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Energy Minimization Methods in Computer Vision and Pattern Recognition: 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009, ... (Lecture Notes in Computer Science, 5681) - Softcover

 
9783642036408: Energy Minimization Methods in Computer Vision and Pattern Recognition: 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009, ... (Lecture Notes in Computer Science, 5681)

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Overthelastdecades,energyminimizationmethods havebecomeanestablished paradigm to resolve a variety of challenges in the ?elds of computer vision and pattern recognition. While traditional approaches to computer vision were often based on a heuristic sequence of processing steps and merely allowed very l- ited theoretical understanding of the respective methods, most state-of-the-art methods are nowadays based on the concept of computing solutions to a given problem by minimizing respective energies. This volume contains the papers presented at the 7th International Conf- ence on Energy Minimization Methods in Computer Vision and Pattern Rec- nition (EMMCVPR 2009), held at the University of Bonn, Germany, August 24-28, 2009. These papers demonstrate that energy minimization methods have become a mature ?eld of research spanning a broad range of areas from discrete graph theoretic approaches and Markov random ?elds to variational methods and partial di?erential equations. Application areas include image segmentation and tracking, shape optimization and registration, inpainting and image deno- ing, color and texture modeling, statistics and learning. Overall, we received 75 high-quality double-blind submissions. Based on the reviewer recommendations, 36paperswereselectedforpublication,18asoraland18asposterpresentations. Both oral and poster papers were attributed the same number of pages in the conference proceedings. Furthermore, we were delighted that three leading experts from the ?elds of computer vision and energy minimization, namely, Richard Hartley (C- berra, Australia), Joachim Weickert (Saarbruc ¨ ken, Germany) and Guillermo Sapiro(Minneapolis,USA)agreedtofurtherenrichtheconferencewithinspiring keynote lectures.

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Overthelastdecades,energyminimizationmethods havebecomeanestablished paradigm to resolve a variety of challenges in the elds of computer vision and pattern recognition. While traditional approaches to computer vision were often based on a heuristic sequence of processing steps and merely allowed very l- ited theoretical understanding of the respective methods, most state-of-the-art methods are nowadays based on the concept of computing solutions to a given problem by minimizing respective energies. This volume contains the papers presented at the 7th International Conf- ence on Energy Minimization Methods in Computer Vision and Pattern Rec- nition (EMMCVPR 2009), held at the University of Bonn, Germany, August 24 28, 2009. These papers demonstrate that energy minimization methods have become a mature eld of research spanning a broad range of areas from discrete graph theoretic approaches and Markov random elds to variational methods and partial di erential equations. Application areas include image segmentation and tracking, shape optimization and registration, inpainting and image deno- ing, color and texture modeling, statistics and learning. Overall, we received 75 high-quality double-blind submissions. Based on the reviewer recommendations, 36paperswereselectedforpublication,18asoraland18asposterpresentations. Both oral and poster papers were attributed the same number of pages in the conference proceedings. Furthermore, we were delighted that three leading experts from the elds of computer vision and energy minimization, namely, Richard Hartley (C- berra, Australia), Joachim Weickert (Saarbruc ken, Germany) and Guillermo Sapiro(Minneapolis,USA)agreedtofurtherenrichtheconferencewithinspiring keynote lectures. 508 pp. Englisch. Seller Inventory # 9783642036408

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Overthelastdecades,energyminimizationmethods havebecomeanestablished paradigm to resolve a variety of challenges in the elds of computer vision and pattern recognition. While traditional approaches to computer vision were often based on a heuristic sequence of processing steps and merely allowed very l- ited theoretical understanding of the respective methods, most state-of-the-art methods are nowadays based on the concept of computing solutions to a given problem by minimizing respective energies. This volume contains the papers presented at the 7th International Conf- ence on Energy Minimization Methods in Computer Vision and Pattern Rec- nition (EMMCVPR 2009), held at the University of Bonn, Germany, August 24 28, 2009. These papers demonstrate that energy minimization methods have become a mature eld of research spanning a broad range of areas from discrete graph theoretic approaches and Markov random elds to variational methods and partial di erential equations. Application areas include image segmentation and tracking, shape optimization and registration, inpainting and image deno- ing, color and texture modeling, statistics and learning. Overall, we received 75 high-quality double-blind submissions. Based on the reviewer recommendations, 36paperswereselectedforpublication,18asoraland18asposterpresen tations. Both oral and poster papers were attributed the same number of pages in the conference proceedings. Furthermore, we were delighted that three leading experts from the elds of computer vision and energy minimization, namely, Richard Hartley (C- berra, Australia), Joachim Weickert (Saarbruc ken, Germany) and Guillermo Sapiro(Minneapolis,USA)agreedtofurtherenrichtheconferencewithinspiring keynote lectures. Seller Inventory # 9783642036408

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Cremers, Daniel|Boykov, Yuri|Blake, Andrew|Schmidt, Frank R.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discrete Optimization and Markov Random Fields.- Multi-label Moves for MRFs with Truncated Convex Priors.- Detection and Segmentation of Independently Moving Objects from Dense Scene Flow.- Efficient Global Minimization for the Multiphase Chan-Vese Model of. Seller Inventory # 5044062

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