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Collaborative tracking of multiple targets

Collaborative tracking of multiple targets

引用

conference on computer Vision and pattern recognition (CVPR)

作者： Ting Yu Ying Wu Department of Electrical & Computer Engineering Northwestern University Evanston IL USA

Coalescence, meaning the tracker associates more than one trajectories to some targets while loses track for others, is a challenging problem for visual tracking of multiple targets, especially when similar targets move close or present occlusions. Existing approaches that are based on joint data association are confronted by the combinatorial complexity due to the concatenation of the state spaces of individual targets. This paper presents a novel collaborative approach with linear complexity to the coalescence problem. The basic idea is the collaborative inference mechanism, in which the estimate of an individual target is not only determined by its own observation and dynamics, but also through the interaction and collaboration with the estimates of its adjacent targets, which leads to a competition mechanism that enables different targets to compete for the common image observations. The theoretical foundation of the new approach is based on Markov networks. Variational analysis of this Markov network reveals a mean field approximation to the posterior density of each target, therefore provides a computationally efficient way for such a difficult inference problem. In addition, a mean field Monte Carlo (MFMC) algorithm is designed to achieve Bayesian inference by simulating the competition among a set of low dimensional particle filters. Compared with the existing solutions, the proposed new collaborative approach stands out by its effectiveness and low computational cost to the coalescence problem, as pronounced in the extensive experiments.

关键词： Collaboration Target tracking Markov random fields Trajectory State-space methods Inference mechanisms computer networks Monte Carlo methods Inference algorithms Algorithm design and analysis

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Alignment of continuous video onto 3D point clouds

Alignment of continuous video onto 3D point clouds

引用

conference on computer Vision and pattern recognition (CVPR)

作者： W. Zhao D. Nister S. Hsu Sarnoff Corporation Princeton NJ USA

We propose a general framework for aligning continuous (oblique) video onto 3D sensor data. We align a point cloud computed from the video onto the point cloud directly obtained from a 3D sensor. This is in contrast to existing techniques where the 2D images are aligned to a 3D model derived from the 3D sensor data. Using point clouds enables the alignment for scenes full of objects that are difficult to model, for example, trees. To compute 3D point clouds from video, motion stereo is used along with a state-of-the-art algorithm for camera pose estimation. Our experiments with real data demonstrate the advantages of the proposed registration algorithm for texturing models in large-scale semi-urban environments. The capability to align video before a 3D model is built from the 3D sensor data opens up new possibilities for 3D modeling. We introduce a novel modeling-through-registration approach that fuses 3D information from both the 3D sensor and the video. Initial experiments with real data illustrate the potential of the proposed approach.

关键词： Cameras Three-dimensional displays Solid modeling Layout image sensors Geometry Laser radar Stereo vision Iterative closest point algorithm computer vision

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The Symbiotic Relationship of Parts and Monolithic Face Representations in Verification

The Symbiotic Relationship of Parts and Monolithic Face Repr...

引用

ieee computer society conference on computer Vision and pattern recognition Workshops (CVPRW)

作者： S. Lucey Advanced Multimedia Processing Laboratory Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

Techniques that treat the face holistically as a vector of pixel values, which we refer to as a monolithic representation, are still widely considered state of the art for the task of face verification in literature. Recently good performance has be attained in the task of face verification, using Gaussian mixture models (GMMs), via estimating a parts (i.e. image patch) face model; where the shape (i.e. spatial) information is largely ignored. In this paper we postulate that the characteristics current algorithms employ for verifying a face using monolithic and parts representations differ and are in many ways symbiotic; lending themselves to synergetic combination and improved verification performance. Results are presented on the BANCA database that demonstrate excellent verification performance in the presence of many common real world variabilities (e.g. camera degradation, minor pose variabilities, some changes in background and lighting).

关键词： Symbiosis Probes Cameras Degradation Face recognition Face detection Laboratories Shape Spatial databases Pixel

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Algebraic solution for the visual hull

Algebraic solution for the visual hull

引用

conference on computer Vision and pattern recognition (CVPR)

作者： M. Brand Kongbin Kang D.B. Cooper Mitsubishi Electric Research Laboratories Inc. Cambridge MA USA LEMS Division of Engineering Brown University Providence RI USA

We introduce an algebraic dual-space method for reconstructing the visual hull of a three-dimensional object from occluding contours observed in 2D images. The method exploits the differential structure of the manifold rather than parallax geometry, and therefore requires no correspondences. We begin by observing that the set of 2D contour tangents determines a surface in a dual space where each point represents a tangent plane to the original surface. The primal and dual surfaces have a symmetric algebra: A point on one is orthogonal to its dual point and tangent basis on the other. Thus the primal surface can be reconstructed if the local dual tangent basis can be estimated. Typically this is impossible because the dual surface is noisy and riddled with tangent singularities due to self-crossings. We identify a directionally-indexed local tangent basis that is well-defined and estimable everywhere on the dual surface. The estimation procedure handles singularities in the dual surface and degeneracies arising from measurement noise. The resulting method has O(N) complexity for N observed contour points and gives asymptotically exact reconstructions of surfaces that are totally observable from occluding contours.

关键词： Surface reconstruction image reconstruction Shape Algebra Computational geometry Manifolds Noise measurement Multi-stage noise shaping Clouds Ray tracing

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Face recognition in the Thermal Infrared Spectrum

Face Recognition in the Thermal Infrared Spectrum

引用

ieee computer society conference on computer Vision and pattern recognition Workshops (CVPRW)

作者： P. Buddharaju I. Pavlidis I. Kakadiaris Computer Science Department University of Houston Houston TX USA

We present a two-stage face recognition method based on infrared imaging and statistical modeling. In the first stage we reduce the search space by finding highly likely candidates before arriving at a singular conclusion during the second stage. Previous work has shown that Bessel forms model accurately the marginal densities of filtered components and can be used to find likely matches but not a unique solution. We present an enhancement to this approach by applying Bessel modeling on the facial region only rather than the entire image and by pipelining a classification algorithm to produce a unique solution. The detailed steps of our method are as follows: First, the faces are separated from the background using adaptive fuzzy connectedness segmentation. Second, Gabor filtering is used as a spectral analysis tool. Third, the derivative filtered images are modeled using two-parameter Bessel forms. Fourth, high probability subjects are short-listed by applying the L^2 -norm on the Bessel models. Finally, the resulting set of highly likely matches is fed to a Bayesian classifier to find the exact match. We show experimentally that segmentation of the facial regions results in better hypothesis pruning and classification performance. We also present comparative experimental results with an eigenface approach to highlight the potential of our method.

关键词： Face recognition Infrared spectra image segmentation Gabor filters Infrared imaging Matched filters Pipeline processing Classification algorithms Filtering Spectral analysis

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Pedestrian Detection and Tracking in Far Infrared images

Pedestrian Detection and Tracking in Far Infrared Images

引用

ieee computer society conference on computer Vision and pattern recognition Workshops (CVPRW)

作者： M. Yasuno N. Yasuda M. Aoki Seikei University Japan NEC San-ei Instruments Limited Tachikawa Tokyo Japan Seikei University Musashino Tokyo Japan

In this paper describes an approach for pedestrian detection in far infrared images. The height of a camera was set up so that people's head might be photoed by the vertical central part of images. In infrared images pedestrians belong to the upper range in the grey-level. Therefore, detects the core (especially face) of a head using the P-tile method. In this approach detects the head area candidate using binarization variable threshold in the search region around core, lowering a threshold. And it makes the search area for detection body and legs. Search area makes below head area candidate. And this method tracks pedestrian after first order prediction. First order prediction uses center of gravity each region and time series.

关键词： Infrared detectors Infrared imaging Cameras Head Humans Vehicles Face detection Gravity image processing Object detection

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A novel fuzzy wavelet approach to contrast enhancement

A novel fuzzy wavelet approach to contrast enhancement

引用

International conference on Machine Learning and Cybernetics (ICMLC)

作者： Guo-Jun Liu Jian-Hua Huang Xiang-Long Tang Jia-Feng Liu Pattern Recognition Center Department of Computer Science Harbin Institute of Technology Harbin China

ISBN: (纸本)0780384032

This work presents a novel contrast enhancement approach based on wavelet transform and fuzzy logic . We first normalize the low contrast image to reduce the effects of different illuminations. Then we choose a specific wavelet transform to convert the normalized image and obtain wavelet coefficients. The low-pass coefficients are fuzzified by the linear operator, and we use both the global and local information to define and enhance the image's global contrast. We utilize nonlinear operator on high-pass coefficients to enhance the details of images. Finally, the inverse wavelet transform is applied to map the result into space domain. The experimental results demonstrate that the approach is very effective in enhancing the low contrast image.

关键词： Discrete wavelet transforms Wavelet transforms Low pass filters Continuous wavelet transforms Fuzzy logic Wavelet coefficients image processing Histograms Neodymium computer science

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Scale selection for anisotropic scale-space: application to volumetric tumor characterization

Scale selection for anisotropic scale-space: application to ...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： K. Okada D. Comaniciu A. Krishnan Siemens Corporate Research Inc. Princeton NJ USA Siemens Medical Solutions Inc. PA USA

A unified approach for treating the scale selection problem in the anisotropic scale-space is proposed. The anisotropic scale-space is a generalization of the classical isotropic Gaussian scale-space by considering the Gaussian kernel with a fully parameterized analysis scale (bandwidth) matrix. The "maximum-over-scales" and the "most-stable-over-scales" criteria are constructed by employing the "L-normalized scale-space derivatives", i.e., response-normalized derivatives in the anisotropic scale-space. This extension allows us to directly analyze the anisotropic (ellipsoidal) shape of local structures. The main conclusions are (i) the norm of the /spl gamma/- and L-normalized anisotropic scale-space derivatives with a constant /spl gamma/ =1/2 are maximized regardless of the signal's dimension iff the analysis scale matrix is equal to the signal's covariance and (ii) the most-stable-over-scales criterion with the isotropic scale-space outperforms the maximum-over-scales criterion in the presence of noise. Experiments with 1D and 2D synthetic data confirm the above findings. 3D implementations of the most-stable-over-scales methods are applied to the problem of estimating anisotropic spreads of pulmonary tumors shown in high-resolution computed-tomography (HRCT) images. Comparison of the first- and second-order methods shows the advantage of exploiting the second-order information.

关键词： Anisotropic magnetoresistance Neoplasms Bandwidth Signal analysis Biomedical imaging Kernel Shape Covariance matrix Gaussian processes image analysis

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Robust occupancy detection from stereo images

Robust occupancy detection from stereo images

引用

International conference on Intelligent Transportation

作者： B. Alefs M. Clabian H. Bischof W. Kropatsch F. Khairallah Advanced Computer Vision GmbH-ACV Vienna Austria Advanced Computer Vision GmbH-ACV Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department University of Technology Vienna Vienna Austria TRW Automotive GmbH Farmington Hills MI USA

Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occupant and the position of the occupant's head. This work presents a method for classification and occupant's head detection based on passive stereo vision. The proposed system uses depth surface analysis and scene statistics together with support vector machines for classification and selection of head candidates. Evaluation of the method shows 99% correct for classification and 98% correct for head detection, using large sets of image data, and image sequences recorded in a driving vehicle.

关键词： Robustness Magnetic heads Vehicle crash testing Sensor systems Stereo vision Layout Statistical analysis Support vector machines Support vector machine classification Vehicle detection

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Boundary Matting for View Synthesis

Boundary Matting for View Synthesis

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ieee computer society conference on computer Vision and pattern recognition Workshops (CVPRW)

作者： S.W. Hasinoff Sing Bing Kang R. Szeliski Department of Computer Science University of Toronto Toronto Canada Interactive Visual Media Group Microsoft Research Limited Redmond WA USA

In the last few years, new view synthesis has emerged as an important application of 3D stereo reconstruction. While the quality of stereo has improved, it is still imperfect, and a unique depth is typically assigned to every pixel. This is problematic at object boundaries, where the pixel colors are mixtures of foreground and background colors. Interpolating views without explicitly accounting for this effect results in objects with a "cut-out" appearance. To produce seamless view interpolation, we propose a method called boundary matting, which represents each occlusion boundary as a 3D curve. We show how this method exploits multiple views to perform fully automatic alpha matting and to simultaneously refine stereo depths at the boundaries. The key to our approach is the unifying 3D representation of occlusion boundaries estimated to sub-pixel accuracy. Starting from an initial estimate derived from stereo, we optimize the curve parameters and the foreground colors near the boundaries. Our objective function maximizes consistency with the input images, favors boundaries aligned with strong edges, and damps large perturbations of the curves. Experimental results suggest that this method enables high-quality view synthesis with reduced matting artifacts.

关键词： Stereo vision Layout Interpolation computer vision computer science Application software Stereo image processing image reconstruction Sampling methods Sprites (computer)

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