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

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. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper comprehensively reviews the recent research advancement on crowd counting and density estimation, including background introduction, summary of traditional methods, review of methods based on convolutional neural network models, reporting and discussion of experimental results, and outlook on future directions.