Moving Objects Eztraction from Video Sequences Based on GMM and Watershed
In this paper, a novel method for extracting moving objects from video sequences, which is based on Gaussian mixture model and watershed, is proposed. In order to overcome the drawback of subjective fixed threshold of traditional temporal segmentation, the difference image is modeled as a mixture of Gaussian distributions and a novel method to decide the model size and initial parameters of GMM is proposed. Then the Expectation-Maximization (EM) algorithm is fulfilled to obtain the Gaussian parameters and temporal moving area is detected; Considering the lack of traditional spatial segmentation algorithm of watershed, an improved watershed algorithm in accord with the human vision characteristics is proposed, it can restrain over-segmentation effectively; the temporal and spatial information fusion is fulfilled by ratio operation, and the video moving objects are obtained. Experimental results demonstrate the validity of the proposed algorithm.
Ren Ming-yi Li Xiao-feng Li Zai-ming
School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, China
国际会议
2009国际通信电路与系统学术会议(ICCCAS 2009)(2009 International Conference on Communications，Circuits and Systems)
成都
英文
525-529
2009-07-23（万方平台首次上网日期，不代表论文的发表时间）