In order to investigate whether or not checkpoints of features surrounding the eye are suitable for eye tracking, we evaluated the checkpoints using statistical hypothesis testing. By combining the checkpoints of features surrounding the eye, the eye tracking system using the template matching was effective for the eye detection. The parameters of the checkpoints were empirically determined to detect the eye in any individual. The statistical hypothesis testing revealed that the empirical setting values of the checkpoints were significantly different from actual facial features obtained using face images. We investigated suitable parameters of the checkpoints derived from actual facial features obtained with facial images. It was revealed that new checkpoint setting's were effective in drastically reducing the possibility of incorrect eye detection, although the correct detection rate was slightly decreased.
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