@inproceedings{86b4394fe1174a9d82b0bb3bd515f06a,
title = "An MCMC-based particle filter for multiple person tracking",
abstract = "This paper presents a Markov Chain Monte Carlo (MCMC) based particle filter to track multiple persons dedicated to video surveillance applications. This hybrid tracker, devoted to networked intelligent cameras, takes benefit from the best properties of both MCMC and joint particle filter. A saliency map-based proposal distribution is shown to limit the well-known burst in terms of particles and MCMC iterations. Qualitative and quantitative results for real-world video data are presented.",
author = "I. Zuriarrain and F. Lerasle and N. Arana and M. Devy",
year = "2008",
doi = "10.1109/icpr.2008.4761045",
language = "English",
isbn = "9781424421756",
series = "Proceedings - International Conference on Pattern Recognition",
publisher = "IEEE Signal Processing Society",
booktitle = "2008 19th International Conference on Pattern Recognition, ICPR 2008",
address = "United States",
}