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

Published:07 June 2005Publication History

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.

References

  1. Christel, M., and Moraveji, N. Finding the Right Shots: Assessing Usability and Performance of a Digital Video Library Interface. In Proc. ACM Multimedia (New York, October 2004), 732--739. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Enser, P.G.B. Pictorial information retrieval. Journal of Documentation, 51, 2 (1995), 126--170.Google ScholarGoogle ScholarCross RefCross Ref
  3. Enser, P.G.B. and Sandom, C.J. Retrieval of Archival Moving Imagery - CBIR Outside the Frame? In Image and Video Retrieval (CIVR 2002 Proceedings), 206--214. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. French, J.C., Chapin, A.C., and Martin, W.N. An Application of Multiple Viewpoints to Content-Based Image Retrieval. In Proc. JCDL (Houston, May 2003), 128--130. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Graham, J. Search engine Google sets sights on video. USA Today, Jan. 25, 2005, www.usatoday.com/tech/news/2005-01-25-google-usat_x.htm http://www.usatoday.com/tech/news/2005-01-25-google-usat_x.htm.Google ScholarGoogle Scholar
  6. Hauptmann, A., and Christel, M. Successful Approaches in the TREC Video Retrieval Evaluations. In Proc. ACM Multimedia (New York, October 2004), 668--675. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Jose, J.M., Furner, J., and Harper, D.J. Spatial querying for image retrieval: a user-oriented evaluation. In Proc. ACM SIGIR (1998), 232--240. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Kraaij, W., Smeaton, A.F., Over, P., and Arlandis, J. TRECVID 2004 - An Introduction. In TRECVID 2004 Proceedings, http://www-nlpir.nist.gov/projects/trecvid/.Google ScholarGoogle Scholar
  9. Lee, H. and Smeaton, A.F. Designing the User Interface for the Físchlár Digital Video Library, J. Digital Info. 2(4), http://jodi.ecs.soton.ac.uk/Articles/v02/i04/Lee/, May 2002.Google ScholarGoogle Scholar
  10. Markkula, M. and Sormunen, E. End-user searching challenges indexing practices in the digital newspaper photo archive. Information Retrieval, 1, 4 (2000), 259--285. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Moënne-Loccoz, N., Janvier, B., Marchand-Maillet, S., and Bruno, E. Managing Video Collections at Large. In ACM Proc. Workshop on Computer Vision meets Databases (Paris, June 2004), 59--66. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Nielsen, J. Heuristic Evaluation. In Nielsen, J., and Mack, R.L. (eds.), Usability Inspection Methods. John Wiley & Sons, New York, NY, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Rasmussen, E. Indexing images. Annual Review of Information Science and Technology, 32 (1997), 169-196.Google ScholarGoogle Scholar
  14. Rodden, K. and Wood, K.R. How Do People Manage Their Digital Photographs? In Proc. CHI (Ft. Lauderdale, FL, April 2003), 409--416. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Shatford, S. Analyzing the Subject of a Picture: A Theoretical Approach. Cataloguing & Classification Quarterly, 6, 3 (Spring 1986), 39--62.Google ScholarGoogle ScholarCross RefCross Ref
  16. Shneiderman, B., Byrd, D., and Croft, W.B. Clarifying Search: A User-Interface Framework for Text Searches. D-Lib Magazine, 3, 1 (January 1997), <http://www.dlib.org>.Google ScholarGoogle Scholar
  17. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., and Jain, R. Content based image retrieval at the end of the early years. IEEE Trans. Pattern Analysis and Machine Intelligence, 22, 12 (2000), 1349--1380. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Soo, V.-W., Lee, C.-Y., Li, C.-C., Chen, S.L., and Chen, C. Automated Semantic Annotation and Retrieval Based on Sharable Ontology and Case-based Learning Techniques. In Proc. JCDL (Houston, May 2003), 61--72. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Urban, J., Jose, J.M., and van Rijgsbergen, C.J. An Adaptive Technique for Content-Based Image Retrieval. Multimedia Tools and Applications, 25 (2005). Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Worring, M., Smeulders, A.W.M, and Santini, S. Interaction in content-based retrieval: an evaluation of the state-of-the-art. LNCS 1929, Springer-Verlag (2000), 26--36. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Yang, M., Wildemuth, B., and Marchionini, G. The relative effectiveness of concept-based versus content-based video retrieval. In Proc. ACM Multimedia (Oct. 2004), 368--371. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Yee, K.-P., Swearingen, K., Li, K., and Hearst, M. Faceted Metadata for Image Search and Browsing. In Proc. CHI (Ft. Lauderdale, FL, April 2003), 401--408. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Zhou, X.S., and Huang, T. Relevance Feedback in Image Retrieval: A Comprehensive Review. ACM Multimedia Systems Journal, 8, 6 (2003), 536--544.Google ScholarGoogle Scholar

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

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        • Published in

          cover image ACM Conferences
          JCDL '05: Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
          June 2005
          450 pages
          ISBN:1581138768
          DOI:10.1145/1065385
          • General Chair:
          • Mary Marlino,
          • Program Chairs:
          • Tamara Sumner,
          • Frank Shipman

          Copyright © 2005 ACM

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          Publication History

          • Published: 7 June 2005

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