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Titlebook: Computer Vision - ECCV 2004; 8th European Confere Tomás Pajdla,Jiří Matas Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 200

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书目名称Computer Vision - ECCV 2004
副标题8th European Confere
编辑Tomás Pajdla,Jiří Matas
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computer Vision - ECCV 2004; 8th European Confere Tomás Pajdla,Jiří Matas Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 200
描述Welcome to the proceedings of the 8th European Conference on Computer - sion! Following a very successful ECCV 2002, the response to our call for papers was almost equally strong – 555 papers were submitted. We accepted 41 papers for oral and 149 papers for poster presentation. Several innovations were introduced into the review process. First, the n- ber of program committee members was increased to reduce their review load. We managed to assign to program committee members no more than 12 papers. Second, we adopted a paper ranking system. Program committee members were asked to rank all the papers assigned to them, even those that were reviewed by additional reviewers. Third, we allowed authors to respond to the reviews consolidated in a discussion involving the area chair and the reviewers. Fourth, thereports,thereviews,andtheresponsesweremadeavailabletotheauthorsas well as to the program committee members. Our aim was to provide the authors with maximal feedback and to let the program committee members know how authors reacted to their reviews and how their reviews were or were not re?ected in the ?nal decision. Finally, we reduced the length of reviewed papers from 15 to 12 pa
出版日期Conference proceedings 2004
关键词3D; Active contour; Optical flow; Stereo; cognition; computational geometry; computer vision; image analysi
版次1
doihttps://doi.org/10.1007/b97873
isbn_softcover978-3-540-21981-1
isbn_ebook978-3-540-24673-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2004
The information of publication is updating

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Learning and Bayesian Shape Extraction for Object Recognitionh taken is Bayesian: we adopt a region-based model that incorporates prior knowledge of specific shapes of interest. To quantify this prior knowledge, we address the problem of learning probability models for collections of observed shapes. Our method is based on the geometric representation and alg
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Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentationropriate cost functional with respect to both a level set function and a (vector-valued) labeling function, we jointly generate a segmentation (by the level set function) and a recognition-driven partition of the image domain (by the labeling function) which indicates where to enforce certain shape
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Integral Invariant Signaturesgroup, obtained by performing integral operations. While such integral invariants enjoy some of the desirable properties of their differential cousins, such as locality of computation (which allows matching under occlusions) and uniqueness of representation (in the limit), they are not as sensitive
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Detecting Keypoints with Stable Position, Orientation, and Scale under Illumination Changesnown as ‘keypoints’ or ‘points of interest’. Their performance depends critically on the accuracy and reliability with which corresponding keypoints can be found in subsequent images. Among the many existing keypoint selection criteria, the popular Förstner-Harris approach explicitly targets geometr
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Spectral Simplification of Graphshed into smaller subgraphs. If this is done, then the process may cast into a hierarchical framework and hence rendered suitable for parallel computation. In this paper we describe a spectral method which can be used to partition graphs into non-overlapping subgraphs. In particular, we demonstrate h
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