Fisher, Pam and Alhabib, Abbas and Giotsas, Vasileios and Andreopoulos, I. (2015) Video Clarity:High Speed Data Mining for Video. In: IBC 2015. Institution of Engineering and Technology, London. ISBN 9781785611858
Full text not available from this repository.Abstract
Video now dominates ICT networks and systems, representing over 64% of global IP traffic1 and over half of all storage within enterprises and data centers2. However, today video cannot be searched in the same way as alphanumeric data - this represents an unyielding `big data' problem. Current video search relies on resource-intensive human annotations placed in a database, as alphanumeric data. This paper describes a new technology innovated by BAFTA (British Academy of Film and Television Arts) and UCL (University College London), which addresses this issue. The technology extracts a compact video signature representing significant features of the video for search, which can then be used for a plethora of applications such as similarity detection, de-duplication of files, piracy detection, and semantic classification. The video signatures are extremely rich yet highly compact, sized at approximately 5 megabytes per running hour of video. This enables video to be searched at the speed of data, allowing video to become a firstclass citizen of ICT networks and systems.