title: Detection of collaborative activity with Kinect depth cameras.
abstract: The health status of elderly subjects is highly correlated to their activities together with their social interactions. Thus, the long term monitoring in home of their health status, shall also address the analysis of collaborative activities. This paper proposes a preliminary approach of such a system which can detect the simultaneous presence of several subjects in a common area using Kinect depth cameras. Most areas in home being dedicated to specific tasks, the localization enables the classification of tasks, whether collaborative or not. A scenario of a 24 hours day shrunk into 24 minutes was used to validate our approach. It pointed out the need of artifacts removal to reach high specificity and good sensitivity.
authors.forename: Loic
authors.initials: L
authors.lastname: Sevrin
authors.forename: Norbert
authors.initials: N
authors.lastname: Noury
authors.forename: Nacer
authors.initials: N
authors.lastname: Abouchi
authors.forename: Fabrice
authors.initials: F
authors.lastname: Jumel
authors.forename: Bertrand
authors.initials: B
authors.lastname: Massot
authors.forename: Jacques
authors.initials: J
authors.lastname: Saraydaryan
mesh_terms: D000054:Acceleration; D016477:Artifacts; D003299:Cooperative Behavior; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation; D010781:Photography / Q000295:instrumentation*; D012371:Robotics