Earticle

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

Abstract
 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

키워드

저자

• Kun Qian [ School of Automation, Southeast University, No.2 Sipailou, Nanjing, 210096, China ]
• Chunhua Hu [ School of Information Science and Technology, Nanjing Forestry University No.159 Longpan Road, Nanjing, 210037, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605