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Robust Moving Object Segmentation with Two Stage Optimization
Jianwei Ding; Xin Zhao; Kaiqi Huang; Tieniu Tan
2011
Conference NameThe First Asian Conference on Pattern Recognition
Source PublicationPattern Recognition, 2011
Pages149-153
Conference Date2011
Conference PlaceBeijing, China
AbstractInspired by interactive segmentation algorithms, we propose an online and unsupervised technique to extract moving objects from videos captured by stationary cameras. Our method consists of two main optimization steps, from local optimal extraction to global optimal segmentation. In the first stage, reliable foreground and background pixels are extracted from input image by modeling distributions of foreground and background with color and motion cues. These reliable pixels provide hard constraints for the next step of segmentation. Then global optimal segmentation of moving object is implemented by graph cuts in the second stage. Experimental results on several challenging videos demonstrate the effectiveness and robustness of the proposed approach.
KeywordFeature Extraction   image Colour Analysis   image Motion Analysis
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12697
Collection智能感知与计算研究中心
Corresponding AuthorKaiqi Huang
Affiliation中国科学院自动化研究所
Recommended Citation
GB/T 7714
Jianwei Ding,Xin Zhao,Kaiqi Huang,et al. Robust Moving Object Segmentation with Two Stage Optimization[C],2011:149-153.
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