Silhouette Segmentation for Near-Fall Detection Through Analysis of Human Movements in Surveillance Videos

Imane Bouraoui, Jean Meunier

2025

Abstract

The detection of near-fall incidents is crucial in surveillance systems to improve safety, prevent future more serious falls and ensure rapid intervention. the main objective of this paper is the detection of movement anomalies in a series of video sequences through silhouette segmentation. First, we begin by isolating the person from the background, keeping only the person's silhouette. This is achieved through two methods: the first involves median pixel, while the second utilizes an algorithm based on pre-trained Mask Regional Convolutional Neural Network (Mask R-CNN) model. the second step involves movement calculation and noise effect minimization. Finally, we conclude by classifying normal and abnormal movement signals obtained using two different classifiers: Support Vector Machine (SVM) and Autoencoder (AE). We then compare the results to determine the most efficient and rapid system for detecting near-falls. the experimental results demonstrate the effectiveness of the proposed approach in detecting near-fall incidents. Specifically, the Mask R-CNN approach outperformed the median pixel method in silhouette extraction, enhancing anomaly detection accuracy. AE surpassed SVM in accuracy and performance, making it suitable for real-time near-fall detection in surveillance applications.

Paper Citation

in Harvard Style

Bouraoui I. and Meunier J. (2025). Silhouette Segmentation for Near-Fall Detection Through Analysis of Human Movements in Surveillance Videos. In Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-730-6, SciTePress, pages 620-627. DOI: 10.5220/0013153500003905

in Bibtex Style

@conference{icpram25,
author={Imane Bouraoui and Jean Meunier},
title={Silhouette Segmentation for Near-Fall Detection Through Analysis of Human Movements in Surveillance Videos},
booktitle={Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2025},
pages={620-627},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013153500003905},
isbn={978-989-758-730-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Silhouette Segmentation for Near-Fall Detection Through Analysis of Human Movements in Surveillance Videos
SN - 978-989-758-730-6
AU - Bouraoui I.
AU - Meunier J.
PY - 2025
SP - 620
EP - 627
DO - 10.5220/0013153500003905
PB - SciTePress