A database approach for modeling and querying video data

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Abstract
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.

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