Beyond Tree Structure Models: A New Occlusion Aware Graphical Model for 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 | 2015-12 |
| 会议日期 | 2015.12.11-2015.12.18 |
| 会议地点 | Santiago, Chile |
| 关键词 | Graphical Model |
| 页码 | 1976-1984 |
| 英文摘要 | Occlusion is a main challenge for human pose estimation, which is largely ignored in popular tree structure models. The tree structure model is simple and convenient for exact inference, but short in modeling the occlusion coherence especially in the case of self-occlusion. We propose an occlusion aware graphical model which is able to model both self-occlusion and occlusion by the other objects simultaneously. The proposed model structure can encodes the interactions between human body parts and objects, and hence enables it to learn occlusion coherence from data discriminatively. We evaluate our model on several public benchmarks for human pose estimation including challenging subsets featuring significant occlusion. The experimental results show that our method obtains comparable accuracy with the state-of-the-arts, and is robust to occlusion for 2D human pose estimation |
| 会议录 | Proceeding of IEEE International Conference on Computer Vision
 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/11648]  |
| 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. Beyond Tree Structure Models: A New Occlusion Aware Graphical Model for Human Pose Estimation[C]. 见:. Santiago, Chile. 2015.12.11-2015.12.18. |
入库方式： OAI收割
来源：自动化研究所
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