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Remote Sens. 2016, 8(1), 28; doi:10.3390/rs8010028

Two Algorithms for the Detection and Tracking of Moving Vehicle Targets in Aerial Infrared Image Sequences

1
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No.9 Dengzhuang South Road, Beijing 100094, China
2
University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Academic Editors: Gonzalo Pajares Martinsanz, Norman Kerle and Prasad S. Thenkabail
Received: 28 October 2015 / Revised: 11 December 2015 / Accepted: 28 December 2015 / Published: 31 December 2015
View Full-Text   |   Download PDF [3821 KB, uploaded 31 December 2015]   |  

Abstract

In this paper, by analyzing the characteristics of infrared moving targets, a Symmetric Frame Differencing Target Detection algorithm based on local clustering segmentation is proposed. In consideration of the high real-time performance and accuracy of traditional symmetric differencing, this novel algorithm uses local grayscale clustering to accomplish target detection after carrying out symmetric frame differencing to locate the regions of change. In addition, the mean shift tracking algorithm is also improved to solve the problem of missed targets caused by error convergence. As a result, a kernel-based mean shift target tracking algorithm based on detection updates is also proposed. This tracking algorithm makes use of the interaction between detection and tracking to correct the tracking errors in real time and to realize robust target tracking in complex scenes. In addition, the validity, robustness and stability of the proposed algorithms are all verified by experiments on mid-infrared aerial sequences with vehicles as targets. View Full-Text
Keywords: moving target detection and tracking; symmetric frame differencing; mean shift; infrared image sequence; aerial platform moving target detection and tracking; symmetric frame differencing; mean shift; infrared image sequence; aerial platform
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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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Cao, Y.; Wang, G.; Yan, D.; Zhao, Z. Two Algorithms for the Detection and Tracking of Moving Vehicle Targets in Aerial Infrared Image Sequences. Remote Sens. 2016, 8, 28.

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