CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2017-04-22
Cited: 0
Clicked: 11607
Chun-xue Wang, Li-gang Liu. Feature matching using quasi-conformal maps[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(5): 644-657.
@article{title="Feature matching using quasi-conformal maps",
author="Chun-xue Wang, Li-gang Liu",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
number="5",
pages="644-657",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500411"
}
%0 Journal Article
%T Feature matching using quasi-conformal maps
%A Chun-xue Wang
%A Li-gang Liu
%J Frontiers of Information Technology & Electronic Engineering
%V 18
%N 5
%P 644-657
%@ 2095-9184
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500411
TY - JOUR
T1 - Feature matching using quasi-conformal maps
A1 - Chun-xue Wang
A1 - Li-gang Liu
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 18
IS - 5
SP - 644
EP - 657
%@ 2095-9184
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1500411
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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