A semantic data model and query language for video databases
Advances in compression techniques, decreasing cost of storage, and high—speed transmission have facilitated the way video is created, stored and distributed. As a consequence, video is now being used in many application areas. The increase in the amount of video data deployed and used in today’s applications not only caused video to draw more attention as a multimedia data type, but also led to the requirement of efﬁcient management of video data. Management of video data paved the way for new research areas, such as indexing and retrieval of videos with respect to their spatio—temporal, visual and semantic contents. In this thesis, semantic content of video is studied, where video metadata, activities, actions and objects of interest are considered within the context of video semantic content. A data model is proposed to model video semantic content, which is extracted from video data by a video annotation tool. A video query language is also provided to support semantic queries on video data.
The outcome of this thesis work will be used in a project, which proposes a video database system architecture with spatio—temporal, object—trajectory and object—apperance query facilities so as to build a complete video search system to query video data by its spatio—temporal, visual and semantic features.