We present a novel method for the shape and motion estimation of a deformable model using error residuals from model-based motion analysis. The motion of the model is first estimated using a model-based least squares method. Using the residuals from the least squares solution, the non-rigid structure of the model can be better estimated by computing how changes in the shape of the model affect its motion parameterization. This method is implemented as a component in a deformable model-based framework that uses optical flow information and edges. This general model-based framework is applied to human face shape and motion estimation. We present experiments that demonstrate that this framework is a considerable improvement over a framework that uses only optical flow information and edges.


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    Title :

    Deformable model-based shape and motion analysis from images using motion residual error


    Contributors:
    DeCarlo, D. (author) / Metaxas, D. (author)


    Publication date :

    1998-01-01


    Size :

    1052629 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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