The goal of this work is to detect a human figure image and localize his joints and limbs along with their associated pixel masks. In this work we attempt to tackle this problem in a general setting. The dataset we use is a collection of sports news photographs of baseball players, varying dramatically in pose and clothing. The approach that we take is to use segmentation to guide our recognition algorithm to salient bits of the image. We use this segmentation approach to build limb and torso detectors, the outputs of which are assembled into human figures. We present quantitative results on torso localization, in addition to shortlisted full body configurations.


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    Title :

    Recovering human body configurations: combining segmentation and recognition


    Contributors:
    Mori, G. (author) / Xiaofeng Ren, (author) / Efros, A.A. (author) / Malik, J. (author)


    Publication date :

    2004-01-01


    Size :

    999985 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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