We address the problem of segmenting a sequence of images of natural scenes into disjoint regions that are characterized by constant spatio-temporal statistics. We model the spatio-temporal dynamics in each region by Gauss-Markov models, and infer the model parameters as well as the boundary of the regions in a variational optimization framework. Numerical results demonstrate that - in contrast to purely texture-based segmentation schemes - our method is effective in segmenting regions that differ in their dynamics even when spatial statistics are identical.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Dynamic texture segmentation


    Beteiligte:
    Doretto, (Autor:in) / Cremers, (Autor:in) / Favaro, (Autor:in) / Soatto, (Autor:in)


    Erscheinungsdatum :

    01.01.2003


    Format / Umfang :

    608505 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Dynamic Texture Segmentation

    Doretto, G. / Cremers, D. / Favaro, P. et al. | British Library Conference Proceedings | 2003


    Quaternion color texture segmentation

    Shi, L. / Funt, B. | British Library Online Contents | 2007


    Dynamic texture segmentation based on deterministic partially self-avoiding walks

    Gonçalves, W. N. / Bruno, O. M. | British Library Online Contents | 2013


    Image Segmentation by Texture Analysis

    Di Ruberto, C. / Rodriguez, G. / Vitulano, S. et al. | British Library Conference Proceedings | 1999


    Image segmentation by texture analysis

    Di Ruberto, C. / Rodriguez, G. / Vitulano, S. | IEEE | 1999