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Robust Moving Object Segmentation with Two Stage Optimization
Jianwei Ding; Xin Zhao; Kaiqi Huang; Tieniu Tan
2011
会议名称The First Asian Conference on Pattern Recognition
会议录名称Pattern Recognition, 2011
页码149-153
会议日期2011
会议地点Beijing, China
摘要Inspired 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.
关键词Feature Extraction   image Colour Analysis   image Motion Analysis
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12697
专题智能感知与计算研究中心
通讯作者Kaiqi Huang
作者单位中国科学院自动化研究所
推荐引用方式
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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