Pedestrians are the most vulnerable participants in urban traffic. The first step toward protecting pedestrians is to reliably detect them. We present a new approach for standing- and walking-pedestrian detection, in urban traffic conditions, using grayscale stereo cameras mounted on board a vehicle. Our system uses pattern matching and motion for pedestrian detection. Both 2-D image intensity information and 3-D dense stereo information are used for classification. The 3-D data are used for effective pedestrian hypothesis generation, scale and depth estimation, and 2-D model selection. The scaled models are matched against the selected hypothesis using high-performance matching, based on the Chamfer distance. Kalman filtering is used to track detected pedestrians. A subsequent validation, based on the motion field's variance and periodicity of tracked walking pedestrians, is used to eliminate false positives.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Stereo-Based Pedestrian Detection for Collision-Avoidance Applications


    Beteiligte:
    Nedevschi, S. (Autor:in) / Bota, S. (Autor:in) / Tomiuc, C. (Autor:in)


    Erscheinungsdatum :

    2009-09-01


    Format / Umfang :

    908073 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    COLLISION AVOIDANCE AND PEDESTRIAN DETECTION SYSTEMS

    NGUYEN VINCENT / NGUYEN QUANG VAN TRUONG | Europäisches Patentamt | 2021

    Freier Zugriff

    Collision avoidance and/or pedestrian detection system

    ENGLANDER BENJAMIN / SERER JULIAN | Europäisches Patentamt | 2022

    Freier Zugriff

    Collision avoidance and/or pedestrian detection system

    ENGLANDER BENJAMIN / SERER JULIAN | Europäisches Patentamt | 2018

    Freier Zugriff

    Collision avoidance and/or pedestrian detection system

    ENGLANDER BENJAMIN / SERER JULIAN | Europäisches Patentamt | 2021

    Freier Zugriff