Most video search technologies currently rely on semantic annotation in which videos have to be manually tagged with keywords so they can be found via a text-based search. As most YouTube users will attest, tagging one or two videos in this way is not particularly problematic. However, manually annotating thousands of clips, as content providers and media libraries regularly do, can be extremely time consuming and costly.
A faster alternative is to use software to automatically extract snippets of a video and create a unique identifier based on a variety of audiovisual features, such as scene, motion and music changes. These so-called digital media fingerprints can then be used to index and search full audio/video content. The technology works well for uncompressed, raw audio and video, but it has not been used effectively with the far more common, space-saving compressed files that stream from websites, are stored in media libraries or are broadcast by TV stations. Until now, that is.
“We wanted to develop a way of indexing and searching compressed video files quickly and easily regardless of their compression format or how or where they are stored,” says Nick Achilleopoulos who oversaw development of the technology as manager of the EU-funded DIVAS project.
To achieve that goal, the DIVAS researchers developed two advanced software engines: one to create fingerprints from compressed audio and/or video and another to use these unique identifiers to carry out content-based searches of audiovisual material.
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