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- Publisher Website: 10.1109/CVPR.2015.7299140
- Scopus: eid_2-s2.0-84959256036
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Conference Paper: Coarse-to-fine region selection and matching
Title | Coarse-to-fine region selection and matching |
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Authors | |
Issue Date | 2015 |
Citation | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2015, v. 07-12-June-2015, p. 5051-5059 How to Cite? |
Abstract | We present a new approach to wide baseline matching. We propose to use a hierarchical decomposition of the image domain and coarse-to-fine selection of regions to match. In contrast to interest point matching methods, which sample salient regions to reduce the cost of comparing all regions in two images, our method eliminates regions systematically to achieve efficiency. One advantage of our approach is that it is not restricted to covariant salient regions, which is too restrictive under large viewpoint and leads to few corresponding regions. Affine invariant matching of regions in the hierarchy is achieved efficiently by a coarse-to-fine search of the affine space. Experiments on two benchmark datasets shows that our method finds more correct correspondence of the image (with fewer false alarms) than other wide baseline methods on large viewpoint change. |
Persistent Identifier | http://hdl.handle.net/10722/325311 |
ISSN | 2023 SCImago Journal Rankings: 10.331 |
DC Field | Value | Language |
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dc.contributor.author | Yang, Yanchao | - |
dc.contributor.author | Lu, Zhaojin | - |
dc.contributor.author | Sundaramoorthi, Ganesh | - |
dc.date.accessioned | 2023-02-27T07:31:27Z | - |
dc.date.available | 2023-02-27T07:31:27Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2015, v. 07-12-June-2015, p. 5051-5059 | - |
dc.identifier.issn | 1063-6919 | - |
dc.identifier.uri | http://hdl.handle.net/10722/325311 | - |
dc.description.abstract | We present a new approach to wide baseline matching. We propose to use a hierarchical decomposition of the image domain and coarse-to-fine selection of regions to match. In contrast to interest point matching methods, which sample salient regions to reduce the cost of comparing all regions in two images, our method eliminates regions systematically to achieve efficiency. One advantage of our approach is that it is not restricted to covariant salient regions, which is too restrictive under large viewpoint and leads to few corresponding regions. Affine invariant matching of regions in the hierarchy is achieved efficiently by a coarse-to-fine search of the affine space. Experiments on two benchmark datasets shows that our method finds more correct correspondence of the image (with fewer false alarms) than other wide baseline methods on large viewpoint change. | - |
dc.language | eng | - |
dc.relation.ispartof | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition | - |
dc.title | Coarse-to-fine region selection and matching | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/CVPR.2015.7299140 | - |
dc.identifier.scopus | eid_2-s2.0-84959256036 | - |
dc.identifier.volume | 07-12-June-2015 | - |
dc.identifier.spage | 5051 | - |
dc.identifier.epage | 5059 | - |