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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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A new 3-D volume processing.method for polyp detection

A new 3-D volume processing method for polyp detection

引用

Annual International conference of the ieee Engineering in Medicine and Biology society (EMBC)

作者： S.B. Gokturk C. Tomasi B. Acar D. Paik C. Beaulieu S. Napel Robotics Lab Computer Science Department University of Stanford USA Department of Radiology University of Stanford USA

Early diagnosis and removal of colonic polyps is effective in the elimination of subsequent carcinoma. This paper presents a new approach for computer-aided detection of polyps. The approach mimics the way the radiologists view CT abdomen images and utilizes several geometric attributes obtained from many triples of mutually orthogonal planes. The histogram of the attributes obtained from a sufficiently large number of perpendicular random images serves as a robust signature to represent the shape. We combine the new 3-D pattern recognition with a support vector machine classifier, and show that the number or the false positive detections in the initial polyp detection studies can be substantially reduced. One of the main contributions of this study is the thorough analysis of planar geometrical attributes. When an appropriate combination of planar attributes is used, the false positive rate is reduced by 87 percent beyond that of the initial stage detector, while maintaining a sensitivity level of 95 percent. Using such methods, radiologists should be able to view CTC data much more efficiently and accurately than without CAD.

关键词： Colonic polyps Computed tomography Abdomen Histograms Robustness Shape pattern recognition Support vector machines Support vector machine classification Detectors

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Equivalence and efficiency of image alignment algorithms

Equivalence and efficiency of image alignment algorithms

引用

conference on computer Vision and pattern recognition (CVPR)

作者： S. Baker I. Matthews The Robotics Institute Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)0769512720

There are two major formulations of image alignment using gradient descent. The first estimates an additive increment to the parameters (the additive approach), the second an incremental warp (the compositional approach). We first prove that these two formulations are equivalent. A very efficient algorithm was proposed by Hager and Belhumeur (1998) using the additive approach that unfortunately can only be applied to a very restricted class of warps. We show that using the compositional approach an equally efficient algorithm (the inverse compositional algorithm) can be derived that can be applied to any set of warps which form a group. While most warps used in computer vision form groups, there are a certain warps that do not. Perhaps most notable is the set of piecewise affine warps used in flexible appearance models (FAMs). We end this paper by extending the inverse compositional algorithm to apply to FAMs.

关键词： Approximation algorithms computer vision Jacobian matrices Active appearance model Robots Nonlinear optics Optical sensors image motion analysis Tracking Motion estimation

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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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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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On 3D scene flow and structure estimation

On 3D scene flow and structure estimation

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conference on computer Vision and pattern recognition (CVPR)

作者： Ye Zhang C. Kambhamettu Video Image Modeling and Synthesis VIMS Laboratory Department of Computer & Information Sciences University of Delaware Newark DE USA

ISBN: (纸本)0769512720

In this paper, novel algorithms computing dense 3D scene flow from multiview image sequences are described. A new hierarchical rule-based stereo matching algorithm is presented to estimate the initial disparity map. Different available constraints under a multiview camera setup are investigated and then utilized in the proposed motion estimation algorithms. We show two different formulations for 3D scene flow computation. One formulation assumes that initial disparity map is accurate while the other does not make this assumption. image segmentation information is used to maintain the motion and depth discontinuities. Iterative implementations are used to successfully compute 3D scene flow and structure at every point in the reference image. Novel hard constraints are introduced in this paper to make the algorithms more accurate and robust. Promising experimental results are seen by applying our algorithms to real imagery.

关键词： Layout image motion analysis Optical sensors Optical computing Motion estimation image sequences Optical noise Iterative algorithms Cameras image segmentation

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A representation of image structure and its application to object selection using freehand sketches

A representation of image structure and its application to o...

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conference on computer Vision and pattern recognition (CVPR)

作者： Kar-Han Tan N. Ahuja Department of Computer Science and Beckman Institute University of Illinois Urbana-Champaign USA Department of Electrical and Computer Engineering and Beckman Institute University of Illinois Urbana-Champaign USA

ISBN: (纸本)0769512720

We present an algorithm for computing a representation of image structure, or image segmentation, and use it for selecting objects in the image with freehand sketches drawn by the user over the image. The sketches are mapped onto image segments whose union forms the intended object. The mapping operation is performed with the aid of a simplicial decomposition of the image segmentation-a triangulation formed with vertices chosen to lie along the medial axes of the segments. Each edge of a triangle lies entirely inside the two segments that contains its vertices. This decomposition captures the adjacency information about the segments as well as the shape of the segment boundaries. Any object boundary is completely contained in a set of triangles. The triangles are also used to formulate the problem of estimating gradual photometric transition across an object boundary, called alpha channel estimation, as a set of local, intratriangle alpha channel estimation problems that can then be solved more accurately, independently, and in parallel. Experimental results are included to show how the algorithm allows selection of image objects with complex boundaries using roughly drawn simple sketches.

关键词： image segmentation Application software image edge detection computer science Shape Photometry Channel estimation Digital images Broadcasting Handheld computers

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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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Learning probabilistic structure for human motion detection

Learning probabilistic structure for human motion detection

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conference on computer Vision and pattern recognition (CVPR)

作者： Y. Song L. Goncalves P. Perona California Institute of Technology Pasadena CA USA Universitá di Padova Italy

ISBN: (纸本)0769512720

Decomposable triangulated graphs have been shown to be efficient and effective for modeling the probabilistic spatio-temporal structure of brief stretches of human motion. In previous work such model structure was handcrafted by expert human observers and labeled data were needed for parameter learning. We present a method to build automatically the structure of the decomposable triangulated graph from unlabeled data. It is based on maximum-likelihood. Taking the labeling of the data as hidden variables, a variant of the EM algorithm can be applied. A greedy algorithm is developed to search for the optimal structure of the decomposable model based on the (conditional) differential entropy of variables. Our algorithm is demonstrated by learning models of human motion completely automatically from unlabeled real image sequences with clutter and occlusion. Experiments on both motion captured data and grayscale image sequences show that the resulting models perform better than the hand-constructed models.

关键词： Humans Motion detection Labeling image sequences Training data Maximum likelihood detection Gray-scale computer vision Biological system modeling Greedy algorithms

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Automatic estimation of the projected light source direction

Automatic estimation of the projected light source direction

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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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Robust online appearance models for visual tracking

Robust online appearance models for visual tracking

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conference on computer Vision and pattern recognition (CVPR)

作者： A.D. Jepson D.J. Fleet T.R. El-Maraghi Department of Computer Science University of Toronto Toronto Canada Xerox Palo Alto Research Center Palo Alto CA USA Xerox Palo Alto Research Center Palo Alto CA Department of Computer Science University of Toronto Toronto

ISBN: (纸本)0769512720

We propose a framework for learning robust, adaptive appearance models to be used for motion-based tracking of natural objects. The approach involves a mixture of stable image structure, learned over long time courses, along with 2-frame motion information and an outlier process. An online EM-algorithm is used to adapt the appearance model parameters over time. An implementation of this approach is developed for an appearance model based on the filter responses from a steerable pyramid. This model is used in a motion-based tracking algorithm to provide robustness in the face of image outliers, such as those caused by occlusions. It also provides the ability to adapt to natural changes in appearance, such as those due to facial expressions or variations in 3D pose. We show experimental results on a variety of natural image sequences of people moving within cluttered environments.

关键词： Robustness Target tracking Biological system modeling Stability Statistics computer science Filters image sequences Motion estimation Clothing

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