Volume 8 Number 9 (Sep. 2013)
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JCP 2013 Vol.8(9): 2239-2244 ISSN: 1796-203X
doi: 10.4304/jcp.8.9.2239-2244

A Background Modeling Algorithm Based on Improved Adaptive Mixture Gaussian

Ming Han1, Jiaomin Liu1, and Yi Sun2
1 College of Information Science and Engineering, Yanshan University, Qinhuangdao, China
2 Hebei Electric Power Research Institute, Shijiazhuang, China


Abstract—For better background modeling in scenes with nonstationary background, a background modeling algorithm based on adaptive parameter adjustment of the Mixture Gaussian is proposed. Mixture Gaussians is applied to learn the distribution of per-pixel in the temporal domain and to control adaptive adjustment of number K of Gaussian components through in increasing, deleting or merging similar Gaussian components adaptively. The new parameters Ck and φK are introuced in the adaptive parameter model. According to the actual situation,the adaptive adjustment of ρ can accurate track the real-time changes with the pixel, which improves the robustness and convergence. Experimental results show that the algorithm can rapidly response when the scene changes in the sequence of video with many uncertain factors, and realize adaptive background modeling and accurate target detection.

Index Terms—Gaussian Mixture Model; background modeling; adaptive adjustment K - ρ; moving target detection

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Cite: Ming Han, Jiaomin Liu, and Yi Sun, " A Background Modeling Algorithm Based on Improved Adaptive Mixture Gaussian," Journal of Computers vol. 8, no. 9, pp. 2239-2244, 2013.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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