Detection and analysis of moving objects in infrared image sequences based on supervised learning

Tianxu Zhang; Wei Zhang; Jun Shen

doi:10.1117/12.539039

25 September 2003 Detection and analysis of moving objects in infrared image sequences based on supervised learning

Tianxu Zhang, Wei Zhang, Jun Shen

Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539039
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China

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.

Citation Download Citation

Tianxu Zhang, Wei Zhang, and Jun Shen "Detection and analysis of moving objects in infrared image sequences based on supervised learning", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.539039

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