Driver Drowsiness Detection Using Multi-Channel Second Order Blind Identifications

It is well known that blink, yawn, and heart rate changes give clue about a human's mental state, such as drowsiness and fatigue. In this paper, image sequences, as the raw data, are captured from smart phones which serve as non-contact optical sensors. Video streams containing subject's f...

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Veröffentlicht in:	IEEE access 2019, Vol.7, p.11829-11843
Hauptverfasser:	Zhang, Chao, Wu, Xiaopei, Zheng, Xi, Yu, Shui
Format:	Artikel
Sprache:	eng
Schlagworte:	Biomedical monitoring blink Blood volume blood volume pulse (BVP) Complexity theory Decision analysis Driver fatigue drowsiness detection Head movement Heart rate Heuristic algorithms Optical measuring instruments Physiology second-order blind identification (SOBI) Signal processing algorithms Vehicles Video data Yawn
Online-Zugang:	Volltext
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