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Journal of Electronic Imaging

Head detection based on skeleton graph method for counting people in crowded environments
Author(s): Kheireddine Aziz; Djamal Merad; Rabah Iguernaissi; Pierre Drap; Bernard Fertil
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Paper Abstract

We describe a method for detecting heads in order to count people in crowded environments using a single camera. The main difference between this method and traditional ones consists of adapting skeleton graph analysis techniques for distinguishing individuals in crowded environments. First, a graph skeleton is calculated for each selected blob in a scene after having performed motion estimation. Then, the structural property of each blob is explored to detect possible heads in order to estimate the number of people. Each detected head in the skeleton silhouette is identified as being in an independent or partial occlusion state and is updated during a tracking process. Finally, the results of our experiments are presented to demonstrate the robustness of our method.

Paper Details

Date Published: 25 January 2016
PDF: 14 pages
J. Electron. Imaging. 25(1) 013012 doi: 10.1117/1.JEI.25.1.013012
Published in: Journal of Electronic Imaging Volume 25, Issue 1
Show Author Affiliations
Kheireddine Aziz, Univ. du Sud Toulon-Var (France)
Djamal Merad, Lab. des Sciences de l'Information et des Systèmes (France)
Aix-Marseille Univ. (France)
Rabah Iguernaissi, Lab. des Sciences de l'Information et des Systèmes (France)
Aix-Marseille Univ. (France)
Pierre Drap, Lab. des Sciences de l'Information et des Systèmes (France)
Aix-Marseille Univ. (France)
Bernard Fertil, Lab. des Sciences de l'Information et des Systèmes (France)
Aix-Marseille Univ. (France)


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