title: Monocular 3D head tracking to detect falls of elderly people.
abstract: Faced with the growing population of seniors, Western societies need to think about new technologies to ensure the safety of elderly people at home. Computer vision provides a good solution for healthcare systems because it allows a specific analysis of people behavior. Moreover, a system based on video surveillance is particularly well adapted to detect falls. We present a new method to detect falls using a single camera. Our approach is based on the 3D trajectory of the head, which allows us to distinguish falls from normal activities using 3D velocities.
authors.affiliation: Dept. of Comput. Sci. & Oper. Res., Montréal Univ., Canada. rougier@iro.umontreal.ca
authors.forename: Caroline
authors.initials: C
authors.lastname: Rougier
authors.forename: Jean
authors.initials: J
authors.lastname: Meunier
authors.forename: Alain
authors.initials: A
authors.lastname: St-Arnaud
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Rousseau
mesh_terms: D000058:Accidental Falls; D000061:Accidents, Home; D000368:Aged; D003201:Computers; D004867:Equipment Design; D006257:Head / Q000473:pathology; D006699:Home Care Services; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional; D010363:Pattern Recognition, Automated; D012984:Software