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Static hand gesture recognition with parallel CNNs for space human-robot interaction
Gao Q(高庆); Liu JG(刘金国); Ju, Zhaojie; Li YM(李杨民); Zhang, Tian; Zhang, Lu
作者部门空间自动化技术研究室
会议名称10th International Conference on Intelligent Robotics and Applications, ICIRA 2017
会议日期August 16-18, 2017
会议地点Wuhan, China
会议录名称Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
出版者Springer Verlag
出版地Berlin
2017
页码462-473
收录类别EI
EI收录号20173504107695
产权排序1
ISSN号0302-9743
ISBN号978-3-319-65288-7
关键词Hri Hand Gesture Recognition Cnn Space Robot
摘要As a new type of human-robot interaction (HRI), hand gesture has many advantages such as natural operation, rich expression and not subject to environ-mental constraints. So it is very suitable for space human-robot interaction tasks in special and harsh environment. Considering that static hand gesture is one of the main gesture expressions in human-computer interaction, so a parallel convolution neural networks (CNNs) is designed to improve the accuracy of static hand gesture recognition in the conditions of complex background and changing illumination. In addition, the method is applied to the operation of space human-robot system with hand gesture control. Various space HRI hand gestures from different subjects are evaluated and tested, and experimental results demonstrate that the proposed method outperforms the single-channel CNN methods and other popular methods with a higher accuracy.
语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/20867
专题空间自动化技术研究室
通讯作者Liu JG(刘金国)
作者单位1.The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
2.University of the Chinese Academy of Science, Beijing, 100049, China
3.The Department of Electromechanical Engineering, University of Macau, Taipa, 999078, China
4.School of Computing, University of Portsmouth, Portsmouth, PO1 3HE, United Kingdom
5.Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing, 100094, China
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GB/T 7714
Gao Q,Liu JG,Ju, Zhaojie,et al. Static hand gesture recognition with parallel CNNs for space human-robot interaction[C]. Berlin:Springer Verlag,2017:462-473.
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