A CNN Based Approach for Crowd Anomaly Detection

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Published Mar 1, 2021
https://doi.org/10.47164/ijngc.v12i1.185
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Volume 12, Issue 1, March 2021

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Kinjal Vishnuprasad Joshi
G H Patel College of Engineering & technology, Gujarat Technological University
Narendra M Patel
Gujart Technological University, Ahmedabad, Gujarat, India

Abstract

Automatic Anomaly detection in a crowd scene is very significant because of more apprehension with people’s safety in a public place. Because of usefulness and complexity, currently, it is an open research area. In this work, a new Convolutional Neural Network (CNN) model is proposed to detect crowd anomaly. Experiments are carried out on two publicly available datasets. The performance is measured by Accuracy and Area Under the ROC Curve (AUC). The experimental results determine the efficacy of the proposed model.

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How to Cite
Kinjal Vishnuprasad Joshi, & Narendra M Patel. (2021). A CNN Based Approach for Crowd Anomaly Detection. International Journal of Next-Generation Computing, 12(1), 01–11. https://doi.org/10.47164/ijngc.v12i1.185
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