By Julien Bect, Laure Blanc-Féraud, Gilles Aubert, Antonin Chambolle (auth.), Tomás Pajdla, Jiří Matas (eds.)
Welcome to the lawsuits of the eighth eu convention on laptop - sion! Following a really profitable ECCV 2002, the reaction to our demand papers was once virtually both robust – 555 papers have been submitted. We authorized forty-one papers for oral and 149 papers for poster presentation. a number of concepts have been brought into the evaluate method. First, the n- ber of software committee contributors was once elevated to minimize their overview load. We controlled to assign to software committee individuals not more than 12 papers. moment, we followed a paper score procedure. software committee contributors have been requested to rank all of the papers assigned to them, even those who have been reviewed via extra reviewers. 3rd, we allowed authors to answer the studies consolidated in a dialogue related to the realm chair and the reviewers. Fourth, thereports,thereviews,andtheresponsesweremadeavailabletotheauthorsas good as to this system committee individuals. Our target used to be to supply the authors with maximal suggestions and to permit this system committee contributors understand how authors reacted to their reports and the way their studies have been or weren't re?ected within the ?nal determination. ultimately, we diminished the size of reviewed papers from 15 to twelve pages. ThepreparationofECCV2004wentsmoothlythankstothee?ortsofthe- ganizing committee, the realm chairs, this system committee, and the reviewers. we're indebted to Anders Heyden, Mads Nielsen, and Henrik J. Nielsen for passing on ECCV traditions and to Dominique Asselineau from ENST/TSI who kindly supplied his GestRFIA convention software program. We thank Jan-Olof Eklundh and Andrew Zisserman for encouraging us to prepare ECCV 2004 in Prague.
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Extra resources for Computer Vision - ECCV 2004: 8th European Conference on Computer Vision, Prague, Czech Republic, May 11-14, 2004. Proceedings, Part IV
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2 Basis Pursuit DeNoising (BPDN) Representing a signal in terms of few high coefficients of a dictionary and a lot of vanishing coefficients allows representation of an image ensuring better performances of shrinkage methods or other restoration methods. The problem is 10 J. Bect et al. to decompose a signal over a possibly large dictionary rather than one orthogonal basis. The dictionary should contain all possible atoms which can be used to represent any images. For example we can use in the dictionary DCT, DST, biorthogonal wavelets, wavelet packets, curvelets, and so on.