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CLC number: TP391

On-line Access: 2017-05-24

Received: 2015-11-26

Revision Accepted: 2016-03-24

Crosschecked: 2017-04-22

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714


Li-gang Liu


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Frontiers of Information Technology & Electronic Engineering  2017 Vol.18 No.5 P.644-657


Feature matching using quasi-conformal maps

Author(s):  Chun-xue Wang, Li-gang Liu

Affiliation(s):  School of Mathematical Sciences, University of Science and Technology of China, Hefei 230026, China

Corresponding email(s):   lgliu@ustc.edu.cn

Key Words:  Feature correspondence, Quasi-conformal map, Splitting method

Chun-xue Wang, Li-gang Liu. Feature matching using quasi-conformal maps[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(5): 644-657.

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author="Chun-xue Wang, Li-gang Liu",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

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%A Chun-xue Wang
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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
%@ 1869-1951
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -

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.


概要:本文提出一种在两幅图像之间寻找保持几何关系一致的特征点对应的自动方法。虽然传统的SIFT(Scale-invariant feature transform)方法能得到一些对应点,但是其中有些对应点是无效的,我们的目标就是去除其中的无效对应点,使得剩下的对应点能够保持在拟共形映射下的几何关系。我们将问题描述为集成Beltrami系数项的拟共形映射的带约束优化问题,是通过交替求解线性系统和线性约束的凸二次规划来求解的。我们的方法非常简单而且对噪声点不敏感,优于一些已有的方法。


Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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