Institutional Repository of Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Holographic Feature Learning of Egocentric-Exocentric Videos for Multi-Domain Action Recognition | |
Huang, Yi1,2,3; Yang, Xiaoshan1,2,3; Gao, Junyun1,2,3; Xu, Changsheng1,2,3 | |
发表期刊 | IEEE TRANSACTIONS ON MULTIMEDIA |
ISSN | 1520-9210 |
2022 | |
卷号 | 24页码:2273-2286 |
摘要 | Though existing cross-domain action recognition methods successfully improve the performance on videos of one view (e.g., egocentric videos) by transferring the knowledge from videos of another view (e.g., exocentric videos), they have limitations in generality because the source and target domains need to be fixed aforehand. In this paper, we propose to solve a more practical task of multi-domain action recognition on egocentric-exocentric videos, which aims to learn a single model to recognize test videos from either egocentric perspective or exocentric perspective by transferring knowledge between two domains. Though previous cross-domain methods can also transfer knowledge from one domain to another one by learning view-invariant representations of two video domains, they are not suitable for the multi-domain action recognition task because they always suffer from the problem of losing view-specific visual information. As a solution to the multi-domain action recognition task, we propose to map a video from either egocentric perspective or exocentric perspective to a global feature space (we call it holographic feature space) that shares both view-invariant and view-specific visual knowledge of two views. Specially, we decompose the video feature into view-invariant component and view-specific component, where view-specific component is written into memory networks for saving view-specific visual knowledge. The final holographic feature combines view-invariant feature and view-specific features of two views based on the memory networks. We demonstrate the effectiveness of the proposed method with extensive experimental results on two public datasets. Moreover, the good performances under the semi-supervised setting show the generality of our model. |
关键词 | Videos Feature extraction Visualization Task analysis Computational modeling Target recognition Prototypes Egocentric videos exocentric videos holographic feature multi-domain action recognition |
DOI | 10.1109/TMM.2021.3078882 |
关键词[WOS] | NETWORKS |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2018AAA0100604] ; National Natural Science Foundation of China[61720106006] ; National Natural Science Foundation of China[61721004] ; National Natural Science Foundation of China[62072455] ; National Natural Science Foundation of China[U1836220] ; National Natural Science Foundation of China[U1705262] ; National Natural Science Foundation of China[61872424] ; Key Research Program of Frontier Sciences of CAS[QYZDJ-SSW-JSC039] ; Beijing Natural Science Foundation[L201001] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Key Research Program of Frontier Sciences of CAS ; Beijing Natural Science Foundation |
WOS研究方向 | Computer Science ; Telecommunications |
WOS类目 | Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications |
WOS记录号 | WOS:000793839600005 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 多模态智能 |
国重实验室规划方向分类 | 多模态协同认知 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/49459 |
专题 | 模式识别国家重点实验室_多媒体计算 |
通讯作者 | Xu, Changsheng |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Peng Cheng Lab, Shenzhen 518066, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Huang, Yi,Yang, Xiaoshan,Gao, Junyun,et al. Holographic Feature Learning of Egocentric-Exocentric Videos for Multi-Domain Action Recognition[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2022,24:2273-2286. |
APA | Huang, Yi,Yang, Xiaoshan,Gao, Junyun,&Xu, Changsheng.(2022).Holographic Feature Learning of Egocentric-Exocentric Videos for Multi-Domain Action Recognition.IEEE TRANSACTIONS ON MULTIMEDIA,24,2273-2286. |
MLA | Huang, Yi,et al."Holographic Feature Learning of Egocentric-Exocentric Videos for Multi-Domain Action Recognition".IEEE TRANSACTIONS ON MULTIMEDIA 24(2022):2273-2286. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Holographic Feature (2409KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 |
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