Driving always involves risk. Various means have been proposed to reduce the risk. Critical motion detection of nearby moving vehicles is one of the important means of preventing accidents. In this paper, a computational model, which is referred to as the dynamic visual model (DVM), is proposed to detect critical motions of nearby vehicles while driving on a highway. The DVM is motivated by the human visual system and consists of three analyzers: 1) sensory analyzers, 2) perceptual analyzers, and 3) conceptual analyzers. In addition, a memory, which is called the episodic memory, is incorporated, through which a number of features of the system, including hierarchical processing, configurability, adaptive response, and selective attention, are realized. A series of experimental results with both single and multiple critical motions are demonstrated and show the feasibility of the proposed system.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Critical Motion Detection of Nearby Moving Vehicles in a Vision-Based Driver-Assistance System


    Beteiligte:
    Shen Cherng, (Autor:in) / Chiung-Yao Fang, (Autor:in) / Chia-Pei Chen, (Autor:in) / Sei-Wang Chen, (Autor:in)


    Erscheinungsdatum :

    2009-03-01


    Format / Umfang :

    1396463 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Critical motion detection of nearby moving vehicles in a vision-based driver-assistance system

    Cherng, Shen / Fang, Chiung-Yao / Chen, Chia-Pei et al. | Tema Archiv | 2009


    Detection of abnormal moving vehicles for intelligent driver assistance system

    Khac, Cuong Nguyen / Park, Ju H. / Jung, Ho-Youl | IEEE | 2016


    Computer Vision Based Driver Assistance Drowsiness Detection

    Emashharawi, Maryam J. S. / Khalifa, Othman O. / Abdul Malik, Noreha et al. | Springer Verlag | 2021


    Vision-Based Driver-Assistance Systems

    Rezaei, Mahdi / Klette, Reinhard | Springer Verlag | 2017