title: Nighttime in-home action monitoring for eldercare.
abstract: In this work, we develop a system to automatically monitoring actions of elderly people at home for safety enhancement and health monitoring. We use an Infrared camera embedded in a living environment to capture images. We study the characteristics of different clothing in Infrared images and develop an efficient silhouette extraction method for Infrared (IR) images using spatio-temporal filtering. We recognize human action using supervised learning methods. Our experimental results demonstrate that our proposed method is efficient.
authors.affiliation: Department of Electrical and Computer Engineering, University of Missouri, Columbia, MO, USA.
authors.forename: Zhongna
authors.initials: Z
authors.lastname: Zhou
authors.forename: Erik Edward
authors.initials: EE
authors.lastname: Stone
authors.forename: Marjorie
authors.initials: M
authors.lastname: Skubic
authors.forename: James
authors.initials: J
authors.lastname: Keller
authors.forename: Zhihai
authors.initials: Z
authors.lastname: He
mesh_terms: D056044:Actigraphy / Q000379:methods*; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007259:Infrared Rays; D008297:Male; D018670:Monitoring, Ambulatory / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013817:Thermography / Q000379:methods*; D051598:Whole Body Imaging / Q000379:methods*