An Updating Method of Self-adaptive Background for Moving Objects Detection in Video
Background subtraction is a general and simple method in real-time detection of moving object. However, it requires the accurate current background image, and so far, no reasonable approach has been designed and implemented for automatic background updating along with the illumination variance, which limits its applications. To overcome the above problem, a new self-adaptive background approximating and updating algorithm based on static background and kalman self-adaptive background(KAB) is presented in this paper.Moreover, the two renewal rates in KAB are obtained by the cumulants of background subtraction in object region and background region. Experimental results demonstrate that the proposed new background updating method can update the background exactly and quickly along with the variance of illumination, the renewal rates can vary with the video automatically and they bring certain noise immunity to the new dynamic background.
Di Fan Maoyong Cao Changzhi Lv
Shandong University of Science and Technology, Qingdao, 266510, China
国际会议
2008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)
镇江
英文
1497-1501
2008-07-07（万方平台首次上网日期，不代表论文的发表时间）