Drowsiness is one of the main reasons for road accidents in the last few years. With the improvement in technology, various accident prevention technologies are evolving. The primary objective of avoidance of road accidents can be achieved through real-time drowsiness detection of a driver using video capturing with face detection. After capturing and detecting the drowsiness by using a camera, the alarm will buzz. The position of head and blinking of eyes are used as the features to detect whether the driver is drowsy or not. The camera captures the real-time drowsiness by using Local Binary Pattern to detect the face and Haar cascade to detect the eyes. A custom eye blinking file has been developed for eye blinking detection and AdaBoost is used to focus on eye movements at the same instant of time.


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    Title :

    Driver Drowsiness Detection System based on LBP and Haar Algorithm


    Contributors:


    Publication date :

    2020-10-07


    Size :

    1523183 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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