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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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Wire Structure pattern Extraction and Tracking From X-Ray Images of Composite Mechanisms

Wire Structure Pattern Extraction and Tracking From X-Ray Im...

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conference on computer vision and pattern recognition (cvpr)

作者： D. Tschumperle J. Fadili GREYC IMAGE (CNRS UMR 6072) Juin Caen Cedex France

This paper introduces a complete pipeline of image processing methods in order to analyze and track the internal structures of a composite material. As a first step, input Xray images are denoised, enhanced, separated into different morphological components, and geometrically filtered in order to isolate the interesting fiber inside the composite material. This requires the design of specific algorithms preserving very thin image details while being able to remove undesired image regions that may be sometimes large. For this purpose, we use state-of the-art techniques based on recent achievements in diffusion PDE’s and modern harmonic analysis tools. Then, the shapes of the remaining fibered composite are individually analyzed by the use of a tensor-based tracking algorithm. We illustrate how this set of techniques allows the dynamic analysis of the composite structure when submitted to external mechanical loads.

关键词： Wire X-ray imaging Optical fiber devices Image processing Composite materials Image analysis Pipelines Algorithm design and analysis Shape Optical fiber testing

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A Novel Data Association Algorithm for Object Tracking in Clutter with Application to Tennis Video Analysis

A Novel Data Association Algorithm for Object Tracking in Cl...

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conference on computer vision and pattern recognition (cvpr)

作者： Fei Yan A. Kostin W. Christmas J. Kittler Centre for Vision Speech and Signal Processing University of Surrey Guildford Surrey UK

It is well recognised that data association is critically important for object tracking. However, in the presence of successive misdetections, a large number of false candidates and an unknown number of abrupt model switchings that happen unpredictably, the data association problem can be very difficult. We tackle these difficulties by using a layered data association scheme. At the object level, trajectories are "grown" from sets of object candidates that have high probabilities of containing only true positives; by this means the otherwise combinatorial complexity is significantly reduced. Dijkstra’s shortest path algorithm is then used to perform data association at the trajectory level. The algorithm is applied to low-quality tennis video sequences to track a tennis ball. Experiments show that the algorithm is robust to abrupt model switchings, and performs well in heavily cluttered environments.

关键词： Algorithm design and analysis Signal processing algorithms Robustness Iterative algorithms Speech analysis Games Filters Maximum likelihood estimation Polynomials Signal analysis

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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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A sequential detection framework for feature tracking within computational constraints

A sequential detection framework for feature tracking within...

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conference on computer vision and pattern recognition (cvpr)

作者： H.S. Richardson S.D. Blostein Department of Electrical Engineering Queen''s University Kingston Kingston ONT Canada

A unified decision-theoretic framework for automating the establishment of feature point correspondences in a temporally dense sequence of images is discussed. The approach extends a recent sequential detection algorithm to guide the detection and tracking of object feature points through an image sequence. The resulting extended feature tracks provide robust feature correspondences, for the estimation of three-dimensional structure and motion, over an extended number of image frames.< >

关键词： computer vision Object detection Robustness Image sequences Constraint theory Motion estimation Intelligent robots Change detection algorithms Detection algorithms Tracking

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Structure from motion for scenes without features

Structure from motion for scenes without features

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conference on computer vision and pattern recognition (cvpr)

作者： A.J. Yezzi S. Soatto Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Computer Science Department University of California Los Angeles CA USA

We describe an algorithm for reconstructing the 3D (three-dimensional) shape of the scene and the relative pose of a number of cameras from a collection of images under the assumption that the scene does not contain photometrically distinct "features". We work under the explicit assumption that the scene is made of a number of smooth surfaces that radiate constant energy isotropically in all directions, and setup a region-based cost functional that we minimize using local gradient flow techniques.

关键词： Layout Cameras Shape Photometry Image reconstruction Surface reconstruction Cost function computer vision computer science Geometry

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Shape representation and classification using the Poisson equation

Shape representation and classification using the Poisson eq...

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conference on computer vision and pattern recognition (cvpr)

作者： L. Gorelick M. Galun E. Sharon R. Basri A. Brandt Department of Computer Science and Applied Math Weizmann Institute of Science Rehovot Israel Division of Applied Math Brown University Providence RI USA

Silhouettes contain rich information about the shape of objects that can be used for recognition and classification. We present a novel approach that allows us to reliably compute many useful properties of a silhouette. Our approach assigns for every internal point of the silhouette a value reflecting the mean time required for a random walk beginning at the point to hit the boundaries. This function can be computed by solving Poisson's equation, with the silhouette contours providing boundary conditions. We show how this function can be used to reliably extract various shape properties including part structure and rough skeleton, local orientation and aspect ratio of different parts, and convex and concave sections of the boundaries. In addition to this we discuss properties of the solution and show how to efficiently compute this solution using multi-grid algorithms. We demonstrate the utility of the extracted properties by using them for shape classification.

关键词： Shape Poisson equations Skeleton computer vision Boundary conditions Application software computer science Data mining Object recognition Belts

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Multi-Resolution Patch Tensor for Facial Expression Hallucination

Multi-Resolution Patch Tensor for Facial Expression Hallucin...

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conference on computer vision and pattern recognition (cvpr)

作者： Kui Jia Shaogang Gong Department of Computer Science Queen''s Mary University of London UK

In this paper, we propose a sequential approach to hallucinate/ synthesize high-resolution images of multiple facial expressions. We propose an idea of multi-resolution tensor for super-resolution, and decompose facial expression images into small local patches. We build a multi-resolution patch tensor across different facial expressions. By unifying the identity parameters and learning the subspace mappings across different resolutions and expressions, we simplify the facial expression hallucination as a problem of parameter recovery in a patch tensor space. We further add a high-frequency component residue using nonparametric patch learning from high-resolution training data. We integrate the sequential statistical modelling into a Bayesian framework, so that given any low-resolution facial image of a single expression, we are able to synthesize multiple facial expression images in high-resolution. We show promising experimental results from both facial expression database and live video sequences.

关键词： Tensile stress Image resolution Training data Bayesian methods Image databases Video sequences Robustness Active appearance model Cameras Principal component analysis

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Reconstruction in the Round Using Photometric Normals and Silhouettes.

Reconstruction in the Round Using Photometric Normals and Si...

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conference on computer vision and pattern recognition (cvpr)

作者： G. Vogiatzis C. Hernandez R. Cipolla Department of Engineering University of Cambridge Cambridge UK

This paper addresses the problem of obtaining complete, detailed reconstructions of shiny textureless objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under varying illumination conditions. In contrast with previous photometric stereo techniques, ours is not limited to a single viewpoint and produces accurate reconstructions in full 3D. A number of images of the object are obtained from multiple viewpoints, under varying lighting conditions. Starting from the silhouettes, the algorithm recovers camera motion and constructs the object’s visual hull. This is then used to recover the illumination and initialise a multi-view photometric stereo scheme to obtain a closed surface reconstruction. The contributions of the paper are twofold: Firstly we describe a robust technique to estimate light directions and intensities and secondly, we introduce a novel formulation of photometric stereo which combines multiple viewpoints and hence allows closed surface reconstructions. The algorithm has been implemented as a practical model acquisition system. Here, a quantitative evaluation of the algorithm on synthetic data is presented together with a complete reconstruction of a challenging real object.

关键词： Photometry Image reconstruction Stereo vision Surface reconstruction Stereo image processing Shape Lighting Cameras computer vision Reflectivity

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Animals on the Web

Animals on the Web

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conference on computer vision and pattern recognition (cvpr)

作者： T.L. Berg D.A. Forsyth Computer Science Division University of California Berkeley USA Department of Computer Science University of Illinois Urbana-Champaign USA

We demonstrate a method for identifying images containing categories of animals. The images we classify depict animals in a wide range of aspects, configurations and appearances. In addition, the images typically portray multiple species that differ in appearance (e.g. ukari’s, vervet monkeys, spider monkeys, rhesus monkeys, etc.). Our method is accurate despite this variation and relies on four simple cues: text, color, shape and texture. Visual cues are evaluated by a voting method that compares local image phenomena with a number of visual exemplars for the category. The visual exemplars are obtained using a clustering method applied to text on web pages. The only supervision required involves identifying which clusters of exemplars refer to which sense of a term (for example, "monkey" can refer to an animal or a bandmember). Because our method is applied to web pages with free text, the word cue is extremely noisy. We show unequivocal evidence that visual information improves performance for our task. Our method allows us to produce large, accurate and challenging visual datasets mostly automatically.

关键词： Animals Web pages Shape Object recognition computer science Voting Image retrieval Image classification pattern recognition Clustering methods

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Estimation of blood flow speed and vessel location from thermal video

Estimation of blood flow speed and vessel location from ther...

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conference on computer vision and pattern recognition (cvpr)

作者： M. Garbey A. Merla I. Pavlidis Computer Science Department University of Houston Houston TX USA

In this paper we present a novel method for estimation of blood flow speed and vessel location from thermal video. The method is based on a bioheat transfer model that reflects the thermo-physiological processes in a skin region proximal to a major vessel. The model assumes the form of a partial differential equation (PDE) with boundary conditions. Initially, we test the soundness of our model by performing direct numerical simulation. Then, we solve the inverse problem both in steady and dynamic states on data provided by a thermal imaging system. Our method opens exciting possibilities in biometrics and biomedicine. Among others, it promises to revolutionize polygraph examinations by eliminating wiring and improving accuracy. It also establishes the feasibility of continuous 2D physiological monitoring of human patients in a contact-free manner.

关键词： Blood flow Skin Partial differential equations Boundary conditions Acoustic testing Performance evaluation Numerical simulation Inverse problems Biomedical imaging Biometrics

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