Automated Quantification of Eye Blink Rate Using VIOLA-JONES Algorithm

Mohammad Hamdan, Hisham A. Shehadeh
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Abstract

In this article, we have proposed a novel tool that helps to objectively quantify eye blink rate. Using the proposed algorithm, a threshold for normal blink rate can be set to test those who have to reduce eye blink rate and are prone to ocular surface dryness. The statistical results show excellent agreement between software-detected number of blinks and visually measured with 90% accuracy for the participants. In addition, the comparison between our tool and other approaches of eye blink monitoring shows that our tool is competitive with only 5% wasted blinks.
基于VIOLA-JONES算法的眨眼频率自动量化
在本文中,我们提出了一种有助于客观量化眨眼率的新工具。使用该算法,可以设置正常眨眼频率的阈值,以测试那些必须减少眨眼频率并容易眼表干燥的人。统计结果表明,软件检测的眨眼次数与视觉测量的眨眼次数之间的一致性非常好,准确率为90%。此外,我们的工具与其他眨眼监测方法的比较表明,我们的工具具有竞争力,只有5%的眨眼浪费。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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