Abstract
Remote monitoring service for elderly persons is important as the aged populations in most developed countries continue growing. To monitor the safety and health of the elderly population, we propose a novel omni-directional vision sensor based system, which can detect and track object motion, recognize human posture, and analyze human behavior automatically. In this work, we have made the following contributions: (1) we develop a remote safety monitoring system which can provide real-time and automatic health care for the elderly persons and (2) we design a novel motion history or energy images based algorithm for motion object tracking. Our system can accurately and efficiently collect, analyze, and transfer elderly activity information and provide health care in real-time. Experimental results show that our technique can improve the data analysis efficiency by 58.5% for object tracking. Moreover, for the human posture recognition application, the success rate can reach 98.6% on average.
Highlights
As the life expectation around the world increases, the aging population problem is becoming more and more urgent and significant
We have made the following contributions: 1. we design and implement an accurate and efficient remote safety monitoring system based on the omni-directional vision sensor (ODVS) images; 2. we develop a novel motion history or energy image (MHoEI) based motion tracking algorithm, which can improve the motion tracking efficiency significantly
The ODVS device is located in the center of the room and its height is about 1.8 m
Summary
As the life expectation around the world increases, the aging population problem is becoming more and more urgent and significant. Huge amounts of resources are required for the government and society to take care of the aged population. It is unrealistic for the family members to provide daily and constant care, which is essential for the safety and health of the elders. Remote monitoring systems which can provide health care services for the elderly persons living alone without the presence of family members are becoming popular and mainstream. Remote health monitoring research has drawn significant attention and resources from university researchers, corporations, and governments in many developed countries [2, 3]. Various cameras or sensors based monitoring systems [4, 5, 17] are developed to provide real-time safety and health monitoring and automatic abnormal behavior analysis for the elderly population. The conventional methods, which utilize single or multiple vision cameras or sensors, suffer from the problems of blind spot and system complexity
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