| Linear Scale and Rotation Invariant Matching. | |
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MedLine Citation:
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PMID: 21135437 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Matching visual patterns that appear scaled, rotated and deformed with respect to each other is a challenging problem. We propose a linear formulation that simultaneously matches feature points and estimates global geometrical transformation in a constrained linear space. The linear scheme enables search space reduction based on the lower convex hull property so that the problem size is largely decoupled from the original hard combinatorial problem. Our method therefore can be used to solve large scale problems that involve a very large number of candidate feature points. Without using pre-pruning in the search, this method is more robust in dealing with weak features and clutter. We apply the proposed method to action detection and image matching. Our results on a variety of images and videos demonstrate that our method is accurate, efficient, and robust. |
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Authors:
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Hao Jiang; Stella X Yu; David R Martin |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2010-11-30 |
Journal Detail:
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Title: IEEE transactions on pattern analysis and machine intelligence Volume: - ISSN: 1939-3539 ISO Abbreviation: - Publication Date: 2010 Nov |
Date Detail:
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Created Date: 2010-12-7 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9885960 Medline TA: IEEE Trans Pattern Anal Mach Intell Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Boston College, Chestnut Hill. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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