Head detection based on skeleton graph method for counting people in crowded environments
| Autor: | Pierre Drap, Rabah Iguernaissi, Djamal Merad, Bernard Fertil, Kheir-Eddine Aziz |
|---|---|
| Přispěvatelé: | Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU), Domingues Vinhas, William, Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Skeleton graph Silhouette 020901 industrial engineering & automation [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Motion estimation 0202 electrical engineering electronic engineering information engineering Computer vision Electrical and Electronic Engineering ComputingMilieux_MISCELLANEOUS ComputingMethodologies_COMPUTERGRAPHICS business.industry Image segmentation 3D modeling Atomic and Molecular Physics and Optics Computer Science Applications Binary data Graph (abstract data type) 020201 artificial intelligence & image processing Artificial intelligence business Smoothing |
| Zdroj: | Journal of Electronic Imaging Journal of Electronic Imaging, SPIE and IS&T, 2016, 25 (1), pp.013012-013012 Journal of Electronic Imaging, 2016, 25 (1), pp.013012-013012 |
| ISSN: | 1017-9909 1560-229X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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