Traffic accidents are a significant global issue, causing injuries, property damage, and traffic congestion, which often delay emergency responses. These challenges highlight the need for more efficient and effective real-time traffic management systems that can improve safety, reduce response times, and improve overall traffic flow. This study proposes a two-stage approach using CCTV footage to enable automatic accident detection and vehicle damage classification. In the first stage, the YOLOv8 model is used for real-time accident detection, achieving a mean Average Precision (mAP) of 0.84, indicating its high accuracy in identifying accidents. The second stage incorporates the EfficientNetB0 model to classify vehicle damage into three categories: normal, moderate, and severe, with an overall accuracy of 0.76, while MobileNetV2 achieves an accuracy of 0.7. By integrating these models, the system demonstrates significant potential for accident detection and vehicle damage classification, thereby contributing to a smarter traffic monitoring system, thereby improving emergency response services for evacuation.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Real-Time Vehicle Damage Classification Based on Accident Detection from CCTV Footage Using Two-Stage Approach


    Beteiligte:


    Erscheinungsdatum :

    03.02.2025


    Format / Umfang :

    1004871 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Real-time Vehicle Count, Speed Estimation and Number Plate Detection using CCTV Footage

    Gaikwad, P. S. / Chaudhari, Pratik / Bhole, Pragati et al. | IEEE | 2023


    CCTV Navigation apparatus and method for providing CCTV footage on plural paths

    CHOI JUNG WOON | Europäisches Patentamt | 2017

    Freier Zugriff

    CCTV Accident Guidance System using CCTV Camera

    KIM DONG CHUL / KANG YONG GU / LEE KYUNG SOO | Europäisches Patentamt | 2020

    Freier Zugriff

    CCTV VEHICLE NUMBER RECOGNITION SYSTEM USING CCTV

    SEO YONG UK | Europäisches Patentamt | 2021

    Freier Zugriff

    CCTV VEHICLE NUMBER RECOGNITION SYSTEM USING CCTV

    Europäisches Patentamt | 2021

    Freier Zugriff