Fall Detection System-Based Posture-Recognition for Indoor Environments

Journal of Imaging

RachidOulad Haj Thami¹  Abderrazak Iazzi²  Mohammed Rziza² 

[1] ADMIR LAB, IRDA, Rabat IT Center, ENSIAS, Mohammed V University in Rabat, Rabat B.P. 1014, Morocco;LRIT, Raba IT Center, Faculty of Sciences, Mohammed V University in Rabat, Rabat B.P. 1014, Morocco;

关键词: fall detection;    human posture recognition;    classification;    background subtraction;    features extraction;    video surveillance;   

DOI  :  10.3390/jimaging7030042

来源: DOAJ

【 摘 要 】

The majority of the senior population lives alone at home. Falls can cause serious injuries, such as fractures or head injuries. These injuries can be an obstacle for a person to move around and normally practice his daily activities. Some of these injuries can lead to a risk of death if not handled urgently. In this paper, we propose a fall detection system for elderly people based on their postures. The postures are recognized from the human silhouette which is an advantage to preserve the privacy of the elderly. The effectiveness of our approach is demonstrated on two well-known datasets for human posture classification and three public datasets for fall detection, using a Support-Vector Machine (SVM) classifier. The experimental results show that our method can not only achieves a high fall detection rate but also a low false detection.

【 授权许可】

Unknown