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
         
        
        
        
        
        
            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"
         
        
        
            Conference_Titel : 
Computer Vision Theory and Applications (VISAPP), 2014 International Conference on