The large and still increasing number of vehicles on the roads has imposed the need for continuously monitoring the traffic behaviour, especially when it comes to illegally parked vehicles that disturb the normal flow of traffic. This paper presents an automatic method for identifying such events in CCTV video, by first tracking all the related objects and then annotating the events with appropriate keywords for storing and retrieval purposes. The method proposed makes use of a combination of video object tracking algorithms and techniques for capturing knowledge in keyword-based ontology structures. Starting from lowlevel visual information extracted from each video frame, high-level semantics such as moving objects are identified and classified. A probabilistic model, which takes its inputs from the visual modules, is used for identifying illegally parked vehicles. Finally, the keyword ontology, constructed automatically from expert descriptions, is linked to objects identified in the video. The results of the conducted experiments are encouraging.