DocumentCode :
3746208
Title :
Fall down detection for surveillance system of health care
Author :
Wei Quan;Naoyuki Kubota
Author_Institution :
Graduate School of System Design, Tokyo Metropolitan University, Japan 191-0065
fYear :
2015
Firstpage :
232
Lastpage :
236
Abstract :
Since the world technology grows faster and faster, the people is becoming much more health than ever before, thus getting longer of living age. On the other hand however, the rising number of elderly people also course the problem such as the aging of population. One case is that the population of elderly who live alone is increasing and more assistance should support on the situation the health care resource is less. Thus we proposed the surveillance system to apply for this situation. This paper focuses on the surveillance system which focuses on the individual house to detect the unmoral behavior such as falling down when elderly people lives alone. And comparing with the most popular methodology such as Aspect Ratios, the method we proposed has conquered its weakness and performed will in most situations.
Keywords :
"Computational modeling","Object detection","Robustness"
Publisher :
ieee
Conference_Titel :
Technologies and Applications of Artificial Intelligence (TAAI), 2015 Conference on
Electronic_ISBN :
2376-6824
Type :
conf
DOI :
10.1109/TAAI.2015.7407088
Filename :
7407088
Link To Document :
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