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Real-time estimation of human attention field in LWIR and color surveillance videos

Real-time estimation of human attention field in LWIR and co...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Alex Leykin Riad Hammoud Department of Computer Science Indiana University Bloomington IN USA Delphi Electronics and Safety Delphi Communications Systems Inc. IN USA

Knowing the visual attention field of a monitored subject is of great value for many applications including surveillance and marketing. This paper proposes first to track peoplepsilas bodies, and then estimates visual attention field for each human using head pose information. The proposed head pose technique aims at estimating the yaw angle only. The method is shown to operate on monocular color camera sequences and is further refined with the data from a thermal sensor. In typical monocular tracking sequences the resolution of the head is very low and parts of the head are occluded with the face often invisible to the camera. We propose a method of combining a skin color detector with the direction of motion in a probabilistic way. We show how head profile obtained from the thermal sequence can be used to further improve the result.

关键词： Humans Surveillance Videos Cameras Monitoring Thermal sensors Face detection Skin Motion detection Detectors

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Efficient scan-window based object detection using GPGPU

Efficient scan-window based object detection using GPGPU

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Li Zhang Ramakant Nevatia Institute of Robotics and Intelligent Systems University of Southern California USA

We describe an efficient design for scan-window based object detectors using a general purpose graphics hardware computing (GPGPU) framework. While the design is particularly applied to built a pedestrian detector that uses histogram of oriented gradient (HOG) features and the support vector machine (SVM) classifiers, the methodology we use is generic and can be applied to other objects, using different features and classifiers. The GPGPU paradigm is utilized for feature extraction and classification, so that the scan windows can be processed in parallel. We further propose to precompute and cache all the histograms in advance, instead of using integral images, which greatly lowers the computation cost. A multi-scale reduce strategy is employed to save expensive CPU-GPU data transfers. Experimental results show that our implementation achieves a more-than-ten-times speed up with no loss on detection rates.

关键词： Object detection Detectors Graphics Hardware Support vector machines Support vector machine classification Rendering (computer graphics) Histograms Feature extraction Intelligent robots

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Sticky vector fields, and other geometric measures on diffusion tensor images

Sticky vector fields, and other geometric measures on diffus...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Laura Astola Luc Florack Department of Mathematics and Computer Science Eindhovan University of Technology Eindhoven Netherlands

This paper is about geometric measures in diffusion tensor imaging (DTI) analysis, and it is a continuation of our previous work (L. Astola et al., 2007), where we discussed two measures for diffusion tensor (DT) image (fiber tractography) analysis. Its contribution is threefold. First, we show how the so called connectivity measure performs on a real DTI image with three different interpolation methods. Secondly, we introduce a new vector field on DTI images, that points out the locally most coherent direction for fiber tracking, and we illustrate it on bundles of tracked fibers. Thirdly, we introduce an inhomogeneity- (edge-, crossing-) detector for symmetric positive matrix valued images, including DTI images. One possible application is segmentation of diffusion tensor fields.

关键词： Tensile stress Diffusion tensor imaging Optical fiber testing Image analysis Interpolation Image edge detection Image segmentation Karhunen-Loeve transforms Anisotropic magnetoresistance Mathematics

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Extending two non-parametric transforms for FPGA based stereo matching using bayer filtered cameras

Extending two non-parametric transforms for FPGA based stere...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Kristian Ambrosch Martin Humenberger Wilfried Kubinger Andreas Steininger Austrian Research Centers Gesellschaft mit beschränkter Haftung ARC Vienna Austria University of Technology Vienna Vienna Austria

Stereo vision has become a very interesting sensing technology for robotic platforms. It offers various advantages, but the drawback is a very high algorithmic effort. Due to the aptitude of certain non-parametric techniques for field programmable gate array (FPGA) based stereo matching, these algorithms can be implemented in highly parallel design while offering adequate real-time behavior. To enable the provision of color images by the stereo sensor for object classification tasks, we propose a technique for extending the rank and the census transform for increased robustness on gray scaled Bayer patterned images. Furthermore, we analyze the extended and the original algorithmspsila behavior on image sets created in controlled environments as well as on real world images and compare their resource usage when implemented on our FPGA based stereo matching architecture.

关键词： Field programmable gate arrays Matched filters Cameras Robot vision systems Algorithm design and analysis Stereo vision Robot sensing systems Color Image sensors Robustness

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3D Spatio-Temporal face recognition using dynamic range model sequences

3D Spatio-Temporal face recognition using dynamic range mode...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Yi Sun Lijun Yin Department of Computer Science State University of New York Binghamton Binghamton NY USA

Research on 3D face recognition has been intensified in recent years. However, most research has focused on the 3D static data analysis. In this paper, we investigate the face recognition problem using dynamic 3D face model sequences. Based on our newly created 3D dynamic face database, we propose to use a spatio-temporal hidden Markov model (HMM) which incorporates 3D surface feature characterization to learn the spatial and temporal information of faces. The advantage of using 3D dynamic data for face recognition has been evaluated by comparing our approach to three conventional approaches: 2D video based temporal HMM model, conventional 2D-texture based approach (e.g., Gabor wavelet based approach), and static 3D-model-based approaches.

关键词： Face recognition Dynamic range Hidden Markov models Spatial databases Lighting Surface fitting Video sequences Sun computer science Data analysis

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New insights into the calibration of ToF-sensors

New insights into the calibration of ToF-sensors

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Marvin Lindner Andreas Kolb Thorsten Ringbeck Institute for Vision and Graphics University of Siegen Germany PMD Technologies Siegen Germany

Time-of-flight (ToF) sensors have become an alternative to conventional distance sensing techniques like laser scanners or image based stereo. ToF sensors provide full range distance information at high frame-rates and thus have a significant impact onto current research in areas like online object recognition, collision prevention or scene reconstruction. However, ToF cameras like the photonic mixer device (PMD) still exhibit a number of challenges regarding static and dynamic effects, e.g. systematic distance errors and motion artefacts, respectively. Sensor calibration techniques reducing static system errors have been proposed and show promising results. However, current calibration techniques in general need a large set of reference data in order to determine the corresponding parameters for the calibration model. This paper introduces a new calibration approach which combines different demodulation techniques for the ToF- camera 's reference signal. Examples show, that the resulting combined demodulation technique yields improved distance values based on only two required reference data sets.

关键词： Calibration

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Likelihood ratio in a SVM framework: Fusing linear and non-linear face classifiers

Likelihood ratio in a SVM framework: Fusing linear and non-l...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Mayank Vatsa Richa Singh Arun Ross Afzel Noore Lane Department of Computer Science and Electrical Engineering West Virginia University USA

The performance of score-level fusion algorithms is often affected by conflicting decisions generated by the constituent matchers/classifiers. This paper describes a fusion algorithm that incorporates the likelihood ratio test statistic in a support vector machine (SVM) framework in order to classify match scores originating from multiple matchers. The proposed approach also takes into account the precision and uncertainties of individual matchers. The resulting fusion algorithm is used to mitigate the effect of covariate factors in face recognition by combining the match scores of linear appearance-based face recognition algorithms with their non-linear counterparts. Experimental results on a heterogeneous face database of 910 subjects suggest that the proposed fusion algorithm can significantly improve the verification performance of a face recognition system. Thus, the contribution of this work is two-fold: (a) the design of a novel fusion technique that incorporates the likelihood ratio test-statistic in a SVM fusion framework; and (b) the application of the technique to face recognition in order to mitigate the effect of covariate factors.

关键词： Support vector machines Support vector machine classification Face recognition Testing Independent component analysis Statistical analysis Principal component analysis Kernel Fusion power generation Uncertainty

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Active sampling via tracking

Active sampling via tracking

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Peter M. Roth Horst Bischof Institute for Computer Graphics and Vision Graz University of Technology Austria

To learn an object detector labeled training data is required. Since unlabeled training data is often given as an image sequence we propose a tracking-based approach to minimize the manual effort when learning an object detector. The main idea is to apply a tracker within an active on-line learning framework for selecting and labeling unlabeled samples. For that purpose the current classifier is evaluated on a test image and the obtained detection result is verified by the tracker. In this way the most valuable samples can be estimated and used for updating the classifier. Thus, the number of needed samples can be reduced and an incrementally better detector is obtained. To enable efficient learning (i.e., to have real-time performance) and to assure robust tracking results, we apply on-line boosting for both, learning and tracking. If the tracker can be initialized automatically no user interaction is needed and we have an autonomous learning/labeling system. In the experiments the approach is evaluated in detail for learning a face detector. In addition, to show the generality, also results for completely different objects are presented.

关键词： Sampling methods Detectors Object detection Training data Labeling Face detection Image sampling Image sequences Testing Robustness

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Autonomous navigation and mapping using monocular low-resolution grayscale vision

Autonomous navigation and mapping using monocular low-resolu...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Vidya N. Murali Stanley T. Birchfield Electrical and Computer Engineering Department Clemson University Clemson SC USA

An algorithm is proposed to answer the challenges of autonomous corridor navigation and mapping by a mobile robot equipped with a single forward-facing camera. Using a combination of corridor ceiling lights, visual homing, and entropy, the robot is able to perform straight line navigation down the center of an unknown corridor. Turning at the end of a corridor is accomplished using Jeffrey divergence and time-to-collision, while deflection from dead ends and blank walls uses a scalar entropy measure of the entire image. When combined, these metrics allow the robot to navigate in both textured and untextured environments. The robot can autonomously explore an unknown indoor environment, recovering from difficult situations like corners, blank walls, and initial heading toward a wall. While exploring, the algorithm constructs a Voronoi-based topo-geometric map with nodes representing distinctive places like doors, water fountains, and other corridors. Because the algorithm is based entirely upon low-resolution (32 times 24) grayscale images, processing occurs at over 1000 frames per second.

关键词： Navigation Gray-scale Cameras Entropy computer vision Robot vision systems Indoor environments Humans Turning Sonar

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Detecting mirror-symmetry of a volumetric shape from its single 2D image

Detecting mirror-symmetry of a volumetric shape from its sin...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Tadamasa Sawada Zygmunt Pizlo Department of Psychological Sciences Purdue University Calumet West Lafayette IN USA

We present a new computational model for verifying whether a 3D shape is mirror-symmetric based on its single 2D image. First, a psychophysical experiment which tested human performance in detection of 3D symmetry is described. These psychophysical results led to the formulation of a new algorithm for symmetry detection. The algorithm first recovers the 3D shape using a priori constraints (symmetry, planarity of contours and 3D compactness) and then evaluates the degree of symmetry of the 3D shape. Reliable discrimination by the algorithm between symmetric and asymmetric 3D shapes involves two measures: similarity of the two halves of a 3D shape and compactness of the 3D shape. Performance of this algorithm is highly correlated with that of the subjects. We conclude that this algorithm is a plausible model of the mechanisms used by the human visual system.

关键词： Shape measurement Image segmentation Humans Psychology Computational modeling Mirrors Semiconductor device modeling Visual system computer vision Testing

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