Information Mining from Multimedia Databases
Ling Guan, Horace H. S. Ip, Paul H. Lewis, Hau−San Wong, Paisarn Muneesawang · EURASIP Journal on Advances in Signal Processing · 2006
Welcome to the special issue on "Information mining from multimedia databases."The main focus of this issue is on information mining techniques for the extraction and interpretation of semantic contents in multimedia databases.The advances in multimedia production technologies have resulted in a rapid proliferation of various forms of media data types on the Internet.Given these high volumes of multimedia data, it is thus essential to extract and interpret their underlying semantic contents from the original signal-based representations without the need for extensive user interaction, and the technique of multimedia information mining plays an important role in this automatic content interpretation process.Due to the spatio-temporal nature of most multimedia data streams, an important requirement for this information mining process is the accurate extraction and characterization of salient events from the original signal-based representation, and the discovery of possible relationships between these events in the form of high-level association rules.The availability of these high-level representations will play an important role in applications such as content-based multimedia information retrieval, preservation of cultural heritage, surveillance, and automatic image/video annotation.For these problems, the main challenges are in the design and analysis of mapping techniques between the signal-level and semantic-level representations, and the adaptive characterization of the notion of saliency for multimedia events in view of its dependence on the preferences of individual users and specific contexts.The focus of the first two papers is on the automatic analysis and interpretation of video contents.X.-P.Zhang and Chen describe a new approach to extracting objects from video sequences which is based on spatio-temporal independent component analysis and multiscale analysis.Specifically, spatio-temporal independent component analysis is