Camera-Based Fall Detection System for the Elderly With Occlusion Recognition

Authors

  • Fouzi LEZZAR LIRE Laboratory Constantine 2 University
  • Djamel BENMERZOUG LIRE Laboratory Constantine 2 University
  • Ilham KITOUNI MISC Laboratory Constantine 2 University

Keywords:

Fall detection, Camra, Machine learning, Deep learning, e-health

Abstract

This paper proposes an algorithm for fall detection using 2D RGB camera. Occlusion, fall, and common daily activities are separated from each other by machine learning algorithms, which were trained on features extracted by a deep learning-based computer vision algorithm. This later is used for person detection. The experimental validation of the proposed approach was conducted on two datasets, one public, and the second created by experiments. For evaluation, several assessment measures are computed. This evaluation shown effectiveness of the proposed solution.

Downloads

Published

29.09.2020

How to Cite

1.
LEZZAR F, BENMERZOUG D, KITOUNI I. Camera-Based Fall Detection System for the Elderly With Occlusion Recognition. Appl Med Inform [Internet]. 2020 Sep. 29 [cited 2024 Nov. 27];42(3):169-7. Available from: https://ami.info.umfcluj.ro/index.php/AMI/article/view/788

Issue

Section

Articles