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Cross-Agent Action Recognition
Wang, Hongsong; Wang, Liang
发表期刊IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
ISSN1051-8215
2018-10-01
卷号28期号:10页码:2908-2919
通讯作者Wang, Liang(wangliang@nlpr.ia.ac.cn)
摘要An action is something which is done by an agent. Most action recognition researchers merely focus on the actions to be recognized, and ignore the differences of agents. Philosophers and behaviorists discover that actions are common among many species, but are performed in different ways and with different levels of sophistication. In this paper, in order to bridge action recognition tasks between different agents, we introduce a new problem, cross-agent action recognition, i.e., recognizing action for one particular agent (target) while training from other agents (source). We model this problem under three different scenarios: single source and single target, multiple sources and single target, and multiple sources and multiple targets. To this end, corresponding methods based on transfer learning are proposed to address these problems. We further design three different strategies to model the situation when a partial labeled data is provided for the target. Experimental results show that the performances of the transfer method are generally better than those of the comparative method without transfer learning, especially when we have multiple sources. Particularly, the transfer method outperforms the others significantly when the source is a human adult. In addition, cross-agent method significantly improves the results when partially labeled data is provided for the target. These demonstrate that for action recognition, knowledge can be transferred across different agents. A straightforward application of this finding is to use human action (training data is abundant) data to enhance animal action recognition.
关键词Cross-agent human action recognition animal action recognition
DOI10.1109/TCSVT.2017.2746092
关键词[WOS]VIEW ACTION RECOGNITION
收录类别SCI
语种英语
资助项目National Key Research and Development Program of China[2016YFB1001000] ; National Natural Science Foundation of China[61525306] ; National Natural Science Foundation of China[61633021] ; National Natural Science Foundation of China[61420106015] ; Beijing Natural Science Foundation[4162058]
项目资助者National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation
WOS研究方向Engineering
WOS类目Engineering, Electrical & Electronic
WOS记录号WOS:000448517900040
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/22804
专题智能感知与计算研究中心
通讯作者Wang, Liang
作者单位Univ Chinese Acad Sci, Chinese Acad Sci, Ctr Res Intelligent Percept & Comp, Natl Lab Pattern Recognit,Inst Automat, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Wang, Hongsong,Wang, Liang. Cross-Agent Action Recognition[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2018,28(10):2908-2919.
APA Wang, Hongsong,&Wang, Liang.(2018).Cross-Agent Action Recognition.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,28(10),2908-2919.
MLA Wang, Hongsong,et al."Cross-Agent Action Recognition".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 28.10(2018):2908-2919.
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