Abstract
In the astronaut-space robot interaction based on hand gestures, the detection and location of hands are the premise and basis of vision-based hand gesture recognition and hand tracking. In this paper, the SSD (Single Shot Multibox Detector) which is a kind of deep learning model is utilized to detect and locate astronaut’s hands for space human-robot interaction (SHRI) based on hand gestures. First of all, in order to meet the needs of hand detection and location, an improved SSD model is designed to detect hands when they are shown as small targets in images. Then, a platform for SHRI is built and a set of hand gestures for SHRI are designed. Finally, the proposed SSD model is validated experimentally on a homemade hand gesture database for proving the superiority of this improved SSD model to small target hands detection.
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Acknowledgments
The authors would like to acknowledge the support from the Research Fund of China Manned Space Engineering (050102), the Key Research Program of the Chinese Academy of Sciences (Y4A3210301), the Natural Science Foundation of China under Grant No. 51775541, 51575412, 51575338 and 51575407, the EU Seventh Framework Programme (FP7)-ICT under Grant No. 611391, and the Research Project of State Key Lab of Digital Manufacturing Equipment & Technology of China under Grant No. DMETKF2017003.
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Gao, Q., Liu, J., Ju, Z., Zhang, L., Li, Y., Liu, Y. (2018). Hand Detection and Location Based on Improved SSD for Space Human-Robot Interaction. In: Chen, Z., Mendes, A., Yan, Y., Chen, S. (eds) Intelligent Robotics and Applications. ICIRA 2018. Lecture Notes in Computer Science(), vol 10984. Springer, Cham. https://doi.org/10.1007/978-3-319-97586-3_15
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DOI: https://doi.org/10.1007/978-3-319-97586-3_15
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