An approach that uses a volume model consisting of cylinders for model-based recognition of pedestrians in real-world images is presented. The human body is represented by a volume model, and medical motion data are used for simulating the movement of walking. This knowledge is exploited to determine the 3-D position, as well as the posture of an observed person. By applying a Kalman filter, the model parameters in consecutive images are incrementally estimated. The approach is tested on real image data.<>


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    Title :

    Incremental recognition of pedestrians from image sequences


    Contributors:
    Rohr, K. (author)


    Publication date :

    1993-01-01


    Size :

    477464 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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