Real-time gender recognition based on 3D human body shape for human-robot interaction

Authors:
Ren C Luo;Xiehao Wu
Affiliations:
National Taiwan University, Taipei, Taiwan Roc;National Taiwan University, Taipei, Taiwan Roc
Venue:
Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction
Year:
2014

Citing 5
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Abstract

Gender roles influence behavior in social interactions. Thus, real-time gender recognition is essential in Human-Robot Interaction (HRI) for providing timely gender information to improve the experience of HRI. Considering the HRI scenario, a 3D-human-body-shape-based gender recognition is investigated. The 3D information is obtained by processing the depth image from an RGB-D camera. In addition, a machine learning method based on a Support Vector Machine (SVM) was applied. The experimental results showed that our system could achieve real-time accurate gender recognition. It enriched the diversity of existing methods for HRI application.