Kinect-based Taiwanese sign-language recognition system

Greg C. Lee, Fu Hao Yeh*, Yi Han Hsiao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)


Gesture-recognition is an important component for many intelligent human–computer interaction applications. For example, a realtime sign-language recognition system would detect and interpret hand gestures. Many vision-based sign-language recognition methods have been proposed over the years with mix results of usability. Some system are limited to recognize only a few gestures, while others require the use of 3D camera to provides depth information to improve recognition accuracy. In this paper, a Kinect-based Taiwanese sign-language recognition system is proposed. Three main features are extracted from the signing gestures, namely hand positions, hand signing direction, and hand shapes. The hand positions are readily available through the input sensor. The signing direction is determined using HMM on trajectory of the hand movement, and a SVM is trained and used to recognize the hand shapes. Experimental results show that the proposed system achieved an 85.14 % recognition rate.

Original languageEnglish
Pages (from-to)261-279
Number of pages19
JournalMultimedia Tools and Applications
Issue number1
Publication statusPublished - 2016 Jan 1


  • Gesture recognition
  • Kinect
  • Sign-language recognition

ASJC Scopus subject areas

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


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