Many existing systems for human body tracking are based on dynamic model-based tracking that is driven by local image features. Alternatively, within a view-based approach, tracking of humans can be accomplished by the learning-based recognition of characteristic body postures which define the spatial positions of interesting points on the human body. Recognition of body postures can be based on simple image descriptors, like the moments of body silhouettes. We present a system that combines these two approaches within a common closed-loop architecture. Central characteristics of our system are: (1) Mapping of image features into a posture space with reduced dimensionality by learning one-to-many mappings from training data by a set of parallel SVM regressions. (2) Selection of the relevant regression hypotheses by a competitive particle filter that is defined over a low-dimensional hidden state space. (3) The recognized postures are used as priors to initialize and support classical model-based tracking using a flexible articulated 2D model that is driven by local image features using a vector field approach. We present pose tracking and reconstruction results based on a combination of view-based and model-based tracking. Increased robustness and improved generalization properties are achieved even for small amounts of training data.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Combining View-Based and Model-Based Tracking of Articulated Human Movements


    Contributors:


    Publication date :

    2005-01-01


    Size :

    923033 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Model-based 3D tracking of an articulated hand

    Stenger, B. / Mendonca, P.R.S. / Cipolla, R. | IEEE | 2001


    Model-Based 3D Tracking of an Articulated Hand

    Stenger, B. / Mendonca, P. R. S. / Cipolla, R. et al. | British Library Conference Proceedings | 2001


    Model-Based Tracking of Self-Occluding Articulated Objects

    Rehg, J. / Kanade, T. / IEEE Computer Society et al. | British Library Conference Proceedings | 1995


    Model-based articulated hand motion tracking for gesture recognition

    Lien, C.-C. / Huang, C.-L. | British Library Online Contents | 1998


    EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation

    Black, M. J. / Jepson, A. D. | British Library Online Contents | 1998