Abstract Multi-channel feature for pedestrian detection is proposed to solve problems of real-time and accuracy of pedestrian detection in this paper. Different from traditional low level feature extraction algorithm, channels such as colours, gradient magnitude and gradient histogram are combined to extract multi-channel feature for describing pedestrian. Then classifier is trained by AdaBoost algorithm. Finally the performance of the algorithm is tested in MATLAB. The result demonstrates that the algorithm has an excellent performance on both detection precision and speed.


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    Titel :

    Multi-channel Feature for Pedestrian Detection


    Beteiligte:
    He, Zhixiang (Autor:in) / Xu, Meihua (Autor:in) / Guo, Aiying (Autor:in)


    Erscheinungsdatum :

    2017-01-01


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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