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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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A deep crowd density classification model for Hajj pilgrimage using fully convolutional neural network.

Md Roman Bhuiyan1, Junaidi Abdullah1, Noramiza Hashim1

  • 1Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Selengor, Malaysia.

Peerj. Computer Science
|May 2, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel fully convolutional neural network (FCNN) for accurate crowd density analysis, particularly for large-scale events like the Hajj pilgrimage. The developed model achieves high accuracy, outperforming existing methods in crowd analysis.

Keywords:
Crowd analysisCrowd density classificationFully convolutional neural network (FCNN)Hajj crowd dataset

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Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Data Science

Background:

  • Traditional crowd analysis methods struggle with accuracy for distant crowds in surveillance footage.
  • High-density crowd analysis is crucial for managing large events like the Hajj and Umrah pilgrimages.

Purpose of the Study:

  • To enhance crowd analysis and density prediction for Hajj and Umrah pilgrimages.
  • To overcome limitations in estimating crowd density from distant surveillance cameras.

Main Methods:

  • A fully convolutional neural network (FCNN)-based approach was developed for crowd density classification.
  • A new dataset, Hajj-Crowd-2021, was created based on Hajj pilgrimage scenarios.
  • The proposed model was validated against existing models and datasets (UCSD, JHU-CROWD).

Main Results:

  • The FCNN-based method achieved 100% accuracy on the Hajj-Crowd-2021 dataset.
  • High accuracies of 98% and 98.16% were obtained on the UCSD and JHU-CROWD datasets, respectively.
  • The proposed model and dataset outperformed state-of-the-art methods in most evaluations.

Conclusions:

  • The FCNN-based approach significantly improves crowd density estimation, especially in challenging, high-density scenarios.
  • The Hajj-Crowd-2021 dataset provides a valuable resource for advancing crowd analysis research.
  • This research offers a robust solution for crowd monitoring in large-scale religious gatherings.