A Robust and Fast Motion Segmentation Method for Video Sequences

摘要：

In this paper, a robust and time-saving method for moving object detection in video sequences is proposed. Unlike methods based on complex background updating models which are computationally expensive, the proposed method can segment moving targets in real-time. It mainly includes three steps. In the first step, the background image is reconstructed by using the long-term and short-term background updating algorithms. The long-term updating algorithm detects the noisy motion regions and ghosts, while the short-term updating algorithm models the background pixel values with single Gaussian distributions, which can deal with slow lighting changes. In the second step, the shadows are removed via the color space based approach. Finally, different targets are located with the projection method. Experimental results prove that the presented method is robust to background noisy motions, shadows and scene changes, and can segment multiple objects precisely and quickly.

关键词： Motion segmentation video sequences background updating shadow removing color space

作者: Ying-hong Liang Sen Guo Zhi-yan Wang Xiao-wei Xu Xiao-ye Cao

作者单位: School of Computer Science, South China University of Technology, Guangzhou 510640, China;Shenzhen i Shenzhen institute of information technology, Shenzhen 518029, China School of Computer Science, South China University of Technology, Guangzhou 510640, China

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）