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Reseach Article

Automatic Estimation of Crowd Density

Published on April 2018 by Jugal Kishor Gupta, S. K. Gupta
International Conference on Recent Developments in Science, Technology, Humanities and Management
Foundation of Computer Science USA
ICRDSTHM2017 - Number 2
April 2018
Authors: Jugal Kishor Gupta, S. K. Gupta
84715cd0-6b05-4a49-af3b-3cc91bfc7ecb

Jugal Kishor Gupta, S. K. Gupta . Automatic Estimation of Crowd Density. International Conference on Recent Developments in Science, Technology, Humanities and Management. ICRDSTHM2017, 2 (April 2018), 7-10.

@article{
author = { Jugal Kishor Gupta, S. K. Gupta },
title = { Automatic Estimation of Crowd Density },
journal = { International Conference on Recent Developments in Science, Technology, Humanities and Management },
issue_date = { April 2018 },
volume = { ICRDSTHM2017 },
number = { 2 },
month = { April },
year = { 2018 },
issn = 0975-8887,
pages = { 7-10 },
numpages = 4,
url = { /proceedings/icrdsthm2017/number2/29315-7018/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Developments in Science, Technology, Humanities and Management
%A Jugal Kishor Gupta
%A S. K. Gupta
%T Automatic Estimation of Crowd Density
%J International Conference on Recent Developments in Science, Technology, Humanities and Management
%@ 0975-8887
%V ICRDSTHM2017
%N 2
%P 7-10
%D 2018
%I International Journal of Computer Applications
Abstract

This paper considers the problem of automatic estimation of crowd densities, an important part of the problem of automatic crowd monitoring and control. Anew technique based on texture description of the images of the area under surveillance is proposed. Two methods based on different approaches of texture analysis, one statistical and another spectral, are applied on real images captured in an area of Liverpool Street Railway Station, London, UK. The results obtained show that both methods present similar general rates of correct estimation, and that the potential use of texture description for the problem of automatic estimation of crowd densities is encouraging

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Index Terms

Computer Science
Information Sciences

Keywords

Crowd Image Surveillance