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检索条件"任意字段=Proceedings - IEEE Computer Society Conference on Pattern Recognition and Image Processing."

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Reconstruction of 3D figure motion from 2D correspondences

Reconstruction of 3D figure motion from 2D correspondences

引用

conference on computer Vision and pattern recognition (CVPR)

作者： D.E. DiFranco Tat-Jen Cham J.M. Rehg Department of EECS MIT Cambridge MA USA School of Computer Engineering Nanyang Technological University Singapore Singapore College of Computing Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)0769512720

We present a method for computing the 3D motion of articulated models from 2D correspondences. An iterative batch algorithm is proposed which estimates the maximum a posteriori trajectory based on 2D measurements subject to a number of constraints. These include (i) kinematic constraints based on a 3D kinematic model, (ii) joint angle limits, (iii) dynamic smoothing, and (iv) 3D key frames which can be specified by the user. The framework handles any variation in the number of constraints as well as partial or missing data. This method is shown to obtain favorable reconstruction results on a number of complex human motion sequences.

关键词： image reconstruction Kinematics Humans Tracking Motion pictures image sequences State-space methods Cameras Educational institutions Iterative algorithms

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Generalized dynamic programming approaches for object detection: detecting spine boundaries and vertebra endplates

Generalized dynamic programming approaches for object detect...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： Guo-Qing Wei JianZhong Qian H. Schramm Imaging Department Siemens Corporate Research Inc. Princeton NJ USA Medical Solutions Siemens AG Erlangen Germany

ISBN: (纸本)0769512720

Object detection employing high-level knowledge is a challenging problem in image analysis. The authors propose a dynamic programming approach to address some related issues in this aspect. In particular, we propose to fuse the detection of two curves to form a dual dynamic programming procedure so that spatial relationships between the two curves can be enforced. In another pursuit of applying object level knowledge, we propose to introduce local backward tracing to the forward propagation step in dynamic programming, so that global constraints, containing even unknown parameters, can be imposed in a progressive manner. These approaches are explained in the context of spine landmark detection. Experimental results are presented to show the efficiency of the proposed methods. The methods are extendable to other application domains.

关键词： Object detection Dynamic programming Active contours image analysis Shape Anatomy Educational institutions Fuses Application software computer vision

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A Bayesian approach to digital matting

A Bayesian approach to digital matting

引用

conference on computer Vision and pattern recognition (CVPR)

作者： Yung-Yu Chuang B. Curless D.H. Salesin R. Szeliski Department of Computer Science and Engineering University of Washington Seattle WA USA Microsoft Research Limited Redmond WA USA

ISBN: (纸本)0769512720

This paper proposes a new Bayesian framework for solving the matting problem, i.e. extracting a foreground element from a background image by estimating an opacity for each pixel of the foreground element. Our approach models both the foreground and background color distributions with spatially-varying sets of Gaussians, and assumes a fractional blending of the foreground and background colors to produce the final output. It then uses a maximum-likelihood criterion to estimate the optimal opacity, foreground and background simultaneously. In addition to providing a principled approach to the matting problem, our algorithm effectively handles objects with intricate boundaries, such as hair strands and fur, and provides an improvement over existing techniques for these difficult cases.

关键词： Bayesian methods Pixel Hair Production computer science Gaussian distribution Maximum likelihood estimation Layout Art Humans

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Using robust methods for automatic extraction of buildings

Using robust methods for automatic extraction of buildings

引用

conference on computer Vision and pattern recognition (CVPR)

作者： C. Vestri F. Devernay Research and Development ISTAR Sophia-Antipolis France INRIA Sophia-Antipolis France

ISBN: (纸本)0769512720

We present a system for modeling buildings from a single correlation-based digital elevation model (DEM). The model is constructed in two stages. The first stage segments the DEM into planar surface patches that describe the building. The second stage generates the final polygonal model of the building using weak geometric constraints. We use robust estimation methods at different stages of our modeling process to develop an efficient and noise-insensitive modeling system. The proposed system is fully automatic and does not use any a priori information about the shape of the buildings. We present results on isolated buildings and on a large area of the city of Berlin.

关键词： Buildings Digital elevation models Solid modeling Shape image reconstruction Wireless networks Research and development Noise robustness Noise shaping Cities and towns

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Segmentation for robust tracking in the presence of severe occlusion

Segmentation for robust tracking in the presence of severe o...

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conference on computer Vision and pattern recognition (CVPR)

作者： C. Gentile O. Camps M. Sznaier National Institute for Standards and Technology Gaithersburg MD USA Department of Electrical Engineering Pennsylvania State University University Park PA USA

ISBN: (纸本)0769512720

Tracking an object in a sequence of images can fail due to partial occlusion or clutter Robustness can be increased by tracking a set of "parts", provided that a suitable set can be identified. In this paper we propose a novel segmentation, specifically designed to improve robustness against occlusion in the context of tracking. The main result shows that tracking the parts resulting from this segmentation outperforms both tracking parts obtained through traditional segmentations, and tracking the entire target. Additional results include a statistical analysis of the correlation between features of a part and tracking error, and identifying a cost function highly correlated with the tracking error.

关键词： Robustness Target tracking Cost function image segmentation Statistical analysis Pixel Prototypes NIST Clustering algorithms Voting

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Using occlusions to aid position estimation for visual motion capture

Using occlusions to aid position estimation for visual motio...

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conference on computer Vision and pattern recognition (CVPR)

作者： M. Ringer T. Drummond L. Lasenby Engineering Department University of Cambridge Cambridge UK

ISBN: (纸本)0769512720

A new method for estimating the pose of a person in a marker-based visual motion capture system is presented. In such systems, certain markers are not detected at each time frame due to occlusion by the subject. It is proposed to estimate the person's pose subject to the constraint that non-detected markers remain occluded and that detected markers remain visible. In this paper, the complete posterior PDF for the person's pose is developed using the constraints mentioned above, as is a least squares solution for determining its maximum. It is shown that the new technique is able to correctly estimate a variety of poses in which many marker occlusions occur and in which typical motion capture systems fail.

关键词： Motion estimation State estimation Cameras image edge detection Motion detection Motion measurement Position measurement Least squares methods Video sequences Feature extraction

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A linear iterative method for auto-calibration using the DAC equation

A linear iterative method for auto-calibration using the DAC...

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conference on computer Vision and pattern recognition (CVPR)

作者： Yongduek Seo A. Heyden R. Cipolla IIP Laboratory POSTECH South Korea MIG Lund University Sweden SVR Laboratory University of Cambridge UK

ISBN: (纸本)0769512720

In this paper, an iterative algorithm for auto-calibration is presented. The proposed algorithm switches between linearly estimating the dual of the absolute conic and the intrinsic parameters, while also incorporating the rank-3 constraint on the intrinsic parameters. The most important property of the algorithm is that it is completely general in the sense that any type of constraint on the intrinsic parameters might be used. The proposed algorithm locates in-between of a non-linear optimization and initial linear computation, and provides robust and sufficiently accurate initial values for a bundle adjustment routine. The performance of the algorithm is shown for both simulated and real data, especially in the important case of natural (zero skew and unit aspect ratio) cameras.

关键词： Iterative methods Equations image reconstruction Iterative algorithms Cameras Calibration Switches Robustness Computational modeling H infinity control

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Parametric representations for nonlinear modeling of visual data

Parametric representations for nonlinear modeling of visual ...

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conference on computer Vision and pattern recognition (CVPR)

作者： Ying Zhu D. Comaniciu V. Ramesh S. Schwartz Electrical Engineering Princeton University Princeton NJ USA Imaging & Visualization Department Siemens Corporate Research Inc. Princeton NJ USA

ISBN: (纸本)0769512720

Accurate characterization of data distribution is of significant importance for vision problems. In many situations, multivariate visual data often spread into a nonlinear manifold in the high-dimensional space, which makes traditional linear modeling techniques ineffective. This paper proposes a generic nonlinear modeling scheme based on parametric data representations. We build a compact representation for the visual data using a set of parameterized basis (wavelet) functions, where the parameters are randomized to characterize the nonlinear structure of the data distribution. Meanwhile, a new progressive density approximation scheme is proposed to obtain an accurate estimate of the probability density, which imposes discrimination power on the model. Both synthetic and real image data are used to demonstrate the strength of our modeling scheme.

关键词： Principal component analysis Parametric statistics Data visualization Scattering Linearity Data engineering Manifolds pattern recognition Time measurement Parameter estimation

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A nonparametric statistical comparison of principal component and linear discriminant subspaces for face recognition

A nonparametric statistical comparison of principal componen...

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conference on computer Vision and pattern recognition (CVPR)

作者： J.R. Beveridge K. She B.A. Draper G.H. Givens Computer Science Department Colorado State University Fort Collins CO USA Statistics Department Colorado State University Fort Collins CO USA

ISBN: (纸本)0769512720

The FERET evaluation compared recognition rates for different semi-automated and automated face recognition algorithms. We extend FERET by considering when differences in recognition rates are statistically distinguishable subject to changes in test imagery. Nearest Neighbor classifiers using principal component and linear discriminant subspaces are compared using different choices of distance metric. Probability distributions for algorithm recognition rates and pairwise differences in recognition rates are determined using a permutation methodology. The principal component subspace with Mahalanobis distance is the best combination; using L2 is second best. Choice of distance measure for the linear discriminant subspace matters little, and performance is always worse than the principal components classifier using either Mahalanobis or L1 distance. We make the source code for the algorithms, scoring procedures and Monte Carlo study available in the hopes others will extend this comparison to newer algorithms.

关键词： Nearest neighbor searches Probes Face recognition Monte Carlo methods image recognition computer science Probability distribution Automatic testing Protocols Statistics

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Texture based classification and segmentation using the Laguerre-Gauss transform

Texture based classification and segmentation using the Lagu...

引用

International Symposium on image and Signal processing.and Analysis

作者： M. Carli A. Neri S. Hatipoglu S.K. Mitra Electrical Engineering Department University of Roma TRE Italy Electrical and Computer Engineering Department University of California Santa Barbara USA

ISBN: (纸本)9539676940

In this paper, we introduce a new tool for the image segmentation problem. For this purpose, we have developed a texture based segmentation and classification strategy based on a representation of the image components by a family of circular harmonic functions (CHF) defining the Laguerre-Gauss transform (LGT). LGT is the polar counterpart of the Hermite transform. By utilizing the outputs of CHF operators at different scales, we use a multiscale segmentation and investigate the performance of CHF texture features.

关键词： image segmentation Gaussian processes Feature extraction Wavelet transforms Testing Spatial databases pattern matching Classification algorithms pattern recognition Polynomials

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