Skip to main content

Temporal Relation Analysis in Audiovisual Documents for Complementary Descriptive Information

  • Conference paper
Adaptive Multimedia Retrieval: User, Context, and Feedback (AMR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3877))

Included in the following conference series:

Abstract

Relations among temporal intervals can be used to detect semantic events in audio visual documents. The aim of our work is to study all the relations that can be observed between different segmentations of a same document. These segmentations are automatically provided by a set of tools. Each tool determines temporal units according to specific low or mid-level features. All this work is achieved without any prior information about the document type (sport, news ...), its structure, or the type of the semantic events we are looking for. Considering binary temporal relations between each couple of segmentations, a parametric representation is proposed. Using this representation, observations are made about temporal relation frequencies. When using relevant segmentations, some semantic events can be inferred from these observations. If they are not relevant enough, or if we are looking for semantic events of a higher level, conjunctions between two temporal relations can turn to be more efficient. In order to illustrate how observations can be made in the parametric representation, an example is given using Allen’s relations. Finally, we present some first results of an experimental phase made on TV news programs.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Tovinkere, V., Qian, R.J.: Detecting Semantic Events in Soccer Games: Toward a Complete Solution. In: Proc. ICME 2001, Tokyo, Japan, August 2001, pp. 1040–1043 (2001)

    Google Scholar 

  2. Bonzanini, A., Leonardi, R., Migliorati, P.: Exploitation of Temporal Dependencies of Descriptors to Extract Semanic information. DEA - University of Brescia, Via Branze, 38– 25123, Brescia, Italy

    Google Scholar 

  3. Xie, L., Chang, S.-F., Divakaran, A., Sun, H.: Structure analysis of soccer video with Hidden Markov Models. In: Proc. IEEE Int’l. Conf. on Acoustics, Speech, and Signal Processing (ICASSP) (2002)

    Google Scholar 

  4. Avrithis, Y., Tsapatsoulis, N., Kollias, S.: Broadcast News Parsing Using Visual Cues: A Robust Face Detection Approach. In: IEEE International Conference on Multimedia and Expo, New York City, NY (July 2000)

    Google Scholar 

  5. Zhou, W., Vellaikal, A., Kuo, C.-C.J.: Rule-based Video Classification System for Basketball Video Indexing. In: ACM Mult. Conf. (2000)

    Google Scholar 

  6. Rui, Y., Gupta, A., Acero, A.: Automatically extracting highlights for TV baseball programs. In: Proc. ACM Multimedia 2002, Los Angeles, CA, USA, pp. 105–115 (2000)

    Google Scholar 

  7. Lefevre, S., Maillard, B., Vincent, N.: 3 classes segmentation for analysis of football audio sequences. In: Proc. ICDSP 2002, Santorin, Greece (July 2002)

    Google Scholar 

  8. Eickeler, S., Muller, S.: Content-Based Video Indexing of TV Broadcast News Using Hidden Markov Models. In: Proc. IEEE ICASSP, Phoenix (1999)

    Google Scholar 

  9. Han, M., Hua, W., Xu, W., Gong, Y.: An integrated baseball digest system using maximum entropy method. In: Proc. ACM Multimedia 2002, Juan Les Pins, France (December 2002)

    Google Scholar 

  10. Petrovic, M., Mihajlovic, V., Jonker, W., Djordievic-Kajan, S.: Multi-modal extraction of highlights from tv formula 1 programs. In: Proc. ICME 2002, Lausanne, Switzerland (August 2002)

    Google Scholar 

  11. Duan, L., Xu, M., Yu, X.-D., Tian, Q.: A unified framework for semantic shot classification in sports videos. In: Proceedings of the tenth ACM international conference on Multimedia, Juan-les-Pins, France, December 01-06 (2002)

    Google Scholar 

  12. Hayes, P.: 1996. A Catalog of temporal theories. Technical report UIUC-BI-AI- 96-01, University of Illinois (1995)

    Google Scholar 

  13. Chittaro, L., Montanari, A.: Trends in Temporal Representation and Reasoning. The Knowledge Engineering Review 11(3), 281–288 (1996)

    Article  Google Scholar 

  14. Chittaro, L., Montanari, A.: Temporal Representation and Reasoning in Artificial Intelligence: Issues and Approaches. Annals of Mathematics and Artificial Intelligence 28, 47–106 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  15. Vila, L.: A Survey on Temporal Reasoning in Artificial Intelligence. Artificial Intelligence Communications 7(1), 4–28 (1994)

    MathSciNet  Google Scholar 

  16. Pani, A.K.: Temporal representation and reasoning in artificial intelligence: A review. Mathematical and Computer Modelling 34, 55–80 (2001)

    Article  MATH  Google Scholar 

  17. Vilain, M., Kautz, H.A.: Constraint propagation algorithms for temporal reasoning. In: AAAI 1986, pp. 132–144 (1986)

    Google Scholar 

  18. Allen, J.F.: Maintaining Knowledge about Temporal Intervals. Communication of ACM 26(11), 832–843 (1983)

    Article  MATH  Google Scholar 

  19. HyTime Information Technology. Hypermedia / Time-based Structuring Language (HyTime), ISO/IEC 10743 (November 1992)

    Google Scholar 

  20. Moulin, B.: Conceptual graph approach for the representation of temporal information in discourse. Knowledge based systems 5(3), 183–192 (1992)

    Article  Google Scholar 

  21. Li, H., Lavin, M.A.: Fast Hough Transform: A Hierarchical Approach. Journal on Graphical Models and Image Processing (CVGIP) (36), 139–161 (November/December 1986)

    Google Scholar 

  22. Freska, C.: Temporal Reasoning Based on Semi-intervals. Artificial Intelligence 54, 199–227 (1992)

    Article  MathSciNet  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

Ibrahim, Z.A.A., Ferrane, I., Joly, P. (2006). Temporal Relation Analysis in Audiovisual Documents for Complementary Descriptive Information. In: Detyniecki, M., Jose, J.M., NĂĽrnberger, A., van Rijsbergen, C.J. (eds) Adaptive Multimedia Retrieval: User, Context, and Feedback. AMR 2005. Lecture Notes in Computer Science, vol 3877. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11670834_12

Download citation

  • DOI: https://doi.org/10.1007/11670834_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32174-3

  • Online ISBN: 978-3-540-32175-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics