基于眼宽比映射(EARM)的眨眼检测眼疲劳估计

Akihiro Kuwahara, Kazu Nishikawa, Rin Hirakawa, Hideaki Kawano, Yoshihisa Nakatoh
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引用次数: 14

摘要

随着信息社会的到来,眼睛的健康在全世界都受到威胁。已经提出了避免这些问题的规则和系统,但由于物理和时间限制以及所涉及的成本以及缺乏眼睛健康意识,大多数用户没有使用它们。在本文中,我们通过检测眼睛的自发眨眼来估计眼睛的疲劳敏感性。实验结果表明,该方法能够以较低的成本对眨眼进行高精度的分类。我们还发现自发眨眼率的中位数与客观估计眼睛疲劳和受试者意识到眼睛疲劳之间的时间有很强的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Eye fatigue estimation using blink detection based on Eye Aspect Ratio Mapping(EARM)

With the advent of the information society, the eyes' health is threatened all over the world. Rules and systems have been proposed to avoid these problems, but most users do not use them due to the physical and time constraints and costs involved and the lack of awareness of eye health. In this paper, we estimate the eye fatigue sensitivity by detecting spontaneous blinks with high accuracy. The experimental results show that the proposed Eye Aspect Ratio Mapping can classify blinks with high accuracy at a low cost. We also found a strong correlation between the median SBR (Spontaneous Blink Rate) and the time between the objective estimation of eye fatigue and the subject's awareness of eye fatigue.

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