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Particle filtering and sparse sampling for multi-person 3D tracking

Author
Canton, C.; Casas, J.; Pardas, M.; Sblendido, R.
Type of activity
Presentation of work at congresses
Name of edition
2008 IEEE International Conference on Image Processing
Date of publication
2008
Presentation's date
2008-10
Book of congress proceedings
Proc. IEEE International Conference on Image Processing, ICIP'08
First page
2644
Last page
2647
DOI
https://doi.org/10.1109/ICIP.2008.4712337 Open in new window
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4712337&tag=1 Open in new window
Abstract
This paper presents a new approach to the problem of simultaneous tracking of several people in low resolution sequences from multiple calibrated cameras. Redundancy among cameras is exploited to generate a discrete 3D colored representation of the scene. Two Monte Carlo based schemes adapted to the incoming 3D discrete data are introduced. First, a particle filtering technique is proposed relying on a volume likelihood function taking into account both occupancy and color information. Sparse sa...
Keywords
Image colour analysis, Image resolution, Image sampling, Image sequences, Monte Carlo methods, Particle filtering (numerical methods), Target tracking
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants