Modeling and Querying Video Data: A Hybrid Approach

This paper develops a video data model and a rule-based query language for video retrieval. A video sequence is split into a set of fragments. Each fragment can be analyzed to extract the information 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: (1) the entities (objects) of interest in a video sequence, (2) generalized strata (a set of fragments), which contain these entities. To represent these 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