NDLI: A Hierarchical Framework Combining Motion and Feature Information for Infrared-Visible Video Registration

Content Provider	MDPI
Author	Sun, Xinglong Xu, Tingfa Zhang, Jizhou Li, Xiangmin
Abstract	In this paper, we propose a novel hierarchical framework that combines motion and feature information to implement infrared-visible video registration on nearly planar scenes. In contrast to previous approaches, which involve the direct use of feature matching to find the global homography, the framework adds coarse registration based on the motion vectors of targets to estimate scale and rotation prior to matching. In precise registration based on keypoint matching, the scale and rotation are used in re-location to eliminate their impact on targets and keypoints. To strictly match the keypoints, first, we improve the quality of keypoint matching by using normalized location descriptors and descriptors generated by the histogram of edge orientation. Second, we remove most mismatches by counting the matching directions of correspondences. We tested our framework on a public dataset, where our proposed framework outperformed two recently-proposed state-of-the-art global registration methods in almost all tested videos.
File Size	3880960
File Format	PDF
e-ISSN	14248220
DOI	10.3390/s17020384
Journal	Sensors
Issue Number	2
Volume Number	17
Language	English
Publisher Date	2017-02-16
Access Restriction	Open
Subject Keyword	infrared-visible registration objective motion vector normalized location edge orientation mismatch elimination
Content Type	Text
Resource Type	Article

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A Hierarchical Framework Combining Motion and Feature Information for Infrared-Visible Video Registration