원문정보
초록
영어
Gesture based natural human-robot interaction paradigm has few physical requirements, and thus can be deployed in many restrictive and challenging environments. In this paper, we propose a robot vision based approach to recognizing intentional arm- pointing gestures of human for an object grasping application. To overcome the limitation of robot onboard vision quality and background cluttering in natural indoor environment, a multi-cue human detection method is proposed. Human body is detected and verified by merging appearance and color features with robust head-shoulder based shape matching for reducing the false detection rate. Then intentional dynamic arm- pointing gestures of a person are identified using Dynamic Time Warping (DTW) technique, whilst unconscious motions of arm and head are rejected. Implementation of a gesture-guided robot grasping task in an indoor environment is given to demonstrate this approach, in which a fast and reliable recognition of pointing gesture recognition is achieved.
목차
1. Introduction
2. Human Body Detection and Verification
2.1. Robust Color Detection Using Color Probability Density Map
2.2. Human Target Verifications
3. Pointing Posture Recognition
4. Experiments and result
5. Conclusion
Acknowledgements
References