A method of locating and tracking rigid moving objects with arbitrary curved surfaces is presented. Motion of the moving objects in a sequence of images is used to perform image segmentation and boundary extraction. The silhouette of the object model is derived by the curvature method of Basri and Ullman. The derived silhouette is then fitted to the observed silhouette to determine the object pose. Correspondence is guided by template matching, where the similarity measure is based on the minimization of the overall Euclidean distance between the derived silhouette and the observed silhouette. Bench tests and simulations confirm the viability of the approach, even when the observed silhouette is imperfect due to partial occlusion of the object or imperfect boundary extraction.<>


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    Title :

    Recovering and tracking pose of curved 3D objects from 2D images


    Contributors:
    Chen, J.L. (author) / Stockman, G.C. (author) / Rao, K. (author)


    Publication date :

    1993-01-01


    Size :

    501717 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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