Particle Video for Crowd Flow Tracking - Entry-Exit Area and Dynamic Occlusion Detection

Antoine Fagette, Patrick Jamet, Daniel Racoceanu, Jean-Yves Dufour

Abstract

In this paper we interest ourselves to the problem of flow tracking for dense crowds. For this purpose, we use a cloud of particles spread on the image according to the estimated crowd density and driven by the optical flow. This cloud of particles is considered as statistically representative of the crowd. Therefore, each particle has physical properties that enable us to assess the validity of its behavior according to the one expected from a pedestrian and to optimize its motion dictated by the optical flow. This leads us to three applications described in this paper: the detection of the entry and exit areas of the crowd in the image, the detection of dynamic occlusions and the possibility to link entry areas with exit ones according to the flow of the pedestrians. We provide the results of our experimentation on synthetic data and show promising results.

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Paper Citation


in Harvard Style

Fagette A., Jamet P., Racoceanu D. and Dufour J. (2014). Particle Video for Crowd Flow Tracking - Entry-Exit Area and Dynamic Occlusion Detection . In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 445-452. DOI: 10.5220/0004827604450452


in Bibtex Style

@conference{icpram14,
author={Antoine Fagette and Patrick Jamet and Daniel Racoceanu and Jean-Yves Dufour},
title={Particle Video for Crowd Flow Tracking - Entry-Exit Area and Dynamic Occlusion Detection},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={445-452},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004827604450452},
isbn={978-989-758-018-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Particle Video for Crowd Flow Tracking - Entry-Exit Area and Dynamic Occlusion Detection
SN - 978-989-758-018-5
AU - Fagette A.
AU - Jamet P.
AU - Racoceanu D.
AU - Dufour J.
PY - 2014
SP - 445
EP - 452
DO - 10.5220/0004827604450452