@InProceedings{	  ruz:etal:2015,
  author	= {C. Ruz, C. Pieringer, B. Peralta, I. Lillo, P. Espinace,
		  R. Gonzalez, B. Wendt, D. Mery, A. Soto},
  title		= {Visual Recognition to Access and Analyze People Density
		  and Flow Patterns in Indoor Environments},
  booktitle	= {IEEE Winter Conference on Applications of Computer Vision
		  (WACV)},
  year		= {2015},
  abstract	= {This work describes our experience developing a system to
		  access density and flow of people in large indoor spaces
		  using a network of RGB cameras. The proposed system is
		  based on a set of overlapped and calibrated cameras. This
		  facilitates the use of geometric constraints that help to
		  reduce visual ambiguities. These constraints are combined
		  with classifiers based on visual appearance to produce an
		  efficient and robust method to detect and track humans. In
		  this work, we argue that flow and density of people are low
		  level measurements that need to be complemented with
		  suitable analytic tools to bridge semantic gaps and become
		  useful information for a target application. Consequently,
		  we also propose a set of analytic tools that help a human
		  user to effectively take advantage of the measurements
		  provided by the system. Finally, we report results that
		  demonstrate the relevance of the proposed ideas.},
  url		= {http://saturno.ing.puc.cl/media/papers_alvaro/WACV-2015-VersionFinal.pdf}
}

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