Effective storage and retrieval of digitised video for reuse in industries such as news broadcasters is a difficult and costly process. It relies on good quality semantic annotation which is notoriously difficult to produce for video content. The CASAM project developed a new approach to supporting annotation of video content by combining the strengths of human annotated with the speed and efficiency of autonomous video analysis. The resulting system is able to support annotation of video with increased quality and quantity of annotation whilst reducing time and cost.
References to the research
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