By Charles B. Owen
Multimedia is altering the layout of database and data retrieval platforms. the buildup of audio, photograph, and video content material is of little use in those structures if the content material can't be retrieved on call for, a severe requirement that has resulted in the advance of recent applied sciences for the research and indexing of media facts. In flip, those applied sciences search to derive details or beneficial properties from a knowledge sort that could facilitate fast retrieval, effective compression, and logical presentation of the information. major paintings that has now not been addressed, even if, is the advantages of examining multiple info kind concurrently. Computed Synchronization for MultimediaApplications offers a brand new framework for the simultaneous research of a number of media info gadgets. the first good thing about this research is computed synchronization, a temporal and spatial alignment of a number of media items.
Computed Synchronization for Multimedia Applications additionally offers a number of particular purposes and a common constitution for the answer of computed synchronization difficulties. The purposes exhibit using this constitution. functions particularly are defined intimately: the alignment of textual content to speech audio, and the alignment of simultaneous English language translations of historical texts. Many extra purposes are mentioned as destiny makes use of of the expertise.
Computed Synchronization for Multimedia Applications comes in handy to researchers, scholars, and builders looking to follow computed synchronization in lots of fields. it's also appropriate as a reference for a graduate-level path in multimedia facts retrieval.
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Extra info for Computed Synchronization for Multimedia Applications
MRGs can model complex phenomena. Continuing with the Chapter 6 example, it is not known when users will pause between words. Linguistic research can predict these pauses, but not with any certainty. Also, various sources of noise may exist between words. Speech systems use various models for noise and pauses. 5 illustrates how an MRG is used to model the possible noise and pauses between words. pau" (pause). The media element transition edges allow for all possible combinations of noise and silence between words, or the case of no inter-word content at all.
R, Vi = 1, .. , N. It is not required that the domain of the media be real valued in this model. It is assumed that there exists some relationship among these media objects such that causal and/or spatial synchronization is meaningful. C. B. , Computed Synchronization for Multimedia Applications © Springer Science+Business Media New York 1999 40 COMPUTED SYNCHRONIZATION FOR MULTIMEDIA APPUCATIONS The problem of synchronization of unrelated media objects is difficult to quantify. Examples of unrelated media objects include text transcripts and speech audio where the transcript does not represent the presented text or alignment of two text documents with no common theme or content.
3 MEDIA ELEMENT TRANSFORMATIONS A common transformation in computed synchronization applications is the selection of a more appropriate media element. As the last section illustrated, mUltiple media element structures can be defined for most media types. SGML documents can be described as sequences of bytes, words, or document sections. Each of these representations is a different causal media stream type. The types are related to each other through equivalence transformations (or semi-equivalence transformations when the alternative representations sacrifice some content).