Loading [a11y]/accessibility-menu.js
Quickest change detection for health-care video surveillance | IEEE Conference Publication | IEEE Xplore

Quickest change detection for health-care video surveillance


Abstract:

Detecting changes in video scenes is of fundamental importance for various video surveillance tasks. Of particular interest are abnormal changes of foreground human behav...Show More

Abstract:

Detecting changes in video scenes is of fundamental importance for various video surveillance tasks. Of particular interest are abnormal changes of foreground human behaviors/activities that could pose damages or dangers to human properties and lives. In this paper, we propose a unified sequential approach to detecting, as soon as possible, human fall incidents for health-care purpose. Specifically, aspect ratio of human body is extracted as the representative feature, based on which an event-inference module parses observed feature sequences for possible falling behavioral signs. Experimental results are reported to show the efficacy of the proposed approach.
Date of Conference: 21-24 May 2006
Date Added to IEEE Xplore: 11 September 2006
Print ISBN:0-7803-9389-9

ISSN Information:

Conference Location: Kos, Greece

Contact IEEE to Subscribe

References

References is not available for this document.