Practical gaze point computing method by 3d position estimation of facial and eye features

  • Authors:
  • Kang Ryoung Park

  • Affiliations:
  • Division of Media Technology, SangMyung University, Seoul, Republic of Korea

  • Venue:
  • AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
  • Year:
  • 2004

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Abstract

This paper addresses the accurate gaze detection method by tracking facial and eye movement at the same time For that, we implemented our gaze detection system with a wide and a narrow view stereo camera In order to make it easier to detect the facial and eye feature positions, the dual IR-LED illuminators are also used for our system The performance of detecting facial features could be enhanced by Support Vector Machine and the eye gaze position on a monitor is computed by a multi-layered perceptron Experimental results show that the RMS error of gaze detection is about 2.4 degrees (1.68 degrees on X axis and 1.71 degrees on Y axis at the Z distance of 50 cm).