This paper proposes a Network Shaped Cascade Classifier(NSCC) based on potential functions for pedestrian detection. Potential function is exploited to capture the nonlinear information in the training set based on the multiple sample centers. A flexible structure in NSCC is used to combine the base classifier and potential function into a nonlinear cascade classifier, and NSCC can well inherit the advantages of the base classifier. We test our classifier on INRIA dataset, and achieve a much better performance than support vector machine.


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    Titel :

    A network shaped cascade classifier based on potential functions for pedestrian detection


    Beteiligte:
    Zhang, Zhongyan (Autor:in) / Zhang, Baochang (Autor:in) / Zhao, Kun (Autor:in) / Yang, Wankou (Autor:in)


    Erscheinungsdatum :

    01.08.2014


    Format / Umfang :

    231380 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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