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Proceedings Paper

A moving target detection algorithm based on GMM and improved Otsu method
Author(s): Zhe Zhao; Yingqing Huang; Xiaoyu Jiang; Xingpeng Yan
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Paper Abstract

Based on Gaussian mixture model, an improved detection algorithm, which aimed at updating the real-time character and accuracy of the moving target detection in intelligent video surveillance systems effectively, is elaborated in this paper. It combines the advantages of GMM and improved maximum between class variance method. The algorithm not only improves the speed of detecting targets in the intelligent systems, but also solves the inherent problems efficiently in poor real-time performance and error detection problem. In conclusion, the experiment results demonstrated that the algorithm has an excellent adaptability and anti-interference performance to fit the complicated situation and changing environment.

Paper Details

Date Published: 24 November 2014
PDF: 6 pages
Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010B (24 November 2014); doi: 10.1117/12.2068911
Show Author Affiliations
Zhe Zhao, Academy of Armored Forces Engineering (China)
Yingqing Huang, Academy of Armored Forces Engineering (China)
Xiaoyu Jiang, Academy of Armored Forces Engineering (China)
Xingpeng Yan, Academy of Armored Forces Engineering (China)


Published in SPIE Proceedings Vol. 9301:
International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
Gaurav Sharma; Fugen Zhou; Jennifer Liu, Editor(s)

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