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Conference papers

Drowsy Driver Detection System Using Eye Blink Patterns

Abstract : This paper presents an automatic drowsy driver monitoring and accident prevention system that is based on monitoring the changes in the eye blink duration. Our proposed method detects visual changes in eye locations using the proposed horizontal symmetry feature of the eyes. Our new method detects eye blinks via a standard webcam in real-time at 110fps for a 320×240 resolution. Experimental results in the JZU [3] eye-blink database showed that the proposed system detects eye blinks with a 94% accuracy with a 1% false positive rate.
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Submitted on : Friday, September 28, 2018 - 2:50:05 PM
Last modification on : Wednesday, May 11, 2022 - 12:34:02 PM
Long-term archiving on: : Monday, December 31, 2018 - 10:33:56 AM

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Taner Danisman, Ioan Marius Bilasco, Chaabane Djeraba, Nacim Ihaddadene. Drowsy Driver Detection System Using Eye Blink Patterns. International Conference on Machine and Web Intelligence (ICMWI 2010), Oct 2010, Alger, Algeria. pp.230-233, ⟨10.1109/ICMWI.2010.5648121⟩. ⟨hal-00812315⟩

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