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Crowd detection and counting using a static and dynamic platform: state of the art

Automated object detection and crowd density estimation are popular and important area in visual surveillance research. The last decades witnessed many significant research in this field however, it is still a challenging problem for automatic visual surveillance. The ever increase in research of th...

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Main Authors: Chaudhry, H., Rahim, M. H. M., Saba, T., Rehman, A.
Format: Article
Published: Inderscience Publishers 2019
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/89468/
http://www.dx.doi.org/10.1504/IJCVR.2019.099435
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spelling my.utm.894682021-02-09T04:26:11Z http://eprints.utm.my/id/eprint/89468/ Crowd detection and counting using a static and dynamic platform: state of the art Chaudhry, H. Rahim, M. H. M. Saba, T. Rehman, A. QA75 Electronic computers. Computer science Automated object detection and crowd density estimation are popular and important area in visual surveillance research. The last decades witnessed many significant research in this field however, it is still a challenging problem for automatic visual surveillance. The ever increase in research of the field of crowd dynamics and crowd motion necessitates a detailed and updated survey of different techniques and trends in this field. This paper presents a survey on crowd detection and crowd density estimation from moving platform and surveys the different methods employed for this purpose. This review category and delineates several detections and counting estimation methods that have been applied for the examination of scenes from static and moving platforms. Inderscience Publishers 2019 Article PeerReviewed Chaudhry, H. and Rahim, M. H. M. and Saba, T. and Rehman, A. (2019) Crowd detection and counting using a static and dynamic platform: state of the art. International Journal of Computational Vision and Robotics, 9 (3). pp. 228-259. ISSN 1752-9131 http://www.dx.doi.org/10.1504/IJCVR.2019.099435 DOI: 10.1504/IJCVR.2019.099435
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Chaudhry, H.
Rahim, M. H. M.
Saba, T.
Rehman, A.
Crowd detection and counting using a static and dynamic platform: state of the art
description Automated object detection and crowd density estimation are popular and important area in visual surveillance research. The last decades witnessed many significant research in this field however, it is still a challenging problem for automatic visual surveillance. The ever increase in research of the field of crowd dynamics and crowd motion necessitates a detailed and updated survey of different techniques and trends in this field. This paper presents a survey on crowd detection and crowd density estimation from moving platform and surveys the different methods employed for this purpose. This review category and delineates several detections and counting estimation methods that have been applied for the examination of scenes from static and moving platforms.
format Article
author Chaudhry, H.
Rahim, M. H. M.
Saba, T.
Rehman, A.
author_facet Chaudhry, H.
Rahim, M. H. M.
Saba, T.
Rehman, A.
author_sort Chaudhry, H.
title Crowd detection and counting using a static and dynamic platform: state of the art
title_short Crowd detection and counting using a static and dynamic platform: state of the art
title_full Crowd detection and counting using a static and dynamic platform: state of the art
title_fullStr Crowd detection and counting using a static and dynamic platform: state of the art
title_full_unstemmed Crowd detection and counting using a static and dynamic platform: state of the art
title_sort crowd detection and counting using a static and dynamic platform: state of the art
publisher Inderscience Publishers
publishDate 2019
url http://eprints.utm.my/id/eprint/89468/
http://www.dx.doi.org/10.1504/IJCVR.2019.099435
_version_ 1691733101756022784
score 13.211869

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