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Action unit detection and key frame selection for human activity prediction

文献类型：期刊论文

作者Wang, Haoran1; Yuan, Chunfeng2; Shen, Jifeng3; Yang, Wankou4; Ling, Haibin5
刊名NEUROCOMPUTING
出版日期2018-11-27
卷号318页码:109-119
关键词Activity prediction Key frame selection Action unit detection Structured SVM
ISSN号0925-2312
DOI10.1016/j.neucom.2018.08.037
通讯作者Wang, Haoran(wanghaoran@ise.neu.edu.cn)
英文摘要Human activity prediction aims to recognize an unfinished activity with limited appearance and motion information. In this paper, we propose to predict an incomplete activity by combining the mid-level action units and the discriminative key frames exploited from each activity class. Specifically, we extract a great deal of action-related volumes from activity videos. Based on a set of low-level powerful features, similar volumes are aggregated into a mid-level feature, named action unit. Then, we detect these action units in each activity video and generate the frame feature by computing the distribution of concurrent action units in a single frame. Notice that human can easily recognize an incomplete activity using scanty key frames composed of representative interrelated action units together. The key frames in each activity class are selected by computing the entropy of each single frame feature. Finally, a structured SVM is trained to recognize activities with different observation ratios. The proposed approach is evaluated on several publicly available datasets in comparison with state-of-the-art approaches. The experimental results and analysis clearly demonstrate the effectiveness of the proposed approach. (C) 2018 Published by Elsevier B.V.
WOS关键词ACTION RECOGNITION ; TRAJECTORIES ; VIDEOS ; MODEL
资助项目National Natural Science Foundation of China[61603080] ; National Natural Science Foundation of China[61701101] ; National Natural Science Foundation of China[61773117] ; Fundamental Research Funds for the Central Universities of China[N160413002] ; Doctor Startup Fund of Liaoning Province[201601019] ; NSF of Jiangsu Province[BK20150470]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000445763500011
出版者ELSEVIER SCIENCE BV
资助机构National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities of China ; Doctor Startup Fund of Liaoning Province ; NSF of Jiangsu Province
源URL[http://ir.ia.ac.cn/handle/173211/25747]  
专题自动化研究所_模式识别国家重点实验室_视频内容安全团队
通讯作者Wang, Haoran
作者单位1.Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
3.Jiangsu Univ, Sch Elect & Informat Engn, Zhenjiang 212013, Peoples R China
4.Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China
5.Temple Univ, Dept Comp & Informat Sci, Philadelphia, PA 19122 USA
推荐引用方式
GB/T 7714		 Wang, Haoran,Yuan, Chunfeng,Shen, Jifeng,et al. Action unit detection and key frame selection for human activity prediction[J]. NEUROCOMPUTING,2018,318:109-119.
APA Wang, Haoran,Yuan, Chunfeng,Shen, Jifeng,Yang, Wankou,&Ling, Haibin.(2018).Action unit detection and key frame selection for human activity prediction.NEUROCOMPUTING,318,109-119.
MLA Wang, Haoran,et al."Action unit detection and key frame selection for human activity prediction".NEUROCOMPUTING 318(2018):109-119.

入库方式： OAI收割

来源：自动化研究所

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