In this paper, we introduce a new technique for shape modelling in the space of implicit polynomials. Registration consists of recovering an optimal one-to-one transformation of a higher order polynomial along with uncertainties measures that are determined according to the covariance matrix of the correspondences at the zero isosurface. In the modelling phase, these measures are used to weight the importance of the training samples phase according to a variable bandwidth non-parametric density estimation process. The selection of the most appropriate kernels to represent the training set is done through the maximum likelihood criterion. Excellent results for patterns of digits, related with the registration and the modelling aspects of our approach demonstrate the potentials of our method.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Modelling shapes with uncertainties: higher order polynomials, variable bandwidth kernels and non parametric density estimation


    Beteiligte:
    Taron, M. (Autor:in) / Paragios, N. (Autor:in) / Jolly, M.-P. (Autor:in)


    Erscheinungsdatum :

    2005-01-01


    Format / Umfang :

    610612 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Modelling Shapes with Uncertainties: Higher Order Polynomials, Variable Bandwidth Kernels and Non Parametric Density Estimation

    Taron, M. / Paragios, N. / Jolly, M.-P. et al. | British Library Conference Proceedings | 2005



    Acoustic shaping in microgravity - Higher order surface shapes

    Wanis, S. / Sercovich, A. / Komerath, N. | AIAA | 1999


    Higher-order SVD analysis for crowd density estimation

    Zhou, B. / Zhang, F. / Peng, L. | British Library Online Contents | 2012


    Diffusion Distributed Quantized State Estimation With Variable Bandwidth

    Liu, Jingzhi / Chen, Feng / Feng, Minyu et al. | IEEE | 2022