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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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Homotopy-based computation of defocus blur and affine transform

Homotopy-based computation of defocus blur and affine transf...

引用

conference on computer vision and pattern recognition (cvpr)

作者： F. Deschenes D. Ziou Département de mathématiques et dinformatique Université de Sherbrook Canada

This paper presents a homotopy-based algorithm for simultaneous recovery of defocus blur and the affine transformation between two images of the same scene. One of the images (and its partial derivatives) is expressed as a function of the second image, partial derivatives of the two images, blur difference, affine parameters and a continuous parameter derived from homotopy methods. All of these unknowns can thus be directly computed by resolving a system of equations. The proposed algorithm is tested using synthetic and real images. The results confirm that dense and accurate estimation can be obtained.

关键词： Equations Radiometry Cameras Layout Brightness Testing Image matching Application software computer vision Image motion analysis

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Motion from 3D line correspondences: linear and nonlinear solutions

Motion from 3D line correspondences: linear and nonlinear so...

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Bartoli R.I. Hartley F. Kahl INRIA Rhône-Alpes France Australian National University Australia Lund University Sweden

We address the problem of aligning two reconstructions of lines and cameras in projective, affine, metric or Euclidean space. We propose several 3D (three-dimensional) and image-related linear algorithms. The result can be used to initialize the nonlinear minimization of several proposed error functions, as well as the maximum likelihood estimator that we derive. We evaluate and compare our algorithms to existing ones using simulated and real data.

关键词： Image reconstruction Cameras Motion estimation Extraterrestrial measurements Maximum likelihood estimation computer vision Layout computer errors Computational modeling Calibration

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Hybrid evolutionary ridge regression approach for high-accurate corner extraction

Hybrid evolutionary ridge regression approach for high-accur...

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Olague B. Hernandez E. Dunn Applied Physics Division CICESE Ensenada Baja California Mexico

Corner measurement is of main concern within the following tasks: camera calibration, image matching, object tracking, recognition and reconstruction. This paper presents a hybrid evolutionary ridge regression approach for the problem of corner modeling. We search model parameters characterizing L-corner models by means of fitting the model to the image data. As the model fitting relies on an initial parameter estimation, we use a global approach to find the global minimum. Experimental results applied to an L-corner using several levels of noise show the advantages and disadvantages of our evolutionary algorithm compared to down-hill simplex and simulated annealing.

关键词： computer vision Parametric statistics Parameter estimation Feature extraction computer science Physics Cameras Calibration Image matching Image recognition

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A sparse texture representation using affine-invariant regions

A sparse texture representation using affine-invariant regio...

引用

conference on computer vision and pattern recognition (cvpr)

作者： S. Lazebnik C. Schmid J. Ponce Beckman Institute University of Illinois Urbana-Champaign USA INRIA Rhône-Alpes Montbonnot Saint Martin France

This paper introduces a texture representation suitable for recognizing images of textured surfaces under a wide range of transformations, including viewpoint changes and nonrigid deformations. At the feature extraction stage, a sparse set of affine-invariant local patches is extracted from the image. This spatial selection process permits the computation of characteristic scale and neighborhood shape for every texture element. The proposed texture representation is evaluated in retrieval and classification tasks using the entire Brodatz database and a collection of photographs of textured surfaces taken from different viewpoints.

关键词： Shape Surface texture Image databases Spatial databases computer vision Detectors Image recognition Feature extraction Information retrieval Cameras

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On region merging: the statistical soundness of fast sorting, with applications

On region merging: the statistical soundness of fast sorting...

引用

conference on computer vision and pattern recognition (cvpr)

作者： F. Nielsen R. Nock Sony CS Laboratories FRL Shinagawa Tokyo Japan DSI-Universite Antilles-Guyane Schoelcher France

This work explores a statistical basis for a process often described in computer vision: image segmentation by region merging following a particular order in the choice of regions. We exhibit a particular blend of algorithmics and statistics whose error is, as we formally show, close to the best possible. This approach can be approximated in a very fast segmentation algorithm for processing images described using most common numerical feature spaces. Simple modifications of the algorithm allow us to cope with occlusions and/or hard noise levels. Experiments on grey-level and color images, obtained with a short C-code, display the quality of the segmentations obtained.

关键词： Merging Sorting Image segmentation Application software computer vision Error analysis computer errors Noise level Color Displays

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Degeneracies, dependencies and their implications in multi-body and multi-sequence factorizations

Degeneracies, dependencies and their implications in multi-b...

引用

conference on computer vision and pattern recognition (cvpr)

作者： L. Zelnik-Manor M. Irani Department of Computer Science and Applied Math Weizmann Institute of Science Rehovot Israel

The body of work on multi-body factorization separates between objects whose motions are independent. In this work we show that in many cases objects moving with different 3D motions will be captured as a single object using these approaches. We analyze what causes these degeneracies between objects and suggest an approach for overcoming some of them. We further show that in the case of multiple sequences linear dependencies can supply information for temporal synchronization of sequences and for spatial matching of points across sequences.

关键词： Layout Character generation Cameras Shape Bismuth computer science Subspace constraints Video sequences Stacking

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Automated multi-camera planar tracking correspondence modeling

Automated multi-camera planar tracking correspondence modeli...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Stauffer C Kinh Tieu Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA

ISBN: (纸本)0769519008

This paper introduces a method for robustly estimating a planar tracking correspondence model (TCM) for a large camera network directly from tracking data and for employing said model to reliably track objects through multiple cameras. By exploiting the unique characteristics of tracking data, our method can reliably estimate a planar TCM in large environments covered by many cameras. It is robust to scenes with multiple simultaneously moving objects and limited visual overlap between the cameras. Our method introduces the capability of automatic calibration of large camera networks in which the topology of camera overlap is unknown and in which all cameras do not necessarily overlap. Quantitative results are shown for a five camera network in which the topology is not specified.

关键词： Layout Robustness Smart cameras Network topology Artificial intelligence Laboratories Calibration Airports computer society computer vision

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Object recognition based on photometric alignment using RANSAC

Object recognition based on photometric alignment using RANS...

引用

conference on computer vision and pattern recognition (cvpr)

作者： T. Okabe Y. Sato Institute of Industrial Science University of Tokyo Meguro Tokyo Japan

For object recognition under varying illumination conditions, we propose a method based on photometric alignment. The photometric alignment is known as a technique that models both diffuse reflection components and attached shadows under a distant point light source by using three basis images. However, in order to reliably reproduce these components in a test image, we have to take into account outliers such as specular reflection components and shadows in the test image. Accordingly, our proposed method utilizes Random Sample Consensus (RANSAC), which has been used successfully for estimating basis images. In the present study, we have conducted experiments using the Yale Face Database B and confirmed that a combination of the photometric alignment and RANSAC provides a simple but effective method for object recognition under varying illumination conditions.

关键词： Object recognition Photometry Optical reflection Lighting Testing Light sources Robustness computer vision Image recognition Stereo vision

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Curvature correction of the Hamilton-Jacobi skeleton

Curvature correction of the Hamilton-Jacobi skeleton

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Torsello E.R. Hancock Department of Computer science University of York York UK

The Hamilton-Jacobi approach has proved to be a powerful and elegant method for extracting the skeleton of a shape. The approach is based on the fact that the inward evolving boundary flux is conservative everywhere except at skeletal points. Nonetheless this method appears to overlook the fact that the linear density of the evolving boundary front is not constant where the front is curved. In this paper we present an analysis, which takes into account variations of density due to boundary curvature. This yields a skeletonization algorithm that is both better localized and less susceptible to boundary noise than the Hamilton-Jacobi method.

关键词： Skeleton Equations Algorithm design and analysis Shape control Noise shaping Image analysis Geometry Biometrics Iterative algorithms Skin

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Video segmentation based on graphical models

Video segmentation based on graphical models

引用

conference on computer vision and pattern recognition (cvpr)

作者： Yang Wang Tele Tan Kia-Fock Loe Institute for Infocomm Research Singapore Department of Computer Science National University of Singapore Singapore

ISBN: (纸本)0769519008

This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notions of distance transformation and Markov random field are used to express spatiotemporal constraints. Given consecutive frames, an optimization method is proposed to maximize the conditional probability density of the three fields in an iterative way. Experimental results show that the approach is robust and generates spatiotemporally coherent segmentation results.

关键词： Graphical models Bayesian methods Markov random fields Robustness Layout Video sequences Video compression Motion estimation Merging Image segmentation

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