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Sensors 2017, 17(2), 384; doi:10.3390/s17020384

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

1
School of Optoelectronics, Image Engineering & Video Technology Lab, Beijing Institute of Technology, Beijing 100081, China
2
Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Academic Editor: A. G. Unil Perera
Received: 28 November 2016 / Revised: 5 February 2017 / Accepted: 10 February 2017 / Published: 16 February 2017
(This article belongs to the Special Issue Infrared Detectors)
View Full-Text   |   Download PDF [3790 KB, uploaded 16 February 2017]   |  

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. View Full-Text
Keywords: infrared-visible registration; objective motion vector; normalized location; edge orientation; mismatch elimination infrared-visible registration; objective motion vector; normalized location; edge orientation; mismatch elimination
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Sun, X.; Xu, T.; Zhang, J.; Li, X. A Hierarchical Framework Combining Motion and Feature Information for Infrared-Visible Video Registration. Sensors 2017, 17, 384.

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