Unsupervised Spatio-Temporal Segmentation for Extracting Moving Objects in Video Sequences
Unsupervised Spatio-Temporal Segmentation for Extracting Moving Objects in Video Sequences作者机构:Institute of Image Communication and information ProcessingShanghai Jiaotong University Institute of Image Communication and Information ProcessingShanghai Jiaotong University
出 版 物:《Journal of Shanghai Jiaotong university(Science)》 (上海交通大学学报(英文版))
年 卷 期:2009年第14卷第2期
页 面:154-161页
核心收录:
学科分类:0711[理学-系统科学] 07[理学] 08[工学] 080203[工学-机械设计及理论] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0802[工学-机械工程]
基 金:the National Natural Science Foundationof China(No.60502034)
主 题:segmentation spatio-temporal region growing outlier rejection watershed
摘 要:Extraction of moving objects is an important and fundamental research topic for many video applications. This paper addresses an unsupervised spatio-temporal segmentation scheme to extract moving objects from video *** temporal segmentation localizes moving objects by comparing the motion vector of each block in each frame with the corresponding global motion vector estimated by an outlier rejection(OR) based ***,the temporal compensation utilizing the temporal coherence of moving objects is considered in the temporal segmentation to solve the temporarily stopping *** detected moving regions usually have discontinuous boundaries and some *** regions are then compensated in the spatial domain. In the spatial segmentation,the watershed algorithm considering the global information improves the accuracy of segmentation in the spatial *** modified mean filter is presented to suppress some *** using a fusion module,moving objects are *** on various sequences have successfully demonstrated the validity of the proposed scheme.