Feature matching via guided motion field consensus

Yizhang Liu; Changcai Yang; Xiong Pan; Zejun Zhang; Zhiyuan Liu

doi:10.1117/12.2539631

14 August 2019 Feature matching via guided motion field consensus

Yizhang Liu, Changcai Yang, Xiong Pan, Zejun Zhang, Zhiyuan Liu

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 1117921 (2019) https://doi.org/10.1117/12.2539631
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

Abstract

In this paper, we proposed a simple yet substantially efficient approach termed as Feature Matching via Guided Motion Field Consensus. The key idea of our approach is to model the transformation between two images by using the motion smooth constraint and use matching results on a small correspondence set with high inlier ratio to guide the matching on the whole image correspondences. In addition, we adopt a new regularization to overcome the overfitting of the matching process. Experiments demonstrate the practicability of our approach, and it is better than the state-of-the-art methods with better accuracy in feature matching.

Citation Download Citation

Yizhang Liu, Changcai Yang, Xiong Pan, Zejun Zhang, and Zhiyuan Liu "Feature matching via guided motion field consensus", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 1117921 (14 August 2019); https://doi.org/10.1117/12.2539631

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