Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-02868-7_26
Title: Fall detection and alert for ageing-at-home of elderly
Authors: Yu, X.
Wang, X.
Kittipanya-Ngam, P.
Eng, H.L.
Cheong, L.-F. 
Keywords: Ageing-at-Home
Assistive Technology
Camera Calibration
Fall Detection
State Change Pattern
Issue Date: 2009
Source: Yu, X.,Wang, X.,Kittipanya-Ngam, P.,Eng, H.L.,Cheong, L.-F. (2009). Fall detection and alert for ageing-at-home of elderly. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5597 LNCS : 209-216. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-02868-7_26
Abstract: Fall detection has been an active research problem as fall detection technology is critical for the ageing-at-home of the elderly and it can enhance life safety of the elderly and boost their confidence of ageing-at-home by immediately alerting fall occurrence to care givers. This paper presents an algorithm of fall detection for the ageing-at-home of the elderly. This algorithm detects fall events by identifying (human) shape state change pattern reflecting a fall incident from video recorded by a single fixed camera. The novelty of the algorithm is multiple. First, it detects fall occurrence by identifying the state change pattern. Second, it uses the camera projection matrix in its computing. Thus, it eliminates camera setting-related learning. Lastly, it adds constraints to state change pattern to reduce false alarms. Experiments show that the proposed algorithm has a promising performance. © 2009 Springer Berlin Heidelberg.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/70291
ISBN: 3642028675
ISSN: 03029743
DOI: 10.1007/978-3-642-02868-7_26
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

9
checked on Dec 5, 2017

Page view(s)

48
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.