Robust Moving Object Segmentation with Two Stage Optimization
文献类型：会议论文
| 作者 | Jianwei Ding; Xin Zhao ; Kaiqi Huang; Tieniu Tan
|
| 出版日期 | 2011 |
| 会议日期 | 2011 |
| 会议地点 | Beijing, China |
| 关键词 | Feature Extraction image Colour Analysis image Motion Analysis |
| 页码 | 149-153 |
| 英文摘要 | 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. |
| 会议录 | Pattern Recognition, 2011
 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12697]  |
| 专题 | 自动化研究所_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]. 见:. Beijing, China. 2011. |
入库方式： OAI收割
来源：自动化研究所
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