Semantic modeling and knowledge representation in multimedia databases

被引:55
作者
Al-Khatib, W
Day, YF
Ghafoor, A
Berra, PB
机构
[1] Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA
[2] Siemens Corp Res, Multimedia Documentat Program, Princeton, NJ 08540 USA
[3] Wright State Univ, Dept Comp Sci & Engn, Dayton, OH 45435 USA
基金
美国国家科学基金会;
关键词
multimedia data modeling; multimedia document modeling; semantic modeling; knowledge representation; content-based retrieval; image databases; video databases; video indexing; query formulation; query processing;
D O I
10.1109/69.755616
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we present the current state of the art in semantic data modeling of multimedia data. Semantic conceptualization can be performed at several levels of information granularity, leading to multilevel indexing and searching mechanisms. Various models at different levels of granularity are compared. At the finest level of granularity, multimedia data can be indexed based on image contents, such as identification of objects and faces. At a coarser level of granularity, indexing of multimedia data can be focused on events and episodes, which are higher level abstractions. In light of the above, we also examine modeling and indexing techniques of multimedia documents.
引用
收藏
页码:64 / 80
页数:17
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