Automatic Learning of an Activity-Based Semantic Scene Model

Authors:
Dimitrios Makris;Tim Ellis
Affiliations:
-;-
Venue:
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Year:
2003

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Abstract

This paper proposes an activity-based semantic model for a scene under visual surveillance. It illustrates methods that allow unsupervised learning of the model, from trajectory data derived from automatic visual surveillance cameras. Results are shown for each method. Finally, thebenefits of such a model in a visual surveillance system are discussed.