Model-Based Eye-Tracking Method for Low-Resolution Eye-Images

نویسندگان

  • Takashi FUKUDA
  • Kosuke MORIMOTO
  • Hayato YAMANA
چکیده

Techniques for estimating gaze without restricting user movements are highly desired for their potential applications. Although commercial gaze estimation systems achieve high accuracy using infrared light, gaze estimation systems with webcams have become indispensable because of their low price. The problem using webcams is that their resolution is too low to estimate the direction of eye-gaze accurately without restricting user movements. Lowresolution eye-images have strong sources of noise that result in inaccurate estimation. In this paper, we propose a novel gaze-estimation method that uses both image processing and geometrical processing to reduce various kinds of noise in low-resolution eye-images and thereby achieve high accuracy. In our experiments, the mean horizontal error of 5 participants is 3.0° and the mean vertical error is 1.5° with calibration. Author

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تاریخ انتشار 2011