MOODS is an object-oriented application development framework for identifying, managing, and storing the embedded content found in multimedia data. "Embedded content" refers to any information that is contained in the data, but is not directly accessible (akin to data mining). With an image, for example, we can talk about the features that appear in the image. With map data, content would include hills, roads, churches, landmarks, etc.
MOODS is a object-oriented framework for quickly and easily developing applications that identify, manage, and store embedded information. The MOODS framework integrates an object-oriented programming language for creating the application, a library of processing operations used to identify content, a knowledge base for identifying complex embedded features, a database for storage and retrieval, and a graphical user interface.
|
|
James Griffioen |
|
|
Raj Yavatkar |
|
|
Robert Adams |
|
|
A Framework for Developing Content-Based Retrieval Systems. Chapter 15 of Intelligent Multimedia Information Retrieval. AAAI/MIT Press. 1997. |
|
|
Automatic
and Dynamic Identification of Metadata in Multimedia. 1st IEEE Metadata Conference. 1996. (PostScript) |
|
|
An
Object-Oriented Model for the Semantic Interpretation of Multimedia Data. ACM Multimedia 1995 Demonstration Summary. 1995. (PostScript) |
|
|
A Semantic
Data Model for Embedded Image Information. IS&T/SPIE. High-Speed Networking and Multimedia Computing. 1995. (PostScript) |
|
|
MOODS: A Multimedia
Information Modeling System. Workshop on Database Systems. ACM Multimedia. 1994. (PostScript) |
|
|
An
Object-Oriented Model for Image Information Representation. Information and Knowledge Management Conference. 1993. (PostScript) |
