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Interactive searching and browsing of video archives: using text and using image matching

Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389, Gurrin, Cathal orcid logoORCID: 0000-0003-4395-7702 and Lee, Hyowon orcid logoORCID: 0000-0003-4395-7702 (2006) Interactive searching and browsing of video archives: using text and using image matching. In: Interactive Video: Algorithms and Technologies. Signals and Commmunication Technologies . Springer Berlin / Heidelberg, pp. 189-206. ISBN 978-3-540-33215-2

Over the last number of decades much research work has been done in the general area of video and audio analysis. Initially the applications driving this included capturing video in digital form and then being able to store, transmit and render it, which involved a large effort to develop compression and encoding standards. The technology needed to do all this is now easily available and cheap, with applications of digital video processing now commonplace, ranging from CCTV (Closed Circuit TV) for security, to home capture of broadcast TV on home DVRs for personal viewing. One consequence of the development in technology for creating, storing and distributing digital video is that there has been a huge increase in the volume of digital video, and this in turn has created a need for techniques to allow effective management of this video, and by that we mean content management. In the BBC, for example, the archives department receives approximately 500,000 queries per year and has over 350,000 hours of content in its library. Having huge archives of video information is hardly any benefit if we have no effective means of being able to locate video clips which are of relevance to whatever our information needs may be. In this chapter we report our work on developing two specific retrieval and browsing tools for digital video information. Both of these are based on an analysis of the captured video for the purpose of automatically structuring into shots or higher level semantic units like TV news stories. Some also include analysis of the video for the automatic detection of features such as the presence or absence of faces. Both include some elements of searching, where a user specifies a query or information need, and browsing, where a user is allowed to browse through sets of retrieved video shots. We support the presentation of these tools with illustrations of actual video retrieval systems developed and working on hundreds of hours of video content.
Item Type:Book Section
Additional Information:The original publication is available at www.springerlink.com
Subjects:Computer Science > Information storage and retrieval systems
Computer Science > Digital video
DCU Faculties and Centres:Research Institutes and Centres > Centre for Digital Video Processing (CDVP)
Research Institutes and Centres > Adaptive Information Cluster (AIC)
Publisher:Springer Berlin / Heidelberg
Official URL:http://dx.doi.org/10.1007/978-3-540-33215-2_9
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, SFI 03/IN.3/I361, Enterprise Ireland
ID Code:375
Deposited On:31 Mar 2008 by DORAS Administrator . Last Modified 02 Nov 2018 15:56

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