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ABSTRACT
While it would seem that digital video libraries should benefit from access mechanisms directed to their visual contents, years of TREC Video Retrieval Evaluation (TRECVID) research have shown that text search against transcript narrative text provides almost all the retrieval capability, even with visually oriented generic topics. A within-subjects study involving 24 novice participants on TRECVID 2004 tasks again confirms this result. The study shows that satisfaction is greater and performance is significantly better on specific and generic information retrieval tasks from news broadcasts when transcripts are available for search. Additional runs with 7 expert users reveal different novice and expert interaction patterns with the video library interface, helping explain the novices' lack of success with image search and visual feature browsing for visual information needs. Analysis of TRECVID visual features well suited for particular tasks provides additional insights into the role of automated feature classification for digital image and video libraries.
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Xiaonan Lu , Prasenjit Mitra , James Z. Wang , C. Lee Giles, Automatic categorization of figures in scientific documents, Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries, June 11-15, 2006, Chapel Hill, NC, USA
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