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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Gaze Detection by Wearable Eye-Tracking and NIR LED-Based Head-Tracking Device Based on SVR

  • Cho, Chul Woo (Department of Electronics and Electrical Engineering, Dongguk University) ;
  • Lee, Ji Woo (Department of Electronics Engineering, Dongguk University) ;
  • Shin, Kwang Yong (Department of Electronics and Electrical Engineering, Dongguk University) ;
  • Lee, Eui Chul (Division of Computer Science, Sangmyung University) ;
  • Park, Kang Ryoung (Division of Electronics and Electrical Engineering, Dongguk University) ;
  • Lee, Heekyung (Broadcasting and Telecommunications Convergence Research Laboratory, ETRI) ;
  • Cha, Jihun (Broadcasting and Telecommunications Convergence Research Laboratory, ETRI)
  • Received : 2011.03.30
  • Accepted : 2012.02.21
  • Published : 2012.08.30
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Abstract

In this paper, a gaze estimation method is proposed for use with a large-sized display at a distance. Our research has the following four novelties: this is the first study on gaze-tracking for large-sized displays and large Z (viewing) distances; our gaze-tracking accuracy is not affected by head movements since the proposed method tracks the head by using a near infrared camera and an infrared light-emitting diode; the threshold for local binarization of the pupil area is adaptively determined by using a p-tile method based on circular edge detection irrespective of the eyelid or eyelash shadows; and accurate gaze position is calculated by using two support vector regressions without complicated calibrations for the camera, display, and user's eyes, in which the gaze positions and head movements are used as feature values. The root mean square error of gaze detection is calculated as $0.79^{\circ}$ for a 30-inch screen.

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References

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