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检索条件"任意字段=2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006"

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Cyclic articulated human motion tracking by sequential ancestral simulation

Cyclic articulated human motion tracking by sequential ances...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Cheng Chang R. Ansari A. Khokhar ECE Department University of Illinois Chicago Chicago IL USA

Accurate tracking of cyclic human motion in video data helps in developing computer-aided applications such as gait analysis, visual surveillance, patient rehabilitation, etc. This paper presents a novel technique for tracking cyclic human motion based on decomposing complex cyclic motion into components and maintaining coupling between components. The decomposition reduces the dimensionality of the problem and enables a graphical modeling of the articulated human body. The coupling between components is modeled by their phase relationship and represented as directed edges in Bayesian networks and undirected edges in Markov random fields. Such coupling is maintained in tracking through ancestral simulation (AS) and Markov potentials in a sequential Monte Carlo tracking framework. We show that the approach handles severe self-occlusion and foreign body occlusion with improved accuracy and efficiency.

关键词： Humans Tracking Biological system modeling Computational modeling Motion analysis computer applications Application software Surveillance Patient rehabilitation Bayesian methods

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Restoration of curved document images through 3D shape modeling

Restoration of curved document images through 3D shape model...

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conference on computer vision and pattern recognition (cvpr)

作者： Zheng Zhang Chew Lim Tan Liying Fan School of Computing National University of Singapore Singapore

In this paper, we address the problem of discovering the 3D shape of a book surface from the shading information in a scanned document image. This shape-from-shading problem is characterized in real world environments by a proximal and a moving light source, Lambertian reflection and a non-uniform albedo distribution. By considering all these factors, we first build the practical model (consists of geometric model and optical model) to reconstruct the 3D shape of book surface. We next restore the scanned image using this shape based on two models, namely de-shading and dewarping models. Finally, we compare the OCR results on the original and restored document image. The experiments show that the geometric and photometric distortions are mostly removed and the OCR results are improved markedly.

关键词： Image restoration Shape Solid modeling Optical character recognition software Books Optical distortion Light sources Optical reflection Geometrical optics Optical variables control

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Diffeomorphic matching of distributions: a new approach for unlabelled point-sets and sub-manifolds matching

Diffeomorphic matching of distributions: a new approach for ...

引用

conference on computer vision and pattern recognition (cvpr)

作者： J. Glaunes A. Trouve L. Younes LAGA Université Paris 13 Villetaneuse France CMLA ENS Cachan Cachan France CIS Johns Hopkins University Baltimore MD USA

In the paper, we study the problem of optimal matching of two generalized functions (distributions) via a diffeomorphic transformation of the ambient space. In the particular case of discrete distributions (weighted sums of Dirac measures), we provide a new algorithm to compare two arbitrary unlabelled sets of points, and show that it behaves properly in limit of continuous distributions on sub-manifolds. As a consequence, the algorithm may apply to various matching problems, such as curve or surface matching (via a sub-sampling), or mixings of landmark and curve data. As the solution forbids high energy solutions, it is also robust towards addition of noise and the technique can be used for nonlinear projection of datasets. We present 2D and 3D experiments.

关键词： Particle measurements computer vision Clustering algorithms Computational Intelligence society Optimal matching Noise robustness Biomedical imaging Spline Interpolation Probability distribution

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Grouping dominant orientations for ill-structured road following

Grouping dominant orientations for ill-structured road follo...

引用

conference on computer vision and pattern recognition (cvpr)

作者： C. Rasmussen Department Computer & Information Sciences University of Delaware Newark DE USA

Many rural roads lack sharp, smoothly curving edges and a homogeneous surface appearance, hampering traditional vision-based road-following methods. However, they often have strong texture cues parallel to the road direction in the form of ruts and tracks left by other vehicles. In this paper, we describe an algorithm for following ill-structured roads in which dominant texture orientations computed with multi-scale Gabor wavelet filters vote for a consensus road vanishing point location. In-plane road curvature and out-of-plane undulation are estimated in each image by tracking the vanishing point indicated by a horizontal image strip as it moves up toward the putative vanishing line. Particle filtering is also used to track the vanishing point sequence induced by road curvature from image to image. Results are shown for vanishing point localization on a variety of road scenes ranging from gravel roads to dirt trails to highways.

关键词： Layout computer vision Road vehicles Gabor filters Voting Road transportation Strips Filtering Particle tracking Image edge detection

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Robust subspace clustering by combined use of kNND metric and SVD algorithm

Robust subspace clustering by combined use of kNND metric an...

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conference on computer vision and pattern recognition (cvpr)

作者： Qifa Ke T. Kanade Computer Science Department Carnegie Mellon University USA

Subspace clustering has many applications in computer vision, such as image/video segmentation and pattern classification. The major issue in subspace clustering is to obtain the most appropriate subspace from the given noisy data. Typical methods (e.g., SVD, PCA, and eigen-decomposition) use least squares techniques, and are sensitive to outliers. In this paper, we present the k-th nearest neighbor distance (kNND) metric, which, without actually clustering the data, can exploit the intrinsic data cluster structure to detect and remove influential outliers as well as small data clusters. The remaining data provide a good initial inlier data set that resides in a linear subspace whose rank (dimension) is upper-bounded. Such linear subspace constraint can then be exploited by simple algorithms, such as iterative SVD algorithm, to (1) detect the remaining outliers that violate the correlation structure enforced by the low rank subspace, and (2) reliably compute the subspace. As an example, we apply our method to extracting layers from image sequences containing dynamically moving objects.

关键词： Robustness Clustering algorithms Iterative algorithms Application software computer vision Image segmentation pattern classification Principal component analysis Least squares methods Nearest neighbor searches

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Probabilistic data association methods in visual tracking of groups

Probabilistic data association methods in visual tracking of...

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conference on computer vision and pattern recognition (cvpr)

作者： G. Gennari G.D. Hager Information Engineering University of Padova Padova Italy Computer Science Johns Hopkins University Baltimore MD USA

Data association is a fundamental problem when tracking large numbers of moving targets. Most commonly employed methods of data association such as the JPDA estimator are combinatorial and therefore do not scale well to large numbers of targets. However, in many cases large numbers of targets form natural groups which can be efficiently tracked. We describe a method for defining groups based on the position and velocity of targets. This definition introduces a natural set of merging and splitting rules that are embedded into a Kalman filtering framework for tracking multiple groups. In cases where groups of different velocities cross, a general methodology for matching measurements to groups is introduced. This algorithm is based on a modified version of the PDA estimator. It is well suited to handle a high number of measurements and extends naturally to additional grouping constraints such as color or shape.

关键词： Target tracking Merging Velocity measurement Personal digital assistants Shape measurement computer vision Data engineering computer science Kalman filters Filtering

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A Rao-Blackwellized particle filter for EigenTracking

A Rao-Blackwellized particle filter for EigenTracking

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conference on computer vision and pattern recognition (cvpr)

作者： Zia Khan T. Balch F. Dellaert College of Computing Georgia Institute of Technology USA

Subspace representations have been a popular way to model appearance in computer vision. In Jepson and Black's influential paper on EigenTracking, they were successfully applied in tracking. For noisy targets, optimization-based algorithms (including EigenTracking) often fail catastrophically after losing track. Particle filters have recently emerged as a robust method for tracking in the presence of multi-modal distributions. To use subspace representations in a particle filter, the number of samples increases exponentially as the state vector includes the subspace coefficients. We introduce an efficient method for using subspace representations in a particle filter by applying Rao-Blackwellization to integrate out the subspace coefficients in the state vector. Fewer samples are needed since part of the posterior over the state vector is analytically calculated. We use probabilistic principal component analysis to obtain analytically tractable integrals. We show experimental results in a scenario in which we track a target in clutter.

关键词： Particle filters Target tracking computer vision Principal component analysis Shape Vectors Particle measurements Robustness Particle tracking State estimation

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Visual odometry and map correlation

Visual odometry and map correlation

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Levin R. Szeliski Microsoft Research Limited UK Hebrew University of Jerusalem Israel

In this paper we study how estimates of ego-motion based on feature tracking (visual odometry) can be improved using a rough (low accuracy) map of where the observer has been. We call the process of aligning the visual ego-motion with the map locations as map correlation. Since absolute estimates of camera position are unreliable, we use stable local information such as change in orientation to perform the alignment. We also detect when the observer's path has crossed back on itself which helps improve both the visual odometry estimates and the alignment between the video and map sequences. The final alignment is computed using a graphical model whose MAP estimate is inferred using loopy belief propagation. Results are presented on a number of indoor and outdoor sequences.

关键词： Cameras Robot vision systems Global Positioning System Yield estimation Motion estimation Simultaneous localization and mapping Graphical models Belief propagation Information resources Distance measurement

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Studies on silhouette quality and gait recognition

Studies on silhouette quality and gait recognition

引用

conference on computer vision and pattern recognition (cvpr)

作者： Zongyi Liu L. Malave S. Sarkar Computer Science and Engineering University of South Florida Tampa FL USA

recognition of a person from gait has been a focus in computer vision. It is one biometric source that can be acquired at a distance. At this nascent stage of gait recognition research, the pertinent research questions are those related to understanding the limits of gait recognition and the quantitative study of the various factors effecting gait. However, performances of contemporary algorithms have been confounded by errors in the extracted silhouettes, which has been the low-level representation of choice. In this work, (i) we present to the research community a segmentation "ground truth" research resource consisting of a set of manually specified part-level silhouettes for 70 subjects from the formulated gait challenge database, under different conditions involving change in surface, shoe-type, and time; a total of about 8000 manual silhouettes. (ii) We expound an HMM eigen stance model-based silhouette reconstruction method to correct for common errors in silhouette detection arising from shadows and background subtraction. And (iii) using these "cleaned" silhouettes and the manual silhouettes we show that the effects of various factors such as surface, time, and shoe on gait recognition are not due to poor silhouette quality. In fact, the recognition performance actually drops with the use of "clean " silhouettes because of removal of correlation in the error pixel patterns.

关键词： Surface reconstruction Hidden Markov models computer vision Biometrics Databases Reconstruction algorithms Error correction Surface cleaning Footwear pattern recognition

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Programmable imaging using a digital micromirror array

Programmable imaging using a digital micromirror array

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conference on computer vision and pattern recognition (cvpr)

作者： S.K. Nayar V. Branzoi T.E. Boult Department of Computer Science Columbia University NY USA Department of Computer Science University of Colorado Colorado Springs CO USA

We introduce the notion of a programmable imaging system. Such an imaging system provides a human user or a vision system significant control over the radiometric and geometric characteristics of the system. This flexibility is achieved using a programmable array of micro-mirrors. The orientations of the mirrors of the array can be controlled with high precision over space and time. This enables the system to select and modulate rays from the light field based on the needs of the application at hand. We have implemented a programmable imaging system that uses a digital micro-mirror device (DMD), which is used in digital light processing. Although the mirrors of this device can only be positioned in one of two states, we show that our system can be used to implement a wide variety of imaging functions, including, high dynamic range imaging, feature detection, and object recognition. We conclude with a discussion on how a micro-mirror array can be used to efficiently control field of view without the use of moving parts.

关键词： Micromirrors Mirrors Humans Machine vision Radio control Control systems Radiometry Optical modulation Dynamic range computer vision

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