An Improved Mixture-of-Gaussians Model for Background Subtraction

作     者：Heng-hui Li Jin-feng Yang Xiao-hui Ren Ren-biao Wu Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Tianjin 300300 P.R.China 

会议名称：《2008 9th International Conference on Signal Processing(ICSP’2008)》

会议日期：2008年

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：supported by NSFC(Grant No.60605008) TianJin Natural Science Foundation(Grant No.07ZCKFGX03700) 

摘      要：The process of background subtraction is always a key step in ***,the mixture of Gaussians（MOG） works well in the background modeling and has been widely used in *** this paper,some new additional constrains are imposed on the updating process of statistics of Gaussian *** reduce computational cost,the numbers of Gaussian models are selected dynamically based on the maximum recurrence time interval（MRTI）.The experimental results show that the proposed method performs well in complex background modeling,and the efficiency in object detection is improved significantly.