Korean Word Search Interface for Wearable Computers Using a Wrist-Mounted Camera Device

  • Hyun Park
  • Hyo-Seok Shi
  • Heon-Hui Kim
  • Kwang-Hyun Park
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 272)


This paper presents a hand shape recognition method and its application to Korean word search interface for wearable computers. We first describe a hand shape recognition method composed of hand region segmentation and recognition. To enforce the recognition performance, a user adaptation process is also proposed in algorithmic details. A Korean word search system is then proposed, which is based on the recognition of Korean manual alphabets using a wrist-mounted camera device. The effectiveness of the proposed method is verified through several experiments for evaluating recognition performance.


Wrist-mounted camera Korean manual alphabet recognition user adaptation hand shape recognition 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Do, J.-H., Kim, J.-B., Park, K.-H., Bang, W.-C., Bien, Z.Z.: Soft Remote Control System using Hand Pointing Gestures. International Journal of Human-Friendly Welfare Robotic Systems (HWRS) 3(1), 27–30 (2002)Google Scholar
  2. 2.
    Mistry, P., Maes, P.: SixthSense – A Wearable Gestural Interface. In: Proceedings of SIGGRAPH Asia 2009, Yokohama, Japan (2009)Google Scholar
  3. 3.
    Park, H., Shi, H.-S., Kim, H.-H., Park, K.-H.: A User Adaptation Method for Hand Shape Recognition Using Wrist-Mounted Camera. The Journal of the Korea Institute of Electronic Communication Sciences 8(6), 805–814 (2013)Google Scholar
  4. 4.
    Hamada, Y., Shimada, N., Shirai, Y.: Hand shape estimation using image transition network. In: Proceedings of Workshop on Human Motion, pp. 161–166 (2000)Google Scholar
  5. 5.
    Ong, E.-J., Bowden, R.: A boosted classifier tree for hand shape detection. In: Proceedings of Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 889–894 (2004)Google Scholar
  6. 6.
    Athitsos, V., Sclaroff, S.: An appearance-based framework for 3D hand shape classification and camera viewpoint estimation. In: Proceedings of Fifth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 40–45 (2002)Google Scholar
  7. 7.
    Quek, F.K.H.: Unencumbered gestural interaction. IEEE MultiMedia 3(4), 36–47 (1996)CrossRefGoogle Scholar
  8. 8.
    Ong, S.C.W., Ranganath, S.: Automatic sign language analysis: a survey and the future beyond lexical meaning. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(6), 873–891 (2005)CrossRefGoogle Scholar
  9. 9.
    Yu, Z., Xilin, C., Debin, Z., Hongxun, Y., Wen, G.: Adaptive sign language recognition with exemplar extraction and MAP/IVFS. IEEE Signal Processing Letters 17(3), 297–300 (2010)CrossRefGoogle Scholar
  10. 10.
    Hasanuzzaman, M., Ampornaramveth, V., Zhang, T., Bhuiyan, M.A., Shirai, Y., Ueno, H.: Real-time vision-based gesture recognition for human robot interaction. In: Proceeding of the IEEE International Conference on Robotics and Biomimetices, August 22-26, pp. 413–418 (2004)Google Scholar
  11. 11.
    Park, K.H.: Betterment of Mobile Sign Language Recognition System. IEEK System and Control 43(1), 1–10 (2006)Google Scholar
  12. 12.
    Jones, M.J., Rehg, J.M.: Statistical color models with application to skin detection. In: Proceedings of the IEEE Computer Vision and Pattern Recognition, pp. 274–280 (1999)Google Scholar
  13. 13.
    Sigal, L., Sclaroff, S., Athitsos, V.: Skin color-based video segmentation under time-varying illumination. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(7), 862–877 (2004)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Hyun Park
    • 1
  • Hyo-Seok Shi
    • 1
  • Heon-Hui Kim
    • 1
  • Kwang-Hyun Park
    • 2
  1. 1.Art and Robotics InstituteKwangwoon UniversitySeoulRepublic of Korea
  2. 2.School of RoboticsKwangwoon UniversitySeoulRepublic of Korea

Personalised recommendations