Geodesic
Crowd counting á la Bourdieu, Automated estimation of the number of people
Computer Science and Information Systems, Tome 17 (2020) no. 3.

Voir la notice de l'article provenant de la source Computer Science and Information Systems website

In recent years, sociologists have taught us how important and emergent the problem of crowd counting is. They have recognised a variety of reasons for this fact, including: public safety (e.g. crushing between people, trampling underfoot, risk of spreading infectious disease, aggression), politics (e.g. police and governent tend to underestimate the number of people, whilst protest organisers tend to overestimate it) and journalism (e.g. accuracy of the estimation of the ground truth supporting an article). The aim of this paper is to investigate models for crowd counting that are inspired by the observations of famous sociologist Pierre Bourdieu. We show that despite the simplicity of the models, we can achieve competitive result. This makes them suitable for low computational power and energy efficient architectures.
Keywords: crowd counting, deep learning, mall dataset, habitus 
@article{CSIS_2020_17_3_a16,
     author = {Karolina Przybylek and Illia Shkroba},
     title = {Crowd counting \'a la {Bourdieu,} {Automated} estimation of the number of people},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {17},
     number = {3},
     year = {2020},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2020_17_3_a16/}
}
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Karolina Przybylek; Illia Shkroba. Crowd counting á la Bourdieu, Automated estimation of the number of people. Computer Science and Information Systems, Tome 17 (2020) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2020_17_3_a16/