Advertisement
Published in:
2016 | OriginalPaper | Chapter
Fall Detection Using Body-Worn Accelerometer and Depth Maps Acquired by Active Camera
Authors : Michal Kepski, Bogdan Kwolek
Published in: Hybrid Artificial Intelligent Systems
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
In the presented system to person fall detection a body-worn accelerometer is used to indicate a potential fall and a ceiling-mounted depth sensor is utilized to authenticate fall alert. In order to expand the observation area the depth sensor has been mounted on a pan-tilt motorized head. If the person acceleration is above a preset threshold the system uses a lying pose detector as well as examines a dynamic feature to authenticate the fall. Thus, more costly fall authentication is not executed frame-by-frame, but instead we fetch from a circular buffer a sequence of depth maps acquired prior to the fall and then process them to confirm fall alert. We show that promising results in terms of sensitivity and specificity can be obtained on publicly available UR Fall Detection dataset.