Addressing the challenge of visual information access from digital image and video libraries

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...

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Vydáno v:Proceedings of the 5th ACM/IEEE Joint Conference on Digital Libraries : Denver, CO, USA, June 7-11, 2005 : digital libraries, cyberinfrastructure for research and education s. 69 - 78
Hlavní autoři: Christel, Michael G., Conescu, Ronald M.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: New York, NY, USA ACM 07.06.2005
IEEE
Edice:ACM Conferences
Témata:
Applied computing > Computers in other domains > Digital libraries and archives
Automatic testing
Broadcasting
Content based retrieval
Digital images
Human computer interaction
Image analysis
Image retrieval
Indexing
Information retrieval
Information systems > Information retrieval
Information systems > Information systems applications > Digital libraries and archives
Software libraries
TRECVID results analysis
video retrieval
TRECVID results analysis
video retrieval
ISBN:1581138768, 9781581138764
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Popis
Shrnutí: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.
Bibliografie:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:1581138768
9781581138764
DOI:10.1145/1065385.1065402