Multimedia Database
Document Sample


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.
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