Energy Minimization Methods in Computer Vision and Pattern Recognition
Publication year: 2007
ISBN: 978-3-540-74198-5
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This volume contains 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. This book makes no distinction between oral and poster papers. It also contiants sections on al- rithms, applications, image parsing, image processing, motion, shape, and thr- dimensional processing.
Subject: Computer Science, Computer Vision, Gabor filter, algorithmic learning, algorithms, clustering, cognition, data mining, energy minimization, feature extraction, geometric computing, graph matching, image analysis, image classification, image processing, reflection
