Dual-hand detection for human-robot interaction by a parallel network based on hand detection and body pose estimation

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	Dual-hand detection for human-robot interaction by a parallel network based on hand detection and body pose estimation
	Zhang X(张鑫)2,3; Liu JG(刘金国)3 ; Ju ZJ(琚兆杰)1,3; Gao Q(高庆)1,2,3
刊名	IEEE Transactions on Industrial Electronics
	2019
卷号	66 期号:12 页码:9663-9672
关键词	Astraunaut assistant robot dual-hand detection human body estimation human–robot interaction parallel deep neural network
ISSN号	0278-0046
产权排序	1
英文摘要	In this paper, a parallel network based on hand detection and body pose estimation is proposed to detect and distinguish human's right and left hands. The network is employed for human-robot interaction (HRI) based on hand gestures. This method fully uses hand feature information and hand information in the human body structure. One channel in the network uses a ResNet-Inception-Single Shot MultiBox Detector to extract hand feature information for human's hand detection. The other channel estimates human body pose first and then estimates the positions of the left and right hands using the forward kinematic tree of the human skeleton structure. Thereafter, the results of the two channels are fused. In the fusion module, the human body structure can be utilized to correct hand detection results and distinguish between the right and left hands. Experimental results verify that the parallel deep neural network can effectively improve the accuracy of hand detection and distinguish between the right and left hands effectively. This method is also used for the hand-gesture-based interaction between astronauts and an astronaut assistant robot. Our method can be suitably used in this HRI system.
资助项目	National Key R&D Program of China[2018YFB1304600] ; Natural Science Foundation of China[51775541] ; CAS Interdisciplinary Innovation Team[JCTD-2018-11] ; Natural Science Foundation of China[51575412]
WOS研究方向	Automation & Control Systems ; Engineering ; Instruments & Instrumentation
语种	英语
WOS记录号	WOS:000480309400056
内容类型	期刊论文
源URL	[http://ir.sia.cn/handle/173321/25464]
专题	沈阳自动化研究所_空间自动化技术研究室
通讯作者	Liu JG(刘金国)
作者单位	1.School of Computing, University of Portsmouth, Portsmouth, PO1 3HE, United Kingdom 2.University of Chinese Academy of Sciences, Beijing 100049, China 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
推荐引用方式 GB/T 7714	Zhang X,Liu JG,Ju ZJ,et al. Dual-hand detection for human-robot interaction by a parallel network based on hand detection and body pose estimation[J]. IEEE Transactions on Industrial Electronics,2019,66(12):9663-9672.
APA	Zhang X,Liu JG,Ju ZJ,&Gao Q.(2019).Dual-hand detection for human-robot interaction by a parallel network based on hand detection and body pose estimation.IEEE Transactions on Industrial Electronics,66(12),9663-9672.
MLA	Zhang X,et al."Dual-hand detection for human-robot interaction by a parallel network based on hand detection and body pose estimation".IEEE Transactions on Industrial Electronics 66.12(2019):9663-9672.