• DocumentCode
    1396027
  • Title

    A database approach for modeling and querying video data

  • Author

    Hacid, Mohand-Said ; Decleir, Cyril ; Kouloumdjian, Jacques

  • Author_Institution
    Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA
  • Volume
    12
  • Issue
    5
  • fYear
    2000
  • Firstpage
    729
  • Lastpage
    750
  • 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
  • Keywords
    constraint handling; content-based retrieval; database indexing; knowledge based systems; object-oriented programming; query languages; video databases; content-based access; data model; database approach; database technology; integrated framework; rule-based query language; video content-based indexing and retrieval; video data indexing; video data querying; video modelling; video sequence; Content based retrieval; Data models; Database languages; Database systems; Image databases; Indexing; Information retrieval; Multimedia databases; Multimedia systems; Video sequences;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.877505
  • Filename
    877505