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Feature matching via guided motion field consensus
Author(s): Yizhang Liu; Changcai Yang; Xiong Pan; Zejun Zhang; Zhiyuan Liu
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Paper 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.

Paper Details

Date Published: 14 August 2019
PDF: 6 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 1117921 (14 August 2019); doi: 10.1117/12.2539631
Show Author Affiliations
Yizhang Liu, Fujian Agriculture and Forestry Univ. (China)
Changcai Yang, Fujian Agriculture and Forestry Univ. (China)
Xiong Pan, Fujian Agriculture and Forestry Univ. (China)
Zejun Zhang, Fujian Agriculture and Forestry Univ. (China)
Zhiyuan Liu, Fujian Agriculture and Forestry Univ. (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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