Facial and Eye Gaze Detection

  • Authors:
  • Kang Ryoung Park;Jeong Jun Lee;Jaihie Kim

  • Affiliations:
  • -;-;-

  • Venue:
  • BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
  • Year:
  • 2002

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Abstract

Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM (Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye's movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.8 cm of RMS error.