ORGM: Occlusion Relational Graphical Model for Human Pose Estimation
文献类型:期刊论文
作者 | Fu, Lianrui1![]() ![]() ![]() |
刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
![]() |
出版日期 | 2017-02-01 |
卷号 | 26期号:2页码:927-941 |
关键词 | Occlusion Pose Estimation Spacial Relationship Mixture Graphical Model |
DOI | 10.1109/TIP.2016.2639441 |
文献子类 | Article |
英文摘要 | Articulated human pose estimation from monocular image is a challenging problem in computer vision. Occlusion is a main challenge for human pose estimation, which is largely ignored in popular tree structured models. The tree structured 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 relational graphical model, which is able to model both self-occlusion and occlusion by the other objects simultaneously. The proposed model can encode the interactions between human body parts and objects, and 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 is superior to the previous state-of-the-arts, and is robust to occlusion for 2D human pose estimation. |
WOS关键词 | PICTORIAL STRUCTURES ; FLEXIBLE MIXTURES ; PARTS |
WOS研究方向 | Computer Science ; Engineering |
语种 | 英语 |
WOS记录号 | WOS:000404773100025 |
资助机构 | National Natural Science Foundation of China(61322209 ; International Partnership Program of the Chinese Academy of Science(173211KYSB20160008) ; 61673375 ; 61403387) |
源URL | [http://ir.ia.ac.cn/handle/173211/15238] ![]() |
专题 | 自动化研究所_智能感知与计算研究中心 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Ctr Res Intelligent Percept & Comp, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Fu, Lianrui,Zhang, Junge,Huang, Kaiqi. ORGM: Occlusion Relational Graphical Model for Human Pose Estimation[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2017,26(2):927-941. |
APA | Fu, Lianrui,Zhang, Junge,&Huang, Kaiqi.(2017).ORGM: Occlusion Relational Graphical Model for Human Pose Estimation.IEEE TRANSACTIONS ON IMAGE PROCESSING,26(2),927-941. |
MLA | Fu, Lianrui,et al."ORGM: Occlusion Relational Graphical Model for Human Pose Estimation".IEEE TRANSACTIONS ON IMAGE PROCESSING 26.2(2017):927-941. |
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。