DocumentCode :
2593586
Title :
Context aware inactivity recognition for visual fall detection
Author :
Jansen, Bart ; Deklerck, Rudi
Author_Institution :
Dept. of Electron. & Informatics, Vrije Univ. Brussel
fYear :
2006
fDate :
Nov. 29 2006-Dec. 1 2006
Firstpage :
1
Lastpage :
4
Abstract :
This paper introduces a method for automatic fall detection, targeted towards the monitoring of elderly people in a nursing home or in their natural home environment. The method uses information extracted from images obtained using novel 3D camera technology, combined with a context model. Visual information consists of body orientation calculated from posture extraction and of periods of inactivity. The context model allows for a different interpretation of the visual fall detection results, depending on the exact location, time and duration of the detected event. The context model is learnt during the ongoing monitoring task without human intervention and automatically adapts to the changing activity patterns of the monitored subject
Keywords :
accidents; feature extraction; geriatrics; patient monitoring; 3D camera technology; automatic visual fall detection; context awareness; context model; elderly people monitoring; inactivity recognition; information extraction; posture extraction; Biological system modeling; Cameras; Computerized monitoring; Context awareness; Context modeling; Data mining; Event detection; Humans; Medical services; Senior citizens;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Health Conference and Workshops, 2006
Conference_Location :
Innsbruck
Print_ISBN :
1-4244-1085-1
Electronic_ISBN :
1-4244-1086-X
Type :
conf
DOI :
10.1109/PCTHEALTH.2006.361657
Filename :
4205148
Link To Document :
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