Context Aware Model for Articulated Human Pose Estimation
文献类型：会议论文
| 作者 | Fu LR(付连锐) ; Junge Zhang; Kaiqi Huang
|
| 出版日期 | 2015-09 |
| 会议日期 | 2015.9.27-2015.9.30 |
| 会议地点 | Quebec, Canada |
| 关键词 | Context Aware Model |
| 英文摘要 | Simple tree model prevails for 2D pose estimation for its simplicity and efficiency. However, the limited kinetic constraints often lead to double-counting and damage the accuracy of leaf parts, and this is largely ignored in previous work. In this paper, we propose a novel enhanced tree model which incorporates both local kinetic constraints and global contextual constraints among non-adjacent parts. By introducing virtual parts, we are able to model richer constraints within a tree structure and dynamic programming can be utilized for efficient inference. Experiments on public benchmarks show that our method is more effective in tackling double counting problem and can improve the localization accuracy, especially for the challenging lower limbs |
| 会议录 | Proceeding of IEEE Conference on Image Processing
 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/11649]  |
| 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 | Fu LR,Junge Zhang,Kaiqi Huang. Context Aware Model for Articulated Human Pose Estimation[C]. 见:. Quebec, Canada. 2015.9.27-2015.9.30. |
入库方式： OAI收割
来源：自动化研究所
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。