Frontiers of Information Technology & Electronic Engineering
>> 2017,
Volume 18,
Issue 5
doi:
10.1631/FITEE.1500411
Article
Featurematching using quasi-conformalmaps
School of Mathematical Sciences, University of Science and Technology of China, Hefei 230026, China
Available online: 2017-06-22
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Abstract
We present a fully automatic method for finding geometrically consistent correspondences while discarding outliers from the candidate point matches in two images. Given a set of candidate matches provided by scale-invariant feature transform (SIFT) descriptors, which may contain many outliers, our goal is to select a subset of these matches retaining much more geometric information constructed by a mapping searched in the space of all diffeomorphisms. This problem can be formulated as a constrained optimization involving both the Beltrami coefficient (BC) term and quasi-conformal map, and solved by an efficient iterative algorithm based on the variable splitting method. In each iteration, we solve two subproblems, namely a linear system and linearly constrained convex quadratic programming. Our algorithm is simple and robust to outliers. We show that our algorithm enables producing more correct correspondences experimentally compared with state-of-the-art approaches.
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