한국멀티미디어학회논문지 (Journal of Korea Multimedia Society)

  • 제14권7호
  • /
  • Pages.866-871
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  • 2011
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  • 1229-7771(pISSN)
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  • 2384-0102(eISSN)
한국멀티미디어학회 (Korea Multimedia Society)
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Hand Gesture Recognition using Improved Hidden Markov Models

  • Xu, Wenkai (Dept. of Information Communication Engineering, Tongmyong University) ;
  • Lee, Eung-Joo (Dept. of Information Communication Engineering, Tongmyong University)
  • 투고 : 2011.03.23
  • 심사 : 2011.06.01
  • 발행 : 2011.07.30
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초록

In this paper, an improved method of hand detecting and hand gesture recognition is proposed, it can be applied in different illumination condition and complex background. We use Adaptive Skin Threshold (AST) to detect the areas of hand. Then the result of hand detection is used to hand recognition through the improved HMM algorithm. At last, we design a simple program using the result of hand recognition for recognizing "stone, scissors, cloth" these three kinds of hand gesture. Experimental results had proved that the hand and gesture can be detected and recognized with high average recognition rate (92.41%) and better than some other methods such as syntactical analysis, neural based approach by using our approach.

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참고문헌

  1. Mubarak Shah. "Face Detection and Gesture Recognition for Human-Computer Interaction," Chapter 4, pp. 83.
  2. Bai yu, "A New Method for Hand Tracking and Hand Gesture Recognition Using Improved CAMSHIFT and SVM Algorithm," Master's Dissertation, Tongmyong University Image Processing Lab, pp. 17, 2010.
  3. N. A.Viet, "A Development of Non-touch Human Computer Interface Technology using Gesture Information," Master's Dissertation Tongmyong ,University Image Processing Lab, pp. 15, 2008.
  4. B.W. Min, H.S. Yoon, and Toskiaki Ejima, "Hand Gesture Recognition Using Hidden Markov Models," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.24, No.1, 1997.
  5. T.E. Startner and A.Pentland, "Visual Recognition of American Sign Language using Hidden Markov Models," In Proceedings of the First International Workshop on Automatic Face and Gesture Recognition, pp. 189-194, 1995.
  6. J. Yang, et al., "Human Action Learning Via Hidden Markov Model," IEEE Trans. On Systems, Man, and Cybernatics, Vol.27, No.1, pp. 34-44, January 1997. https://doi.org/10.1109/3468.553220
  7. Bai Yu, Sang-Yun Park, Yun-Sik Kim, In- Gab Jeong, Soo-Yol Ok, and Eung-Joo Lee, "Hand Tracking and Hand Gesture Recognition for Human Computer Interaction," Journal of Korea Multimedia Society, Vol.14, No.2, pp. 182-193, 2011. https://doi.org/10.9717/kmms.2011.14.2.182

피인용 문헌

  1. Human-Computer Natur al User Inter face Based on Hand Motion Detection and Tracking vol.15, pp.4, 2012, https://doi.org/10.9717/kmms.2012.15.4.501
  2. Human Gesture Recognition Technology Based on User Experience for Multimedia Contents Control vol.15, pp.10, 2012, https://doi.org/10.9717/kmms.2012.15.10.1196
  3. Dynamic Human Activity Recognition Based on Improved FNN Model vol.15, pp.4, 2012, https://doi.org/10.9717/kmms.2012.15.4.417