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Automatic Eye Winks Interpretation System for Human-Machine Interface

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Abstract

This paper proposes an automatic eye-wink interpretation system for human-machine interface to benefit the severely handicapped people. Our system consists of (1) applying the support vector machine (SVM) to detect the eyes, (2) using the template matching algorithm to track the eyes, (3) using SVM classifier to verify the open or closed eyes and convert the eye winks into a sequence of codes (0 or 1), and (4) applying the dynamic programming to translate the code sequence to a certain valid command. Different from the previous eye-gaze tracking methods, our system identifies the open or closed eye, and then interprets the eye winking as certain commands for human-machine interface. In the experiments, our system demonstrates better performance as well as higher accuracy.

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Correspondence to Che Wei-Gang.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Wei-Gang, C., Huang, C. & Hwang, W. Automatic Eye Winks Interpretation System for Human-Machine Interface. J Image Video Proc 2007, 065184 (2007) doi:10.1155/2007/65184

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Keywords

  • Support Vector Machine
  • Image Processing
  • Pattern Recognition
  • Support Vector
  • Computer Vision