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Robot User Control System using Hand Gesture Recognizer

수신호 인식기를 이용한 로봇 사용자 제어 시스템

  • 손수원 (고려대학교 전기전자전파공학과) ;
  • 배정훈 ;
  • 양철종 (고려대학교 전기전자전파공학과) ;
  • 왕한 (고려대학교 전기전자전파공학과) ;
  • 고한석 (고려대학교 전기전자전파공학과)
  • Received : 2011.01.27
  • Accepted : 2011.03.14
  • Published : 2011.04.01

Abstract

This paper proposes a robot control human interface using Markov model (HMM) based hand signal recognizer. The command receiving humanoid robot sends webcam images to a client computer. The client computer then extracts the intended commanding hum n's hand motion descriptors. Upon the feature acquisition, the hand signal recognizer carries out the recognition procedure. The recognition result is then sent back to the robot for responsive actions. The system performance is evaluated by measuring the recognition of '48 hand signal set' which is created randomly using fundamental hand motion set. For isolated motion recognition, '48 hand signal set' shows 97.07% recognition rate while the 'baseline hand signal set' shows 92.4%. This result validates the proposed hand signal recognizer is indeed highly discernable. For the '48 hand signal set' connected motions, it shows 97.37% recognition rate. The relevant experiments demonstrate that the proposed system is promising for real world human-robot interface application.

Keywords

References

  1. T. Schlomer, et al. "Gesture recognition with a wii controller," Proc. of the Second International Conference on Tangible and Embedded Interaction (TEI'08), Bonn, Germany. pp. 11-14, Feb. 2008.
  2. H. S. Park, et al., "HMM-based gesture recognition for robot contro," Pattern Recognition and Image Analysis, Pt 1, vol. 3522, pp. 607-614, Jun. 2005. https://doi.org/10.1007/11492429_73
  3. H. Kang, W. L. Chang, and K. C. Jung, "Recognition-based gesture spotting in video games," Pattern Recognition Letters, vol. 25, no. 15, pp. 1701-1714, Nov. 2004. https://doi.org/10.1016/j.patrec.2004.06.016
  4. D. Kortenkamp, E. Huber, and R. P. Bonasso, "Recognizing and interpreting gestures on a mobile robot," Proc. of the Thirteenth National Conference on Artificial Intelligence and the Eighth Innovative Applications of Artificial Intelligence Conference, vol 2, pp. 915-921, Aug. 1996.
  5. J. Y. Oh and C. W. Lee, "Survey: Gesture recognition techniques for intelligent robot," Journal of Control, Automation and System Engineering(in Korean), vol. 10, no. 9, pp. 771-778, Sep. 2004. https://doi.org/10.5302/J.ICROS.2004.10.9.771
  6. I. M. Kim, W. C. Kim, K. S. Yun, and J. M. Lee, "Navigation of a mobile robot using hand gesture recognition," Journal of Control, Automation and Systems engineering(in Korean), vol. 8, no. 7, Jul. 2002. https://doi.org/10.5302/J.ICROS.2002.8.7.599
  7. Y. Wu and T. S. Huang, "Vision-based gesture recognition: A review," Gesture-Based Communication in Human-Computer Interaction, vol. 1739, pp. 103-115, 1999. https://doi.org/10.1007/3-540-46616-9_10
  8. A. Just and S. Marcel, "A comparative study of two state-of-the-art sequence processing techniques for hand gesture recognition," Computer Vision and Image Understanding, vol. 113, no. 4, pp. 532-543, Apr. 2009. https://doi.org/10.1016/j.cviu.2008.12.001
  9. N. Yanghee and W. KwangYun, "Recognition of space-time hand-gestures using hidden markov model," VRST: ACM symposium on Virtual reality software and Technology, Hong Kong, China, pp. 51-58, Jul. 1996.
  10. H. K. Lee and J. H. Kim, "An HMM-based threshold model approach for gesture recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 961-973, Oct. 1999. https://doi.org/10.1109/34.799904
  11. S. Eickeler, A. Kosmala, and G. Rigoll, "Hidden markov model based continuous online gesture recognition," Fourteenth International Conference on Pattern Recognition, vol. 1, no. 2, pp. 1206-1208, Aug. 1999.
  12. S. W. Shon, J. Beh, C. J. Yang, H. Wang, and H. S. Ko, "Hand motiondesign for performance enhancement of vision based hand signal recognizer," Journal of IEEK, SP, vol. 48, no. 4, Jul. 2011.
  13. P. Dreuw, et al., "Speech recognition techniques for a sign language recognition system," Interspeech, Antwerp, Belguim, pp. 705-708, Aug. 2007.