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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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Kernel principal angles for classification machines with applications to image sequence interpretation

Kernel principal angles for classification machines with app...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： L. Wof A. Shashua Sch. of Comput. Sci. & Eng. Hebrew Univ. of Jerusalem Israel School of Computer Science and Engineering Hebrew University of Jerusalem Jerusalem Israel

We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A, B) defined over pairs of matrices A, B based on the concept of principal angles between two linear subspaces. We show that the principal angles can be recovered using only inner-products between pairs of column vectors of the input matrices thereby allowing the original column vectors of A, B to be mapped onto arbitrarily high-dimensional feature spaces. We apply this technique to inference over image sequences applications of face recognition and irregular motion trajectory detection.

关键词： Kernel image sequences Vectors Face detection Video sequences Engines Application software computer science Face recognition Motion detection

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A sparse texture representation using affine-invariant regions

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

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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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A critical configuration for reconstruction from rectilinear motion

A critical configuration for reconstruction from rectilinear...

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conference on computer Vision and pattern recognition (CVPR)

作者： R. Hartley F. Kahl RSISE Australian National University Australia Centre for Mathematical Sciences Lund University Sweden

This paper investigates critical configurations for projective reconstruction from multiple images taken by a camera moving in a straight line. Projective reconstruction refers to a determination of the 3D (three-dimensional) geometrical configuration of a set of 3D points and cameras, given only correspondences between points in the images. A configuration of points and cameras is critical if it cannot be determined uniquely (up to a projective transform) from the image coordinates of the points. It is shown that a configuration consisting of any number of cameras lying on a straight line, and any number of points lying on a twisted cubic constitutes a critical configuration. An alternative configuration consisting of a set of points and cameras all lying on a rational quartic curve exists.

关键词： Cameras image reconstruction computer society computer vision pattern recognition

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Homotopy-based computation of defocus blur and affine transform

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

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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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Independent component analysis in a facial local residue space

Independent component analysis in a facial local residue spa...

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conference on computer Vision and pattern recognition (CVPR)

作者： Tae-Kyun Kim Hyunwoo Kim Wonjun Hwang Seok-Cheol Kee J. Kittler Centre for Vision Speech and Signal Processing University of Surrey UK Human Computer Interaction Laboratory Samsung Advanced Institute of Technology South Korea

In this paper, we propose an ICA (Independent Component Analysis) based face recognition algorithm, which is robust to illumination and pose variation. Generally, it is well known that the first few eigenfaces represent illumination variation rather than identity. Most PCA (Principal Component Analysis)-based methods have overcome illumination variation by discarding the projection to a few leading eigenfaces. The space spanned after removing a few leading eigenfaces is called the "residual face space". We found that ICA in the residual face space provides more efficient encoding in terms of redundancy reduction and robustness to pose variation as well as illumination variation, owing to its ability to represent non-Gaussian statistics. Moreover, a face image is separated into several facial components, local spaces, and each local space is represented by the ICA bases (independent components) of its corresponding residual space. The statistical models of face images in local spaces are relatively simple and facilitate classification by a linear encoding. Various experimental results show that the accuracy of face recognition is significantly improved by the proposed method under large illumination and pose variations.

关键词： Independent component analysis Principal component analysis Face recognition Lighting Statistics image databases Face detection Space technology Speech analysis Signal processing.algorithms

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Switching observation models for contour tracking in clutter

Switching observation models for contour tracking in clutter

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conference on computer Vision and pattern recognition (CVPR)

作者： Ying Wu Gang Hua Ting Yu Department of Electrical & Computer Engineering Northwestern University Evanston IL USA

ISBN: (纸本)0769519008

We propose a generative model approach to contour tracking against nonstationary clutter and to coping with occlusions by explicit modelling and inferring. The proposed dynamic Bayesian networks consist of multiple hidden processes, which model the target, the clutter and the occlusions. The image observation models, which depict the generation of the image features, are conditioned on all the hidden processes. Based on this framework, the tracker can automatically switch among different observation models according to the hidden states of the clutter and occlusions. In addition, the inference of these hidden states provides self-evaluations for the tracker. The tracking and inference are implemented based on sequence Monte Carlo techniques. The effectiveness of the proposed approach to robust tracking and inferring nonstationary clutter and occlusion is demonstrated for a variety of image sequences.

关键词： Clutter Target tracking Interference Bayesian methods image generation Switches Robustness Gaussian processes Monte Carlo methods image sequences

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Object recognition based on photometric alignment using RANSAC

Object recognition based on photometric alignment using RANS...

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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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Estimating 3D hand pose from a cluttered image

Estimating 3D hand pose from a cluttered image

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conference on computer Vision and pattern recognition (CVPR)

作者： V. Athitsos S. Sclaroff Computer Science Department Boston University Boston MA USA

A method is proposed that can generate a ranked list of plausible three-dimensional hand configurations that best match an input image. Hand pose estimation is formulated as an image database indexing problem, where the closest matches for an input hand image are retrieved from a large database of synthetic hand images. In contrast to previous approaches, the system can function in the presence of clutter, thanks to two novel clutter-tolerant indexing methods. First, a computationally efficient approximation of the image-to-model chamfer distance is obtained by embedding binary edge images into a high-dimensional Euclidean space. Second, a general-purpose, probabilistic line matching method identifies those line segment correspondences between model and input images that are the least likely to have occurred by chance. The performance of this clutter tolerant approach is demonstrated in quantitative experiments with hundreds of real hand images.

关键词： image databases Indexing Impedance matching image retrieval image segmentation Information retrieval computer vision computer science Embedded computing Humans

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Constructing 3D city models by merging ground-based and airborne views

Constructing 3D city models by merging ground-based and airb...

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conference on computer Vision and pattern recognition (CVPR)

作者： C. Frueh A. Zakhor Video and Image Processing Laboratory University of California Berkeley USA

In this paper, we present a fast approach to automated generation of textured 3D city models with both high details at ground level, and complete coverage for bird's-eye view. A close-range facade model is acquired at the ground level by driving a vehicle equipped with laser scanners and a digital camera under normal traffic conditions on public roads; a far-range Digital Surface Map (DSM), containing complementary roof and terrain shape, is created from airborne laser scans, then triangulated, and finally texture mapped with aerial imagery. The facade models are first registered with respect to the DSM by using Monte-Carlo-Localization, and then merged with the DSM by removing redundant parts and filling gaps. The developed algorithms are evaluated on a data set acquired in downtown Berkeley.

关键词： Cities and towns Merging Laser modes Land vehicles Road vehicles Vehicle driving Digital cameras Traffic control Surface texture Surface emitting lasers

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A variational framework for image segmentation combining motion estimation and shape regularization

A variational framework for image segmentation combining mot...

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conference on computer Vision and pattern recognition (CVPR)

作者： D. Cremers Department of Computer Science University of California Los Angeles CA USA

Based on a geometric interpretation of the optic flow constraint equation, we propose a conditional probability on the spatio-temporal image gradient. We consistently derive a variational approach for the segmentation of the image domain into regions of homogeneous motion. The proposed energy functional extends the Mumford-Shah functional from gray value segmentation to motion segmentation. It depends on the spatio-temporal image gradient calculated from only two consecutive images of an image sequence. Moreover, it depends on motion vectors for a set of regions and a boundary separating these regions. In contrast to most alternative approaches, the problems of motion estimation and motion segmentation are jointly solved by minimizing a single functional. Numerical evaluation with both explicit and implicit (level set based) representations of the boundary shows the strengths and limitations of our approach.

关键词： image segmentation Motion estimation Shape Motion segmentation computer vision Geometrical optics image motion analysis Equations image sequences Level set

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