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Eye blink based fatigue detection

Alojzij Blatnik (2016) Eye blink based fatigue detection. MSc thesis.

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    This master thesis analyses possible approaches for eye fatigue detection based on eye blinking. We have found multiple approaches for eye blink detection. The approach based on consequent images acquired from a video camera is the least invasive for the user and does not require additional hardware, hence we analysed multiple methods of this approach. The method which gave best results detects eye blinks by analysing movements on two consequent images. The second method which also gives satisfactory results detects eye blinks using open eye template matching. The third method detects eye blinks by analysing the amount of black color in the eye region. This method showed that the amount of black color does not decrease enough to reliably detect eye blinks, since the surface of eyelashes increases the amount of black color in the eye area when the eye is closed. For these methods we have built a framework which in one thread captures images at maximum speed of the camera and saves them at the end of a linked list. In the second thread, the framework takes the images from the beginning of the linked list and transmits them to the method for processing. That makes it possible to detect very short eye blinks and to use a method which does not run in real time all the time. When the method detects low eye blink rate, it informs the user with an audio signal. We developed a solution for personal computers with the Linux operating system and smartphones with the Android operating system.

    Item Type: Thesis (MSc thesis)
    Keywords: eye fatigue detection, blink, smartphone, computer vision, OpenCV
    Number of Pages: 80
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    prof. dr. Branko Šter283Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1537158083)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 3503
    Date Deposited: 02 Sep 2016 17:08
    Last Modified: 30 Sep 2016 11:37
    URI: http://eprints.fri.uni-lj.si/id/eprint/3503

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