Kinect-based Taiwanese sign-language recognition system

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

研究成果: 雜誌貢獻文章同行評審

24 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
頁(從 - 到)261-279
頁數19
期刊Multimedia Tools and Applications
75
發行號1
DOIs
出版狀態已發佈 - 2016 一月 1

ASJC Scopus subject areas

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

指紋 深入研究「Kinect-based Taiwanese sign-language recognition system」主題。共同形成了獨特的指紋。

引用此