We present a robust framework for real-time processing of 3D motion capture data. It autonomously analyzes the input data to build a model of the observed subjects, and is expected to perform in situations where the observed features are unstable or frequently occluded. We have implemented the method and presently rely on a marker based motion capture system to provide unlabeled 3D coordinates of non-occluded markers. However, we hope this to be a step towards using regular video camera systems with feature detection to perform autonomous markerless motion capture.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Autonomous real-time model building for optical motion capture


    Contributors:
    Rajko, S. (author) / Qian, G. (author)


    Publication date :

    2005-01-01


    Size :

    112672 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Autonomous Real-Time Model Building for Optical Motion Capture

    Rajko, S. / Qian, G. | British Library Conference Proceedings | 2005



    Real-time motion planning for agile autonomous vehicles

    Frazzoli, E. / Dahleh, M.A. / Feron, E. | Tema Archive | 2001


    Virtual Fashion Show Using Real-Time Markerless Motion Capture

    Okada, R. / Stenger, B. / Ike, T. et al. | British Library Conference Proceedings | 2006


    Real-Time Motion Planning for Agile Autonomous Vehicles

    Emilio Frazzoli / Munther A. Dahleh / Eric Feron | AIAA | 2002