Vision-based Human Fall Detection Systems: A Review
Asma Benkaci, Layth Sliman, Hachemi Nabil Dellys
Abstract
Falling is a significant threat for old people and disabled persons. Therefore, it is necessary to develop an automated fall detection system to make them more independent and to mitigate the physical and psychological consequences of falls. Such a system can lower the death rate among dependent people who live alone. This paper presents a review of vision-based techniques, algorithms and databases used in detecting falls. Recently proposed systems are analyzed and compared. The literature review underscores the promising potential of camera-based fall detection systems and highlights areas for further research and development.
Topics & Concepts
Computer scienceArtificial intelligenceHuman–computer interactionData scienceComputer visionComputer securityContext-Aware Activity Recognition SystemsNon-Invasive Vital Sign MonitoringGait Recognition and Analysis