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Robust Moving Object Segmentation with Two Stage Optimization
Jianwei Ding; Xin Zhao; Kaiqi Huang; Tieniu Tan
Conference NameThe First Asian Conference on Pattern Recognition
Source PublicationPattern Recognition, 2011
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
Document Type会议论文
Corresponding AuthorKaiqi Huang
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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