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Proceedings Paper

Detection and analysis of moving objects in infrared image sequences based on supervised learning
Author(s): Tianxu Zhang; Wei Zhang; Jun Shen
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Paper Abstract

Optical Flow computing doesn't require the rigorous corresponding relationship among features of sequential images, so this approach is widely used in computer vision field including detection and dynamic analysis of moving objects. But it is rarely used in infrared images because of the high noise levels of images. This article proposes a moving object pre-detection algorithm based on supervised learning, image pair difference significance test and minimum cost Bayes rule. This algorithm can not only efficiently be applied in indicating moving objects in infrared image sequences, but also in optical flow computing and behavior analysis of the moving objects.

Paper Details

Date Published: 25 September 2003
PDF: 8 pages
Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.539039
Show Author Affiliations
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)
Wei Zhang, Huazhong Univ. of Science and Technology (China)
Jun Shen, Univ. de Bordeaux III (France)


Published in SPIE Proceedings Vol. 5286:
Third International Symposium on Multispectral Image Processing and Pattern Recognition

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