A Database Approach for Modeling and Querying Video Data

  • Authors:

  • Mohand-Saïd Hacid;Cyril Decleir;Jacques Kouloumdjian

  • Affiliations:

  • -;-;-

  • Venue:
  • IEEE Transactions on Knowledge and Data Engineering
  • Year:
  • 2000

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Abstract

Indexing video data is essential for providing content-based access. In this paper, we consider how database technology can offer an integrated framework for modeling and querying video data. As many concerns in video (e.g., modeling and querying) are also found in databases, databases provide an interesting angle to attack many of the problems. From a video applications perspective, database systems provide a nice basis for future video systems. More generally, database research will provide solutions to many video issues, even if these are partial or fragmented. From a database perspective, video applications provide beautiful challenges. Next generation database systems will need to provide support for multimedia data (e.g., image, video, audio). These data types require new techniques for their management (i.e., storing, modeling, querying, etc.). Hence, new solutions are significant. This paper develops 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 (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: 1) the entities (objects) of interest in the domain of a video sequence, and 2) video frames which contain these entities. To represent this information, our data model allows facts as well as objects and constraints. The model consists of two layers: 1) Feature & Content Layer (or Audiovisual Layer), intended to contain video visual features such as colors, contours, etc., 2) Semantic Layer, which provides the (conceptual) content dimension of videos. We present a declarative, rule-based, constraint query language that can be used to infer relationships about information represented in the model. Queries can refer to the form dimension (i.e., information of the Feature & Content Layer), to the content dimension (i.e., information of the Semantic Layer), or to both. A program of the language is a rule-based system formalizing our knowledge of a video target application and it can also be considered as a (deductive) video database on its own right. The language has both a clear declarative and operational semantics.