A database approach for modeling and querying video data

Indexing video data is essential for providing content based access. We consider how database technology can offer an integrated framework for modeling and querying video data. We develop a data model and a rule-based query language for video content based indexing and retrieval. The data model is designed around the object and constraint paradigms. A video sequence is split into a set of fragments. Each fragment can be analyzed to extract the information (i.e., symbolic descriptions) of interest that can be put into a database. This database can then be searched to find information of interest. Two types of information are considered: the entities (i.e., objects) of interest in the domain of a video sequence; video frames which contain these entities. To represent this information, our data model allows facts as well as objects and constraints. We present a declarative, rule-based, constraint query language that can be used to infer relationships about information represented in the model. The language has a clear declarative and operational semantics.