A new Framework for Elderly Fall Detection Using Coupled Hidden Markov Models
Journal: The International Arab Journal of Information Technology (Vol.16, No. 4)Publication Date: 2019-07-01
Authors : Mabrouka Hagui; Mohamed Mahjoub; Faycel ElAyeb;
Page : 775-783
Keywords : Fall detection; feature extraction; shape deformation; motion history of image; coupled hidden markov models.;
Abstract
Falls are a most common problem for old people. They can result in dangerous consequences even death. Many recent works have presented different approaches to detect fall and prevent dangerous outcomes. In this paper, human fall detection from video streams based on a Coupled Hidden Markov Model (CHMM) has been proposed. The CHMM was used to model the motion and static spatial characteristic of human silhouette. The validity of current proposed method was demonstrated with experiments on Le2i database, Weizman database and video from Youtube simulating falls and normal activities. Experimental results showed the superiority of the CHMM for video fall detection.
Other Latest Articles
- Load decrease on the environment in the building of pump storage plant (PSP)
- Automatic Screening of Retinal Lesions for Grading Diabetic Retinopathy
- A Certificate-Based AKA Protocol Secure Against Public Key Replacement Attacks
- Intrusion Detection System using Fuzzy Rough Set Feature Selection and Modified KNN Classifier
- Influence of stress level in concrete constructions at ultrasound speed
Last modified: 2019-09-09 15:38:36