Events Detection Using a Video-Surveillance Ontology and a Rule-Based Approach

In this paper, we propose the use of a Video-surveillance Ontology and a rule-based approach to detect an event. The scene is described using the concepts presented in the ontology. Then, the blobs are extracted from the video stream and are represented using the bounding boxes that enclose them. Finally, a set of rules have been proposed and have been applied to videos selected from PETS 2012 challenge that contain multiple objects events (e.g. Group walking, Group splitting, etc.).

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