Multimedia Database

							Multimedia
 Database
       By
  Lili Wangsa
Coding
   Homogeneity
    - continuous and homogenous on appearance
    - possible to detect outline/shape object
   Compactness
    - tend to be connected together
    - parts usually closed tied together
   Symmetry
    - most natural object have a symmetry
    - detected as a strong feature for indexing
Indexing
   Inversion of terms
    - selecting keywords and use them as index
   Multi-attribute
    - data coded into several categories based on bit
    pattern
    - signature (index and retrieved used)
   Clustering
    - coded by several categories, stored in a vector
    - using similarity matrices
Retrieval
   Query by Contents
   Iconic Query
   SQL Query
   Mixed Query
References
   [1]. A. D. Bimbo, M. Campanai, and P. Nesi, A three-dimensional iconic environment for
       image database querying, IEEE Trans. Software Eng, 1993.

   [2]. M. Flickner, H. Sawhney, W.Niblack, J. Ashley, Q. Huang, B. Dom, M Gorkhani, J
        Hafner, D. Lee, D. Petkovic, D. Steele, and P. Yanker, Query by image and video
        content: QBIC system, IEEE Computer 28, 1995.

   [3]. S. K. Chang and T. Kunii, Pictorial database systems, IEEE Computer Nov, 1981.

   [4]. A. Gupta, S. Santiniy, Toward Feature Algebras in Visual Databases: The Case
       for a Histogram Algebra, VDB-5, Int. Conf. On Visual Databases, Tokyo, 2000.

   [5]. E. Izquierdo, J. R. Casas, R. Leonardi, P. Migliorati, Noel E. O'Connor,
        I. Kompatsiaris and M. G. Strintzis, "Advanced Content-Based Semantic
        Scene Analysis and Information Retrieval: The SCHEMA project",
        Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2003),
        London, 2003.