Optical Flow Statistics for Violent Crowd Behavior Detection

Pallavi Deepak Chakole, Vishal R. Satpute

2025

Abstract

We proposed an approach for identifying human violent behavior by evaluating the optical flow of a series of sequences obtained from a video. The term Violent or Violence refers to an event that arises, causing of unexpected displacement of a crowd. “Crowd Behaviour Analysis” is an important research topic that falls under the area of image processing and computer vision, machine learning, and deep learning, which have been investigated by researchers. Proceeding with this attitude, a simple and novel method based on the amount of movement present in the current frame with respect to its previous frame has to be presented here. The methodology employed is as follows: the optical flow of two consecutive frames will be calculated. Further, correlation coefficients will be calculated by considering the magnitude of the optical flow of successive frames. From those correlation values, we can know how much the successive frames are similar or correlated. High correlation coefficients pointed that, there will be less movement in the crowd, a lower rate of change of velocity, and thus normal behavior or non-violent event. On contradictory if the correlation coefficients seem to be low, there will be more movement in the crowd, a high rate of change of velocity, and thus abnormal behavior or violent event detected. Decision criteria have to be set for a particular threshold value that has been selected adaptively, below which we can get violent events. Implementation has to be done on MATLAB R2021b, using the UMN video dataset consisting of 11 videos of three different scenarios. Evaluation results concluded that the proposed methodology can able to detect violent anomalies somehow accurately.

Paper Citation

in Harvard Style

Chakole P. and Satpute V. (2025). Optical Flow Statistics for Violent Crowd Behavior Detection. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 557-564. DOI: 10.5220/0013628300004664

in Bibtex Style

@conference{incoft25,
author={Pallavi Chakole and Vishal Satpute},
title={Optical Flow Statistics for Violent Crowd Behavior Detection},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT},
year={2025},
pages={557-564},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013628300004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT
TI - Optical Flow Statistics for Violent Crowd Behavior Detection
SN - 978-989-758-763-4
AU - Chakole P.
AU - Satpute V.
PY - 2025
SP - 557
EP - 564
DO - 10.5220/0013628300004664
PB - SciTePress