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Proceedings Paper

Infrared small target tracking by discriminative classification based on Gaussian mixture model in compressive sensing domain
Author(s): Chuanyun Wang; Fei Song; Shiyin Qin
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Paper Abstract

Addressing the problems of infrared small target tracking in forward looking infrared (FLIR) system, a new infrared small target tracking method is presented, in which features binding of both target gray intensity and spatial relationship is implemented by compressive sensing so as to construct the Gaussian mixture model of compressive appearance distribution. Subsequently, naive Bayesian classification is carried out over testing samples acquired with non-uniform sampling probability to identify the most credible location of targets from background scene. A series of experiments are carried out over four infrared small target image sequences with more than 200 images for each sequence, the results demonstrate the effectiveness and advantages of the proposed method in both success rate and precision rate.

Paper Details

Date Published: 10 February 2017
PDF: 9 pages
Proc. SPIE 10250, International Conference on Optical and Photonics Engineering (icOPEN 2016), 102502L (10 February 2017); doi: 10.1117/12.2266719
Show Author Affiliations
Chuanyun Wang, BeiHang Univ. (China)
Shenyang Aerospace Univ. (China)
Fei Song, Chinese Institute of Electronics (China)
Shiyin Qin, BeiHang Univ. (China)

Published in SPIE Proceedings Vol. 10250:
International Conference on Optical and Photonics Engineering (icOPEN 2016)
Anand Krishna Asundi; Xiyan Huang; Yi Xie, Editor(s)

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