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检索条件"任意字段=2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005"

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Understanding popout through repulsion

Understanding popout through repulsion

引用

conference on computer vision and pattern recognition (cvpr)

作者： S.X. Yu J. Shi Robotics Institute Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)0769512720

Perceptual popout is defined by both feature similarity and local feature contrast. We identify these two measures with attraction and repulsion, and unify the dual processes of association by attraction and segregation by repulsion in a single grouping framework. We generalize normalized cuts to multi-way partitioning with these dual measures. We expand graph partitioning approaches to weight matrices with negative entries, and provide a theoretical basis for solution regularization in such algorithms. We show that attraction, repulsion and regularization each contributes in a unique way to popout. Their roles are demonstrated in various salience detection and visual search scenarios. This work opens up the possibilities of encoding negative correlations in constraint satisfaction problems, where solutions by simple and robust eigendecomposition become possible.

关键词： Image segmentation Brain modeling Image edge detection Filters Cognitive robotics Partitioning algorithms Encoding Robustness Feature extraction Object recognition

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Discrimination of motion based on traces in the space of probability functions over feature relations

Discrimination of motion based on traces in the space of pro...

引用

conference on computer vision and pattern recognition (cvpr)

作者： S. Sarkar I.R. Vega Computer Science and Engineering Department University of South Florida Tampa FL USA

ISBN: (纸本)0769512720

In this paper we demonstrate that it is possible to discriminate between high level motion types such as walking, jogging, or running based on just the change in the relational statistics among the detected image features, without the need for object models, perfect segmentation, or tracking. Instead of the statistics of the feature attributes themselves, we consider the distribution of the statistics of the relations among the features. We represent the observed distribution of feature relations in an image as a point in a space where the Euclidean distance is related to the Bhattacharya distance between probability functions. Different motion types sweep out different traces in this Space of Probability Functions (SoPF). We demonstrate the effectiveness of this representation on image sequences of human in motion, gathered using a digital video camera. We show that it is not only possible to distinguish between motion types but also to discriminate between persons based on the SoPF traces.

关键词： Probability Statistical distributions Legged locomotion Object detection Motion detection computer vision Image segmentation Tracking Euclidean distance Image sequences

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Automatic estimation of the projected light source direction

Automatic estimation of the projected light source direction

引用

conference on computer vision and pattern recognition (cvpr)

作者： P. Nillius J.O. Eklundh Computational Vision & Active Perception Laboaratory (CVAP) Department of Numerical Analysis and Computing Science Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)0769512720

We present a fully automatic algorithm for estimating the projected light source direction from a single image. The requirement is that there exists a segment of an occluding contour of an object with locally Lambertian surface reflectance in the image. The algorithm consists of three stages. First a heuristic algorithm picks out potential occluding contours using color and edge information. Secondly, for each contour the light source direction is estimated using a shading model. In the final stage the results from the estimations are fused together in a Bayesian network to arrive at the most likely light source direction. The probabilistic model takes into account that the contours from the first stage might not be occluding contours. Using the same framework the contours are also classified as occluding or not. Experiments test the second stage, estimating the light source direction from an occluding contour, as well as the full algorithm.

关键词： Light sources Image segmentation Geometry Lighting computer vision Bayesian methods Shape Integrated circuit modeling Laboratories Numerical analysis

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A radical approach to handwritten Chinese character recognition using active handwriting models

A radical approach to handwritten Chinese character recognit...

引用

conference on computer vision and pattern recognition (cvpr)

作者： D. Shi S.R. Gunn R.I. Damper Image Speech and Intelligent Systems (ISIS) Research Group Department of Electronics and Computer Science University of Southampton Southampton UK

ISBN: (纸本)0769512720

This paper applies active handwriting models (AHM) to handwritten Chinese character recognition. Exploiting active shape models (ASM), the AHM can capture the handwriting variation from character skeletons. The AHM has the following characteristics: principal component analysis is applied to capture variations caused by handwriting, an energy functional on the basis of chamfer distance transform is introduced as a criterion to fit the model to a target character skeleton, and the dynamic tunneling algorithm (DTA) is incorporated with gradient descent to search for shape parameters. The AHM is used within a radical approach to handwritten Chinese characters recognition, which converts the complex pattern recognition problem to recognizing a small set of primitive structures-radicals. Our initial experiments are conducted on 98 radicals covering 1400 loosely-constrained Chinese character categories written by 200 different writers. The correct matching rate is 94.2% on these 2.8/spl times/10/sup 5/ characters. Comparison with existing radical approaches shows that our method achieves superior performance.

关键词： Character recognition pattern recognition Handwriting recognition Skeleton Shape Gunn devices Shock absorbers Damping Speech Intelligent systems

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Bending invariant representations for surfaces

Bending invariant representations for surfaces

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Elad R. Kimmel Department of Computer Science Technion-Israel Institute of Technology Technion Haifa Israel

ISBN: (纸本)0769512720

Isometric surfaces share the same geometric structure also known as the first fundamental form. For example, bending of a given surface, that includes length preserving deformations without tearing or stretching the surface, are considered to be isometric. We present a method to construct a bending invariant canonical form for such surfaces. This invariant representation is an embedding of the intrinsic geodesic structure of the surface in a finite dimensional Euclidean space, in which geodesic distances are approximated by Euclidean ones. The canonical representation is constructed by first measuring the intergeodesic distances between points on the surfaces. Next, multi-dimensional scaling (MDS) techniques are applied to extract a finite dimensional flat space in which geodesic distances are represented as Euclidean ones. The geodesic distances are measured by the efficient fast marching on triangulated domains numerical algorithm. Applying this transform to various objects with similar geodesic structures (similar first fundamental form) maps isometric objects into similar canonical forms. We show a simple surface classification method based on the bending invariant canonical form.

关键词： Level measurement Face detection computer science Cities and towns computer vision Face recognition Heuristic algorithms Shape Quaternions Eigenvalues and eigenfunctions

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View-based human activity recognition by indexing and sequencing

View-based human activity recognition by indexing and sequen...

引用

conference on computer vision and pattern recognition (cvpr)

作者： J. Ben-Arie P. Pandit S. Rajaram ECE Department M C 154 University of Illinois Chicago Chicago IL USA

ISBN: (纸本)0769512720

A novel method for view-based recognition of human activity is presented. The basic idea of our method is that activities can be positively identified from a sparsely sampled sequence of few body poses acquired from videos. In our approach, an activity is represented by a set of pose and velocity vectors for the major body parts (hands, legs and torso) and stored in a set of multidimensional hash tables. We show that robust recognition of a sequence of body pose vectors can be achieved by a method of indexing and sequencing and it requires only few vectors (i.e. sampled body poses in video frames). We find that the probability of false alarm drops exponentially with the increased number of sampled body poses. We also achieve speed invariant recognition by eliminating the time factor and replacing it with sequence information. Experiments performed with videos having 8 different activities show robust recognition even for different viewing directions.

关键词： Humans Indexing Video sequences Torso Leg Robustness Legged locomotion Multidimensional systems Time factors Streaming media

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Piecewise planar segmentation for automatic scene modeling

Piecewise planar segmentation for automatic scene modeling

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conference on computer vision and pattern recognition (cvpr)

作者： A. Bartoli INRIA Rhône-Alpes Saint Ismier France

ISBN: (纸本)0769512720

In this paper, we investigate the problem of the automatic creation of 3D models of man-made environments that we represent as collections of textured planes. A typical approach is to automatically compute a sparse feature reconstruction and to manually give their plane-memberships as well as the delineation of the planes. Textures are then extracted from the images while optimizing the model, typically the disparity between marked and predicted edges. We propose a means to automatically estimate the model of the scene, in terms of the number of planes and their parameters from a point feature reconstruction. The method is based on random sampling of reconstructed points to generate plane hypotheses. Each of these is then evaluated using a measure of approximate photoconsistency while recovering the corresponding plane delineation. We then compute the maximum likelihood estimate of all scene parameters, i.e. the set of planes and reconstructed points as well as relative camera pose, with respect to actual images. The approach is validated on simulated data and real images.

关键词： Layout Image reconstruction Semiconductor device modeling Maximum likelihood estimation Cameras Computational modeling Rendering (computer graphics) Image sampling computer vision Image segmentation

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A weighted non-negative matrix factorization for local representations

A weighted non-negative matrix factorization for local repre...

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conference on computer vision and pattern recognition (cvpr)

作者： D. Guillamet M. Bressan J. Vitria Centre de Visióper Computador Department Informàtica Universitat Autònoma Barcelona Barcelona Spain

ISBN: (纸本)0769512720

The paper presents an improvement of the classical Non-negative Matrix Factorization (NMF) approach for dealing with local representations of image objects. NHF, when applied to global data representations such as faces presents a high ability to represent local features of the original data in an unsupervised way. However, when applied to local representations, NMF generates redundant basis. This work implements an improvement on the original NMF approach by incorporating prior knowledge in the form of a weight matrix extracted from the training data. A detailed mathematical description of the inclusion of this weight matrix is provided, and results demonstrating its advantages are included. Furthermore, the original NMF approach lacks a hierarchy of the elements of the estimated basis. A technique to determine an ordered set of discriminant basis is also presented. Finally, the effectiveness of the weighted approach with respect to the classical approach is experimentally compared. This is done by implementing a clustering algorithm that automatically extracts object parts from the NMF representation of an image database corresponding to newspapers.

关键词： Principal component analysis Data mining Training data computer vision pattern recognition Lighting Testing Histograms Image databases Artificial intelligence

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Gait recognition using static, activity-specific parameters

Gait recognition using static, activity-specific parameters

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conference on computer vision and pattern recognition (cvpr)

作者： A.F. Bobick A.Y. Johnson Georgia Technology GVU Center and College of Computing Atlanta GA USA Electrical and Computer Engineering Georgia Tech Atlanta GA USA

ISBN: (纸本)0769512720

A gait-recognition technique that recovers static body and stride parameters of subjects as they walk is presented. This approach is an example of an activity-specific biometric: a method of extracting identifying properties of an individual or of an individual's behavior that is applicable only when a person is performing that specific action. To evaluate our parameters, we derive an expected confusion metric (related to mutual information), as opposed to reporting a percent correct with a limited database. This metric predicts how well a given feature vector will filter identity in a large population. We test the utility of a variety of body and stride parameters recovered in different viewing conditions on a database consisting of 15 to 20 subjects walking at both an angled and frontal-parallel view with respect to the camera, both indoors and out. We also analyze motion-capture data of the subjects to discover whether confusion in the parameters is inherently a physical or a visual measurement error property.

关键词： Spatial databases Biometrics Data mining Mutual information Filters Testing Visual databases Legged locomotion Cameras Data analysis

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Semi-dense stereo correspondence with dense features

Semi-dense stereo correspondence with dense features

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conference on computer vision and pattern recognition (cvpr)

作者： O. Veksler NEC Research Institute Inc. Princeton NJ USA

ISBN: (纸本)0769512720

We present a new feature based algorithm for stereo correspondence. Most of the previous feature based methods match sparse features like edge pixels, producing only sparse disparity maps. Our algorithm detects and matches dense features between the left and right images of a stereo pair, producing a semi-dense disparity map. Our dense feature is defined with respect to both images of a stereo pair, and it is computed during the stereo matching process, not a preprocessing step. In essence, a dense feature is a connected set of pixels in the left image and a corresponding set of pixels in the right image such that the intensity edges on the boundary of these sets are stronger than their matching error (which is basically the difference in intensities between corresponding boundary pixels). Our algorithm produces accurate semi-dense disparity maps, leaving featureless regions in the scene unmatched It is robust, requires little parameter tuning, can handle brightness differences between images, and is fast (linear complexity).

关键词： Stereo vision Pixel Image edge detection Layout Correlation National electric code Robustness Brightness computer vision Application software

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