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    Detection and recognition of traffic signs inside the attentional visual field of drivers

    Detection and recognition of traffic signs inside the attentional visual field of drivers


    Traffic sign detection and recognition systems are essential components of Advanced Driver Assistance Systems and self-driving vehicles. In this contribution we present a vision-based framework which detects and recognizes traffic signs inside the attentional visual field of drivers. This technique takes advantage of the driver 3D absolute gaze point obtained through the combined use of a front-view stereo imaging system and a non-contact 3D gaze tracker. We used a linear Support Vector Machine as a classifier and a Histogram of Oriented Gradient as features for detection. Recognition is performed by using Scale Invariant Feature Transforms and color information. Our technique detects and recognizes signs which are in the field of view of the driver and also provides indication when one or more signs have been missed by the driver.

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    Title :

    Detection and recognition of traffic signs inside the attentional visual field of drivers

    Contributors:
    Zabihi, S.J. (author) / Zabihi, S.M. (author) / Beauchemin, S.S. (author) / Bauer, M.A. (author)
    Published in:

    2017 IEEE Intelligent Vehicles Symposium (IV) ; 583-588

    Publication date :

    2017-06-01

    Size :

    726200 byte

    ISBN :

    978-1-5090-4804-5 , 978-1-5090-4803-8

    DOI :

    https://doi.org/10.1109/IVS.2017.7995781

    Type of media :

    Conference paper

    Type of material :

    Electronic Resource

    Language :

    English

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