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Titlebook: Energy Minimization Methods in Computer Vision and Pattern Recognition; 6th International Co Alan L. Yuille,Song-Chun Zhu,Yongtian Wang Con

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书目名称Energy Minimization Methods in Computer Vision and Pattern Recognition
副标题6th International Co
编辑Alan L. Yuille,Song-Chun Zhu,Yongtian Wang
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Energy Minimization Methods in Computer Vision and Pattern Recognition; 6th International Co Alan L. Yuille,Song-Chun Zhu,Yongtian Wang Con
描述This volume contains the papers presented at the Sixth International Conference on Energy Minimization Methods on Computer Vision and Pattern Recognition (EMMCVPR 2007), held at the Lotus Hill Institute, Ezhou, Hubei, China, August 27–29, 2007. The motivation for this conference is the realization that many problems in computer vision and pattern recognition can be formulated in terms of probabilistic inference or optimization of energy functions. EMMCVPR 2007 addressed the critical issues of representation, learning, and inference. Important new themes include pr- abilistic grammars, image parsing, and the use of datasets with ground-truth to act as benchmarks for evaluating algorithms and as a way to train learning algorithms. Other themes include the development of efficient inference algorithms using advanced techniques from statistics, computer science, and applied mathematics. We received 140 submissions for this workshop. Each paper was reviewed by three committee members. Based on these reviews we selected 22 papers for oral presen- tion and 15 papers for poster presentation. This book makes no distinction between oral and poster papers. We have organized these papers in se
出版日期Conference proceedings 2007
关键词Computer Vision; Gabor filter; algorithmic learning; algorithms; clustering; cognition; data mining; energy
版次1
doihttps://doi.org/10.1007/978-3-540-74198-5
isbn_softcover978-3-540-74195-4
isbn_ebook978-3-540-74198-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2007
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Efficient Shape Matching Via Graph Cutshe other. To determine an optimal correspondence is a computationally challenging combinatorial problem. Traditionally it has been formulated as a shortest path problem which can be solved efficiently by Dynamic Time Warping..In this paper, we show that shape matching can be cast as a problem of fin
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An Energy Minimisation Approach to Attributed Graph Regularisationctional whose extremum is achieved efficiently by a gradient descend optimisation process. As a result of the treatment given in this paper to the regularisation problem, constraints can be enforced in a straightforward manner. This provides a means to solve a number of problems in computer vision a
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CIDER: Corrected Inverse-Denoising Filter for Image Restorationmotivated by a recent algorithm ForWaRD, which uses a regularized inverse filter followed by a wavelet denoising scheme. In ForWaRD, the restored image obtained by the regularized inverse filter is a biased estimate of the original image. In CIDER, the correction term is added to this restored image
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