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|Title:||Fall detection and alert for ageing-at-home of elderly|
State Change Pattern
|Citation:||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)|
|Appears in Collections:||Staff Publications|
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