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A survey of crowd counting and density estimation based on convolutional neural network.

Authors :
Fan, Zizhu
Zhang, Hong
Zhang, Zheng
Lu, Guangming
Zhang, Yudong
Wang, Yaowei
Source :
Neurocomputing. Feb2022, Vol. 472, p224-251. 28p.
Publication Year :
2022

Abstract

Crowd counting and crowd density estimation methods are of great significance in the field of public security. Estimating crowd density and counting from single image or video frame has become an essential part of a computer vision system in various scenarios. In this paper, we comprehensively review the recent research advancement on crowd counting and density estimation. First of all, we introduce the background of crowd counting and crowd density estimation. Second, the traditional crowd counting methods are summarized. Third, we focus on reviewing the crowd counting and crowd density methods based on convolutional neural network (CNN) models. Next, we report and discuss the experimental results of a number of typical methods on benchmark datasets. Finally, we present the promising future directions of crowd counting and crowd density. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
472
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
154339098
Full Text :
https://doi.org/10.1016/j.neucom.2021.02.103