Yawning detection is a key means in driver fatigue detection, which suffers difficulties including head poses, facial expressions, illumination variations, occlusions, etc. Yet, most previous methods mainly focus on frontal faces, and are deficient to deal with different facial actions under arbitrary poses in the actual driving environment. In this study, we propose a novel Joint Head Pose and Facial Action Network (JHPFA-Net) for driver yawning detection across arbitrary poses in videos, with three main parts including a Geometric-based Key-frame Selection Module (GK-Module), a Face Frontalization with Warp Attention Module (FF-Module) and a dual-channel classifier for Head Pose & Facial Action Fusion Module (HF-Module). Firstly, the GK-Module is proposed to extract geometric vectors and to construct a two-stage judgment mechanism, with the purpose of dealing with frame redundancy and improving the efficiency of JHPFA-Net structure. Secondly, distinguished with existing methods, the FF-Module is proposed to synthesize photo-realistic frontal faces, which can be used for capturing the facial actions under arbitrary poses. Finally, the HF-Module is proposed to fuse head pose attributes and facial modalities together, for the purpose of achieving pose-invariant detection and improving accuracy. Extensive experiments show that the proposed JHPFA-Net achieves state-of-the-art results comparing with some representative methods on the public YawDD benchmark, and it performs well in real-time application.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    JHPFA-Net: Joint Head Pose and Facial Action Network for Driver Yawning Detection Across Arbitrary Poses in Videos


    Beteiligte:
    Lu, Yansha (Autor:in) / Liu, Chunsheng (Autor:in) / Chang, Faliang (Autor:in) / Liu, Hui (Autor:in) / Huan, Hengqiang (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.11.2023


    Format / Umfang :

    3168486 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Yawning detection for monitoring driver fatigue based on two cameras

    Li, Lingling / Chen, Yangzhou / Li, Zhenlong | IEEE | 2009


    Driver Head Pose Detection From Naturalistic Driving Data

    Chai, Weiheng / Chen, Jiajing / Wang, Jiyang et al. | IEEE | 2023


    DD-POSE - A LARGE-SCALE DRIVER HEAD POSE BENCHMARK

    Roth, Markus / Gavrila, Dariu M. | British Library Conference Proceedings | 2019


    DD-Pose - A large-scale Driver Head Pose Benchmark

    Roth, Markus / Gavrila, Dariu M. | IEEE | 2019


    Driver Head Pose Estimation by Regression

    Tessema, Yodit / Höffken, Matthias / Kreßel, Ulrich | Springer Verlag | 2015