Video understanding for complex activity recognition

Authors:
Florent Fusier;Valéry Valentin;François Brémond;Monique Thonnat;Mark Borg;David Thirde;James Ferryman
Affiliations:
ORION Team, INRIA Sophia-Antipolis, 2004 Route des Lucioles BP 93, 06902, Sophia antipolis, France;ORION Team, INRIA Sophia-Antipolis, 2004 Route des Lucioles BP 93, 06902, Sophia antipolis, France;ORION Team, INRIA Sophia-Antipolis, 2004 Route des Lucioles BP 93, 06902, Sophia antipolis, France;ORION Team, INRIA Sophia-Antipolis, 2004 Route des Lucioles BP 93, 06902, Sophia antipolis, France;The University of Reading, Whiteknights, Computational Vision Group, 2004 Route des Lucioles BP 93, RG6 6AY, Reading, UK;The University of Reading, Whiteknights, Computational Vision Group, 2004 Route des Lucioles BP 93, RG6 6AY, Reading, UK;The University of Reading, Whiteknights, Computational Vision Group, 2004 Route des Lucioles BP 93, RG6 6AY, Reading, UK
Venue:
Machine Vision and Applications
Year:
2007

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Abstract

This paper presents a real-time video understanding system which automatically recognises activities occurring in environments observed through video surveillance cameras. Our approach consists in three main stages: Scene Tracking, Coherence Maintenance, and Scene Understanding. The main challenges are to provide a robust tracking process to be able to recognise events in outdoor and in real applications conditions, to allow the monitoring of a large scene through a camera network, and to automatically recognise complex events involving several actors interacting with each others. This approach has been validated for Airport Activity Monitoring in the framework of the European project AVITRACK.