Title :
Detecting fall events based on motion history and shape change on a multi-camera network
Author :
Güney Kayım;Ceyhun Burak Akgül
fDate :
4/1/2012 12:00:00 AM
Abstract :
One of the greatest risk for seniors is to fall when they are alone. Detection of the fall event and early intervention minimizes the effect of the fall. The fall event could be observed without necessity of a companion thanks to advances in computer vision. This paper aims to detect the fall events using information received from motion history and shape change. Additionally, the effect of multi-camera network to this approach is analyzed.
Keywords :
"History","Shape","Reactive power","Kalman filters","Conference proceedings","Biomedical engineering","Conferences"
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2012 20th
Print_ISBN :
978-1-4673-0055-1
DOI :
10.1109/SIU.2012.6204844