title: Fall detection using multiple cameras.
abstract: Today, different ways are suggested to help elderly people in case of emergency. Our aim here is to propose a novel method, without any wearable device, to detect falls on the floor with a multiple cameras system. This proposal uses image analysis to localise people and reconstruct their 3D shape and position. The particularity of this contribution is the use of cameras sharing a large common field of view. Experimental results obtained with 14 different fall scenarios and 14 normal daily activities showed a 100% fall detection efficiency.
authors.affiliation: Instut de genie biomedical, University of Montreal, Montreal, Quebec, Canada. auvinet@iro.umontreal.ca
authors.forename: Edouard
authors.initials: E
authors.lastname: Auvinet
authors.forename: Lionel
authors.initials: L
authors.lastname: Reveret
authors.forename: Alain
authors.initials: A
authors.lastname: St-Arnaud
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Rousseau
authors.forename: Jean
authors.initials: J
authors.lastname: Meunier
mesh_terms: D000054:Acceleration; D000058:Accidental Falls / Q000517:prevention & control*; D000203:Activities of Daily Living; D000465:Algorithms; D003198:Computer Simulation; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D015203:Reproducibility of Results; D013686:Telemetry / Q000295:instrumentation* / Q000379:methods; D014159:Transducers; D014741:Video Recording