Malaysian Journal of Computer Science (ISSN 0127-9084)
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Article Information
Title:Adaptive Visual Gesture Recognition for Human-Robot Interaction
Auhtor(s): Mohammad Hasanuzzaman ,Saifuddin Mohammad Tareeq ,Tao Zhang ,Vuthichai Ampornaramveth ,Hironobu Gotoda ,Yoshiaki Shirai ,Haruki Ueno ,
Journal:Malaysian Journal of Computer Science (ISSN 0127-9084)
Volume:20, No 1
Year:2007
Keywords:visual gesture recognition, human-robot interaction, multi-cluster based learning, SPAK
Abstract:This paper presents an adaptive visual gesture recognition method for human–robot interaction using a knowledge-based software platform. The system is capable of recognizing users, static gestures comprised of the face and hand poses, and dynamic gestures of face in motion. The system learns new users, poses using multi-cluster approach, and combines computer vision and knowledge-based approaches in order to adapt to new users, gestures and robot behaviors. In the proposed method, a frame-based knowledge model is defined for the person-centric gesture interpretation and human-robot interaction. It is implemented using the Frame-based Software Platform for Agent and Knowledge Management (SPAK). The effectiveness of this method has been demonstrated by an experimental human-robot interaction system using a humanoid robot, namely, ‘Robovie’.
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