[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9717/kmms.2016.19.5.797

Drowsiness Sensing System by Detecting Eye-blink on Android based Smartphones

Vununu, Caleb (Dept. of IT Convergence and Application Engineering, PuKyong National University)
Seung, Teak-Young (Dept. of IT Convergence and Application Engineering, PuKyong National University)
Moon, Kwang-Seok (Dept. of Electronics Eng., PuKyong Nat'l University)
Lee, Suk-Hwan (l University)
Kwon, Ki-Ryong (Dept. of Information Security, TongMyong University)

Publication Information

Journal of Korea Multimedia Society / v.19, no.5, 2016 , pp. 797-807 More about this Journal

Abstract

The discussion in this paper aims to introduce an approach to detect drowsiness with Android based smartphones using the OpenCV platform tools. OpenCV for Android actually provides powerful tools for real-time body's parts tracking. We discuss here about the maximization of the accuracy in real-time eye tracking. Then we try to develop an approach for detecting eye blink by analyzing the structure and color variations of human eyes. Finally, we introduce a time variable to capture drowsiness.

Keywords

Eye-blink Detection; Drowsiness Sensing System; Global Maximum Point; Global Minimum Point; Closed Eyes Detection;

Citations & Related Records

Reference

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