3D HUMAN TRACKING WITH GAUSSIAN PROCESS ANNEALED PARTICLE FILTER

Leonid Raskin, Ehud Rivlin, Michael Rudzsky

2007

Abstract

We present an approach for tracking human body parts with prelearned motion models in 3D using multiple cameras. We use an annealed particle filter to track the body parts and a Gaussian Process Dynamical Model in order to reduce the dimensionality of the problem, increase the tracker's stability and learn the motion models. We also present an improvement for the weighting function that helps to its use in occluded scenes. We compare our results to the results achieved by a regular annealed particle filter based tracker and show that our algorithm can track well even for low frame rate sequences.

Paper Citation

in Harvard Style

Raskin L., Rivlin E. and Rudzsky M. (2007). 3D HUMAN TRACKING WITH GAUSSIAN PROCESS ANNEALED PARTICLE FILTER . In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 978-972-8865-74-0, pages 459-465. DOI: 10.5220/0002056804590465

in Bibtex Style

@conference{visapp07,
author={Leonid Raskin and Ehud Rivlin and Michael Rudzsky},
title={3D HUMAN TRACKING WITH GAUSSIAN PROCESS ANNEALED PARTICLE FILTER},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2007},
pages={459-465},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002056804590465},
isbn={978-972-8865-74-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - 3D HUMAN TRACKING WITH GAUSSIAN PROCESS ANNEALED PARTICLE FILTER
SN - 978-972-8865-74-0
AU - Raskin L.
AU - Rivlin E.
AU - Rudzsky M.
PY - 2007
SP - 459
EP - 465
DO - 10.5220/0002056804590465