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1999
Journal Article
Titel
Content-based retrieval from digital video
Abstract
There is already a huge demand for efficient image indexing and content-based retrieval. With TV going digital, advances in real-time videa decompression, easy access to the Internet and the availability of cheap mass storage and fast graphics adaptor cards, digital video will become the next "big" media. Unfortunately , automatic indexing and feature extraction from digital video is even harder than still-image analysis. Presently, automatic analysis of digital video is mostly restricted to automatic detection of scene changes. In this paper we present a framework suitable to immediately explore the consequences of content-based videa retrieval with a high granularity of video content. The framework employs Semantic networks to represent video contents on a high level of abstraction and uses time-varying senitive regions to link objects in a video to the knowledge base. A prototype was implemented under NEXTSTEP, exploiting the rich user-interface capabilities of this platform to feat ure drag and drop queries and authoring of the videa retrieval system.