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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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Illumination subspace for multibody motion segmentation

Illumination subspace for multibody motion segmentation

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Maki H. Hattori Research and Development Center Toshiba Corporation Kawasaki Japan

ISBN: (纸本)0769512720

This paper presents a new method for automatically separating the motion of multiple independently moving objects in a sequence of images based on the notion of illumination subspace. We show that intensities of observed trajectories of image features on a single body lie on a linearly independent frame space with three, or fewer, dimensions. We then argue that it is possible in theory to determine the grouping of the feature points by way of separating the illumination subspaces. As a clue for practical separation, we also introduce the surface interaction matrix which is valid for Lambertian reflectance surface. Recently, several authors have presented different algorithms on this task of grouping by factorization-based procedures using the coordinates of image features. While the challenges in their approaches are to realize the robust performance in the presence of noise, we propose to incorporate the above photometric analysis available at given feature points in the conventional schemes of motion segmentation, and show that the performance is indeed stabilized through experiments on real and synthetic image sequences.

关键词： Lighting Motion segmentation computer vision Reflectivity Noise robustness Photometry Image analysis Image motion analysis Image sequence analysis Performance analysis

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Depth layers from occlusions

Depth layers from occlusions

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Schodl I. Essa GVU Center College of Computing Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)0769512720

We present a method to extract relative depth information from an uncalibrated monocular video sequence. Our method detects occlusions caused by an object moving in a static scene to infer relative depth relationships between scene parts. Our approach does not rely on any strong assumptions about the object or the scene to aid in this segmentation into layers. In general, the problem of building relative depth relationships from occlusion events is underconstrained, even in the absence of observation noise. A minimum description length algorithm is used to reliably calculate layer opacities and their depth relationships in the absence of hard constraints. Our approach extends previously published approaches that are restricted to work with a certain type of moving object or require strong image edges to allow for an a-priori segmentation of the scene. We also discuss ideas on how to extend our algorithm to make use of a richer set of observations.

关键词： Layout Video sequences Educational institutions Object detection Image segmentation Humans Shape Data mining Encoding computer vision

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Issues on the geometry of central catadioptric image formation

Issues on the geometry of central catadioptric image formati...

引用

conference on computer vision and pattern recognition (cvpr)

作者： J.P. Barreto H. Araujo Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra Portugal

ISBN: (纸本)0769512720

An imaging system with a single effective viewpoint is called a central projection system. The conventional perspective camera is an example of a central projection system. Systems using mirrors to enhance the field of view while keeping a unique center of projection are also examples of central projection systems. Perspective image formation can be described by a linear model with well known properties. In general central catadioptric imaging, the mapping between points in the world and in the image is highly nonlinear. The paper establishes a general model for central catadioptric image formation made up of three functions: a linear function mapping the world into an oriented projective plane, a nonlinear transformation between two oriented projective planes, and a collineation in the plane. The model is used to study issues in the projection of lines. The equations and geometric properties of general catadioptric imaging of lines are derived. The application of the results in auto-calibration of central catadioptric systems and reconstruction are discussed. A method to calibrate the system using three line images is presented.

关键词： Cameras Mirrors Nonlinear equations Application software Data mining Computational geometry Robot vision systems computer vision Surveillance Virtual reality

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Generalized dynamic programming approaches for object detection: detecting spine boundaries and vertebra endplates

Generalized dynamic programming approaches for object detect...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Guo-Qing Wei JianZhong Qian H. Schramm Imaging Department Siemens Corporate Research Inc. Princeton NJ USA Medical Solutions Siemens AG Erlangen Germany

ISBN: (纸本)0769512720

Object detection employing high-level knowledge is a challenging problem in image analysis. The authors propose a dynamic programming approach to address some related issues in this aspect. In particular, we propose to fuse the detection of two curves to form a dual dynamic programming procedure so that spatial relationships between the two curves can be enforced. In another pursuit of applying object level knowledge, we propose to introduce local backward tracing to the forward propagation step in dynamic programming, so that global constraints, containing even unknown parameters, can be imposed in a progressive manner. These approaches are explained in the context of spine landmark detection. Experimental results are presented to show the efficiency of the proposed methods. The methods are extendable to other application domains.

关键词： Object detection Dynamic programming Active contours Image analysis Shape Anatomy Educational institutions Fuses Application software computer vision

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Two-body segmentation from two perspective views

Two-body segmentation from two perspective views

引用

conference on computer vision and pattern recognition (cvpr)

作者： L. Wolf A. Shashua School of Computer Science and Engineering Hebrew University Jerusalem Israel Computer Science Department University of Stanford USA

ISBN: (纸本)0769512720

We consider a scene containing two independently and generally moving objects, viewed by two general perspective views. Using matching points arising from both objects simultaneously we derive a geometrical constraint, applicable to points from both objects, we call the segmentation matrix. We then use this constraint in order to recover the fundamental matrices associated with, each object, or simply to segment the scene into the two objects. Moreover, when the two bodies move in pure translation relative to each other we can both segment the scene and recover the affine calibration (homography at infinity) of the camera geometry. Unlike algorithms suggested in the past we need only two images, we work with general projective cameras (rather than affine or orthographic) and with general body motion, and no prior information beyond point matches is required.

关键词： Image segmentation Layout Cameras computer science Calibration Symmetric matrices H infinity control Impedance matching Geometry Solid modeling

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Non-metric image-based rendering for video stabilization

Non-metric image-based rendering for video stabilization

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conference on computer vision and pattern recognition (cvpr)

作者： C. Buehler M. Bosse L. McMillan MIT Laboratory for Computer Science Cambridge MA USA

ISBN: (纸本)0769512720

We consider the problem of video stabilization: removing unwanted image perturbations due to unstable camera motions. We approach this problem from an image-based rendering (IBR) standpoint. Given an unstabilized video sequence, the task is to synthesize a new sequence as seen from a stabilized camera trajectory. This task is relatively straightforward if one has a Euclidean reconstruction of the unstabilized camera trajectory and a suitable IBR algorithm. However, it is often not feasible to obtain a Euclidean reconstruction from an arbitrary video sequence. In light of this problem, we describe IBR techniques for non-metric reconstructions, which are often much easier to obtain since they do not require camera calibration. These rendering techniques are well suited to the video stabilization problem. The key idea behind our techniques is that all measurements are specified in the image space, rather than in the non-metric space.

关键词： Rendering (computer graphics) Cameras Image reconstruction Video sequences Layout Software algorithms Laboratories computer science Calibration Image sequences

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Calibrated, registered images of an extended urban area

Calibrated, registered images of an extended urban area

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conference on computer vision and pattern recognition (cvpr)

作者： S. Teller M. Antone Z. Bodnar M. Bosse S. Coorg M. Jethwa N. Master MIT Computer Graphics Group USA

ISBN: (纸本)0769512720

We describe a dataset of several thousand calibrated, geo-referenced, high dynamic range color images, acquired under uncontrolled, variable illumination in an outdoor region spanning hundreds of meters. All image, feature, calibration, and geo-referencing data are available at http://***/data. Calibrated imagery is of fundamental interest in a wide variety of applications. We have made this data available in the belief that researchers in computer graphics, computer vision, photogrammetry and digital cartography will find it useful in several ways: as a test set for their own algorithms; as a calibrated image set for applications such as image-based rendering, metric 3D reconstruction, and appearance recovery; and as controlled imagery for integration into existing GIS systems and applications. The Web-based interface to the data provides interactive viewing of high-dynamic-range images and mosaics; extracted edge and point features; intrinsic and extrinsic calibration, along with maps of the ground context in which the images were acquired; the spatial adjacency relationships among images; the epipolar geometry relating adjacent images; compass and absolute scale overlays; and quantitative consistency measures for the calibration data.

关键词： Urban areas Calibration Application software Dynamic range Color Lighting computer graphics computer vision System testing Rendering (computer graphics)

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Investigation of measures for grouping by graph partitioning

Investigation of measures for grouping by graph partitioning

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conference on computer vision and pattern recognition (cvpr)

作者： P. Soundararajan S. Sarkar Computer Science and Engineering University of South Florida Tampa USA

ISBN: (纸本)0769512720

Grouping by graph partitioning is an effective engine for perceptual organization. This graph partitioning process, mainly motivated by computational efficiency considerations, is usually implemented as recursive bi-partitioning, where at each step the graph is broken into two parts based on a partitioning measure. We study four such measures, namely, the minimum cut, average cut, Shi-Malik normalized cut, and a variation of the Shi-Malik normalized cut. Using probabilistic analysis we show that the minimization of the average cut and the normalized cut measure, using recursive bi-partitioning will, on an average, result in the correct segmentation. The minimum cut and the variation of the normalized cut will, on an average, not result in the correct segmentation and we can precisely express the conditions. Based on a rigorous empirical evaluation, we also show that, in practice, the quality of the groups generated using minimum, average or normalized cuts are statistically equivalent for object recognition, i.e. the best, the mean, and the variation of the qualities are statistically equivalent. We also find that for certain image classes, such as aerial and scenes with man-made objects in man-made surroundings, the performance of grouping by partitioning is the worst, irrespective of the cut measure.

关键词： Object recognition Layout computer science Acoustical engineering Engines Statistics Image segmentation Clustering methods

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A nonparametric statistical comparison of principal component and linear discriminant subspaces for face recognition

A nonparametric statistical comparison of principal componen...

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conference on computer vision and pattern recognition (cvpr)

作者： J.R. Beveridge K. She B.A. Draper G.H. Givens Computer Science Department Colorado State University Fort Collins CO USA Statistics Department Colorado State University Fort Collins CO USA

ISBN: (纸本)0769512720

The FERET evaluation compared recognition rates for different semi-automated and automated face recognition algorithms. We extend FERET by considering when differences in recognition rates are statistically distinguishable subject to changes in test imagery. Nearest Neighbor classifiers using principal component and linear discriminant subspaces are compared using different choices of distance metric. Probability distributions for algorithm recognition rates and pairwise differences in recognition rates are determined using a permutation methodology. The principal component subspace with Mahalanobis distance is the best combination; using L2 is second best. Choice of distance measure for the linear discriminant subspace matters little, and performance is always worse than the principal components classifier using either Mahalanobis or L1 distance. We make the source code for the algorithms, scoring procedures and Monte Carlo study available in the hopes others will extend this comparison to newer algorithms.

关键词： Nearest neighbor searches Probes Face recognition Monte Carlo methods Image recognition computer science Probability distribution Automatic testing Protocols Statistics

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Image-based modeling and rendering of surfaces with arbitrary BRDFs

Image-based modeling and rendering of surfaces with arbitrar...

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conference on computer vision and pattern recognition (cvpr)

作者： M.L. Koudelka P.N. Belhumeur S. Magda D.J. Kriegman Center for Computer Vision & Control EE and CS Yale University New Heaven CT USA Beckman Institute Computer Science University of Illinois Urbana IL USA

ISBN: (纸本)0769512720

A goal of image-based rendering is to synthesize as realistically as possible man made and natural objects. The paper presents a method for image-based modeling and rendering of objects with arbitrary (possibly anisotropic and spatially varying) BRDFs. An object is modeled by sampling the surface's incident light field to reconstruct a non-parametric apparent BRDF at each visible point on the surface, This can be used to render the object from the same viewpoint but under arbitrarily specified illumination. We demonstrate how these object models can be embedded in synthetic scenes and rendered under global illumination which captures the interreflections between real and synthetic objects. We also show how these image-based models can be automatically composited onto video footage with dynamic illumination so that the effects (shadows and shading) of the lighting on the composited object match those of the scene.

关键词： Rendering (computer graphics) Reflectivity Surface reconstruction Lighting Light sources Anisotropic magnetoresistance Layout Image reconstruction Solid modeling Bidirectional control

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