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| A Modeling and Target Detection Algorithm Based on Adaptive Adjustment K-ρ for Mixture Gaussian Background |
| Han Ming①③ Liu Jiao-min①② Meng Jun-ying①③ Wang Zhen-zhou② |
①(College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China)
②(Institute of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China)
③(Department of Computer Science, Shijiazhuang University, Shijiazhuang 050035, China) |
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Abstract A modeling and target detection algorithm based on adaptive adjustment K-ρ for Mixture Gaussian background is proposed for complex scenes with non-stationary background. The Mixture Gaussian Model (GMM) is applied to learn the distribution of per-pixel in the temporal domain, then a method is constructed for adaptively adjusting the number K of Gaussian components, and the number K will be added, deleted, or merged with similar Gaussian components according to different situation. Furthermore, two new parameters are introduced in the adaptive parameter model, and the parameter ρ is adaptively adjusted according to the actual situation, which assures that the background modeling and target detection real-time changes with the pixel. The property of real-time and accuracy reduces the loss of information for moving target and improves the robustness and convergence. Experimental results show that the algorithm responses rapidly when the scene changes in the sequence of video with many uncertain factors, and realizes adaptive background modeling and accurate target detection.
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Received: 18 September 2013
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Corresponding Authors:
Han Ming
E-mail: han_ming2008@126.com
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2014, Vol. 36 
