01-01
To understand dynamic developmental processes, living tissues have to be imaged frequently and for extended periods of time. Root development is extensively studied at cellular resolution to understand basic mechanisms underlying pattern formation and maintenance in plants. Unfortunately, ensuring continuous specimen access, while preserving physiological conditions and preventing photo-damage, poses major barriers to measurements of cellular dynamics in growing organs such as plant roots. We present a system that integrates optical sectioning through light sheet fluorescence microscopy with hydroponic culture that enables us to image, at cellular resolution, a vertically growing Arabidopsis root every few minutes and for several consecutive days. We describe novel automated routines to track the root tip as it grows, to track cellular nuclei and to identify cell divisions. We demonstrate the system's capabilities by collecting data on divisions and nuclear dynamics. PMID:21731697
Real-time Human Activity Recognition
NASA Astrophysics Data System (ADS)
Albukhary, N.; Mustafah, Y. M.
2017-11-01
The traditional Closed-circuit Television (CCTV) system requires human to monitor the CCTV for 24/7 which is inefficient and costly. Therefore, there’s a need for a system which can recognize human activity effectively in real-time. This paper concentrates on recognizing simple activity such as walking, running, sitting, standing and landing by using image processing techniques. Firstly, object detection is done by using background subtraction to detect moving object. Then, object tracking and object classification are constructed so that different person can be differentiated by using feature detection. Geometrical attributes of tracked object, which are centroid and aspect ratio of identified tracked are manipulated so that simple activity can be detected.
Exotic mosquito threats require strategic surveillance and response planning.
Webb, Cameron E; Doggett, Stephen L
2016-12-14
Mosquito-borne diseases caused by endemic pathogens such as Ross River, Barmah Forest and Murray Valley encephalitis viruses are an annual concern in New South Wales (NSW), Australia. More than a dozen mosquito species have been implicated in the transmission of these pathogens, with each mosquito occupying a specialised ecological niche that influences their habitat associations, host feeding preferences and the environmental drivers of their abundance. The NSW Arbovirus Surveillance and Mosquito Monitoring Program provides an early warning system for potential outbreaks of mosquito-borne disease by tracking annual activity of these mosquitoes and their associated pathogens. Although the program will effectively track changes in local mosquito populations that may increase with a changing climate, urbanisation and wetland rehabilitation, it will be less effective with current surveillance methodologies at detecting or monitoring changes in exotic mosquito threats, where different surveillance strategies need to be used. Exotic container-inhabiting mosquitoes such as Aedes aegypti and Ae. albopictus pose a threat to NSW because they are nuisance-biting pests and vectors of pathogens such as dengue, chikungunya and Zika viruses. International movement of humans and their belongings have spread these mosquitoes to many regions of the world. In recent years, these two mosquitoes have been detected by the Australian Government Department of Agriculture and Water Resources at local airports and seaports. To target the detection of these exotic mosquitoes, new trapping technologies and networks of surveillance locations are required. Additionally, incursions of these mosquitoes into urban areas of the state will require strategic responses to minimise substantial public health and economic burdens to local communities.
Small Orbital Stereo Tracking Camera Technology Development
NASA Technical Reports Server (NTRS)
Bryan, Tom; Macleod, Todd; Gagliano, Larry
2015-01-01
On-Orbit Small Debris Tracking and Characterization is a technical gap in the current National Space Situational Awareness necessary to safeguard orbital assets and crew. This poses a major risk of MOD damage to ISS and Exploration vehicles. In 2015 this technology was added to NASA's Office of Chief Technologist roadmap. For missions flying in or assembled in or staging from LEO, the physical threat to vehicle and crew is needed in order to properly design the proper level of MOD impact shielding and proper mission design restrictions. Need to verify debris flux and size population versus ground RADAR tracking. Use of ISS for In-Situ Orbital Debris Tracking development provides attitude, power, data and orbital access without a dedicated spacecraft or restricted operations on-board a host vehicle as a secondary payload. Sensor Applicable to in-situ measuring orbital debris in flux and population in other orbits or on other vehicles. Could enhance safety on and around ISS. Some technologies extensible to monitoring of extraterrestrial debris as well to help accomplish this, new technologies must be developed quickly. The Small Orbital Stereo Tracking Camera is one such up and coming technology. It consists of flying a pair of intensified megapixel telephoto cameras to evaluate Orbital Debris (OD) monitoring in proximity of International Space Station. It will demonstrate on-orbit optical tracking (in situ) of various sized objects versus ground RADAR tracking and small OD models. The cameras are based on Flight Proven Advanced Video Guidance Sensor pixel to spot algorithms (Orbital Express) and military targeting cameras. And by using twin cameras we can provide Stereo images for ranging & mission redundancy. When pointed into the orbital velocity vector (RAM), objects approaching or near the stereo camera set can be differentiated from the stars moving upward in background.
Small Orbital Stereo Tracking Camera Technology Development
NASA Technical Reports Server (NTRS)
Bryan, Tom; MacLeod, Todd; Gagliano, Larry
2016-01-01
On-Orbit Small Debris Tracking and Characterization is a technical gap in the current National Space Situational Awareness necessary to safeguard orbital assets and crew. This poses a major risk of MOD damage to ISS and Exploration vehicles. In 2015 this technology was added to NASA's Office of Chief Technologist roadmap. For missions flying in or assembled in or staging from LEO, the physical threat to vehicle and crew is needed in order to properly design the proper level of MOD impact shielding and proper mission design restrictions. Need to verify debris flux and size population versus ground RADAR tracking. Use of ISS for In-Situ Orbital Debris Tracking development provides attitude, power, data and orbital access without a dedicated spacecraft or restricted operations on-board a host vehicle as a secondary payload. Sensor Applicable to in-situ measuring orbital debris in flux and population in other orbits or on other vehicles. Could enhance safety on and around ISS. Some technologies extensible to monitoring of extraterrestrial debris as well To help accomplish this, new technologies must be developed quickly. The Small Orbital Stereo Tracking Camera is one such up and coming technology. It consists of flying a pair of intensified megapixel telephoto cameras to evaluate Orbital Debris (OD) monitoring in proximity of International Space Station. It will demonstrate on-orbit optical tracking (in situ) of various sized objects versus ground RADAR tracking and small OD models. The cameras are based on Flight Proven Advanced Video Guidance Sensor pixel to spot algorithms (Orbital Express) and military targeting cameras. And by using twin cameras we can provide Stereo images for ranging & mission redundancy. When pointed into the orbital velocity vector (RAM), objects approaching or near the stereo camera set can be differentiated from the stars moving upward in background.
CRF-Based Model for Instrument Detection and Pose Estimation in Retinal Microsurgery.
Alsheakhali, Mohamed; Eslami, Abouzar; Roodaki, Hessam; Navab, Nassir
2016-01-01
Detection of instrument tip in retinal microsurgery videos is extremely challenging due to rapid motion, illumination changes, the cluttered background, and the deformable shape of the instrument. For the same reason, frequent failures in tracking add the overhead of reinitialization of the tracking. In this work, a new method is proposed to localize not only the instrument center point but also its tips and orientation without the need of manual reinitialization. Our approach models the instrument as a Conditional Random Field (CRF) where each part of the instrument is detected separately. The relations between these parts are modeled to capture the translation, rotation, and the scale changes of the instrument. The tracking is done via separate detection of instrument parts and evaluation of confidence via the modeled dependence functions. In case of low confidence feedback an automatic recovery process is performed. The algorithm is evaluated on in vivo ophthalmic surgery datasets and its performance is comparable to the state-of-the-art methods with the advantage that no manual reinitialization is needed.
Space Shuttle Star Tracker Challenges
NASA Technical Reports Server (NTRS)
Herrera, Linda M.
2010-01-01
The space shuttle fleet of avionics was originally designed in the 1970's. Many of the subsystems have been upgraded and replaced, however some original hardware continues to fly. Not only fly, but has proven to be the best design available to perform its designated task. The shuttle star tracker system is currently flying as a mixture of old and new designs, each with a unique purpose to fill for the mission. Orbiter missions have tackled many varied missions in space over the years. As the orbiters began flying to the International Space Station (ISS), new challenges were discovered and overcome as new trusses and modules were added. For the star tracker subsystem, the growing ISS posed an unusual problem, bright light. With two star trackers on board, the 1970's vintage image dissector tube (IDT) star trackers track the ISS, while the new solid state design is used for dim star tracking. This presentation focuses on the challenges and solutions used to ensure star trackers can complete the shuttle missions successfully. Topics include KSC team and industry partner methods used to correct pressurized case failures and track system performance.
Real-time 3D motion tracking for small animal brain PET
NASA Astrophysics Data System (ADS)
Kyme, A. Z.; Zhou, V. W.; Meikle, S. R.; Fulton, R. R.
2008-05-01
High-resolution positron emission tomography (PET) imaging of conscious, unrestrained laboratory animals presents many challenges. Some form of motion correction will normally be necessary to avoid motion artefacts in the reconstruction. The aim of the current work was to develop and evaluate a motion tracking system potentially suitable for use in small animal PET. This system is based on the commercially available stereo-optical MicronTracker S60 which we have integrated with a Siemens Focus-220 microPET scanner. We present measured performance limits of the tracker and the technical details of our implementation, including calibration and synchronization of the system. A phantom study demonstrating motion tracking and correction was also performed. The system can be calibrated with sub-millimetre accuracy, and small lightweight markers can be constructed to provide accurate 3D motion data. A marked reduction in motion artefacts was demonstrated in the phantom study. The techniques and results described here represent a step towards a practical method for rigid-body motion correction in small animal PET. There is scope to achieve further improvements in the accuracy of synchronization and pose measurements in future work.
Jones, Hendrée E.; Fischer, Gabriele; Heil, Sarah H.; Kaltenbach, Karol; Martin, Peter R.; Coyle, Mara G.; Selby, Peter; Stine, Susan M.; O’Grady, Kevin E.; Arria, Amelia M.
2015-01-01
Aims The Maternal Opioid Treatment: Human Experimental Research (MOTHER) project, an eight-site randomized, double-blind, double-dummy, flexible-dosing, parallel-group clinical trial is described. This study is the most current – and single most comprehensive – research effort to investigate the safety and efficacy of maternal and prenatal exposure to methadone and buprenorphine. Methods The MOTHER study design is outlined, and its basic features are presented. Conclusions At least seven important lessons have been learned from the MOTHER study: (1) an interdisciplinary focus improves the design and methods of a randomized clinical trial; (2) multiple sites in a clinical trial present continuing challenges to the investigative team due to variations in recruitment goals, patient populations, and hospital practices that in turn differentially impact recruitment rates, treatment compliance, and attrition; (3) study design and protocols must be flexible in order to meet the unforeseen demands of both research and clinical management; (4) staff turnover needs to be addressed with a proactive focus on both hiring and training; (5) the implementation of a protocol for the treatment of a particular disorder may identify important ancillary clinical issues worthy of investigation; (6) timely tracking of data in a multi-site trial is both demanding and unforgiving; and, (7) complex multi-site trials pose unanticipated challenges that complicate the choice of statistical methods, thereby placing added demands on investigators to effectively communicate their results. PMID:23106924
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
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.
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
Recognizing visual focus of attention from head pose in natural meetings.
Ba, Sileye O; Odobez, Jean-Marc
2009-02-01
We address the problem of recognizing the visual focus of attention (VFOA) of meeting participants based on their head pose. To this end, the head pose observations are modeled using a Gaussian mixture model (GMM) or a hidden Markov model (HMM) whose hidden states correspond to the VFOA. The novelties of this paper are threefold. First, contrary to previous studies on the topic, in our setup, the potential VFOA of a person is not restricted to other participants only. It includes environmental targets as well (a table and a projection screen), which increases the complexity of the task, with more VFOA targets spread in the pan as well as tilt gaze space. Second, we propose a geometric model to set the GMM or HMM parameters by exploiting results from cognitive science on saccadic eye motion, which allows the prediction of the head pose given a gaze target. Third, an unsupervised parameter adaptation step not using any labeled data is proposed, which accounts for the specific gazing behavior of each participant. Using a publicly available corpus of eight meetings featuring four persons, we analyze the above methods by evaluating, through objective performance measures, the recognition of the VFOA from head pose information obtained either using a magnetic sensor device or a vision-based tracking system. The results clearly show that in such complex but realistic situations, the VFOA recognition performance is highly dependent on how well the visual targets are separated for a given meeting participant. In addition, the results show that the use of a geometric model with unsupervised adaptation achieves better results than the use of training data to set the HMM parameters.
Human emotions track changes in the acoustic environment.
Ma, Weiyi; Thompson, William Forde
2015-11-24
Emotional responses to biologically significant events are essential for human survival. Do human emotions lawfully track changes in the acoustic environment? Here we report that changes in acoustic attributes that are well known to interact with human emotions in speech and music also trigger systematic emotional responses when they occur in environmental sounds, including sounds of human actions, animal calls, machinery, or natural phenomena, such as wind and rain. Three changes in acoustic attributes known to signal emotional states in speech and music were imposed upon 24 environmental sounds. Evaluations of stimuli indicated that human emotions track such changes in environmental sounds just as they do for speech and music. Such changes not only influenced evaluations of the sounds themselves, they also affected the way accompanying facial expressions were interpreted emotionally. The findings illustrate that human emotions are highly attuned to changes in the acoustic environment, and reignite a discussion of Charles Darwin's hypothesis that speech and music originated from a common emotional signal system based on the imitation and modification of environmental sounds.
Thyme to touch: Infants possess strategies that protect them from dangers posed by plants
Wertz, Annie E.; Wynn, Karen
2013-01-01
Plants have been central to human life as sources of food and raw materials for artifact construction over evolutionary time. But plants also have chemical and physical defenses (such as harmful toxins and thorns) that provide protection from herbivores. The presence of these defenses has shaped the behavioral strategies of non-human animals. Here we report evidence that human infants possess strategies that would serve to protect them from dangers posed by plants. Across two experiments, infants as young as eight months exhibit greater reluctance to manually explore plants compared to other entities. These results expand the growing literature showing that infants are sensitive to certain ancestrally recurrent dangers, and provide a basis for further exploration. PMID:24161794
NASA Astrophysics Data System (ADS)
Pansing, Craig W.; Hua, Hong; Rolland, Jannick P.
2005-08-01
Head-mounted display (HMD) technologies find a variety of applications in the field of 3D virtual and augmented environments, 3D scientific visualization, as well as wearable displays. While most of the current HMDs use head pose to approximate line of sight, we propose to investigate approaches and designs for integrating eye tracking capability into HMDs from a low-level system design perspective and to explore schemes for optimizing system performance. In this paper, we particularly propose to optimize the illumination scheme, which is a critical component in designing an eye tracking-HMD (ET-HMD) integrated system. An optimal design can improve not only eye tracking accuracy, but also robustness. Using LightTools, we present the simulation of a complete eye illumination and imaging system using an eye model along with multiple near infrared LED (IRLED) illuminators and imaging optics, showing the irradiance variation of the different eye structures. The simulation of dark pupil effects along with multiple 1st-order Purkinje images will be presented. A parametric analysis is performed to investigate the relationships between the IRLED configurations and the irradiance distribution at the eye, and a set of optimal configuration parameters is recommended. The analysis will be further refined by actual eye image acquisition and processing.
SLAMM: Visual monocular SLAM with continuous mapping using multiple maps
Md. Sabri, Aznul Qalid; Loo, Chu Kiong; Mansoor, Ali Mohammed
2018-01-01
This paper presents the concept of Simultaneous Localization and Multi-Mapping (SLAMM). It is a system that ensures continuous mapping and information preservation despite failures in tracking due to corrupted frames or sensor’s malfunction; making it suitable for real-world applications. It works with single or multiple robots. In a single robot scenario the algorithm generates a new map at the time of tracking failure, and later it merges maps at the event of loop closure. Similarly, maps generated from multiple robots are merged without prior knowledge of their relative poses; which makes this algorithm flexible. The system works in real time at frame-rate speed. The proposed approach was tested on the KITTI and TUM RGB-D public datasets and it showed superior results compared to the state-of-the-arts in calibrated visual monocular keyframe-based SLAM. The mean tracking time is around 22 milliseconds. The initialization is twice as fast as it is in ORB-SLAM, and the retrieved map can reach up to 90 percent more in terms of information preservation depending on tracking loss and loop closure events. For the benefit of the community, the source code along with a framework to be run with Bebop drone are made available at https://github.com/hdaoud/ORBSLAMM. PMID:29702697
A biplanar X-ray approach for studying the 3D dynamics of human track formation.
Hatala, Kevin G; Perry, David A; Gatesy, Stephen M
2018-05-09
Recent discoveries have made hominin tracks an increasingly prevalent component of the human fossil record, and these data have the capacity to inform long-standing debates regarding the biomechanics of hominin locomotion. However, there is currently no consensus on how to decipher biomechanical variables from hominin tracks. These debates can be linked to our generally limited understanding of the complex interactions between anatomy, motion, and substrate that give rise to track morphology. These interactions are difficult to study because direct visualization of the track formation process is impeded by foot and substrate opacity. To address these obstacles, we developed biplanar X-ray and computer animation methods, derived from X-ray Reconstruction of Moving Morphology (XROMM), to analyze the 3D dynamics of three human subjects' feet as they walked across four substrates (three deformable muds and rigid composite panel). By imaging and reconstructing 3D positions of external markers, we quantified the 3D dynamics at the foot-substrate interface. Foot shape, specifically heel and medial longitudinal arch deformation, was significantly affected by substrate rigidity. In deformable muds, we found that depths measured across tracks did not directly reflect the motions of the corresponding regions of the foot, and that track outlines were not perfectly representative of foot size. These results highlight the complex, dynamic nature of track formation, and the experimental methods presented here offer a promising avenue for developing and refining methods for accurately inferring foot anatomy and gait biomechanics from fossil hominin tracks. Copyright © 2018 Elsevier Ltd. All rights reserved.
Human operator tracking performance with a vibrotactile display
NASA Technical Reports Server (NTRS)
Inbar, Gideon F.
1991-01-01
Vibrotactile displays have been designed and used as a sensory aid for the blind. In the present work the same 6 x 24 'Optacon' type vibrotactile display (VTD) was used to characterize human operator (HO) tracking performance in pursuit and compensatory tasks. The VTD was connected via a microprocessor to a one-dimensional joy stick manipulator. Various display schemes were tested on the VDT, and were also compared to visual tracking performance using a specially constructed photo diode matrix display comparable to the VTD.
Li, Bin; Fu, Hong; Wen, Desheng; Lo, WaiLun
2018-05-19
Eye tracking technology has become increasingly important for psychological analysis, medical diagnosis, driver assistance systems, and many other applications. Various gaze-tracking models have been established by previous researchers. However, there is currently no near-eye display system with accurate gaze-tracking performance and a convenient user experience. In this paper, we constructed a complete prototype of the mobile gaze-tracking system ' Etracker ' with a near-eye viewing device for human gaze tracking. We proposed a combined gaze-tracking algorithm. In this algorithm, the convolutional neural network is used to remove blinking images and predict coarse gaze position, and then a geometric model is defined for accurate human gaze tracking. Moreover, we proposed using the mean value of gazes to resolve pupil center changes caused by nystagmus in calibration algorithms, so that an individual user only needs to calibrate it the first time, which makes our system more convenient. The experiments on gaze data from 26 participants show that the eye center detection accuracy is 98% and Etracker can provide an average gaze accuracy of 0.53° at a rate of 30⁻60 Hz.
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
Selection and Evaluation of Chemical Indicators for Waste Stream Identification
NASA Astrophysics Data System (ADS)
DeVita, W. M.; Hall, J.
2015-12-01
Human and animal wastes pose a threat to the quality of groundwater, surface water and drinking water. This is especially of concern for private and public water supplies in agricultural areas of Wisconsin where land spreading of livestock waste occurs on thin soils overlaying fractured bedrock. Current microbial source tracking (MST) methods for source identification requires the use of polymerase chain reaction (PCR) techniques. Due to cost, these tests are often not an option for homeowners, municipalities or state agencies with limited resources. The Water and Environmental Analysis Laboratory sought to develop chemical methods to provide lower cost processes to determine sources of fecal waste using fecal sterols, pharmaceuticals (human and veterinary) and human care/use products in ground and surface waters using solid phase extraction combined with triple quadrupole mass spectrometry. The two separate techniques allow for the detection of fecal sterol and other chemical markers in the sub part per billion-range. Fecal sterol ratios from published sources were used to evaluate drinking water samples and wastewater from onsite waste treatment systems and municipal wastewater treatment plants. Pharmaceuticals and personal care products indicative of human waste included: acetaminophen, caffeine, carbamazepine, cotinine, paraxanthine, sulfamethoxazole, and the artificial sweeteners; acesulfame, saccharin, and sucralose. The bovine antibiotic sulfamethazine was also targeted. Well water samples with suspected fecal contamination were analyzed for fecal sterols and PPCPs. Results were compared to traditional MST results from the Wisconsin State Laboratory of Hygiene. Chemical indicators were found in 6 of 11 drinking water samples, and 5 of 11 were in support of MST results. Lack of detection of chemical indicators in samples contaminated with fecal waste supports the need for confirmatory methods and advancement of chemical indicator detection technologies.
Dynamic inverse models in human-cyber-physical systems
NASA Astrophysics Data System (ADS)
Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar
2016-05-01
Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.
Johnston, Christopher; Byappanahalli, Muruleedhara N.; Gibson, Jacqueline MacDonald; Ufnar, Jennifer A.; Whitman, Richard L.; Stewart, Jill R.
2013-01-01
Microbial source tracking assays to identify sources of waterborne contamination typically target genetic markers of host-specific microorganisms. However, no bacterial marker has been shown to be 100% host-specific, and cross-reactivity has been noted in studies evaluating known source samples. Using 485 challenge samples from 20 different human and animal fecal sources, this study evaluated microbial source tracking markers including the Bacteroides HF183 16S rRNA, M. smithii nifH, and Enterococcus esp gene targets that have been proposed as potential indicators of human fecal contamination. Bayes' Theorem was used to calculate the conditional probability that these markers or a combination of markers can correctly identify human sources of fecal pollution. All three human-associated markers were detected in 100% of the sewage samples analyzed. Bacteroides HF183 was the most effective marker for determining whether contamination was specifically from a human source, and greater than 98% certainty that contamination was from a human source was shown when both Bacteroides HF183 and M. smithii nifH markers were present. A high degree of certainty was attained even in cases where the prior probability of human fecal contamination was as low as 8.5%. The combination of Bacteroides HF183 and M. smithii nifH source tracking markers can help identify surface waters impacted by human fecal contamination, information useful for prioritizing restoration activities or assessing health risks from exposure to contaminated waters.
Dimensional analyses of frontal posed smile attractiveness in Japanese female patients.
Hata, Kyoko; Arai, Kazuhito
2016-01-01
To identify appropriate dimensional items in objective diagnostic analysis for attractiveness of frontal posed smile in Japanese female patients by comparing with the result of human judgments. Photographs of frontal posed smiles of 100 Japanese females after orthodontic treatment were evaluated by 20 dental students (10 males and 10 females) using a visual analogue scale (VAS). The photographs were ranked based on the VAS evaluations and the 25 photographs with the highest evaluations were selected as group A, and the 25 photos with the lowest evaluations were designated group B. Then 12 dimensional items of objective analysis selected from a literature review were measured. Means and standard deviations for measurements of the dimensional items were compared between the groups using the unpaired t-test with a significance level of P < .05. Mean values were significantly smaller in group A than in group B for interlabial gap, intervermilion distance, maxillary gingival display, maximum incisor exposure, and lower lip to incisor (P < .05). Significant differences were observed only in the vertical dimension, not in the transverse dimension. Five of the 12 objective diagnostic items were correlated with human judgments of the attractiveness of frontal posed smile in Japanese females after orthodontic treatment.
What interests them in the pictures?--differences in eye-tracking between rhesus monkeys and humans.
Hu, Ying-Zhou; Jiang, Hui-Hui; Liu, Ci-Rong; Wang, Jian-Hong; Yu, Cheng-Yang; Carlson, Synnöve; Yang, Shang-Chuan; Saarinen, Veli-Matti; Rizak, Joshua D; Tian, Xiao-Guang; Tan, Hen; Chen, Zhu-Yue; Ma, Yuan-Ye; Hu, Xin-Tian
2013-10-01
Studies estimating eye movements have demonstrated that non-human primates have fixation patterns similar to humans at the first sight of a picture. In the current study, three sets of pictures containing monkeys, humans or both were presented to rhesus monkeys and humans. The eye movements on these pictures by the two species were recorded using a Tobii eye-tracking system. We found that monkeys paid more attention to the head and body in pictures containing monkeys, whereas both monkeys and humans paid more attention to the head in pictures containing humans. The humans always concentrated on the eyes and head in all the pictures, indicating the social role of facial cues in society. Although humans paid more attention to the hands than monkeys, both monkeys and humans were interested in the hands and what was being done with them in the pictures. This may suggest the importance and necessity of hands for survival. Finally, monkeys scored lower in eye-tracking when fixating on the pictures, as if they were less interested in looking at the screen than humans. The locations of fixation in monkeys may provide insight into the role of eye movements in an evolutionary context.
Person detection, tracking and following using stereo camera
NASA Astrophysics Data System (ADS)
Wang, Xiaofeng; Zhang, Lilian; Wang, Duo; Hu, Xiaoping
2018-04-01
Person detection, tracking and following is a key enabling technology for mobile robots in many human-robot interaction applications. In this article, we present a system which is composed of visual human detection, video tracking and following. The detection is based on YOLO(You only look once), which applies a single convolution neural network(CNN) to the full image, thus can predict bounding boxes and class probabilities directly in one evaluation. Then the bounding box provides initial person position in image to initialize and train the KCF(Kernelized Correlation Filter), which is a video tracker based on discriminative classifier. At last, by using a stereo 3D sparse reconstruction algorithm, not only the position of the person in the scene is determined, but also it can elegantly solve the problem of scale ambiguity in the video tracker. Extensive experiments are conducted to demonstrate the effectiveness and robustness of our human detection and tracking system.
Voice tracking and spoken word recognition in the presence of other voices
NASA Astrophysics Data System (ADS)
Litong-Palima, Marisciel; Violanda, Renante; Saloma, Caesar
2004-12-01
We study the human hearing process by modeling the hair cell as a thresholded Hopf bifurcator and compare our calculations with experimental results involving human subjects in two different multi-source listening tasks of voice tracking and spoken-word recognition. In the model, we observed noise suppression by destructive interference between noise sources which weakens the effective noise strength acting on the hair cell. Different success rate characteristics were observed for the two tasks. Hair cell performance at low threshold levels agree well with results from voice-tracking experiments while those of word-recognition experiments are consistent with a linear model of the hearing process. The ability of humans to track a target voice is robust against cross-talk interference unlike word-recognition performance which deteriorates quickly with the number of uncorrelated noise sources in the environment which is a response behavior that is associated with linear systems.
USA Space Debris Environment, Operations, and Research Updates
NASA Technical Reports Server (NTRS)
Liou, J.-C.
2018-01-01
Space Missions in 2017 Earth Satellite Population Collision Avoidance Maneuvers Post mission Disposal of U.S.A. Spacecraft Space Situational Awareness (SSA) and the Space Debris Sensor (SDS) A total of 86 space launches placed more than 400 spacecraft into Earth orbits during 2017, following the trend of increase over the past decade NASA has established conjunction assessment processes for its human spaceflight and uncrewed spacecraft to avoid accidental collisions with objects tracked by the U.S. Space Surveillance Network - NASA also assists other U.S. government spacecraft owners with conjunction assessments and subsequent maneuvers The ISS has conducted 25 debris collision avoidance maneuvers since 1999 - None in 2016-2017, but an ISS visiting vehicle had one collision avoidance maneuver in 2017 During 2017 NASA executed or assisted in the execution of 21 collision avoidance maneuvers by uncrewed spacecraft - Four maneuvers were conducted to avoid debris from Fengyun-1C - Two maneuvers were conducted to avoid debris from the collision of Cosmos 2251 and Iridium 33 - One maneuver was conducted to avoid the ISS NASA has established conjunction assessment processes for its human spaceflight and uncrewed spacecraft to avoid accidental collisions with objects tracked by the U.S. Space Surveillance Network - NASA also assists other U.S. government spacecraft owners with conjunction assessments and subsequent maneuvers The ISS has conducted 25 debris collision avoidance maneuvers since 1999 - None in 2016-2017, but an ISS visiting vehicle had one collision avoidance maneuver in 2017 During 2017 NASA executed or assisted in the execution of 21 collision avoidance maneuvers by uncrewed spacecraft - Four maneuvers were conducted to avoid debris from Fengyun-1C - Two maneuvers were conducted to avoid debris from the collision of Cosmos 2251 and Iridium 33 The 2014-15 NASA Engineering and Safety Center (NESC) study on the micrometeoroid and orbital debris (MMOD) assessment for the Joint Polar Satellite System (JPSS) provided the following findings - Millimeter-sized orbital debris pose the highest penetration risk to most operational spacecraft in LEO - The most effective means to collect direct measurement data on millimetersized debris above 600 km altitude is to conduct in situ measurements - There is currently no in situ data on such small debris above 600 km altitude Since the orbital debris population follows a power-law size distribution, there are many more millimeter-sized debris than the large tracked objects - Current conjunction assessments and collision avoidance maneuvers against the tracked objects (which are typically 10 cm and larger) only address a small fraction (<1%) of the mission-ending risk from orbital debris To address the millimeter-sized debris data gap above 600 km, NASA has recently developed an innovative in situ measurement instrument - the Space Debris Sensor (SDS) - One maneuver was conducted to avoid the ISS
21 CFR 821.20 - Devices subject to tracking.
Code of Federal Regulations, 2010 CFR
2010-04-01
... Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED... within § 821.1(a) must track that device in accordance with this part, if FDA issues a tracking order to... the criteria of section 519(e)(1) of the act and, by virtue of the order, the sponsor must track the...
21 CFR 821.20 - Devices subject to tracking.
Code of Federal Regulations, 2011 CFR
2011-04-01
... Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED... within § 821.1(a) must track that device in accordance with this part, if FDA issues a tracking order to... the criteria of section 519(e)(1) of the act and, by virtue of the order, the sponsor must track the...
Did Humans Live with Dinosaurs? Excavating "Man Tracks" along the Paluxy River
ERIC Educational Resources Information Center
Moore, Randy
2014-01-01
The alleged "man tracks" beside dinosaur tracks near Glen Rose, Texas, are among the most enduring pieces of evidence used by young-Earth creationists to reject evolution. Despite the tracks' fame, their most persistent advocate--that is, Carl Baugh of the Creation Evidence Museum--has published neither (1) peer-reviewed papers in…
Track Picture Book. Elementary Science Study.
ERIC Educational Resources Information Center
Webster, David; And Others
This picture book was designed to be used with an Elementary Science Study unit that provides opportunities for students in grades 4-6 to study animal tracks. Shown within this book are numerous examples of tracks, including those of tires, human beings, animal tracks, and others in various media, such as snow, sand, mud, dust, and cement. (CS)
Development of a Human Neurovascular Unit Organotypic Systems Model of Early Brain Development
The inability to model human brain and blood-brain barrier development in vitro poses a major challenge in studies of how chemicals impact early neurogenic periods. During human development, disruption of thyroid hormone (TH) signaling is related to adverse morphological effects ...
75 FR 82011 - Web-Distributed Labeling of Pesticides
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-29
... with pesticide labeling, thereby improving protection of human health and the environment from risks... pesticide products will not pose unreasonable adverse effects to human health or the environment. EPA..., when EPA amends the labeling of a pesticide product to incorporate new protections for human health or...
Code of Federal Regulations, 2010 CFR
2010-04-01
... AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) DRUGS FOR HUMAN USE... communication means. A waiver request is required to contain at least one of the following: (1) An explanation... noncompliance would not pose a significant and unreasonable risk to human subjects of the investigation and that...
Human Behavior from a Chronobiological Perspective.
ERIC Educational Resources Information Center
Hoskins, Carol Noll
1980-01-01
The rhythmic patterning of man's biochemical, physiological, and psychological behavior and the temporal relationships among various functions are the province of chronobiology. Citing animal and human studies, the author documents the progress of this new science and poses complex questions that it may answer about human behavior. (Editor/SJL)
Scanning mid-IR laser apparatus with eye tracking for refractive surgery
NASA Astrophysics Data System (ADS)
Telfair, William B.; Yoder, Paul R., Jr.; Bekker, Carsten; Hoffman, Hanna J.; Jensen, Eric F.
1999-06-01
A robust, real-time, dynamic eye tracker has been integrated with the short pulse mid-infrared laser scanning delivery system previously described. This system employs a Q- switched Nd:YAG laser pumped optical parametric oscillator operating at 2.94 micrometers. Previous ablation studies on human cadaver eyes and in-vivo cat eyes demonstrated very smooth ablations with extremely low damage levels similar to results with an excimer. A 4-month healing study with cats indicated no adverse healing effects. In order to treat human eyes, the tracker is required because the eyes move during the procedure due to both voluntary and involuntary motions such as breathing, heartbeat, drift, loss of fixation, saccades and microsaccades. Eye tracking techniques from the literature were compared. A limbus tracking system was best for this application. Temporal and spectral filtering techniques were implemented to reduce tracking errors, reject stray light, and increase signal to noise ratio. The expanded-capability system (IRVision AccuScan 2000 Laser System) has been tested in the lab on simulated eye targets, glass eyes, cadaver eyes, and live human subjects. Circular targets ranging from 10-mm to 14-mm diameter were successfully tracked. The tracker performed beyond expectations while the system performed myopic photorefractive keratectomy procedures on several legally blind human subjects.
Armand, Mehran; Armiger, Robert S.; Kutzer, Michael D.; Basafa, Ehsan; Kazanzides, Peter; Taylor, Russell H.
2012-01-01
Intraoperative patient registration may significantly affect the outcome of image-guided surgery (IGS). Image-based registration approaches have several advantages over the currently dominant point-based direct contact methods and are used in some industry solutions in image-guided radiation therapy with fixed X-ray gantries. However, technical challenges including geometric calibration and computational cost have precluded their use with mobile C-arms for IGS. We propose a 2D/3D registration framework for intraoperative patient registration using a conventional mobile X-ray imager combining fiducial-based C-arm tracking and graphics processing unit (GPU)-acceleration. The two-stage framework 1) acquires X-ray images and estimates relative pose between the images using a custom-made in-image fiducial, and 2) estimates the patient pose using intensity-based 2D/3D registration. Experimental validations using a publicly available gold standard dataset, a plastic bone phantom and cadaveric specimens have been conducted. The mean target registration error (mTRE) was 0.34 ± 0.04 mm (success rate: 100%, registration time: 14.2 s) for the phantom with two images 90° apart, and 0.99 ± 0.41 mm (81%, 16.3 s) for the cadaveric specimen with images 58.5° apart. The experimental results showed the feasibility of the proposed registration framework as a practical alternative for IGS routines. PMID:22113773
Designing Tracking Software for Image-Guided Surgery Applications: IGSTK Experience
Enquobahrie, Andinet; Gobbi, David; Turek, Matt; Cheng, Patrick; Yaniv, Ziv; Lindseth, Frank; Cleary, Kevin
2009-01-01
Objective Many image-guided surgery applications require tracking devices as part of their core functionality. The Image-Guided Surgery Toolkit (IGSTK) was designed and developed to interface tracking devices with software applications incorporating medical images. Methods IGSTK was designed as an open source C++ library that provides the basic components needed for fast prototyping and development of image-guided surgery applications. This library follows a component-based architecture with several components designed for specific sets of image-guided surgery functions. At the core of the toolkit is the tracker component that handles communication between a control computer and navigation device to gather pose measurements of surgical instruments present in the surgical scene. The representations of the tracked instruments are superimposed on anatomical images to provide visual feedback to the clinician during surgical procedures. Results The initial version of the IGSTK toolkit has been released in the public domain and several trackers are supported. The toolkit and related information are available at www.igstk.org. Conclusion With the increased popularity of minimally invasive procedures in health care, several tracking devices have been developed for medical applications. Designing and implementing high-quality and safe software to handle these different types of trackers in a common framework is a challenging task. It requires establishing key software design principles that emphasize abstraction, extensibility, reusability, fault-tolerance, and portability. IGSTK is an open source library that satisfies these needs for the image-guided surgery community. PMID:20037671
Song, Shuang; Zhang, Changchun; Liu, Li; Meng, Max Q-H
2018-02-01
Flexible surgical robot can work in confined and complex environments, which makes it a good option for minimally invasive surgery. In order to utilize flexible manipulators in complicated and constrained surgical environments, it is of great significance to monitor the position and shape of the curvilinear manipulator in real time during the procedures. In this paper, we propose a magnetic tracking-based planar shape sensing and navigation system for flexible surgical robots in the transoral surgery. The system can provide the real-time tip position and shape information of the robot during the operation. We use wire-driven flexible robot to serve as the manipulator. It has three degrees of freedom. A permanent magnet is mounted at the distal end of the robot. Its magnetic field can be sensed with a magnetic sensor array. Therefore, position and orientation of the tip can be estimated utilizing a tracking method. A shape sensing algorithm is then carried out to estimate the real-time shape based on the tip pose. With the tip pose and shape display in the 3D reconstructed CT model, navigation can be achieved. Using the proposed system, we carried out planar navigation experiments on a skull phantom to touch three different target positions under the navigation of the skull display interface. During the experiments, the real-time shape has been well monitored and distance errors between the robot tip and the targets in the skull have been recorded. The mean navigation error is [Formula: see text] mm, while the maximum error is 3.2 mm. The proposed method provides the advantages that no sensors are needed to mount on the robot and no line-of-sight problem. Experimental results verified the feasibility of the proposed method.
Barsingerhorn, A D; Boonstra, F N; Goossens, H H L M
2017-02-01
Current stereo eye-tracking methods model the cornea as a sphere with one refractive surface. However, the human cornea is slightly aspheric and has two refractive surfaces. Here we used ray-tracing and the Navarro eye-model to study how these optical properties affect the accuracy of different stereo eye-tracking methods. We found that pupil size, gaze direction and head position all influence the reconstruction of gaze. Resulting errors range between ± 1.0 degrees at best. This shows that stereo eye-tracking may be an option if reliable calibration is not possible, but the applied eye-model should account for the actual optics of the cornea.
65 Main-Track Train Collisions, 1997 through 2002 - Review, Analysis, Findings and Recommendations
DOT National Transportation Integrated Search
2006-08-01
The Collision Analysis Working Group (CAWG) reviewed and analyzed main-track collision of both freight and passenger trainss involving human factor issues and to make safety findings and recommendations. CAWG agreed to review main track train collisi...
HRM in the Knowledge-based Economy: Is There an Afterlife?
ERIC Educational Resources Information Center
Raich, Mario
2002-01-01
Explains changes in the workplace attributed to the knowledge economy and poses questions for businesses, workers, and the human resources function. Outlines new expectations of and a new framework for human resource management. (SK)
Child Labor and Environmental Health: Government Obligations and Human Rights
Amon, Joseph J.; Buchanan, Jane; Cohen, Jane; Kippenberg, Juliane
2012-01-01
The Convention concerning the Prohibition and Immediate Action for the Elimination of the Worst Forms of Child Labour was adopted by the International Labour Organization in 1999. 174 countries around the world have signed or ratified the convention, which requires countries to adopt laws and implement programs to prohibit and eliminate child labor that poses harms to health or safety. Nonetheless, child labor continues to be common in the agriculture and mining sectors, where safety and environmental hazards pose significant risks. Drawing upon recent human rights investigations of child labor in tobacco farming in Kazakhstan and gold mining in Mali, the role of international human rights mechanisms, advocacy with government and private sector officials, and media attention in reducing harmful environmental exposures of child workers is discussed. Human rights-based advocacy in both cases was important to raise attention and help ensure that children are protected from harm. PMID:23316246
Rhodes, Michael Grant
2013-08-01
The International Journal of Health Policy and Management (IJHPM) is a new journal that aims to stimulate not only inter-disciplinary research relating to health, but even an entire new generation of such journals. The challenges of improving human health worldwide clearly suggest 'why' such a journal is needed, but 'how' bridges and junctions across fields of study towards this end might be found poses other questions. From the agnosticism of many sciences with respect to human health, to the great faith others place in more esoteric movements for human well-being, both suggest finding common factors in the many equations that affect human health. Particularly, as it is typically defined professionally, it might pose more fundamental challenges than those which appear first. However, the first editorial and edition quietly assure that the journal is in good hands, and that the search for a new generation of journals has begun.
Fatal H5N6 Avian Influenza Virus Infection in a Domestic Cat and Wild Birds in China.
Yu, Zhijun; Gao, Xiaolong; Wang, Tiecheng; Li, Yanbing; Li, Yongcheng; Xu, Yu; Chu, Dong; Sun, Heting; Wu, Changjiang; Li, Shengnan; Wang, Haijun; Li, Yuanguo; Xia, Zhiping; Lin, Weishi; Qian, Jun; Chen, Hualan; Xia, Xianzhu; Gao, Yuwei
2015-06-02
H5N6 avian influenza viruses (AIVs) may pose a potential human risk as suggested by the first documented naturally-acquired human H5N6 virus infection in 2014. Here, we report the first cases of fatal H5N6 avian influenza virus (AIV) infection in a domestic cat and wild birds. These cases followed human H5N6 infections in China and preceded an H5N6 outbreak in chickens. The extensive migration routes of wild birds may contribute to the geographic spread of H5N6 AIVs and pose a risk to humans and susceptible domesticated animals, and the H5N6 AIVs may spread from southern China to northern China by wild birds. Additional surveillance is required to better understand the threat of zoonotic transmission of AIVs.
Effects of Detailed Illustrations on Science Learning: An Eye-Tracking Study
ERIC Educational Resources Information Center
Lin, Yu Ying; Holmqvist, Kenneth; Miyoshi, Kiyofumi; Ashida, Hiroshi
2017-01-01
The eye-tracking method was used to assess the influence of detailed, colorful illustrations on reading behaviors and learning outcomes. Based on participants' subjective ratings in a pre-study, we selected eight one-page human anatomy lessons. In the main study, participants learned these eight human anatomy lessons; four were accompanied by…
Haptic Tracking Permits Bimanual Independence
ERIC Educational Resources Information Center
Rosenbaum, David A.; Dawson, Amanda A.; Challis, John H.
2006-01-01
This study shows that in a novel task--bimanual haptic tracking--neurologically normal human adults can move their 2 hands independently for extended periods of time with little or no training. Participants lightly touched buttons whose positions were moved either quasi-randomly in the horizontal plane by 1 or 2 human drivers (Experiment 1), in…
Zimmermann, Jan; Vazquez, Yuriria; Glimcher, Paul W; Pesaran, Bijan; Louie, Kenway
2016-09-01
Video-based noninvasive eye trackers are an extremely useful tool for many areas of research. Many open-source eye trackers are available but current open-source systems are not designed to track eye movements with the temporal resolution required to investigate the mechanisms of oculomotor behavior. Commercial systems are available but employ closed source hardware and software and are relatively expensive, limiting wide-spread use. Here we present Oculomatic, an open-source software and modular hardware solution to eye tracking for use in humans and non-human primates. Oculomatic features high temporal resolution (up to 600Hz), real-time eye tracking with high spatial accuracy (<0.5°), and low system latency (∼1.8ms, 0.32ms STD) at a relatively low-cost. Oculomatic compares favorably to our existing scleral search-coil system while being fully non invasive. We propose that Oculomatic can support a wide range of research into the properties and neural mechanisms of oculomotor behavior. Copyright © 2016 Elsevier B.V. All rights reserved.
Multisensor-based human detection and tracking for mobile service robots.
Bellotto, Nicola; Hu, Huosheng
2009-02-01
One of fundamental issues for service robots is human-robot interaction. In order to perform such a task and provide the desired services, these robots need to detect and track people in the surroundings. In this paper, we propose a solution for human tracking with a mobile robot that implements multisensor data fusion techniques. The system utilizes a new algorithm for laser-based leg detection using the onboard laser range finder (LRF). The approach is based on the recognition of typical leg patterns extracted from laser scans, which are shown to also be very discriminative in cluttered environments. These patterns can be used to localize both static and walking persons, even when the robot moves. Furthermore, faces are detected using the robot's camera, and the information is fused to the legs' position using a sequential implementation of unscented Kalman filter. The proposed solution is feasible for service robots with a similar device configuration and has been successfully implemented on two different mobile platforms. Several experiments illustrate the effectiveness of our approach, showing that robust human tracking can be performed within complex indoor environments.
Adoption of Internet2 in a Southwestern University: Human Resources Concerns
ERIC Educational Resources Information Center
Mendoza-Diaz, Noemi V.; Dooley, Larry M.; Dooley, Kim E.
2007-01-01
Human Resources are often times challenged by the integration of new technologies (Benson, Johnson, & Kichinke, 2002). Universities pose a unique challenge since they reluctantly adapt to changes (Torraco & Hoover, 2005; Watkins 2005). This is a dissertation study of the human resource concerns about adopting Internet2 in a…
75 FR 76461 - Petition for a Ban on Triclosan; Notice of Availability
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-08
... widespread use'' of triclosan poses significant risks to human health and the environment. In addition, the... human health and the environment, failed to conduct separate assessments for triclosan residues in... comprehensive review of the potential risks to human health and the environment resulting from the registered...
Potential for Gulls to Transport Bacteria from Human Waste Sites to Beaches
Contamination of recreational beaches due to fecal waste from gulls complicates beach monitoring and may pose a risk to public health. Gulls that feed at human waste sites may ingest human-associated fecal microorganisms associated with that waste. If these gulls also visit beach...
McCamy, Michael B.; Otero-Millan, Jorge; Leigh, R. John; King, Susan A.; Schneider, Rosalyn M.; Macknik, Stephen L.; Martinez-Conde, Susana
2015-01-01
Human eyes move continuously, even during visual fixation. These “fixational eye movements” (FEMs) include microsaccades, intersaccadic drift and oculomotor tremor. Research in human FEMs has grown considerably in the last decade, facilitated by the manufacture of noninvasive, high-resolution/speed video-oculography eye trackers. Due to the small magnitude of FEMs, obtaining reliable data can be challenging, however, and depends critically on the sensitivity and precision of the eye tracking system. Yet, no study has conducted an in-depth comparison of human FEM recordings obtained with the search coil (considered the gold standard for measuring microsaccades and drift) and with contemporary, state-of-the art video trackers. Here we measured human microsaccades and drift simultaneously with the search coil and a popular state-of-the-art video tracker. We found that 95% of microsaccades detected with the search coil were also detected with the video tracker, and 95% of microsaccades detected with video tracking were also detected with the search coil, indicating substantial agreement between the two systems. Peak/mean velocities and main sequence slopes of microsaccades detected with video tracking were significantly higher than those of the same microsaccades detected with the search coil, however. Ocular drift was significantly correlated between the two systems, but drift speeds were higher with video tracking than with the search coil. Overall, our combined results suggest that contemporary video tracking now approaches the search coil for measuring FEMs. PMID:26035820
Man-made space debris - Does it restrict free access to space
NASA Technical Reports Server (NTRS)
Wolfe, M.; Chobotov, V.; Kessler, D.; Reynolds, R.
1981-01-01
Consideration is given to the hazards posed by existing and future man-made space debris to spacecraft operations. The components of the hazard are identified as those fragments resulting from spacecraft explosions and spent stages which can be tracked, those fragments which are too small to be tracked at their present distances, and future debris, which, if present trends in spacecraft design and operation continue, may lead to an unacceptably high probability of collision with operational spacecraft within a decade. It is argued that a coordinated effort must be undertaken by all space users to evaluate means of space debris control in order to allow for the future unrestricted use of near-earth space. A plan for immediate action to forestall the space debris problem by activities in the areas of education, debris monitoring and collection technology, space vehicle design, space operational procedures and practices and space policies and treaties is proposed.
Interacting with target tracking algorithms in a gaze-enhanced motion video analysis system
NASA Astrophysics Data System (ADS)
Hild, Jutta; Krüger, Wolfgang; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen
2016-05-01
Motion video analysis is a challenging task, particularly if real-time analysis is required. It is therefore an important issue how to provide suitable assistance for the human operator. Given that the use of customized video analysis systems is more and more established, one supporting measure is to provide system functions which perform subtasks of the analysis. Recent progress in the development of automated image exploitation algorithms allow, e.g., real-time moving target tracking. Another supporting measure is to provide a user interface which strives to reduce the perceptual, cognitive and motor load of the human operator for example by incorporating the operator's visual focus of attention. A gaze-enhanced user interface is able to help here. This work extends prior work on automated target recognition, segmentation, and tracking algorithms as well as about the benefits of a gaze-enhanced user interface for interaction with moving targets. We also propose a prototypical system design aiming to combine both the qualities of the human observer's perception and the automated algorithms in order to improve the overall performance of a real-time video analysis system. In this contribution, we address two novel issues analyzing gaze-based interaction with target tracking algorithms. The first issue extends the gaze-based triggering of a target tracking process, e.g., investigating how to best relaunch in the case of track loss. The second issue addresses the initialization of tracking algorithms without motion segmentation where the operator has to provide the system with the object's image region in order to start the tracking algorithm.
Human emotions track changes in the acoustic environment
Ma, Weiyi; Thompson, William Forde
2015-01-01
Emotional responses to biologically significant events are essential for human survival. Do human emotions lawfully track changes in the acoustic environment? Here we report that changes in acoustic attributes that are well known to interact with human emotions in speech and music also trigger systematic emotional responses when they occur in environmental sounds, including sounds of human actions, animal calls, machinery, or natural phenomena, such as wind and rain. Three changes in acoustic attributes known to signal emotional states in speech and music were imposed upon 24 environmental sounds. Evaluations of stimuli indicated that human emotions track such changes in environmental sounds just as they do for speech and music. Such changes not only influenced evaluations of the sounds themselves, they also affected the way accompanying facial expressions were interpreted emotionally. The findings illustrate that human emotions are highly attuned to changes in the acoustic environment, and reignite a discussion of Charles Darwin’s hypothesis that speech and music originated from a common emotional signal system based on the imitation and modification of environmental sounds. PMID:26553987
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 ...
EPA'S HUMAN EXPOSURE MEASUREMENT PROGRAM
The goal of NERL's Exposure Research Program is to improve the scientific basis for conducting human exposure assessments that are part of the EPA's risk assessment, risk management and compliance process. Overall, we aim to address aggregate and cumulative exposures that pose...
Probabilistic Elastic Part Model: A Pose-Invariant Representation for Real-World Face Verification.
Li, Haoxiang; Hua, Gang
2018-04-01
Pose variation remains to be a major challenge for real-world face recognition. We approach this problem through a probabilistic elastic part model. We extract local descriptors (e.g., LBP or SIFT) from densely sampled multi-scale image patches. By augmenting each descriptor with its location, a Gaussian mixture model (GMM) is trained to capture the spatial-appearance distribution of the face parts of all face images in the training corpus, namely the probabilistic elastic part (PEP) model. Each mixture component of the GMM is confined to be a spherical Gaussian to balance the influence of the appearance and the location terms, which naturally defines a part. Given one or multiple face images of the same subject, the PEP-model builds its PEP representation by sequentially concatenating descriptors identified by each Gaussian component in a maximum likelihood sense. We further propose a joint Bayesian adaptation algorithm to adapt the universally trained GMM to better model the pose variations between the target pair of faces/face tracks, which consistently improves face verification accuracy. Our experiments show that we achieve state-of-the-art face verification accuracy with the proposed representations on the Labeled Face in the Wild (LFW) dataset, the YouTube video face database, and the CMU MultiPIE dataset.
Feature tracking for automated volume of interest stabilization on 4D-OCT images
NASA Astrophysics Data System (ADS)
Laves, Max-Heinrich; Schoob, Andreas; Kahrs, Lüder A.; Pfeiffer, Tom; Huber, Robert; Ortmaier, Tobias
2017-03-01
A common representation of volumetric medical image data is the triplanar view (TV), in which the surgeon manually selects slices showing the anatomical structure of interest. In addition to common medical imaging such as MRI or computed tomography, recent advances in the field of optical coherence tomography (OCT) have enabled live processing and volumetric rendering of four-dimensional images of the human body. Due to the region of interest undergoing motion, it is challenging for the surgeon to simultaneously keep track of an object by continuously adjusting the TV to desired slices. To select these slices in subsequent frames automatically, it is necessary to track movements of the volume of interest (VOI). This has not been addressed with respect to 4DOCT images yet. Therefore, this paper evaluates motion tracking by applying state-of-the-art tracking schemes on maximum intensity projections (MIP) of 4D-OCT images. Estimated VOI location is used to conveniently show corresponding slices and to improve the MIPs by calculating thin-slab MIPs. Tracking performances are evaluated on an in-vivo sequence of human skin, captured at 26 volumes per second. Among investigated tracking schemes, our recently presented tracking scheme for soft tissue motion provides highest accuracy with an error of under 2.2 voxels for the first 80 volumes. Object tracking on 4D-OCT images enables its use for sub-epithelial tracking of microvessels for image-guidance.
Environmental Impact Statement: Peacekeeper Missile System Deactivation and Dismantlement
2000-12-01
adverse human health or environmental effects of its programs, policies, and activities on minority populations and low-income populations. In...PCB) are suspected human carcinogens. Improper handling of PCB items or releases of PCBs could have adverse effects on human health and the...human health effects , or pose a substantial present or potential hazard to human health or the environment. Only those materials listed as hazardous
Smart Distributed Sensor Fields: Algorithms for Tactical Sensors
2013-12-23
ranging from detecting, identifying, localizing/tracking interesting events, discarding irrelevant data, to providing actionable intelligence currently...tracking interesting events, discarding irrelevant data, to providing actionable intelligence currently requires significant human super- vision. Human...view of the overall system. The main idea is to reduce the problem to the relevant data, and then reason intelligently over that data. This process
ERIC Educational Resources Information Center
Ferry, Alissa L.; Fló, Ana; Brusini, Perrine; Cattarossi, Luigi; Macagno, Francesco; Nespor, Marina; Mehler, Jacques
2016-01-01
To understand language, humans must encode information from rapid, sequential streams of syllables--tracking their order and organizing them into words, phrases, and sentences. We used Near-Infrared Spectroscopy (NIRS) to determine whether human neonates are born with the capacity to track the positions of syllables in multisyllabic sequences.…
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.
Chaaraoui, Alexandros Andre; Flórez-Revuelta, Francisco
2014-01-01
This paper presents a novel silhouette-based feature for vision-based human action recognition, which relies on the contour of the silhouette and a radial scheme. Its low-dimensionality and ease of extraction result in an outstanding proficiency for real-time scenarios. This feature is used in a learning algorithm that by means of model fusion of multiple camera streams builds a bag of key poses, which serves as a dictionary of known poses and allows converting the training sequences into sequences of key poses. These are used in order to perform action recognition by means of a sequence matching algorithm. Experimentation on three different datasets returns high and stable recognition rates. To the best of our knowledge, this paper presents the highest results so far on the MuHAVi-MAS dataset. Real-time suitability is given, since the method easily performs above video frequency. Therefore, the related requirements that applications as ambient-assisted living services impose are successfully fulfilled.
Quantifying Pilot Visual Attention in Low Visibility Terminal Operations
NASA Technical Reports Server (NTRS)
Ellis, Kyle K.; Arthur, J. J.; Latorella, Kara A.; Kramer, Lynda J.; Shelton, Kevin J.; Norman, Robert M.; Prinzel, Lawrence J.
2012-01-01
Quantifying pilot visual behavior allows researchers to determine not only where a pilot is looking and when, but holds implications for specific behavioral tracking when these data are coupled with flight technical performance. Remote eye tracking systems have been integrated into simulators at NASA Langley with effectively no impact on the pilot environment. This paper discusses the installation and use of a remote eye tracking system. The data collection techniques from a complex human-in-the-loop (HITL) research experiment are discussed; especially, the data reduction algorithms and logic to transform raw eye tracking data into quantified visual behavior metrics, and analysis methods to interpret visual behavior. The findings suggest superior performance for Head-Up Display (HUD) and improved attentional behavior for Head-Down Display (HDD) implementations of Synthetic Vision System (SVS) technologies for low visibility terminal area operations. Keywords: eye tracking, flight deck, NextGen, human machine interface, aviation
Li, Mengfei; Hansen, Christian; Rose, Georg
2017-09-01
Electromagnetic tracking systems (EMTS) have achieved a high level of acceptance in clinical settings, e.g., to support tracking of medical instruments in image-guided interventions. However, tracking errors caused by movable metallic medical instruments and electronic devices are a critical problem which prevents the wider application of EMTS for clinical applications. We plan to introduce a method to dynamically reduce tracking errors caused by metallic objects in proximity to the magnetic sensor coil of the EMTS. We propose a method using ramp waveform excitation based on modeling the conductive distorter as a resistance-inductance circuit. Additionally, a fast data acquisition method is presented to speed up the refresh rate. With the current approach, the sensor's positioning mean error is estimated to be 3.4, 1.3 and 0.7 mm, corresponding to a distance between the sensor and center of the transmitter coils' array of up to 200, 150 and 100 mm, respectively. The sensor pose error caused by different medical instruments placed in proximity was reduced by the proposed method to a level lower than 0.5 mm in position and [Formula: see text] in orientation. By applying the newly developed fast data acquisition method, we achieved a system refresh rate up to approximately 12.7 frames per second. Our software-based approach can be integrated into existing medical EMTS seamlessly with no change in hardware. It improves the tracking accuracy of clinical EMTS when there is a metallic object placed near the sensor coil and has the potential to improve the safety and outcome of image-guided interventions.
Multi-object tracking of human spermatozoa
NASA Astrophysics Data System (ADS)
Sørensen, Lauge; Østergaard, Jakob; Johansen, Peter; de Bruijne, Marleen
2008-03-01
We propose a system for tracking of human spermatozoa in phase-contrast microscopy image sequences. One of the main aims of a computer-aided sperm analysis (CASA) system is to automatically assess sperm quality based on spermatozoa motility variables. In our case, the problem of assessing sperm quality is cast as a multi-object tracking problem, where the objects being tracked are the spermatozoa. The system combines a particle filter and Kalman filters for robust motion estimation of the spermatozoa tracks. Further, the combinatorial aspect of assigning observations to labels in the particle filter is formulated as a linear assignment problem solved using the Hungarian algorithm on a rectangular cost matrix, making the algorithm capable of handling missing or spurious observations. The costs are calculated using hidden Markov models that express the plausibility of an observation being the next position in the track history of the particle labels. Observations are extracted using a scale-space blob detector utilizing the fact that the spermatozoa appear as bright blobs in a phase-contrast microscope. The output of the system is the complete motion track of each of the spermatozoa. Based on these tracks, different CASA motility variables can be computed, for example curvilinear velocity or straight-line velocity. The performance of the system is tested on three different phase-contrast image sequences of varying complexity, both by visual inspection of the estimated spermatozoa tracks and by measuring the mean squared error (MSE) between the estimated spermatozoa tracks and manually annotated tracks, showing good agreement.
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.
They Might be Giants: Small-Scale RPAs as a Threat to Air Base Defense and Air Power Projection
2014-06-01
experience on C-5, KC-10, and C-17 aircraft as well as multiple General Electric jet and turbofan engines. He takes command of the 730th Air Mobility...pneumatic and electric controls for stabilization and launched from a portable track. Once it arrived near the target, it would kill its engine, shed...airfield lie beyond or under the path of any interceptor’s bullets. To pose a metaphor, it is akin to using a sports car to chase a honeybee, but
Mathematical model for production of an industry focusing on worker status
NASA Astrophysics Data System (ADS)
Visalakshi, V.; kiran kumari, Sheshma
2018-04-01
Productivity improvement is posing a great challenge for industry everyday because of the difficulties in keeping track and priorising the variables that have significant impact on the productivity. The variation in production depends on the linguistic variables such as worker commitment, worker motivation and worker skills. Since the variables are linguistic we try to propose a model which gives an appropriate production of an industry. Fuzzy models aids the relationship between the factors and status. The model will support the industry to focus on the mentality of worker to increase the production.
A gunner model for an AAA tracking task with interrupted observations
NASA Technical Reports Server (NTRS)
Yu, C. F.; Wei, K. C.; Vikmanis, M.
1982-01-01
The problem of modeling a trained human operator's tracking performance in an anti-aircraft system under various display blanking conditions is discussed. The input to the gunner is the observable tracking error subjected to repeated interruptions (blanking). A simple and effective gunner model was developed. The effect of blanking on the gunner's tracking performance is approached via modeling the observer and controller gains.
Kotani, Manato; Shimono, Kohei; Yoneyama, Toshihiro; Nakako, Tomokazu; Matsumoto, Kenji; Ogi, Yuji; Konoike, Naho; Nakamura, Katsuki; Ikeda, Kazuhito
2017-09-01
Eye tracking systems are used to investigate eyes position and gaze patterns presumed as eye contact in humans. Eye contact is a useful biomarker of social communication and known to be deficient in patients with autism spectrum disorders (ASDs). Interestingly, the same eye tracking systems have been used to directly compare face scanning patterns in some non-human primates to those in human. Thus, eye tracking is expected to be a useful translational technique for investigating not only social attention and visual interest, but also the effects of psychiatric drugs, such as oxytocin, a neuropeptide that regulates social behavior. In this study, we report on a newly established method for eye tracking in common marmosets as unique New World primates that, like humans, use eye contact as a mean of communication. Our investigation was aimed at characterizing these primates face scanning patterns and evaluating the effects of oxytocin on their eye contact behavior. We found that normal common marmosets spend more time viewing the eyes region in common marmoset's picture than the mouth region or a scrambled picture. In oxytocin experiment, the change in eyes/face ratio was significantly greater in the oxytocin group than in the vehicle group. Moreover, oxytocin-induced increase in the change in eyes/face ratio was completely blocked by the oxytocin receptor antagonist L-368,899. These results indicate that eye tracking in common marmosets may be useful for evaluating drug candidates targeting psychiatric conditions, especially ASDs. Copyright © 2017 Elsevier Ltd. All rights reserved.
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.
The Near-Earth Object Camera: A Next-Generation Minor Planet Survey
NASA Astrophysics Data System (ADS)
Mainzer, Amy K.; Wright, Edward L.; Bauer, James; Grav, Tommy; Cutri, Roc M.; Masiero, Joseph; Nugent, Carolyn R.
2015-11-01
The Near-Earth Object Camera (NEOCam) is a next-generation asteroid and comet survey designed to discover, characterize, and track large numbers of minor planets using a 50 cm infrared telescope located at the Sun-Earth L1 Lagrange point. Proposed to NASA's Discovery program, NEOCam is designed to carry out a comprehensive inventory of the small bodies in the inner regions of our solar system. It address three themes: 1) quantify the potential hazard that near-Earth objects may pose to Earth; 2) study the origins and evolution of our solar system as revealed by its small body populations; and 3) identify the best destinations for future robotic and human exploration. With a dual channel infrared imager that observes at 4-5 and 6-10 micron bands simultaneously through the use of a beamsplitter, NEOCam enables measurements of asteroid diameters and thermal inertia. NEOCam complements existing and planned visible light surveys in terms of orbital element phase space and wavelengths, since albedos can be determined for objects with both visible and infrared flux measurements. NEOCam was awarded technology development funding in 2011 to mature the necessary megapixel infrared detectors.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hattemer-Frey, H.A.; Brandt, E.J.; Travis, C.C.
Commercial genetic engineering is advancing into areas that require the small-scale introduction of genetically engineered microorganisms (GEMs) to better quantify variables that affect microorganism distribution and survival and to document potential long-term consequences. A recombinant DNA marker system, the lacZY marker, developed by the Monsanto Agricultural Co., enables the distribution and fate of marked fluorescent pseudomonad organisms to be monitored under actual field conditions. Critical evaluation of GEMs under field conditions is imperative if plant-beneficial effects are to be correlated with organism release. This paper evaluates the effectiveness of this marker system and its ability to facilitate the assessment ofmore » risks associated with deliberate environmental introductions of genetically engineered microorganisms. Results of prerelease contained growth chamber and field experiments demonstrated that: (1) the scientific risk assessment methodology adopted by Monsanto and approved by the U.S. Environmental Protection Agency was appropriate and comprehensive; (2) the deliberate introduction of a GEM did not pose unacceptable or unforeseen risks to human health or the environment; (3) the lacZY marker is an effective environmental tracking tool; and (4) regulatory oversight should reflect the expected risk and not be excessively burdensome for all GEMs.« less
Conditioned social dominance threat: observation of others' social dominance biases threat learning.
Haaker, Jan; Molapour, Tanaz; Olsson, Andreas
2016-10-01
Social groups are organized along dominance hierarchies, which determine how we respond to threats posed by dominant and subordinate others. The persuasive impact of these dominance threats on mental and physical well-being has been well described but it is unknown how dominance rank of others bias our experience and learning in the first place. We introduce a model of conditioned social dominance threat in humans, where the presence of a dominant other is paired with an aversive event. Participants first learned about the dominance rank of others by observing their dyadic confrontations. During subsequent fear learning, the dominant and subordinate others were equally predictive of an aversive consequence (mild electric shock) to the participant. In three separate experiments, we show that participants' eye-blink startle responses and amygdala reactivity adaptively tracked dominance of others during observation of confrontation. Importantly, during fear learning dominant vs subordinate others elicited stronger and more persistent learned threat responses as measured by physiological arousal and amygdala activity. Our results characterize the neural basis of learning through observing conflicts between others, and how this affects subsequent learning through direct, personal experiences. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Conditioned social dominance threat: observation of others’ social dominance biases threat learning
Molapour, Tanaz; Olsson, Andreas
2016-01-01
Social groups are organized along dominance hierarchies, which determine how we respond to threats posed by dominant and subordinate others. The persuasive impact of these dominance threats on mental and physical well-being has been well described but it is unknown how dominance rank of others bias our experience and learning in the first place. We introduce a model of conditioned social dominance threat in humans, where the presence of a dominant other is paired with an aversive event. Participants first learned about the dominance rank of others by observing their dyadic confrontations. During subsequent fear learning, the dominant and subordinate others were equally predictive of an aversive consequence (mild electric shock) to the participant. In three separate experiments, we show that participants’ eye-blink startle responses and amygdala reactivity adaptively tracked dominance of others during observation of confrontation. Importantly, during fear learning dominant vs subordinate others elicited stronger and more persistent learned threat responses as measured by physiological arousal and amygdala activity. Our results characterize the neural basis of learning through observing conflicts between others, and how this affects subsequent learning through direct, personal experiences. PMID:27217107
There is sufficient epidemiological evidence supported by experimental data that some PAH-containing complex environmental mixtures pose risks to human health by increasing lung cancer incidence. The International Agency for Research on Cancer has determined that human respirator...
Due to its presence in water as a volatile disinfection byproduct, BDCM, which is mutagenic and a rodent carcinogen, poses a risk for exposure via multiple routes. We developed a refined human PBPK model for BDCM (including new chemical-specific human parameters) to evaluate the...
Unit: Where Humans Came From, Inspection Pack, First Trial Print.
ERIC Educational Resources Information Center
Australian Science Education Project, Toorak, Victoria.
"Where Humans Came From" is a set of materials designed for use by students (aged 15-16) to assist them in investigating the problem posed in the title. The student book briefly outlines the essential features of four explanations of human origin: special creation (Judeo-Christian, Greek, Australian Aboriginal, American Indian accounts);…
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.
The TREC Interactive Track: An Annotated Bibliography.
ERIC Educational Resources Information Center
Over, Paul
2001-01-01
Discussion of the study of interactive information retrieval (IR) at the Text Retrieval Conferences (TREC) focuses on summaries of the Interactive Track at each conference. Describes evolution of the track, which has changed from comparing human-machine systems with fully automatic systems to comparing interactive systems that focus on the search…
25 CFR 900.52 - What type of property is the property management system required to track?
Code of Federal Regulations, 2012 CFR
2012-04-01
... INDIAN HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES CONTRACTS UNDER THE INDIAN SELF-DETERMINATION AND EDUCATION ASSISTANCE ACT Standards for Tribal or Tribal Organization Management Systems... required to track? The property management system of the Indian tribe or tribal organization shall track...
25 CFR 900.52 - What type of property is the property management system required to track?
Code of Federal Regulations, 2014 CFR
2014-04-01
... INDIAN HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES CONTRACTS UNDER THE INDIAN SELF-DETERMINATION AND EDUCATION ASSISTANCE ACT Standards for Tribal or Tribal Organization Management Systems... required to track? The property management system of the Indian tribe or tribal organization shall track...
25 CFR 900.52 - What type of property is the property management system required to track?
Code of Federal Regulations, 2011 CFR
2011-04-01
... INDIAN HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES CONTRACTS UNDER THE INDIAN SELF-DETERMINATION AND EDUCATION ASSISTANCE ACT Standards for Tribal or Tribal Organization Management Systems... required to track? The property management system of the Indian tribe or tribal organization shall track...
25 CFR 900.52 - What type of property is the property management system required to track?
Code of Federal Regulations, 2010 CFR
2010-04-01
... INDIAN HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES CONTRACTS UNDER THE INDIAN SELF-DETERMINATION AND EDUCATION ASSISTANCE ACT Standards for Tribal or Tribal Organization Management Systems... required to track? The property management system of the Indian tribe or tribal organization shall track...
25 CFR 900.52 - What type of property is the property management system required to track?
Code of Federal Regulations, 2013 CFR
2013-04-01
... INDIAN HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES CONTRACTS UNDER THE INDIAN SELF-DETERMINATION AND EDUCATION ASSISTANCE ACT Standards for Tribal or Tribal Organization Management Systems... required to track? The property management system of the Indian tribe or tribal organization shall track...
CD24 tracks divergent pluripotent states in mouse and human cells
Shakiba, Nika; White, Carl A.; Lipsitz, Yonatan Y.; Yachie-Kinoshita, Ayako; Tonge, Peter D; Hussein, Samer M. I.; Puri, Mira C.; Elbaz, Judith; Morrissey-Scoot, James; Li, Mira; Munoz, Javier; Benevento, Marco; Rogers, Ian M.; Hanna, Jacob H.; Heck, Albert J. R.; Wollscheid, Bernd; Nagy, Andras; Zandstra, Peter W
2015-01-01
Reprogramming is a dynamic process that can result in multiple pluripotent cell types emerging from divergent paths. Cell surface protein expression is a particularly desirable tool to categorize reprogramming and pluripotency as it enables robust quantification and enrichment of live cells. Here we use cell surface proteomics to interrogate mouse cell reprogramming dynamics and discover CD24 as a marker that tracks the emergence of reprogramming-responsive cells, while enabling the analysis and enrichment of transgene-dependent (F-class) and -independent (traditional) induced pluripotent stem cells (iPSCs) at later stages. Furthermore, CD24 can be used to delineate epiblast stem cells (EpiSCs) from embryonic stem cells (ESCs) in mouse pluripotent culture. Importantly, regulated CD24 expression is conserved in human pluripotent stem cells (PSCs), tracking the conversion of human ESCs to more naive-like PSC states. Thus, CD24 is a conserved marker for tracking divergent states in both reprogramming and standard pluripotent culture. PMID:26076835
Self-organizing neural integration of pose-motion features for human action recognition
Parisi, German I.; Weber, Cornelius; Wermter, Stefan
2015-01-01
The visual recognition of complex, articulated human movements is fundamental for a wide range of artificial systems oriented toward human-robot communication, action classification, and action-driven perception. These challenging tasks may generally involve the processing of a huge amount of visual information and learning-based mechanisms for generalizing a set of training actions and classifying new samples. To operate in natural environments, a crucial property is the efficient and robust recognition of actions, also under noisy conditions caused by, for instance, systematic sensor errors and temporarily occluded persons. Studies of the mammalian visual system and its outperforming ability to process biological motion information suggest separate neural pathways for the distinct processing of pose and motion features at multiple levels and the subsequent integration of these visual cues for action perception. We present a neurobiologically-motivated approach to achieve noise-tolerant action recognition in real time. Our model consists of self-organizing Growing When Required (GWR) networks that obtain progressively generalized representations of sensory inputs and learn inherent spatio-temporal dependencies. During the training, the GWR networks dynamically change their topological structure to better match the input space. We first extract pose and motion features from video sequences and then cluster actions in terms of prototypical pose-motion trajectories. Multi-cue trajectories from matching action frames are subsequently combined to provide action dynamics in the joint feature space. Reported experiments show that our approach outperforms previous results on a dataset of full-body actions captured with a depth sensor, and ranks among the best results for a public benchmark of domestic daily actions. PMID:26106323
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.
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.
Video see-through augmented reality for oral and maxillofacial surgery.
Wang, Junchen; Suenaga, Hideyuki; Yang, Liangjing; Kobayashi, Etsuko; Sakuma, Ichiro
2017-06-01
Oral and maxillofacial surgery has not been benefitting from image guidance techniques owing to the limitations in image registration. A real-time markerless image registration method is proposed by integrating a shape matching method into a 2D tracking framework. The image registration is performed by matching the patient's teeth model with intraoperative video to obtain its pose. The resulting pose is used to overlay relevant models from the same CT space on the camera video for augmented reality. The proposed system was evaluated on mandible/maxilla phantoms, a volunteer and clinical data. Experimental results show that the target overlay error is about 1 mm, and the frame rate of registration update yields 3-5 frames per second with a 4 K camera. The significance of this work lies in its simplicity in clinical setting and the seamless integration into the current medical procedure with satisfactory response time and overlay accuracy. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Sub-micron accurate track navigation method ``Navi'' for the analysis of Nuclear Emulsion
NASA Astrophysics Data System (ADS)
Yoshioka, T.; Yoshida, J.; Kodama, K.
2011-03-01
Sub-micron accurate track navigation in Nuclear Emulsion is realized by using low energy signals detected by automated Nuclear Emulsion read-out systems. Using those much dense ``noise'', about 104 times larger than the real tracks, the accuracy of the track position navigation reaches to be sub micron only by using the information of a microscope field of view, 200 micron times 200 micron. This method is applied to OPERA analysis in Japan, i.e. support of human eye checks of the candidate tracks, confirmation of neutrino interaction vertexes and to embed missing track segments to the track data read-out by automated systems.
Gorman, Susanna M
2011-09-01
Australian Human Research Ethics Committees (HRECs) have to contend with ever-increasing workloads and responsibilities which go well beyond questions of mere ethics. In this article, I shall examine how the roles of HRECs have changed, and show how this is reflected in the iterations of the National Statement on Ethical Conduct in Human Research 2007 (NS). In particular I suggest that the focus of the National Statement has shifted to concentrate on matters of research governance at the expense of research ethics, compounded by its linkage to the Australian Code for the Responsible Conduct of Research (2007) in its most recent iteration. I shall explore some of the challenges this poses for HRECs and institutions and the risks it poses to ensuring that Australian researchers receive clear ethical guidance and review.
NASA Astrophysics Data System (ADS)
Kladis, Georgios P.; Menon, Prathyush P.; Edwards, Christopher
2016-12-01
This article proposes a systematic analysis for a tracking problem which ensures cooperation amongst a swarm of unmanned aerial vehicles (UAVs), modelled as nonlinear systems with linear and angular velocity constraints, in order to achieve different goals. A distributed Takagi-Sugeno (TS) framework design is adopted for the representation of the nonlinear model of the dynamics of the UAVs. The distributed control law which is introduced is composed of both node and network level information. Firstly, feedback gains are synthesised using a parallel distributed compensation (PDC) control law structure, for a collection of isolated UAVs; ignoring communications among the swarm. Then secondly, based on an alternation-like procedure, the resulting feedback gains are used to determine Lyapunov matrices which are utilised at network level to incorporate into the control law, the relative differences in the states of the vehicles, and to induce cooperative behaviour. Eventually stability is guaranteed for the entire swarm. The control synthesis is performed using tools from linear control theory: in particular the design criteria are posed as linear matrix inequalities (LMIs). An example based on a UAV tracking scenario is included to outline the efficacy of the approach.
Real-time classification of vehicles by type within infrared imagery
NASA Astrophysics Data System (ADS)
Kundegorski, Mikolaj E.; Akçay, Samet; Payen de La Garanderie, Grégoire; Breckon, Toby P.
2016-10-01
Real-time classification of vehicles into sub-category types poses a significant challenge within infra-red imagery due to the high levels of intra-class variation in thermal vehicle signatures caused by aspects of design, current operating duration and ambient thermal conditions. Despite these challenges, infra-red sensing offers significant generalized target object detection advantages in terms of all-weather operation and invariance to visual camouflage techniques. This work investigates the accuracy of a number of real-time object classification approaches for this task within the wider context of an existing initial object detection and tracking framework. Specifically we evaluate the use of traditional feature-driven bag of visual words and histogram of oriented gradient classification approaches against modern convolutional neural network architectures. Furthermore, we use classical photogrammetry, within the context of current target detection and classification techniques, as a means of approximating 3D target position within the scene based on this vehicle type classification. Based on photogrammetric estimation of target position, we then illustrate the use of regular Kalman filter based tracking operating on actual 3D vehicle trajectories. Results are presented using a conventional thermal-band infra-red (IR) sensor arrangement where targets are tracked over a range of evaluation scenarios.
Duan, Liya; Guan, Tao; Yang, Bo
2009-01-01
Augmented reality (AR) is a field of computer research which deals with the combination of real world and computer generated data. Registration is one of the most difficult problems currently limiting the usability of AR systems. In this paper, we propose a novel natural feature tracking based registration method for AR applications. The proposed method has following advantages: (1) it is simple and efficient, as no man-made markers are needed for both indoor and outdoor AR applications; moreover, it can work with arbitrary geometric shapes including planar, near planar and non planar structures which really enhance the usability of AR systems. (2) Thanks to the reduced SIFT based augmented optical flow tracker, the virtual scene can still be augmented on the specified areas even under the circumstances of occlusion and large changes in viewpoint during the entire process. (3) It is easy to use, because the adaptive classification tree based matching strategy can give us fast and accurate initialization, even when the initial camera is different from the reference image to a large degree. Experimental evaluations validate the performance of the proposed method for online pose tracking and augmentation.
Model identification and vision-based H∞ position control of 6-DoF cable-driven parallel robots
NASA Astrophysics Data System (ADS)
Chellal, R.; Cuvillon, L.; Laroche, E.
2017-04-01
This paper presents methodologies for the identification and control of 6-degrees of freedom (6-DoF) cable-driven parallel robots (CDPRs). First a two-step identification methodology is proposed to accurately estimate the kinematic parameters independently and prior to the dynamic parameters of a physics-based model of CDPRs. Second, an original control scheme is developed, including a vision-based position controller tuned with the H∞ methodology and a cable tension distribution algorithm. The position is controlled in the operational space, making use of the end-effector pose measured by a motion-tracking system. A four-block H∞ design scheme with adjusted weighting filters ensures good trajectory tracking and disturbance rejection properties for the CDPR system, which is a nonlinear-coupled MIMO system with constrained states. The tension management algorithm generates control signals that maintain the cables under feasible tensions. The paper makes an extensive review of the available methods and presents an extension of one of them. The presented methodologies are evaluated by simulations and experimentally on a redundant 6-DoF INCA 6D CDPR with eight cables, equipped with a motion-tracking system.
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
Can eye-tracking technology improve situational awareness in paramedic clinical education?
Williams, Brett; Quested, Andrew; Cooper, Simon
2013-01-01
Human factors play a significant part in clinical error. Situational awareness (SA) means being aware of one's surroundings, comprehending the present situation, and being able to predict outcomes. It is a key human skill that, when properly applied, is associated with reducing medical error: eye-tracking technology can be used to provide an objective and qualitative measure of the initial perception component of SA. Feedback from eye-tracking technology can be used to improve the understanding and teaching of SA in clinical contexts, and consequently, has potential for reducing clinician error and the concomitant adverse events.
Human supervision and microprocessor control of an optical tracking system
NASA Technical Reports Server (NTRS)
Bigley, W. J.; Vandenberg, J. D.
1981-01-01
Gunners using small calibre anti-aircraft systems have not been able to track high-speed air targets effectively. Substantial improvement in the accuracy of surface fire against attacking aircraft has been realized through the design of a director-type weapon control system. This system concept frees the gunner to exercise a supervisory/monitoring role while the computer takes over continuous target tracking. This change capitalizes on a key consideration of human factors engineering while increasing system accuracy. The advanced system design, which uses distributed microprocessor control, is discussed at the block diagram level and is contrasted with the previous implementation.
Human Centered Hardware Modeling and Collaboration
NASA Technical Reports Server (NTRS)
Stambolian Damon; Lawrence, Brad; Stelges, Katrine; Henderson, Gena
2013-01-01
In order to collaborate engineering designs among NASA Centers and customers, to in clude hardware and human activities from multiple remote locations, live human-centered modeling and collaboration across several sites has been successfully facilitated by Kennedy Space Center. The focus of this paper includes innovative a pproaches to engineering design analyses and training, along with research being conducted to apply new technologies for tracking, immersing, and evaluating humans as well as rocket, vehic le, component, or faci lity hardware utilizing high resolution cameras, motion tracking, ergonomic analysis, biomedical monitoring, wor k instruction integration, head-mounted displays, and other innovative human-system integration modeling, simulation, and collaboration applications.
COMPLEX MIXTURES OF CHEMICAL CARCINOGENS: PRINCIPLES OF ACTION AND HUMAN CANCER
There is strong epidemiological evidence supported by experimental animal data that complex environmental mixtures pose a risk to human health producing increases in cancer incidence. Understanding the chemical and biological properties of these mixtures leads to a clearer unde...
Preparation of a Burkholderia mallei Vaccine
2002-01-01
Glanders , caused by Burkholderia Mallei , is a significant disease for humans due to the serious nature of the infection. It is recognized that B... Mallei is an organism with tremendous infectivity that poses a significant hazard to humans exposed to aerosols containing this organism.
The Human Sciences Program and the Future.
ERIC Educational Resources Information Center
Carter, Jack L.
1982-01-01
Discusses the interdisciplinary/multidisciplinary nature of the BSCS Human Sciences Program and problems associated with the development, dissemination, and use of such curricula. Poses a series of questions related to these problems and discusses influences of single-issues pressure groups on science teaching. (JN)
Barrett, Damon
2010-03-01
This commentary addresses some of the challenges posed by the broader normative, legal and policy framework of the United Nations for the international drug control system. The 'purposes and principles' of the United Nations are presented and set against the threat based rhetoric of the drug control system and the negative consequences of that system. Some of the challenges posed by human rights law and norms to the international drug control system are also described, and the need for an impact assessment of the current system alongside alternative policy options is highlighted as a necessary consequence of these analyses. Copyright (c) 2010 Elsevier B.V. All rights reserved.
Experimental investigation of control/display augmentation effects in a compensatory tracking task
NASA Technical Reports Server (NTRS)
Garg, Sanjay; Schmidt, David K.
1988-01-01
The effects of control/display augmentation on human performance and workload have been investigated for closed-loop, continuous-tracking tasks by a real-time, man-in-the-loop simulation study. The experimental results obtained indicate that only limited improvement in actual tracking performance is obtainable through display augmentation alone; with a very high level of display augmentation, tracking error will actually deteriorate. Tracking performance improves when status information is furnished for reasonable levels of display quickening; again, very high quickening levels lead to tracking error deterioration due to the incompatibility between the status information and the quickened signal.
Batey, Michael A.; Almeida, Gilberto S.; Wilson, Ian; Dildey, Petra; Sharma, Abhishek; Blair, Helen; Hide, I. Geoff; Heidenreich, Olaf; Vormoor, Josef; Maxwell, Ross J.; Bacon, Chris M.
2014-01-01
Ewing sarcoma and osteosarcoma represent the two most common primary bone tumours in childhood and adolescence, with bone metastases being the most adverse prognostic factor. In prostate cancer, osseous metastasis poses a major clinical challenge. We developed a preclinical orthotopic model of Ewing sarcoma, reflecting the biology of the tumour-bone interactions in human disease and allowing in vivo monitoring of disease progression, and compared this with models of osteosarcoma and prostate carcinoma. Human tumour cell lines were transplanted into non-obese diabetic/severe combined immunodeficient (NSG) and Rag2−/−/γc−/− mice by intrafemoral injection. For Ewing sarcoma, minimal cell numbers (1000–5000) injected in small volumes were able to induce orthotopic tumour growth. Tumour progression was studied using positron emission tomography, computed tomography, magnetic resonance imaging and bioluminescent imaging. Tumours and their interactions with bones were examined by histology. Each tumour induced bone destruction and outgrowth of extramedullary tumour masses, together with characteristic changes in bone that were well visualised by computed tomography, which correlated with post-mortem histology. Ewing sarcoma and, to a lesser extent, osteosarcoma cells induced prominent reactive new bone formation. Osteosarcoma cells produced osteoid and mineralised “malignant” bone within the tumour mass itself. Injection of prostate carcinoma cells led to osteoclast-driven osteolytic lesions. Bioluminescent imaging of Ewing sarcoma xenografts allowed easy and rapid monitoring of tumour growth and detection of tumour dissemination to lungs, liver and bone. Magnetic resonance imaging proved useful for monitoring soft tissue tumour growth and volume. Positron emission tomography proved to be of limited use in this model. Overall, we have developed an orthotopic in vivo model for Ewing sarcoma and other primary and secondary human bone malignancies, which resemble the human disease. We have shown the utility of small animal bioimaging for tracking disease progression, making this model a useful assay for preclinical drug testing. PMID:24409320
Application of unscented Kalman filter for robust pose estimation in image-guided surgery
NASA Astrophysics Data System (ADS)
Vaccarella, Alberto; De Momi, Elena; Valenti, Marta; Ferrigno, Giancarlo; Enquobahrie, Andinet
2012-02-01
Image-guided surgery (IGS) allows clinicians to view current, intra-operative scenes superimposed on preoperative images (typically MRI or CT scans). IGS systems use localization systems to track and visualize surgical tools overlaid on top of preoperative images of the patient during surgery. The most commonly used localization systems in the Operating Rooms (OR) are optical tracking systems (OTS) due to their ease of use and cost effectiveness. However, OTS' suffer from the major drawback of line-of-sight requirements. State space approaches based on different implementations of the Kalman filter have recently been investigated in order to compensate for short line-of-sight occlusion. However, the proposed parameterizations for the rigid body orientation suffer from singularities at certain values of rotation angles. The purpose of this work is to develop a quaternion-based Unscented Kalman Filter (UKF) for robust optical tracking of both position and orientation of surgical tools in order to compensate marker occlusion issues. This paper presents preliminary results towards a Kalman-based Sensor Management Engine (SME). The engine will filter and fuse multimodal tracking streams of data. This work was motivated by our experience working in robot-based applications for keyhole neurosurgery (ROBOCAST project). The algorithm was evaluated using real data from NDI Polaris tracker. The results show that our estimation technique is able to compensate for marker occlusion with a maximum error of 2.5° for orientation and 2.36 mm for position. The proposed approach will be useful in over-crowded state-of-the-art ORs where achieving continuous visibility of all tracked objects will be difficult.
Music-Elicited Emotion Identification Using Optical Flow Analysis of Human Face
NASA Astrophysics Data System (ADS)
Kniaz, V. V.; Smirnova, Z. N.
2015-05-01
Human emotion identification from image sequences is highly demanded nowadays. The range of possible applications can vary from an automatic smile shutter function of consumer grade digital cameras to Biofied Building technologies, which enables communication between building space and residents. The highly perceptual nature of human emotions leads to the complexity of their classification and identification. The main question arises from the subjective quality of emotional classification of events that elicit human emotions. A variety of methods for formal classification of emotions were developed in musical psychology. This work is focused on identification of human emotions evoked by musical pieces using human face tracking and optical flow analysis. Facial feature tracking algorithm used for facial feature speed and position estimation is presented. Facial features were extracted from each image sequence using human face tracking with local binary patterns (LBP) features. Accurate relative speeds of facial features were estimated using optical flow analysis. Obtained relative positions and speeds were used as the output facial emotion vector. The algorithm was tested using original software and recorded image sequences. The proposed technique proves to give a robust identification of human emotions elicited by musical pieces. The estimated models could be used for human emotion identification from image sequences in such fields as emotion based musical background or mood dependent radio.
Estimating the gaze of a virtuality human.
Roberts, David J; Rae, John; Duckworth, Tobias W; Moore, Carl M; Aspin, Rob
2013-04-01
The aim of our experiment is to determine if eye-gaze can be estimated from a virtuality human: to within the accuracies that underpin social interaction; and reliably across gaze poses and camera arrangements likely in every day settings. The scene is set by explaining why Immersive Virtuality Telepresence has the potential to meet the grand challenge of faithfully communicating both the appearance and the focus of attention of a remote human participant within a shared 3D computer-supported context. Within the experiment n=22 participants rotated static 3D virtuality humans, reconstructed from surround images, until they felt most looked at. The dependent variable was absolute angular error, which was compared to that underpinning social gaze behaviour in the natural world. Independent variables were 1) relative orientations of eye, head and body of captured subject; and 2) subset of cameras used to texture the form. Analysis looked for statistical and practical significance and qualitative corroborating evidence. The analysed results tell us much about the importance and detail of the relationship between gaze pose, method of video based reconstruction, and camera arrangement. They tell us that virtuality can reproduce gaze to an accuracy useful in social interaction, but with the adopted method of Video Based Reconstruction, this is highly dependent on combination of gaze pose and camera arrangement. This suggests changes in the VBR approach in order to allow more flexible camera arrangements. The work is of interest to those wanting to support expressive meetings that are both socially and spatially situated, and particular those using or building Immersive Virtuality Telepresence to accomplish this. It is also of relevance to the use of virtuality humans in applications ranging from the study of human interactions to gaming and the crossing of the stage line in films and TV.
Kohler, Jillian Clare; Hoffmann, Julia; Mungala, Lucy
2017-01-01
Abstract The global fight against HIV/AIDS continues to pose challenges: infection rates are on the rise in many settings, stigma and discrimination remain rampant, and the global response is under increasing financial pressure. There is a high risk of losing what has been achieved so far in the fight against HIV and AIDS, but also the momentum to meet the so-called Fast Track targets for 2030. In light of these trends, it is fundamental to focus on the human rights of key populations (KPs)—especially to health, non-discrimination, access to information, and to equal and meaningful participation in political and public affairs—by placing them at the center of the global HIV response. Such rights, and the demand for more transparency, accountability, and participation (TAP), have been recognized as both a necessary social justice imperative, and as a way to build more responsive, inclusive, and sustainable health systems. This article will argue that embracing TAP as key guiding principles of the global HIV response (especially in low- and middle-income countries) could have the potential to create the conditions for KPs to have their human rights fulfilled, and to expand their participation in the decision-making processes that guide the efforts against the epidemic. It will then propose a number of avenues for further engagement between different communities of practice in terms of research, agendas, and policy and practices that could be beneficial in maximizing the impact of the global efforts to end HIV/AIDS. PMID:29302176
Monitoring the elimination of human African trypanosomiasis: Update to 2014
Priotto, Gerardo; Paone, Massimo; Diarra, Abdoulaye; Grout, Lise; Mattioli, Raffaele C.; Argaw, Daniel
2017-01-01
Background The World Health Organization (WHO) has targeted the elimination of Human African trypanosomiasis (HAT) ‘as a public health problem’ by 2020. The selected indicators of elimination should be monitored every two years, and we provide here a comprehensive update to 2014. The monitoring system is underpinned by the Atlas of HAT. Results With 3,797 reported cases in 2014, the corresponding milestone (5,000 cases) was surpassed, and the 2020 global target of ‘fewer than 2,000 reported cases per year’ seems within reach. The areas where HAT is still a public health problem (i.e. > 1 HAT reported case per 10,000 people per year) have halved in less than a decade, and in 2014 they corresponded to 350 thousand km2. The number and potential coverage of fixed health facilities offering diagnosis and treatment for HAT has expanded, and approximately 1,000 are now operating in 23 endemic countries. The observed trends are supported by sustained surveillance and improved reporting. Discussion HAT elimination appears to be on track. For gambiense HAT, still accounting for the vast majority of reported cases, progress continues unabated in a context of sustained intensity of screening activities. For rhodesiense HAT, a slow-down was observed in the last few years. Looking beyond the 2020 target, innovative tools and approaches will be increasingly needed. Coordination, through the WHO network for HAT elimination, will remain crucial to overcome the foreseeable and unforeseeable challenges that an elimination process will inevitably pose. PMID:28531222
Neurobiological mechanisms underlying the blocking effect in aversive learning.
Eippert, Falk; Gamer, Matthias; Büchel, Christian
2012-09-19
Current theories of classical conditioning assume that learning depends on the predictive relationship between events, not just on their temporal contiguity. Here we employ the classic experiment substantiating this reasoning-the blocking paradigm-in combination with functional magnetic resonance imaging (fMRI) to investigate whether human amygdala responses in aversive learning conform to these assumptions. In accordance with blocking, we demonstrate that significantly stronger behavioral and amygdala responses are evoked by conditioned stimuli that are predictive of the unconditioned stimulus than by conditioned stimuli that have received the same pairing with the unconditioned stimulus, yet have no predictive value. When studying the development of this effect, we not only observed that it was related to the strength of previous conditioned responses, but also that predictive compared with nonpredictive conditioned stimuli received more overt attention, as measured by fMRI-concurrent eye tracking, and that this went along with enhanced amygdala responses. We furthermore observed that prefrontal regions play a role in the development of the blocking effect: ventromedial prefrontal cortex (subgenual anterior cingulate) only exhibited responses when conditioned stimuli had to be established as nonpredictive for an outcome, whereas dorsolateral prefrontal cortex also showed responses when conditioned stimuli had to be established as predictive. Most importantly, dorsolateral prefrontal cortex connectivity to amygdala flexibly switched between positive and negative coupling, depending on the requirements posed by predictive relationships. Together, our findings highlight the role of predictive value in explaining amygdala responses and identify mechanisms that shape these responses in human fear conditioning.
ERIC Educational Resources Information Center
Geri, George A.; Hubbard, David C.
Two adaptive psychophysical procedures (tracking and "yes-no" staircase) for obtaining human visual contrast sensitivity functions (CSF) were evaluated. The procedures were chosen based on their proven validity and the desire to evaluate the practical effects of stimulus transients, since tracking procedures traditionally employ gradual…
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.
Hatala, Kevin G; Roach, Neil T; Ostrofsky, Kelly R; Wunderlich, Roshna E; Dingwall, Heather L; Villmoare, Brian A; Green, David J; Braun, David R; Harris, John W K; Behrensmeyer, Anna K; Richmond, Brian G
2017-11-01
Tracks can provide unique, direct records of behaviors of fossil organisms moving across their landscapes millions of years ago. While track discoveries have been rare in the human fossil record, over the last decade our team has uncovered multiple sediment surfaces within the Okote Member of the Koobi Fora Formation near Ileret, Kenya that contain large assemblages of ∼1.5 Ma fossil hominin tracks. Here, we provide detailed information on the context and nature of each of these discoveries, and we outline the specific data that are preserved on the Ileret hominin track surfaces. We analyze previously unpublished data to refine and expand upon earlier hypotheses regarding implications for hominin anatomy and social behavior. While each of the track surfaces discovered at Ileret preserves a different amount of data that must be handled in particular ways, general patterns are evident. Overall, the analyses presented here support earlier interpretations of the ∼1.5 Ma Ileret track assemblages, providing further evidence of large, human-like body sizes and possibly evidence of a group composition that could support the emergence of certain human-like patterns of social behavior. These data, used in concert with other forms of paleontological and archaeological evidence that are deposited on different temporal scales, offer unique windows through which we can broaden our understanding of the paleobiology of hominins living in East Africa at ∼1.5 Ma. Copyright © 2017 Elsevier Ltd. All rights reserved.
Liu, Xinyang; Plishker, William; Zaki, George; Kang, Sukryool; Kane, Timothy D.; Shekhar, Raj
2017-01-01
Purpose Common camera calibration methods employed in current laparoscopic augmented reality systems require the acquisition of multiple images of an entire checkerboard pattern from various poses. This lengthy procedure prevents performing laparoscope calibration in the operating room (OR). The purpose of this work was to develop a fast calibration method for electromagnetically (EM) tracked laparoscopes, such that calibration can be performed in the OR on demand. Methods We designed a mechanical tracking mount to uniquely and snugly position an EM sensor to an appropriate location on a conventional laparoscope. A tool named fCalib was developed to calibrate intrinsic camera parameters, distortion coefficients, and extrinsic parameters (transformation between the scope lens coordinate system and the EM sensor coordinate system) using a single image that shows an arbitrary portion of a special target pattern. For quick evaluation of calibration result in the OR, we integrated a tube phantom with fCalib and overlaid a virtual representation of the tube on the live video scene. Results We compared spatial target registration error between the common OpenCV method and the fCalib method in a laboratory setting. In addition, we compared the calibration re-projection error between the EM tracking-based fCalib and the optical tracking-based fCalib in a clinical setting. Our results suggested that the proposed method is comparable to the OpenCV method. However, changing the environment, e.g., inserting or removing surgical tools, would affect re-projection accuracy for the EM tracking-based approach. Computational time of the fCalib method averaged 14.0 s (range 3.5 s – 22.7 s). Conclusions We developed and validated a prototype for fast calibration and evaluation of EM tracked conventional (forward viewing) laparoscopes. The calibration method achieved acceptable accuracy and was relatively fast and easy to be performed in the OR on demand. PMID:27250853