We present a method for simultaneously learning linear models of multiple high dimensional data sets and the dependencies between them. For example, we learn asymmetrically coupled linear models for the faces of two different people and show how these models can be used to animate one face given a video sequence of the other. We pose the problem as a form of Asymmetric Coupled Component Analysis (ACCA) in which we simultaneously learn the subspaces for reducing the dimensionality of each dataset while coupling the parameters of the low dimensional representations. Additionally, a dynamic form of ACCA is proposed, that extends this work to model temporal dependencies in the data sets. To account for outliers and missing data, we formulate the problem in a statistically robust estimation framework. We review connections with previous work and illustrate the method with examples of synthesized dancing and the animation of facial avatars.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Dynamic coupled component analysis


    Beteiligte:
    De la Torre, F. (Autor:in) / Black, M.J. (Autor:in)


    Erscheinungsdatum :

    2001-01-01


    Format / Umfang :

    941514 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Dynamic Coupled Component Analysis

    De la Torre, F. / Black, M. J. / IEEE | British Library Conference Proceedings | 2001


    Stochastic Launcher-Satellite Coupled Dynamic Analysis

    Pellissetti, M.F. | Online Contents | 2006


    Stochastic launcher-satellite coupled dynamic analysis

    Fransen, S. / Pellissetti, M. F. / Pradlwarter, H. J. et al. | British Library Conference Proceedings | 2005


    Stochastic Launcher-Satellite Coupled Dynamic Analysis

    Manuel Pellissetti / Sebastiaan Fransen / Helmut Pradlwarter et al. | AIAA | 2006


    Methodologies for launcher-payload coupled dynamic analysis

    Fransen, S. / European Space Agency | British Library Conference Proceedings | 2005