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 in2007 IEEE Conference on Computer Vision and Pattern Recognition pp. 1 - 8
Main Authors Kannala, J., Brandt, S.S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2007
Subjects
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ISBN9781424411795
1424411793
ISSN1063-6919
1063-6919
DOI10.1109/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.
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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StartPage 1
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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