Quasi-Dense Wide Baseline Matching Using Match Propagation
In this paper we propose extensions to the match propagation algorithm which is a technique for computing quasi-dense point correspondences between two views. The extensions make the match propagation applicable for wide baseline matching, i.e., for cases where the camera pose can vary a lot between...
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Published in | 2007 IEEE Conference on Computer Vision and Pattern Recognition pp. 1 - 8 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.06.2007
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Subjects | |
Online Access | Get full text |
ISBN | 9781424411795 1424411793 |
ISSN | 1063-6919 1063-6919 |
DOI | 10.1109/CVPR.2007.383247 |
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Abstract | In this paper we propose extensions to the match propagation algorithm which is a technique for computing quasi-dense point correspondences between two views. The extensions make the match propagation applicable for wide baseline matching, i.e., for cases where the camera pose can vary a lot between the views. Our first extension is to use a local affine model for the geometric transformation between the images. The estimate of the local transformation is obtained from affine covariant interest regions which are used as seed matches. The second extension is to use the second order intensity moments to adapt the current estimate of the local affine transformation during the propagation. This allows a single seed match to propagate into regions where the local transformation between the views differs from the initial one. The experiments with real data show that the proposed techniques improve both the quality and coverage of the quasi-dense disparity map. |
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AbstractList | In this paper we propose extensions to the match propagation algorithm which is a technique for computing quasi-dense point correspondences between two views. The extensions make the match propagation applicable for wide baseline matching, i.e., for cases where the camera pose can vary a lot between the views. Our first extension is to use a local affine model for the geometric transformation between the images. The estimate of the local transformation is obtained from affine covariant interest regions which are used as seed matches. The second extension is to use the second order intensity moments to adapt the current estimate of the local affine transformation during the propagation. This allows a single seed match to propagate into regions where the local transformation between the views differs from the initial one. The experiments with real data show that the proposed techniques improve both the quality and coverage of the quasi-dense disparity map. |
Author | Kannala, J. Brandt, S.S. |
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Snippet | In this paper we propose extensions to the match propagation algorithm which is a technique for computing quasi-dense point correspondences between two views.... |
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SubjectTerms | Algorithm design and analysis Cameras Computer vision Geometry Image reconstruction Image sequences Layout Machine vision Solid modeling Surface reconstruction |
Title | Quasi-Dense Wide Baseline Matching Using Match Propagation |
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