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Robot learning through observation via coarse-to-fine grained video summarization

文献类型：期刊论文

作者Zhang, Yujia1; Li, Qianzhong1,2; Zhao, Xiaoguang1; Tan, Min1
刊名APPLIED SOFT COMPUTING
出版日期2021-02-01
卷号99页码:15
ISSN号1568-4946
关键词Robotic vision Learning through observation Coarse-to-fine video summarization
DOI10.1016/j.asoc.2020.106913
通讯作者Zhang, Yujia(zhangyujia2014@ia.ac.cn)
英文摘要Learning human daily behavior is important for enabling robots to perform tasks and assist people. However, most prior work either requires specific sensors for capturing data or heavily relies on prior knowledge of human motion, which can be difficult to obtain. To alleviate the above problems, we propose a novel pipeline for robots to learn human behavior based on coarse-to-fine video summarization using a single Kinect camera. Specifically, the robot first retrieves information of general interest followed by a task-specific content retrieval, then focuses on fine-grained motion clips of human behavior, and guides itself by using an object-centric learning method to complete the desired task. Our work has three unique advantages: (1) it enables the robot to effectively capture granularity hierarchies of human behavior which efficiently exploits multi-stage information while alleviating disturbances and redundancies in visual data; (2) it obtains knowledge by focusing on object movements in summarized motion clips which does not require any prior knowledge of human motion; (3) it only requires a single Kinect sensor for the robot to learn human behavior which is fully accessible and easy to equip. Experiments in an office environment were performed to validate the efficiency and effectiveness of the proposed framework, and the results indicate that this approach exhibits good learning efficacy for the robot to understand human behavior and learn to perform tasks. (C) 2020 Elsevier B.V. All rights reserved.
资助项目National Key Research and Development Program of China[2017YFC0820203] ; National Natural Science Foundation of China[61673378]
WOS研究方向Computer Science
语种英语
出版者ELSEVIER
WOS记录号WOS:000608174700007
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/42915]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者Zhang, Yujia
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Yujia,Li, Qianzhong,Zhao, Xiaoguang,et al. Robot learning through observation via coarse-to-fine grained video summarization[J]. APPLIED SOFT COMPUTING,2021,99:15.
APA Zhang, Yujia,Li, Qianzhong,Zhao, Xiaoguang,&Tan, Min.(2021).Robot learning through observation via coarse-to-fine grained video summarization.APPLIED SOFT COMPUTING,99,15.
MLA Zhang, Yujia,et al."Robot learning through observation via coarse-to-fine grained video summarization".APPLIED SOFT COMPUTING 99(2021):15.

入库方式： OAI收割

来源：自动化研究所

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