| Dynamic programming and graph algorithms in computer vision. | |
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MedLine Citation:
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PMID: 20660950 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition. |
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Authors:
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Pedro F Felzenszwalb; Ramin Zabih |
Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S. |
Journal Detail:
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Title: IEEE transactions on pattern analysis and machine intelligence Volume: 33 ISSN: 1939-3539 ISO Abbreviation: IEEE Trans Pattern Anal Mach Intell Publication Date: 2011 Apr |
Date Detail:
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Created Date: 2011-05-02 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9885960 Medline TA: IEEE Trans Pattern Anal Mach Intell Country: United States |
Other Details:
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Languages: eng Pagination: 721-40 Citation Subset: IM |
Affiliation:
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Department of Computer Science, University of Chicago, 1100 E. 58th St., Chicago, IL 60637, USA. pff@cs.uchicago.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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| Grant Support | |
ID/Acronym/Agency:
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P41RR023953/RR/NCRR NIH HHS; R21EB008138/EB/NIBIB NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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