On learning higher-order consistency potentials for multi-class pixel labeling
Date
2012
Authors
Park, Kyoungup
Gould, Stephen
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Publisher
Springer
Abstract
Pairwise Markov random fields are an effective framework for solving many pixel labeling problems in computer vision. However, their performance is limited by their inability to capture higher-order correlations. Recently proposed higher-order models are
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Keywords: Consistency constraints; Consistency model; Higher order correlation; Markov Random Fields; Multi-class; Optimal parameter; Semantic segmentation; Computer vision; Image segmentation; Pixels
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Type
Conference paper
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Restricted until
2037-12-31
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