A novel video object segmentation based on recursive Kernel Density Estimation
文献类型：会议论文
| 作者 | Zhu, Q; Guanzheng Liu; Zhen Wang; Hao Chen; Xie, Y. |
| 出版日期 | 2011 |
| 会议名称 | 2011 International Conference on Information and Automation, ICIA 2011 |
| 会议地点 | Shenzhen, China |
| 英文摘要 | Dynamic video segmentation is an important research topic in computer vision. In this paper, we present a novel recursive Kernel Density Estimation based video segmentation method. In the algorithm, local maximum in the density functions is approximated recursively via a mean shift method firstly. Via a proposed thresholding scheme, components and parameters in the mixture Gaussian distributions can be selected adaptively, and finally converge to a relative stable background distribution mode. In the segmentation, foreground is firstly separated by simple background subtraction method. And then, the Bayes classifier is introduced to eliminate the misclassifications points to improve the segmentation quality. Experiments on four typical video clips are used to compare with some previous algorithms |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/3529]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 作者单位 | 2011 |
| 推荐引用方式 GB/T 7714 | Zhu, Q,Guanzheng Liu,Zhen Wang,et al. A novel video object segmentation based on recursive Kernel Density Estimation[C]. 见:2011 International Conference on Information and Automation, ICIA 2011. Shenzhen, China. |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。