Presentation | 2014-03-13 Study of Clustering Feature Points of Moving Objects From Dynamic RGB-D Images : Proposing a Method that Combines Supervoxel and Multi Label Graph-Cut Naotomo Tatematsu, Jun Ohya, Larry S. Davis, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper proposes a method that can discriminate feature points of each moving object from the still background by utilizing supervoxel and Multi-label Graph-Cut. The ordinal clustering method based on multi label graph-cut has a problem that can not classify small movement object. To solve this problem, our method utilize initial cluster based on supervoxel and construct multi-labeled-graph by the unit of group that belongs same supervoxel. This improvement enable accurate clustering feature points even if the amount of movement is small. Experiments using multiple moving objects and real stereo sequences demonstrate the effectiveness of our proposed method. |
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Paper # | PRMU2013-189 |
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Committee | PRMU |
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Conference Date | 2014/3/6(1days) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
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Title (in English) | Study of Clustering Feature Points of Moving Objects From Dynamic RGB-D Images : Proposing a Method that Combines Supervoxel and Multi Label Graph-Cut |
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1st Author's Name | Naotomo Tatematsu |
1st Author's Affiliation | Graduate School of Global Information and Telecommunication Studies, Waseda University() |
2nd Author's Name | Jun Ohya |
2nd Author's Affiliation | Department of Computer Science, University of Maryland College Park |
3rd Author's Name | Larry S. Davis |
3rd Author's Affiliation | Department of Computer Science, University of Maryland College Park |
Date | 2014-03-13 |
Paper # | PRMU2013-189 |
Volume (vol) | vol.113 |
Number (no) | 493 |
Page | pp.pp.- |
#Pages | 6 |
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