| Cross-Agent Action Recognition |
| Wang, Hongsong ; Wang, Liang
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| 发表期刊 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
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| ISSN | 1051-8215
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| 2018-10-01
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| 卷号 | 28期号:10页码:2908-2919 |
| 通讯作者 | Wang, Liang(wangliang@nlpr.ia.ac.cn)
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| 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
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| DOI | 10.1109/TCSVT.2017.2746092
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| 关键词[WOS] | VIEW ACTION RECOGNITION
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| 收录类别 | SCI
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| 语种 | 英语
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| 资助项目 | Beijing Natural Science Foundation[4162058]
; National Natural Science Foundation of China[61420106015]
; National Natural Science Foundation of China[61633021]
; National Natural Science Foundation of China[61525306]
; National Key Research and Development Program of China[2016YFB1001000]
; 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]
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| 项目资助者 | National Key Research and Development Program of China
; National Natural Science Foundation of China
; Beijing Natural Science Foundation
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| WOS研究方向 | Engineering
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| WOS类目 | Engineering, Electrical & Electronic
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| WOS记录号 | WOS:000448517900040
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| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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| 引用统计 |
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| 文献类型 | 期刊论文
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| 条目标识符 | http://ir.ia.ac.cn/handle/173211/22804
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| 专题 | 模式识别实验室
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| 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
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| 第一作者单位 | 模式识别国家重点实验室
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| 通讯作者单位 | 模式识别国家重点实验室
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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.
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| APA |
Wang, Hongsong,&Wang, Liang.(2018).Cross-Agent Action Recognition.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,28(10),2908-2919.
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| 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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