Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Detecting method for drivers' drowsiness applicable to individual features
It is inevitable for driver assist and warning systems to consider the drivers' state of consciousness. Drowsiness is one of the important factors in estimating the drivers' state of consciousness. A method to extract the driver's initial stage of drowsiness was developed by means of the blink measurement irrelevant to the surrounding brightness and individual characteristics with motion pictures processing. The result was that an increase of the long eyelid closure time was the key factor in estimating the initial stage of drivers' drowsiness while driving. And the state of drowsiness could be presumed by checking the frequencies of long eyelid closure time per unit period.
Detecting method for drivers' drowsiness applicable to individual features
It is inevitable for driver assist and warning systems to consider the drivers' state of consciousness. Drowsiness is one of the important factors in estimating the drivers' state of consciousness. A method to extract the driver's initial stage of drowsiness was developed by means of the blink measurement irrelevant to the surrounding brightness and individual characteristics with motion pictures processing. The result was that an increase of the long eyelid closure time was the key factor in estimating the initial stage of drivers' drowsiness while driving. And the state of drowsiness could be presumed by checking the frequencies of long eyelid closure time per unit period.
Detecting method for drivers' drowsiness applicable to individual features
Hamada, T. (Autor:in) / Ito, T. (Autor:in) / Adachi, K. (Autor:in) / Nakano, T. (Autor:in) / Yamamoto, S. (Autor:in)
01.01.2003
478793 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Detecting Method for Drivers' Drowsiness Applicable to Individual Features
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