A Study on Crowd Detection and Density Analysis for Safety Control

Authors

  • Chaudhari MD Computer, Pune Institute of Computer Technology, Savitribai Phule Pune University, Pune, India
  • Ghotkar AS Computer, Pune Institute of Computer Technology, Savitribai Phule Pune University, Pune, India

DOI:

https://doi.org/10.26438/ijcse/v6i4.424428

Keywords:

Pattern Recognition, Computer Vision, Crowd Density Estimation, Detection, CNN

Abstract

Most of the studies based on tracking individuals, crowd counting, finding the region of motion and crowd detection. Crowd detection and density estimation from crowded images have a wide range of application such as crime detection, congestion, public safety, crowd abnormalities, visual surveillance and urban planning. The purpose of crowd density analysis is to calculate the concentration of the crowd in the videos of observers. Pattern recognition technique helps to estimate the crowd detection count and density by using face and detection. The job of detecting a face in the crowd is complicated due to its variability present in human faces including color, pose, expression, position, orientation, and illumination. The counting performance has been steadily improved because of Deep Convolutional Neural Network.

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Published

2025-11-12
CITATION
DOI: 10.26438/ijcse/v6i4.424428
Published: 2025-11-12

How to Cite

[1]
M. D. Chaudhari and A. S. Ghotkar, “A Study on Crowd Detection and Density Analysis for Safety Control”, Int. J. Comp. Sci. Eng., vol. 6, no. 4, pp. 424–428, Nov. 2025.

Issue

Vol. 6 No. 4 (2018): IJCSE April Edition

Section

Survey Article

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