We present a mathematical formulation for curve and surface reconstruction algorithms by introduction of auxiliary variables. For deformable models and templates, two step iterative algorithms have been often used where, at each iteration, the model is first locally deformed according to the potential data attraction and then globally smoothed. We show how these approaches can be interpreted as the introduction of auxiliary variables and the minimization of a two variables energy. This permits us to transform an implicit data constraint defined by a non convex potential into an explicit convex reconstruction problem. We show some mathematical properties and results on this new auxiliary problem, in particular when the potential is a function of the distance to the closest feature point. We then illustrate our approach for some deformable models and templates and image restoration.<>


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Auxiliary variables for deformable models


    Contributors:
    Cohen, L.D. (author)


    Publication date :

    1995-01-01


    Size :

    646752 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Auxiliary Variables for Deformable Models

    Cohen, L. / IEEE Computer Society / Technical Committee on Pattern Analysis and Machine Intelligence | British Library Conference Proceedings | 1995


    Blended Deformable Models

    DeCarlo, D. / Metaxas, D. / Institute of Electrical and Electronics Engineers; Computer Society | British Library Conference Proceedings | 1994


    Blended deformable models

    DeCarlo / Metaxas | IEEE | 1994


    Monocular 3D Object Detection Utilizing Auxiliary Learning With Deformable Convolution

    Chen, Jiun-Han / Shieh, Jeng-Lun / Haq, Muhamad Amirul et al. | IEEE | 2024


    Parametrically deformable contour models

    Staib, L.H. / Duncan, J.S. | IEEE | 1989