Hand detection and location based on improved SSD for space human-robot interaction

Qing Gao, Jinguo Liu, Zhaojie Ju, Lu Zhang, Yangmin Li, Yuwang Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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.
Original languageEnglish
Title of host publicationIntelligent Robotics and Applications
Subtitle of host publication11th International Conference, ICIRA 2018, Newcastle, NSW, Australia, August 9–11, 2018, Proceedings, Part I
EditorsZhiyong Chen, Alexandre Mendes, Yamin Yan, Shifeng Chen
ISBN (Electronic)978-3-319-97586-3
ISBN (Print)978-3-319-97585-6
Publication statusPublished - Sept 2018
Event11th International Conference on Intelligent Robotics and Applications - Australia, Newcastle, Australia
Duration: 9 Aug 201811 Aug 2018

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


Conference11th International Conference on Intelligent Robotics and Applications
Abbreviated titleICIRA 2018
Internet address


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