Activity summarisation and fall detection in a supportive home environment

This source preferred by Hammadi Nait-Charif

Authors: Nait-Charif, H. and McKenna, S.J.

Editors: Kittler, J., Petrou, M. and Nixon, M.

Volume: 4

Pages: 323-326

Publisher: IEEE Computer Society

Place of Publication: Los Alamitos

This data was imported from DBLP:

Authors: Nait-Charif, H. and McKenna, S.J.

http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9258

Pages: 323-326

Publisher: IEEE Computer Society

DOI: 10.1109/ICPR.2004.1333768

This data was imported from Scopus:

Authors: Nait-Charif, H. and McKenna, S.J.

Volume: 4

Pages: 323-326

DOI: 10.1109/ICPR.2004.1333768

Automatic semantic summarisation of human activity and detection of unusual inactivity are useful goals for a vision system operating in a supportive home environment. Learned models of spatial context are used in conjunction with a tracker to achieve these goals. The tracker uses a coarse ellipse model and a particle filter to cope with cluttered scenes with multiple sources of illumination. Summarisation in terms of semantic regions is demonstrated using acted scenes through automatic recovery of the instructions given to the actor. The use of 'unusual inactivity' detection as a cue for fall detection is also demonstrated.

This data was imported from Web of Science (Lite):

Authors: Nait-Charif, H. and McKenna, S.J.

Pages: 323-326

DOI: 10.1109/ICPR.2004.1333768

The data on this page was last updated at 05:09 on February 24, 2020.