We present a novel approach for full body pose tracking using stochastic sampling. A volumetric reconstruction of a person is extracted from silhouettes in multiple video images. Then, an articulated body model is fitted to the data with stochastic meta descent (SMD) optimization. By comparing even a simplified version of SMD to the commonly used Levenberg-Marquardt method, we demonstrate the power of stochastic compared to deterministic sampling, especially in cases of noisy and incomplete data. Moreover, color information is added to improve the speed and robustness of the tracking. Results are shown for several challenging sequences, with tracking of 24 degrees of freedom in less than 1 second per frame.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Full body tracking from multiple views using stochastic sampling


    Beteiligte:
    Kehl, R. (Autor:in) / Bray, M. (Autor:in) / Van Gool, L. (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    843813 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    3D Human Body Model Acquisition from Multiple Views

    Kakadiaris, I. / Metaxas, D. / IEEE Computer Society et al. | British Library Conference Proceedings | 1995


    3D human body model acquisition from multiple views

    Kakadiaris, I.A. / Metaxas, D. | IEEE | 1995


    Modelling and tracking articulated motion from multiple camera views

    Ringer, Maurice / Lasenby, Joan | TIBKAT | 2001


    Tracking hybrid 2D-3D human models from multiple views

    Eng-Jon Ong / Shaogang Gong | IEEE | 1999


    Markerless tracking of complex human motions from multiple views

    Kehl, R. / Gool, L. V. | British Library Online Contents | 2006