Pedestrian safety has become an important issue for automobile design. Although a lot of research has been done or is ongoing in developing in-car camera-based pedestrian protection systems, robust and reliable in-car camera based pedestrian analysis is still very challenging, especially for real-time systems or large scale dataset analysis. In this paper, we propose a new pedestrian detection and analysis system based on automatic categorization. A category-based multi-stage pedestrian detection and data analysis approach is developed to efficiently process the extremely large scale driving data collected in this research. The experimental results on part of the collecting dataset show that the proposed method is promising.


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    Titel :

    Automatic categorization-based multi-stage pedestrian detection


    Beteiligte:
    Yang, Kai (Autor:in) / Du, Eliza Yingzi (Autor:in) / Jiang, Pingge (Autor:in) / Chen, Yaobin (Autor:in) / Sherony, Rini (Autor:in) / Takahashi, Hiroyuki (Autor:in)


    Erscheinungsdatum :

    01.09.2012


    Format / Umfang :

    646646 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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