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    3D Candidate Selection Method for Pedestrian Detection on Non-Planar Roads

    3D Candidate Selection Method for Pedestrian Detection on Non-Planar Roads


    This paper describes a stereo-vision-based candidate selection method for pedestrian detection from a moving vehicle. Non-dense 3D maps are computed by using epipolar geometry and a robust correlation process. Non-flat road assumption is used for correcting pitch angle variations. Thus, non obstacle points can be easily removed since they lay on the road. Generic obstacles are selected by using Subtractive Clustering algorithm in a 3D space with an adaptive radius. This clustering technique can be configurable for different types of obstacles. An optimal configuration for pedestrian detection is presented in this work.

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    Titel :

    3D Candidate Selection Method for Pedestrian Detection on Non-Planar Roads

    Beteiligte:
    Fernandez, D. (Autor:in) / Parra, I. (Autor:in) / Sotelo, M. A. (Autor:in) / Revenga, P. (Autor:in) / Alvarez, S. (Autor:in) / Gavilan, M. (Autor:in)
    Erschienen in:

    2007 IEEE Intelligent Vehicles Symposium ; 1162-1167

    Erscheinungsdatum :

    2007-06-01

    Format / Umfang :

    1099701 byte

    ISBN :

    1-4244-1067-3 , 1-4244-1068-1

    ISSN :

    1931-0587

    DOI :

    https://doi.org/10.1109/IVS.2007.4290275

    Medientyp :

    Aufsatz (Konferenz)

    Format :

    Elektronische Ressource

    Sprache :

    Englisch

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