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International Journal of Computational Science and Engineering Research
Volume 3, Issue 1 (January - March)
Article type: Original Article
Published: 26 September 2026 |Pages: 37 - 43 |ISSN: 3107 - 8605
https://doi.org/10.63328/IJCSER-V3RI1P4
Copyright © 2026 Kodeboina Suresh et al.
International Journal of Computational Science and Engineering Research
Open Access publication.

Spatio-Temporal Modeling for Abnormal Behaviour Detection in Crowd Scenes

Kodeboina SureshiD1, Sk.AkbariD2, T Murali MohaniD3, and Ravindra Lal Weeraratne KoggalageiD4

Abstract

In this paper, an alternative technique for determining unexpected human-movement regions is presented and demonstrated. In particular, we propose an efficient alternative to human activity by bounding or identifying individual humans or their parts, denoting an actuator or effect -intensifying tracking. The proposed movement effect map serves as a comprehensive representation of motion velocity characteristics, which includes the movement direction and magnitude of objects or subjects that interact with each other inside a particular area or group. Record Terms: Strange movement discovery, imaginative and prescient-primarily based reconnaissance, movement impact map, swarmed scenes/domestic.

Keywords: Crowd Anomaly Detection, Spatio-Temporal Feature Learning, Video Surveillance Analytics, DL

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How to cite this article

Kuppireddy Krishna Reddy, Yagireddi Ramesh, J V G Prakasa Rao Pyla , Ravindra Lal Weeraratne Koggalage , “ Real-Time Stampede Risk Prediction from Crowd Videos Using YOLOv8 and Spatio-Temporal Modeling “ , International Journal of Computational Science and Engineering Research, vol. 3, Issue. 1, p. 49 - 57, January 2026, Cross Reff DOI : https://doi.org/10.63328/IJCSER-V3RI1P5