Paper Title
Improving Blink Detection Using Convolutional Neural Networks

Abstract
Recently, million people are suffered from computer vision syndrome (a.k.a. CVS) because they are inappropriately using device screens. To prevent CVS, a software module called EyeGuard has been developed. This paper proposes an improved version of blink detection mechanism in the EyeGuard. The blink detection mechanism is implemented using convolution neural networks. The experimental evaluation reveals that the introduced mechanism has a mean absolute percentage error (MAPE) of 5.2 per cent and 4.8 per cent at the distance of 60 cm. and 80 cm., respectively. These values are significantly reduced from the original version which hasan MAPE of 14.25 per cent and 18.25 per centat the distance of 60 cm. and 80 cm., respectively. Keywords - Blink Detection, Computer Vision Syndrome, Convolutional Neural Networks.

Author - Thara Angskun, Wanchatpookhuntod, Jitimon Angskun

Published : Volume-7,Issue-5  ( May, 2020 )

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