DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Ouk | - |
dc.contributor.author | Kweon, In So | - |
dc.date.accessioned | 2011-08-11T05:57:24Z | - |
dc.date.available | 2011-08-11T05:57:24Z | - |
dc.date.issued | 2008 | - |
dc.identifier.citation | IEEE International Conference on Image Processing | en |
dc.identifier.uri | http://hdl.handle.net/10203/24863 | - |
dc.description.abstract | In this paper, feature point matching is formulated as an optimization problem in which the uniqueness condition is constrained. We propose a novel score function based on homography-induced pairwise constraints, and a novel optimization algorithm based on relaxation labeling. Homographyinduced pairwise constraints are effective for image pairs with viewpoint or scale changes, unlike previous pairwise constraints. The proposed optimization algorithm searches for a uniqueness-constrained solution, while the original relaxation-labeling algorithm is appropriate for finding manyto- one correspondences. The effectiveness of the proposed method is shown by experiments involving image pairs with viewpoint or scale changes in addition to repeated textures and nonrigid deformation. The proposed method is also applied to object recognition, giving some promising results. | en |
dc.description.sponsorship | This work has been funded by the IT R&D program of MIC/IITA [2006- S-028-01, Development of Cooperative Network-based Humanoids Technology] and the Korean MOST for NRL program [Grant number M1-0302-00- 0064]. | en |
dc.language.iso | en_US | en |
dc.publisher | IEEE | en |
dc.subject | wide-baseline stereo | en |
dc.subject | affine regions | en |
dc.subject | pairwise constraints | en |
dc.subject | relaxation labeling | en |
dc.title | REDUCING AMBIGUITY IN FEATURE POINT MATCHING BY PRESERVING LOCAL GEOMETRIC CONSISTENCY | en |
dc.type | Article | en |
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