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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"

共 6858 条记录，以下是4941-4950 订阅

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Inferring 3D body pose from silhouettes using activity manifold learning

Inferring 3D body pose from silhouettes using activity manif...

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Elgammal Chan-Su Lee Department of Computer Science Rutgers University New Brunswick NJ USA

We aim to infer 3D body pose directly from human silhouettes. Given a visual input (silhouette), the objective is to recover the intrinsic body configuration, recover the viewpoint, reconstruct the input and detect any spatial or temporal outliers. In order to recover intrinsic body configuration (pose) from the visual input (silhouette), we explicitly learn view-based representations of activity manifolds as well as learn mapping functions between such central representations and both the visual input space and the 3D body pose space. The body pose can be recovered in a closed form in two steps by projecting the visual input to the learned representations of the activity manifold, i.e., finding the point on the learned manifold representation corresponding to the visual input, followed by interpolating 3D pose.

关键词： Humans Image reconstruction Motion analysis Solid modeling Kinematics Cameras computer science Surveillance Biological system modeling Geometry

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The Wavelet Transformation for Temporal Gene Expression Analysis

The Wavelet Transformation for Temporal Gene Expression Anal...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： J.Z. Song K.M. Duan M. Surette Department of Microbiology and Infectious Diseases Health Sciences Centre University of Calgary Calgary AB Canada

A variety of high throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy for can be applied in the analysis of data sets of thousands of genes during cellular differentiation and response.

关键词： Wavelet analysis Gene expression Throughput Data mining Hidden Markov models pattern analysis Wavelet transforms Delay effects Production Biochemical analysis

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Appearance Learning by Adaptive Kalman Filters for FLIR Tracking

Appearance Learning by Adaptive Kalman Filters for FLIR Trac...

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ieee computer society conference on computer vision and pattern recognition Workshops

作者： Vijay Venkataraman Guoliang Fan Xin Fan Joseph P. Havlicek School of Electrical & Computer Engineering Oklahoma State University School of Electrical & Computer Engineering OklahomaState University School of Electrical & Computer Engineering University of Oklahoma

ISBN: (纸本)9781424439942

This paper addresses the challenging issue of target tracking and appearance learning in Forward Looking Infrared (FLIR) sequences. Tracking and appearance learning are formulated as a joint state estimation problem with two parallel inference processes. Specifically, a new adaptive Kalman filter is proposed to learn histogram-based target appearances. A particle filter is used to estimate the target position and size, where the learned appearance plays an important role. Our appearance learning algorithm is compared against two existing methods and experiments on the AMCOM FLIR dataset validate its effectiveness.

关键词： Target tracking State estimation Particle filters Inference algorithms

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The viewing graph

The viewing graph

引用

conference on computer vision and pattern recognition (cvpr)

作者： N. Levi M. Werman School of Computer Science Hebrew University of Jerusalem Jerusalem Israel

The problem we study is: given N views and a subset of the (/sub 2//sup N/) interview fundamental matrices, which of the other fundamental matrices can we compute using only the pre-computed fundamental matrices. This has applications in 3D (three-dimensional) reconstruction and when we want to reproject an area of one view on another, or to compute epipolar lines when the correspondence problem is too difficult to compute between every two views. A complete solution using linear algorithms to compute the missing fundamental matrices are given for up to six views. In many cases problems with more than six views can also be handled.

关键词： Tensile stress Cameras computer vision computer science Computational geometry Layout Three dimensional displays Equations computer society pattern recognition

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Trajectories and events

Trajectories and events

引用

conference on computer vision and pattern recognition (cvpr)

作者： S.M. Haynes R. Jain AI Laboratory Department of EECS University of Michigan Ann Arbor MI USA

A solution to the correspondence problem using constraint satisfaction is described. It uses a real-time line-fitting algorithm to detect changes in a point's motion parameters as they happen. A trajectory is hypothesized for a single point's motion. Since the event detected may be wrong, multiple trajectories are hypothesized for each point. A correspondence is drawn from the set of hypothesized trajectories. The algorithm is robust, working on noisy and non-rigid motion data, and does not use false precision.< >

关键词： Position measurement Event detection Artificial intelligence Laboratories Motion detection Robustness computer vision Geometry Stereo vision Equations

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Segmentation and grouping of object boundaries using energy minimization

Segmentation and grouping of object boundaries using energy ...

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conference on computer vision and pattern recognition (cvpr)

作者： D.A. Trytten M. Tuceryan Department of Computer Science Michigan State University East Lansing MI USA

An algorithm is described which performs curvilinear grouping of image edge elements for detecting object boundaries. The method works by generating hypotheses and selecting the best one. A neighborhood definition based on Delaunay graph is used to keep the number of generated hypotheses small. An energy minimizing curve is fit to the generated hypotheses to evaluate the grouping and locate discontinuities.< >

关键词： Image edge detection Object detection Image segmentation Minimization methods computer science Detection algorithms Image reconstruction Humans Data preprocessing Detectors

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Role of shape and kinematics in human movement analysis

Role of shape and kinematics in human movement analysis

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conference on computer vision and pattern recognition (cvpr)

作者： A. Veeraraghavan A.R. Chowdhury R. Chellappa Department of ECE University of Maryland College Park USA Department of Electrical Engineering University of California Riverside USA

Human gait and activity analysis from video is presently attracting a lot of attention in the computer vision community. In this paper we analyze the role of two of the most important cues in human motion-shape and kinematics. We present an experimental framework whereby it is possible to evaluate the relative importance of these two cues in computer vision based recognition algorithms. In the process, we propose a new gait recognition algorithm by computing the distance between two sequences of shapes that lie on a spherical manifold. In our experiments, shape is represented using Kendall's definition of shape. Kinematics is represented using a Linear Dynamical system We place particular emphasis on human gait. Our conclusions show that shape plays a role which is more significant than kinematics in current automated gait based human identification algorithms. As a natural extension we study the role of shape and kinematics in activity recognition. Our experiments indicate that we require models that contain both shape and kinematics in order to perform accurate activity classification. These conclusions also allow us to explain the relative performance of many existing methods in computer-based human activity modeling.

关键词： Kinematics Humans computer vision Motion analysis Educational institutions Biological system modeling Biometrics Algorithm design and analysis Active shape model Psychology

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Toward a scale-space aspect graph: solids of revolution

Toward a scale-space aspect graph: solids of revolution

引用

conference on computer vision and pattern recognition (cvpr)

作者： Sung-Il Pae J. Ponce Department of Computer Science and Beckman Institute University of Illinois Urbana IL USA

This paper addresses the problem of constructing the scale-space aspect graph of a solid of revolution whose surface is the zero set of a polynomial volumetric density undergoing a Gaussian diffusion process. Equations for the associated visual event surfaces are derived, and polynomial curve tracing techniques are used to delineate these surfaces. An implementation and examples are presented, and limitations as well as extensions of the proposed approach are discussed.

关键词： Polynomials Geometry Diffusion processes Cameras Gaussian processes computer science Solid modeling Object recognition Image resolution Spatial resolution

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A discriminative learning framework with pairwise constraints for video object classification

A discriminative learning framework with pairwise constraint...

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conference on computer vision and pattern recognition (cvpr)

作者： Rong Yan Jian Zhang Jie Yang A. Hauptmann School of Computer Science Carnegie Mellon University Pittsburgh PA USA

In video object classification, insufficient labeled data may at times be easily augmented with pairwise constraints on sample points, i.e, whether they are in the same class or not. In this paper, we proposed a discriminative learning approach, which incorporates pairwise constraints into a conventional margin-based learning framework. The proposed approach offers several advantages over existing approaches dealing with pairwise constraints. First, as opposed to learning distance metrics, the new approach derives its classification power by directly modeling the decision boundary. Second, most previous work handles labeled data by converting them to pairwise constraints and thus leads too much more computation. The proposed approach can handle pairwise constraints together with labeled data so that the computation is greatly reduced. The proposed approach is evaluated on a people classification task with two surveillance video datasets.

关键词： Feedback Surveillance Training data Time factors Humans computer science Streaming media Video sharing Cameras Video sequences

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recognition of handwritten phrases as applied to street name images

Recognition of handwritten phrases as applied to street name...

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conference on computer vision and pattern recognition (cvpr)

作者： G. Kim V. Govindaraju Center of Excellence for Document Analysis and Recognition State University of New York University at Buffalo Amherst NY USA

A method for recognition of street name phrases collected from mail pieces is presented in this paper. Some of the challenges posed by the problem are: (i) patron errors, (ii) non-standardized way of abbreviating names, and (iii) variable number of words in a street name image. A neural network has been designed to segment words in a phrase, a street name in this case, using distances between components and style of writing. The network learns the type of spacing (including size) that one should expect between different pairs of characters in handwritten test. Experiments show perfect word segmentation performance at about 85% of cases. Unlike conventional methods, where lexicon entries are expanded to take care of all variations of prefixes and sizes, substring matching is attempted only between the main body of a lexicon entry and the word segments of an image. Efforts to reduce computational complexity are successfully made by the sharing of character segmentation results between the segmentation and recognition phases. 83% phrase recognition accuracy is achieved on a test set.

关键词： Handwriting recognition Image recognition Image segmentation Character recognition Writing Statistics Venus Text analysis Image analysis Postal services

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