@inbook {bCanton-Ferrer08b,
	title = {Multi-Person Tracking Strategies Based on Voxel Analysis},
	booktitle = {Multimodal Technologies for Perception of Humans},
	volume = {4625},
	year = {2008},
	pages = {91{\textendash}103},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin / Heidelberg},
	abstract = {<p>This paper presents two approaches to the problem of simultaneous tracking of several people in low resolution sequences from multiple calibrated cameras. Spatial redundancy is exploited to generate a discrete 3D binary representation of the foreground objects in the scene. Color information obtained from a zenithal camera view is added to this 3D information. The first tracking approach implements heuristic association rules between blobs labelled according to spatiotemporal connectivity criteria. Association rules are based on a cost function which considers their placement and color histogram. In the second approach, a particle filtering scheme adapted to the incoming 3D discrete data is proposed. A volume likelihood function and a discrete 3D re-sampling procedure are introduced to evaluate and drive particles. Multiple targets are tracked by means of multiple particle filters and interaction among them is modeled through a 3D blocking scheme. Evaluation over the CLEAR 2007 database yields quantitative results assessing the performance of the proposed algorithm for indoor scenarios.</p>},
	isbn = {978-3-540-68584-5},
	doi = {10.1007/978-3-540-68585-2_7},
	url = {http://www.springerlink.com/content/k08w4000844220gr/},
	author = {Cristian Canton-Ferrer and Salvador, J. and Casas, J. and M. Pard{\`a}s}
}
