In this paper we present an example-based approach to learn a given class of complex shapes, and recognize instances of that shape with outliers. The system consists of a two-layer custom-designed neural network. We apply this approach to the recognition of pedestrians carrying objects from a single camera. The system is able to capture and model an ample range of pedestrian shapes at varying poses and camera orientations, and achieves a 90% correct recognition rate.


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    Title :

    Modelling pedestrian shapes for outlier detection: a neural net based approach


    Contributors:
    Nanda, H. (author) / Benabdelkedar, C. (author) / Davis, L. (author)


    Publication date :

    2003-01-01


    Size :

    384668 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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