DocumentCode
3669658
Title
Detecting unusual inactivity by introducing activity histogram comparisons
Author
Rainer Planinc;Martin Kampel
Author_Institution
Computer Vision Lab, Vienna University of Technology, Favoritenstrasse 9-11/183-2, A-1040, Austria
Volume
2
fYear
2014
Firstpage
313
Lastpage
320
Abstract
Unusual inactivity at elderly´s homes is an evidence that help is needed. Hence, the automatic detection of abnormal behaviour with a low number of false positives is desired. The aim of this work is to improve the accuracy of inactivity detection by introducing a new approach based on histogram comparison in order to reliably detect abnormal behaviour in elderly´s homes. The proposed approach compares activity histograms with a pre-trained reference histogram and detects deviations from normal behavior. Evaluation is performed on a dataset containing 103 days of activity, where six days were reported as containing “unusual” inactivity (i.e., longer absence from home) by an elderly couple.
Keywords
"Histograms","Sensors","Tracking","Training","Training data"
Publisher
ieee
Conference_Titel
Computer Vision Theory and Applications (VISAPP), 2014 International Conference on
Type
conf
Filename
7294947
Link To Document