Cross-Agent Action Recognition
文献类型：期刊论文
| 作者 | Wang, Hongsong ; Wang, Liang
|
| 刊名 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
 |
| 出版日期 | 2018-10-01 |
| 卷号 | 28期号:10页码:2908-2919 |
| 关键词 | Cross-agent human action recognition animal action recognition |
| ISSN号 | 1051-8215 |
| DOI | 10.1109/TCSVT.2017.2746092 |
| 通讯作者 | Wang, Liang(wangliang@nlpr.ia.ac.cn) |
| 英文摘要 | 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. |
| WOS关键词 | VIEW ACTION RECOGNITION |
| 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] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000448517900040 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/22803]  |
| 专题 | 自动化研究所_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. |
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。