Overview
Introduction
| In 1994, an ambitious project in the multimedia domain was started at
the University of Mannheim under the guidance of
Prof. Dr. W. Effelsberg. We realized that multimedia applications
using continuous media like video and audio data absolutely require
access to semantic contents of these media types in a manner similar
to that for textual and numerical data. Imagine a situation for
textual media in which large digital collections of books, reports,
articles etc. exist but nobody is able to search for pertinent
keywords. Content analysis of continuous data, especially of video
data, is currently based mainly on manual annotations. This implies
that the searchable content is reduced to the annotated content, which
usually does not contain the required information. The aim of the MoCA
project is therefore to extract structural and semantic content of
videos automatically.
During the past years, different applications have been implemented and the scope of the project has concentrated on the analysis of movie material such as can be found on TV, in cinemas and in video-on-demand databases. This has provided access to a great amount of input data for our algorithms. The algorithms developed for video and audio analysis thus concentrate on movie material. However, they are also applicable to general video and audio material. Analysis features developed and used within the MoCA project fall into four different categories:
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