SportsCap: Monocular 3D Human Motion Capture and Fine-Grained Understanding in Challenging Sports Videos
2021-10
发表期刊INTERNATIONAL JOURNAL OF COMPUTER VISION
ISSN0920-5691
EISSN1573-1405
卷号129期号:10页码:2846-2864
DOI10.1007/s11263-021-01486-4
摘要Markerless motion capture and understanding of professional non-daily human movements is an important yet unsolved task, which suffers from complex motion patterns and severe self-occlusion, especially for the monocular setting. In this paper, we propose SportsCap-the first approach for simultaneously capturing 3D human motions and understanding fine-grained actions from monocular challenging sports video input. Our approach utilizes the semantic and temporally structured sub-motion prior in the embedding space for motion capture and understanding in a data-driven multi-task manner. To enable robust capture under complex motion patterns, we propose an effective motion embedding module to recover both the implicit motion embedding and explicit 3D motion details via a corresponding mapping function as well as a sub-motion classifier. Based on such hybrid motion information, we introduce a multi-stream spatial-temporal graph convolutional network to predict the fine-grained semantic action attributes, and adopt a semantic attribute mapping block to assemble various correlated action attributes into a high-level action label for the overall detailed understanding of the whole sequence, so as to enable various applications like action assessment or motion scoring. Comprehensive experiments on both public and our proposed datasets show that with a challenging monocular sports video input, our novel approach not only significantly improves the accuracy of 3D human motion capture, but also recovers accurate fine-grained semantic action attribute.
关键词Human modeling 3D motion capture Motion understanding
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收录类别SCIE ; EI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000681171700003
出版者SPRINGER
原始文献类型Article; Early Access
引用统计
文献类型期刊论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/127834
专题信息科学与技术学院_PI研究组_马月昕
信息科学与技术学院_PI研究组_虞晶怡组
信息科学与技术学院_博士生
信息科学与技术学院_PI研究组_许岚组
通讯作者Xu, Lan; Yu, Jingyi
作者单位
1.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai Engn Res Ctr Intelligent Vis & Imaging, Shanghai, Peoples R China;
2.Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Shanghai, Peoples R China;
3.Univ Chinese Acad Sci, Shanghai, Peoples R China;
4.Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan, Peoples R China
第一作者单位信息科学与技术学院
通讯作者单位信息科学与技术学院
第一作者的第一单位信息科学与技术学院
推荐引用方式
GB/T 7714
Chen, Xin,Pang, Anqi,Yang, Wei,et al. SportsCap: Monocular 3D Human Motion Capture and Fine-Grained Understanding in Challenging Sports Videos[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2021,129(10):2846-2864.
APA Chen, Xin,Pang, Anqi,Yang, Wei,Ma, Yuexin,Xu, Lan,&Yu, Jingyi.(2021).SportsCap: Monocular 3D Human Motion Capture and Fine-Grained Understanding in Challenging Sports Videos.INTERNATIONAL JOURNAL OF COMPUTER VISION,129(10),2846-2864.
MLA Chen, Xin,et al."SportsCap: Monocular 3D Human Motion Capture and Fine-Grained Understanding in Challenging Sports Videos".INTERNATIONAL JOURNAL OF COMPUTER VISION 129.10(2021):2846-2864.
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