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Energy Minimization Methods in Computer Vision and Pattern Recognition PDF
By:Anand Rangarajan,Baba Vemuri,Alan L. Yuille
Published on 2005-10-31 by Springer Science & Business Media

This volume consists of the 42 papers presented at the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recog- tion (EMMCVPR 2005), which was held at the Hilton St. Augustine Historic Bayfront, St. Augustine, Florida, USA, during November9 11,2005.This wo- shop is the ?fth in a series which began with EMMCVPR 1997 held in Venice, Italy, in May 1997 and continued with EMMCVPR 1999 held in York, UK, in July 1999, EMMCVPR 2001 held in Sophia-Antipolis, France, in September 2001 and EMMCVPR 2003 held in Lisbon, Portugal, in July 2003. Many problems in computer vision and pattern recognition (CVPR) are couchedintheframeworkofoptimization.Theminimizationofaglobalquantity, often referred to as the energy, forms the bulwark of most approachesin CVPR. Disparate approaches such as discrete and probabilistic formulations on the one hand and continuous, deterministic strategies on the other often have optimi- tion or energy minimization as a common theme. Instances of energy minimi- tion arise in Gibbs/Markov modeling, Bayesian decision theory, geometric and variational approaches and in areas in CVPR such as object recognition and - trieval, image segmentation, registration, reconstruction, classi?cation and data mining. The aim of this workshop was to bring together researchers with interests in thesedisparateareasofCVPRbutwithanunderlyingcommitmenttosomeform of not only energy minimization but global optimization in general. Although thesubjectistraditionallywellrepresentedinmajorinternationalconferenceson CVPR, recent advances information geometry, Bayesian networks and gra- ical models, Markov chain Monte Carlo, graph algorithms, implicit methods in variational approaches and PDEs deserve an informal and focused hearing in a workshop setting.|

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