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Proceedings Paper

Mean shift-based object tracking in FLIR imagery using multiple features
Author(s): Wei Yang; Junshan Li; Deqin Shi; Wen Cheng
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Paper Abstract

A novel object tracking algorithm for FLIR imagery based on mean shift using multiple features is proposed to improve the tracking performance. First, the appearance model of infrared object is represented in the combination of gray space, LBP texture space, and orientation space with different feature weight. And then, the mean shift algorithm is employed to find the object location. An on-line feature weight update mechanism is developed based on Fisher criteria, which measure the discrimination of object and background effectively. Experiment results demonstrate the effectiveness and robustness of the proposed method for object tracking in FLIR imagery.

Paper Details

Date Published: 30 October 2009
PDF: 6 pages
Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74960T (30 October 2009); doi: 10.1117/12.832386
Show Author Affiliations
Wei Yang, Xi'an Research Institute of High Technology (China)
Junshan Li, Xi'an Research Institute of High Technology (China)
Deqin Shi, Xi'an Research Institute of High Technology (China)
Wen Cheng, Xi'an Research Institute of High Technology (China)


Published in SPIE Proceedings Vol. 7496:
MIPPR 2009: Pattern Recognition and Computer Vision
Mingyue Ding; Bir Bhanu; Friedrich M. Wahl; Jonathan Roberts, Editor(s)

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