Skip to main content

Pic-A-Topic: Gathering Information Efficiently from Recorded TV Shows on Travel

  • Conference paper
Information Retrieval Technology (AIRS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4182))

Included in the following conference series:

  • 956 Accesses

Abstract

We introduce a system called Pic-A-Topic, which analyses closed captions of Japanese TV shows on travel to perform topic segmentation and topic sentence selection. Our objective is to provide a table-of-contents interface that enables efficient viewing of desired topical segments within recorded TV shows to users of appliances such as hard disk recorders and digital TVs. According to our experiments using 14.5 hours of recorded travel TV shows, Pic-A-Topic’s F1-measure for the topic segmentation task is 82% of manual performance on average. Moreover, a preliminary user evaluation experiment suggests that this level of performance may be indistinguishable from manual performance.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aoki, H., Shimotsuji, S., Hori, O.: A Shot Classification Method of Selecting Key-Frames for Video Browsing. In: Proceedings of ACM Multimedia 1996 (1996)

    Google Scholar 

  2. Aoki, H.: High-Speed Topic Organizer of TV Shows Using Video Dialog Detection (in Japanese). IEICE Transactions on Information and Systems J88-D-II(1), 17–27 (2005)

    Google Scholar 

  3. Boykin, S., Merlino, A.: Machine Learning of Event Segmentation for News on Demand. Communications of the ACM 43(2), 35–41 (2000)

    Article  Google Scholar 

  4. Chua, T.-S., et al.: Story Boundary Detection in Large Broadcast News Video Archives - Techniques, Experience and Trends. In: Proceedings of ACM Multimedia 2004 (2004)

    Google Scholar 

  5. Hauptmann, A.G., Lee, D.: Topic Labeling of Broadcast News Stories in the Informedia Digital Video Library. In: Proceedings of ACM Digital Libraries 1998 (1998)

    Google Scholar 

  6. Hauptmann, A.G., Witbrock, M.J.: Story Segmentation and Detection of Commercials in Broadcast News Video. Advances in Digital Libraries 1998 (1998)

    Google Scholar 

  7. Hearst, M.A.: Multi-Paragraph Segmentation of Expository Text. In: Proceedings of ACL 1994, pp. 9–16 (1994)

    Google Scholar 

  8. Ide, I., et al.: Threading News Video Topics. In: ACM SIGMM Workshop on Multimedia Information Retrieval (MIR 2003), pp. 239–246 (2003)

    Google Scholar 

  9. Jasinschi, R.S., et al.: Integrated Multimedia Processing for Topic Segmentation and Classification. In: Proceedings of IEEE ICIP (2001)

    Google Scholar 

  10. Mani, I., et al.: The TIPSTER SUMMAC Text Summarization Evaluation. In: Proceedings of EACL 1999, pp. 77–85 (1999)

    Google Scholar 

  11. Miyamori, H., Tanaka, K.: Webified Video: Media Conversion from TV Program to Web Content and their Integrated Viewing Method. In: Proceedings of ACM WWW 2005 (2005)

    Google Scholar 

  12. Nitta, N., Babaguchi, N.: Story Segmentation of Broadcasted Sports Videos for Semantic Content Acquisition (in Japanese). IEICE Transactions on Information and Systems J86-D-II 8, 1222–1233 (2003)

    Google Scholar 

  13. Over, P., Kraaij, W., Smeaton, A.F.: TRECVID 2005 - An Introduction. In: Proceedings of TREC 2005 (2005)

    Google Scholar 

  14. Pickering, M., Wong, L., Rüger, S.M.: ANSES: Summarisation of News Video. In: Bakker, E.M., Lew, M., Huang, T.S., Sebe, N., Zhou, X.S. (eds.) CIVR 2003. LNCS, vol. 2728, pp. 481–486. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  15. Robertson, S.E., Sparck Jones, K.: Simple, Proven Approaches to Text Retrieval. University of Cambridge Computer Laboratory, TR356 (1997)

    Google Scholar 

  16. Rui, Y., Gupta, A., Acero, A.: Automatically Extracting Highlights for TV Baseball Programs. In: Proceedings of ACM Multimedia 2000(2000)

    Google Scholar 

  17. Sakai, T., et al.: Efficient Analysis of Student Questionnaires using Information Retrieval Techniques (in Japanese). In: Proceedings of the National Conference 2003/Spring of the Japan Society for Management Information, pp. 182–185 (2003)

    Google Scholar 

  18. Sakai, T., et al.: ASKMi: A Japanese Question Answering System based on Semantic Role Analysis. In: Proceedings of RIAO 2004, pp. 215–231 (2004)

    Google Scholar 

  19. Sakai, T.: Advanced Technologies for Information Access. International Journal of Computer Processing of Oriental Languages 18(2), 95–113 (2005)

    Article  Google Scholar 

  20. Smeaton, A.F., et al.: The Físchlár-News-Stories System: Personalised Access to an Archive of TV News. In: Proceedings of RIAO 2004 (2004)

    Google Scholar 

  21. Smith, M.A., Kanade, T.: Video Skimming and Characterization through the Combination of Image and Language Understanding. In: Proceedings of IEEE ICCV 1998 (1998)

    Google Scholar 

  22. Uehara, T., Horikawa, M., Sumita, K.: Navigation System for News Programs Featuring Direct Access to Desired Scenes (in Japanese). Toshiba Review 55(10) (2000)

    Google Scholar 

  23. Yamada, I., et al.: Meta-Data Generation for Football Games using Announcer’s Commentary (in Japanese). In: Proceedings of Forum on Information Technology 2004, pp. 177–178 (2004)

    Google Scholar 

  24. Zhang, H.-J., et al.: Video Parsing, Retrieval and Browsing: An Integrated and Content-Based Solution. In: ACM Multimedia 1995, pp. 15–24 (1995)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sakai, T., Uehara, T., Sumita, K., Shimomori, T. (2006). Pic-A-Topic: Gathering Information Efficiently from Recorded TV Shows on Travel. In: Ng, H.T., Leong, MK., Kan, MY., Ji, D. (eds) Information Retrieval Technology. AIRS 2006. Lecture Notes in Computer Science, vol 4182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880592_33

Download citation

  • DOI: https://doi.org/10.1007/11880592_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45780-0

  • Online ISBN: 978-3-540-46237-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics