Events detection using a video-surveillance Ontology and a rule-based approach

Mohammed Yassine Kazi Tani (1) , Adel Lablack (2) , Abdelghani Ghomari (1) , Ioan Marius Bilasco (3, 2, 4)

1 University of Oran Es-Senia [Oran] | Université d'Oran Es-Senia [Oran]
2 LIFL - FOX MIIRE
3 LIFL - Laboratoire d'Informatique Fondamentale de Lille
4 Université de Lille, Sciences et Technologies

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.).

Mots clés: Ontology; Video surveillance; blobs; rules

Domaines: Multimédia [cs.MM]

Mohammed Yassine Kazi Tani, Adel Lablack, Abdelghani Ghomari, Ioan Marius Bilasco. Events detection using a video-surveillance Ontology and a rule-based approach. ECCV 2014 : Workshops on Computer Vision, Sep 2014, Zurich, Switzerland. pp 299-308, ⟨10.1007/978-3-319-16181-5_21⟩. ⟨hal-01075090⟩