The rise of sophisticated in-car multimedia solutions has led to both positive and negative impacts on the road-user’s driving experience. A drastic increase in the number of road accidents due to drivers’ inattention is a clear negative consequence. Thus, there has been an increased interest lately in measuring real-time driver cognitive load to alert them to focus on driving. Quantifying the ability to solve a task, such as driving safely, is difficult to accomplish in terms of diversity of subjects, their emotional state or fatigue at a given time. In this paper, a pipeline is presented that obtains ground truth labels for cognitive load from video and biosignal data. The experimental design for inducing the cognitive load state and the data processing are presented as part of the pipeline. This methodology was validated using the biosignal data collected from 31 subjects and conducting a comparative analysis between cognitive and non-cognitive states.


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    Titel :

    Inducing and obtaining cognitive load ground truth data in automotive scenarios


    Beteiligte:
    Osten, Wolfgang (Herausgeber:in) / Nikolaev, Dmitry P. (Herausgeber:in) / Zhou, Jianhong (Jessica) (Herausgeber:in) / Sultana, Alina E. (Autor:in) / Nicolae, Irina E. (Autor:in) / Fulop, Szabolcs (Autor:in) / Aursulesei, Ruxandra (Autor:in) / O'Callaghan, David (Autor:in)

    Kongress:

    Fifteenth International Conference on Machine Vision (ICMV 2022) ; 2022 ; Rome, Italy


    Erschienen in:

    Proc. SPIE ; 12701 ; 1270116


    Erscheinungsdatum :

    07.06.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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