Finding correspondences in wide baseline setups is a challenging problem. Existing approaches have focused largely on developing better feature descriptors for correspondence and on accurate recovery of epipolar line constraints. This paper focuses on the challenging problem of finding correspondences once approximate epipolar constraints are given. We introduce a novel method that integrates a deformation model. Specifically, we formulate the problem as finding the largest number of corresponding points related by a bounded distortion map that obeys the given epipolar constraints. We show that, while the set of bounded distortion maps is not convex, the subset of maps that obey the epipolar line constraints is convex, allowing us to introduce an efficient algorithm for matching. We further utilize a robust cost function for matching and employ majorization-minimization for its optimization. Our experiments indicate that our method finds significantly more accurate maps than existing approaches.
|Title of host publication||2015 International Conference on Computer Vision, ICCV 2015|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||9|
|State||Published - 17 Feb 2015|
|Event||15th IEEE International Conference on Computer Vision, ICCV 2015 - Santiago, Chile|
Duration: 11 Dec 2015 → 18 Dec 2015
|Name||Proceedings of the IEEE International Conference on Computer Vision|
|Volume||2015 International Conference on Computer Vision, ICCV 2015|
|Conference||15th IEEE International Conference on Computer Vision, ICCV 2015|
|Period||11/12/15 → 18/12/15|
Bibliographical noteFunding Information:
The research was supported in part by the Israel Science Foundation, Grants No. 1265/14 and 1284/12, I-CORE program of the Israel PBC and ISF (Grant No. 4/11) and the European Research Council (ERC Starting Grant "SurfComp", Grant No. 307754).
© 2015 IEEE.