Facial Pose Interpretation for Human-Robot Symbiosis
Bhuiyan, Md. Al-Amin
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This paper addresses the issues for the concepts of a vision based facial pose recognition system using knowledge based approach for human-robot symbiosis. The system is based on visual information of the human face and is commenced with the face recognition and facial pose classification scheme using pattern-matching strategies. With the knowledge of the known user’s profile, facial attributes are then classified and robots are instructed to perform some specific tasks by issuing corresponding commands. This paper discusses the concepts of facial attributes for human-robot interaction and SIS with its motivations and applications especially to symbiotic robots. The present state of the art in vision, recent computing models for pose interpretation and a few implementations of these novel computing concepts are presented.
- February 2009