Adaptive Background Update Based on Mixture Models of Gaussian

摘要：

In computer vision system, detection of moving targets has interference in subsequent processes including classification, tracking and recognition. Background subtraction method is commonly used in image segmentation for moving region of video. This paper puts emphasis on background model update based on mixture models of Gaussian in complicated situation, and implements an adaptive learning method to update background models. Each pixel is classified into 4 different types: still background, dynamic background, moving object, temporary still object. And the proposed method reduces the computational complexity.

作者: Feng Wang Shuguang Dai

作者单位: School of Optical-Electrical and Computer Enginnering,University of Shanghai for Science and Technology,Shanghai 200093,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Information and Automation(2009年 IEEE信息与自动化国际学术会议)

会议地点: 珠海、澳门

会议语种:英文

页码: 336-339

在线出版日期: 2009-06-22（万方平台首次上网日期，不代表论文的发表时间）