A new model selection criterion based on physical characteristics of underlying motion models is proposed. The proposed criterion is then incorporated in a robust motion segmentation scheme, which is based upon robust least K-th order statistical model fitting. The proposed model criterion has been compared with many other competing techniques and is shown to be more suitable for the motion segmentation task. The motion segmentation algorithm has been tested (and shown to be successful) on a number of synthetic and real image sequences.


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    Title :

    Motion analysis: model selection and motion segmentation


    Contributors:


    Publication date :

    2003-01-01


    Size :

    420375 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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