Optimal Relative Pose With Unknown Correspondences

Johan Fredriksson, Viktor Larsson, Carl Olsson, Fredrik Kahl; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 1728-1736

Abstract


Previous work on estimating the epipolar geometry of two views relies on being able to reliably match feature points based on appearance. In this paper, we go one step further and show that it is feasible to compute both the epipolar geometry and the correspondences at the same time based on geometry only. We do this in a globally optimal manner. Our approach is based on an efficient branch and bound technique in combination with bipartite matching to solve the correspondence problem. We rely on several recent works to obtain good bounding functions to battle the combinatorial explosion of possible matchings. It is experimentally demonstrated that more difficult cases can be handled and that more inlier correspondences can be obtained by being less restrictive in the matching phase.

Related Material


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[bibtex]
@InProceedings{Fredriksson_2016_CVPR,
author = {Fredriksson, Johan and Larsson, Viktor and Olsson, Carl and Kahl, Fredrik},
title = {Optimal Relative Pose With Unknown Correspondences},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2016}
}