Improving Mixture Gaussian Background Model by Integrating Trace Information Obtained from Kalman Filter

摘要：

Intelligent video analysis, which analyzes behaviors of moving objects in the scene, determines their trajectories, morphological changes and detects abnormal behaviors by setting certain rules, is a combination of techniques such as image processing, computer vision, artificial intelligence, and so on. The very algorithm system mainly includes four parts. They are foreground extraction, object recognition, tracking and high-level processing named behavior understanding. Among them, foreground extraction is the most crucial and basic part which has great impact on the follow-up operations. Our work in this paper improves mixture Gaussian background model, a popular foreground extraction algorithm, by integrating trace information obtained from Kalman filter. This helps remove large blocks of noise caused by suddenly illumination change or non-periodic sway of branches and get a more accurate mask image.

作者: HE Shan GUAN Qing XU Sheng LI Ying WU Yao

作者单位: School of Communication and Information, University of Electronic Science and Technology of China, Cheng Du, China

会议类型: 国际会议

会议名称: 2010 International Conference on Communications,Circuits and Systems(2010年通信、电路与系统国际会议)

会议地点: 成都

会议语种:英文

页码: 378-382

在线出版日期: 2010-06-28（万方平台首次上网日期，不代表论文的发表时间）