Automated scene understanding for airport aprons

Authors:
James Ferryman;Mark Borg;David Thirde;Florent Fusier;Valéry Valentin;François Brémond;Monique Thonnat;Josep Aguilera;Martin Kampel
Affiliations:
Computational Vision Group, The University of Reading, UK;Computational Vision Group, The University of Reading, UK;Computational Vision Group, The University of Reading, UK;ORION Team, INRIA Sophia-Antipolis, France;ORION Team, INRIA Sophia-Antipolis, France;ORION Team, INRIA Sophia-Antipolis, France;ORION Team, INRIA Sophia-Antipolis, France;Pattern Recognition and Image Processing Group, Vienna University of Technology, Austria;Pattern Recognition and Image Processing Group, Vienna University of Technology, Austria
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

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Abstract

This paper presents a complete visual surveillance system for automatic scene interpretation of airport aprons. The system comprises two main modules — Scene Tracking and Scene Understanding. The Scene Tracking module is responsible for detecting, tracking and classifying the semantic objects within the scene using computer vision. The Scene Understanding module performs high level interpretation of the observed objects by detecting video events using cognitive vision techniques based on spatio-temporal reasoning. The performance of the system is evaluated for a series of pre-defined video events specified using a video event ontology.