Skip to main content
SpringerLink
Log in

Logical Formalization of Multimedia Interpretation

  • Chapter
Book cover Knowledge-Driven Multimedia Information Extraction and Ontology Evolution

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6050))

Abstract

Nowadays, many documents in local repositories as well as in resources on the web are multimedia documents that contain not only textual but also visual and auditory information. Despite this fact, retrieval techniques that rely only on information from textual sources are still widely used due to the success of current text indexing technology. However, to increase precision and recall of multimedia retrieval, the exploitation of information from all modalities is indispensable, and high-level descriptions of multimedia content are required. These symbolic descriptions, also called deep-level semantic annotations, play a crucial role in facilitating expressive multimedia retrieval. Even for text-based retrieval systems, deep-level descriptions of content are useful (see, e.g., [7]).

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

Access this chapter

Log in via an institution
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. Aliseda, A.: Abductive Reasoning: Logical Investigations into Discovery and Explanation. Synthese Library, vol. 330. Springer, Heidelberg (2006)

    MATH  Google Scholar 

  2. Appelt, D.E., Hobbs, J.R., Bear, J., Israel, D.J., Tyson, M.: FASTUS: A Finite-state Processor for Information Extraction from Real-world Text. In: Proceedings of IJCAI, pp. 1172–1178 (1993)

    Google Scholar 

  3. Artale, A., Lutz, C., Toman, D.: A description logic of change. In: Veloso, M. (ed.) Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI 2007), pp. 218–223. AAAI Press, Menlo Park (2007)

    Google Scholar 

  4. Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)

    MATH  Google Scholar 

  5. Baader, F., Bauer, A., Baumgartner, P., Cregan, A., Gabaldon, A., Ji, K., Lee, K., Rajaratnam, D., Schwitter, R.: A Novel Architecture for Situation Awareness Systems. In: Giese, M., Waaler, A. (eds.) TABLEAUX 2009. LNCS, vol. 5607, pp. 77–92. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  6. Badler, N.: Temporal scene analysis: Conceptual descriptions of object movements, report tr-80. Technical report, Dept. of CS, University of Toronto (1975)

    Google Scholar 

  7. Bast, H., Chitea, A., Suchanek, F., Weber, I.: Ester: efficient search on text, entities, and relations. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2007), pp. 671–678 (2007)

    Google Scholar 

  8. Belongie, S., Malik, J., Puzicha, J.: Shape Matching and Object Recognition Using Shape Contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 24(24), 509–522 (2002)

    Article  Google Scholar 

  9. Canny, J.F.: A Computational Approach To Edge Detection. IEEE Transactions on Pattern Recognition and Machine Intelligence 8(6), 679–698 (1986)

    Article  Google Scholar 

  10. Castano, S., Espinosa, S., Ferrara, A., Karkaletsis, V., Kaya, A., Möller, R., Montanelli, S., Petasis, G., Wessel, M.: Multimedia Interpretation for Dynamic Ontology Evolution. Journal of Logic and Computation, Advance Access published on September 30 (2008), doi:10.1093/logcom/exn049

    Google Scholar 

  11. Charniak, E., Goldman, R.: Probabilistic Abduction For Plan Recognition. Technical report, Brown University, Tulane University (1991)

    Google Scholar 

  12. Cucerzan, S., Yarowsky, D.: Language Independent Named Entity Recognition Combining Morphological and Contextual Evidence. In: Proceedings of Joint SIGDAT Conf. on Emprical Methods in Natural Language Processing and Very Large Corpora (1999)

    Google Scholar 

  13. Espinosa, S., Kaya, A., Melzer, S., Möller, R., Wessel, M.: Towards a Media Interpretation Framework for the Semantic Web. In: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI 2007), November 2007, pp. 374–380. IEEE Computer Society, Washington, DC, USA (2007)

    Chapter  Google Scholar 

  14. Genesereth, M.R., Nilsson, N.J.: Logical Foundations of Artificial Intelligence. Morgan Kaufmann Publ. Inc., Los Altos (1987)

    MATH  Google Scholar 

  15. Gries, O., Möller, R., Nafissi, A., Rosenfeld, M., Sokolski, K., Wessel, M.: A probabilistic abduction engine for media interpretation based on ontologies. In: Alferes, J., Hitzler, P., Lukasiewicz, T. (eds.) RR 2010. LNCS, vol. 6333, pp. 182–194. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  16. Grishman, R.: Information Extraction. In: Handbook of Computational Linguistics Information Extraction (2003)

    Google Scholar 

  17. Haarslev, V.: Formal semantics of visual languages using spatial reasoning. In: Proceedings of the 11th IEEE Symposium on Visual Languages, Darmstadt, Germany, September 5-9, pp. 156–163. IEEE Press, Los Alamitos (1995)

    Chapter  Google Scholar 

  18. Haarslev, V.: A fully formalized theory for describing visual notations. In: Proceedings of the AVI 1996 Post-Conference Workshop on Theory of Visual Languages, Gubbio, Italy, May 30 (1996)

    Google Scholar 

  19. Harris, C., Stephens, M.: A Combined Corner and Edge Detector. In: Proceedings of 4th Alvey Vision Conference, pp. 147–151 (1988)

    Google Scholar 

  20. Hobbs, J., Stickel, M., Martin, P., Edwards, D.: Interpretation as Abduction. In: Proceedings of the Conference on 26th Annual Meeting of the Association for Computational Linguistics (1988)

    Google Scholar 

  21. Hobbs, J.R., Stickel, M., Martin, P.: Interpretation as abduction. Artificial Intelligence 63, 69–142 (1993)

    Article  Google Scholar 

  22. Hummel, B., Thiemann, W., Lulcheva, I.: Description logic for vision-based intersection understanding. In: Proc. Cognitive Systems with Interactive Sensors (COGIS). Stanford University, CA (2007)

    Google Scholar 

  23. Hummel, B.: Description Logic for Scene Understanding at the example of Urban Road Intersections. Südwestdeutscher Verlag für Hochschulschriften (2010)

    Google Scholar 

  24. Jaffar, J., Michaylov, S., Stuckey, P.J., Yap, R.H.C.: The CLP(R) language and system. ACM Transactions on Programming Languages and Systems 14(3), 339–395 (1992)

    Article  Google Scholar 

  25. Jing, Y., Baluja, S.: PageRank for Product Image Search. In: Proceedings of 17th International World Wide Web Conference WWW 2008 (April 2008)

    Google Scholar 

  26. Katz, B., Lin, J., Stauffer, C., Grimson, E.: Answering Questions About Moving Objects in Surveillance Videos. In: Proceedings of AAAI Spring Symposium on New Directions in Question Answering (March 2003)

    Google Scholar 

  27. Kockskämper, S., Neumann, B., Schick, M.: Extending process monitoring by event recognition. In: Proc. Second International Conference on Intelligent System Engineering, ISE 1994, pp. 455–460 (1994)

    Google Scholar 

  28. Leibe, B., Schiele, B.: Interleaved Object Categorization and Segmentation. In: Proceedings of British Machine Vision Conference (BMVC 2003) (September 2003)

    Google Scholar 

  29. Lowe, D.G.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)

    Article  Google Scholar 

  30. MacGregor, R.M., Bates, R.: The Loom Representation Language. Technical Report ISI/RS-87-188, Information Sciences Institute, University of Southern California (1987)

    Google Scholar 

  31. Matsuyama, T., Hwang, V.S.: SIGMA: A Knowledge-Based Aerial Image Understanding System. Perseus Publishing (1990)

    Google Scholar 

  32. Mikolajczyk, K., Schmid, C.: A Performance Evaluation of Local Desciptors. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 27(10), 1615–1630 (2005)

    Article  Google Scholar 

  33. Möller, R., Neumann, B.: Ontology-based Reasoning Techniques for Multimedia Interpretation and Retrieval. In: Semantic Multimedia and Ontologies: Theory and Applications. Springer, Heidelberg (2008)

    Google Scholar 

  34. Mulder, J.A., Mackworth, A.K., Havens, W.S.: Knowledge structuring and constrataint satisfaction: The Mapsee approach. IEEE Transactions in Pattern Analysis and Machine Intelligence 10(6), 866–879 (1988)

    Article  Google Scholar 

  35. Neumann, B., Möller, R.: On Scene Interpretation with Description Logics. In: Christensen, H.I., Nagel, H.-H. (eds.) Cognitive Vision Systems. LNCS, vol. 3948, pp. 247–275. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  36. Neumann, B., Novak, H.-J.: NAOS: Ein System zur natürlichsprachlichen Beschreibung zeitveränderlicher Szenenxs. Informatik Forschung und Entwicklung 1, 83–92 (1986)

    Google Scholar 

  37. Neumann, B., Weiss, T.: Navigating through logic-based scene models for high-level scene interpretations. In: Crowley, J.L., Piater, J.H., Vincze, M., Paletta, L. (eds.) ICVS 2003. LNCS, vol. 2626, pp. 212–222. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  38. Neumann, B.: Retrieving events from geometrical descriptions of time-varying scenes. In: Schmidt, J.W., Thanos, C. (eds.) Foundations of Knowledge Base Management – Contributions from Logic, Databases, and Artificial Intelligence, p. 443. Springer, Heidelberg (1985)

    Google Scholar 

  39. Neumann, B., Novak, H.-J.: Event models for recognition and natural language description of events in real-world image sequences. In: Proc. International Joint Conference on Artificial Intelligence, IJCAI 1983, pp. 724–726 (1983)

    Google Scholar 

  40. Peirce, C.S.: Deduction, Induction and Hypothesis. In: Popular Science Monthly, vol. 13, pp. 470–482 (1878)

    Google Scholar 

  41. Poole, D., Goebel, R., Aleliunas, R.: Theorist: A Logical Reasoning System for Defaults and Diagnosis. In: Cercone, N., McCalla, G. (eds.) The Knowledge Frontier: Essays in the Representation of Knowledge, pp. 331–352. Springer, Heidelberg (1987)

    Chapter  Google Scholar 

  42. Poole, D., Mackworth, A.: Artificial Intelligence: foundations of computational agents. Cambridge University Press, New York (2010)

    Book  MATH  Google Scholar 

  43. Poole, D.: Probabilistic horn abduction and bayesian networks. Artificial Intelligence 64(1), 81–129 (1993)

    Article  MATH  Google Scholar 

  44. Poole, D.: The independent choice logic and beyond. In: De Raedt, L., Frasconi, P., Kersting, K., Muggleton, S.H. (eds.) Probabilistic Inductive Logic Programming. LNCS (LNAI), vol. 4911, pp. 222–243. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  45. Reiter, R., Macworth, A.K.: The Logic of Depiction. Technical Report 87-24, Department of Computer Science, University of British Columbia, Vancouver, Canada (1987)

    Google Scholar 

  46. Reiter, R., Macworth, A.K.: A Logical Framework for Depiction and Image Interpretation. Artificial Intelligence 41, 125–155 (1989/90)

    Article  MathSciNet  MATH  Google Scholar 

  47. Russ, T., Price, K., MacGregor, R.M., Nevatia, R., Salemi, B.: VEIL: Research in Knowledge Representation for Computer Vision, Final Report. Technical Report A051143, Information Sciences Institute, University of Southern California (February 1998)

    Google Scholar 

  48. Russ, T.A., MacGregor, R.M., Salemi, B.: VEIL: Combining Semantic Knowledge with Image Understanding. In: Firschein, O., Strat, T.M. (eds.) Radius: Image Understanding for Imagery Intelligence, pp. 409–418. Morgan Kaufmann, San Francisco (1997)

    Google Scholar 

  49. Saathoff, C., Staab, S.: Exploiting spatial context in image region labelling using fuzzy constraint reasoning. In: Ninth International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2008), pp. 16–19 (2008)

    Google Scholar 

  50. Schröder, C.: Bildinterpretation durch Modellkonstruktion: Eine Theorie zur rechnergestützten Analyse von Bildern. PhD thesis, University of Hamburg (1998)

    Google Scholar 

  51. Se, S., Lowe, D., Little, J.J.: Global Localization using Distinctive Visual Features. In: Proceedings of International Conference on Intelligent Robots and Systems (IROS 2002), Lausanne, Switzerland, pp. 226–231 (November 2002)

    Google Scholar 

  52. Shanahan, M.P.: Perception as Abduction: Turning Sensor Data Into Meaningful Representation. Cognitive Science 1, 103–134 (2005)

    Article  Google Scholar 

  53. Sonka, M., Hlavac, V., Boyle, R.: Image Processing, Analysis, and Machine Vision. Thomson Learning (April 2007)

    Google Scholar 

  54. Tsotsos, J.K., Mylopoulos, J., Covvey, H.D., Zucker, S.W.: A framework for visual motion understanding. IEEE Transactions on Pattern Analysis and Machine Intelligence (1980)

    Google Scholar 

  55. Viola, P., Jones, M.: Robust Real-time Object Detection. International Journal of Computer Vision (2001)

    Google Scholar 

  56. Wessel, M., Luther, M., Möller, R.: What happened to Bob? Semantic data mining of context histories. In: Proc. of the 2009 International Workshop on Description Logics DL 2009, Oxford, United Kingdom, July 27-30. CEUR Workshop Proceedings, vol. 477 (2009)

    Google Scholar 

  57. Wessel, M., Möller, R.: A high performance semantic web query answering engine. In: Horrocks, I., Sattler, U., Wolter, F. (eds.) Proc. International Workshop on Description Logics (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical Engineering and Information Technology, Hamburg University of Technology, Hamburg, Germany

    Sofia Espinosa, Atila Kaya & Ralf Möller

Authors
  1. Sofia Espinosa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Atila Kaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ralf Möller
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Informatics and Telecommunications, National Centre for Scientific Research “Demokritos”, P.O. box 60228, 15310, Ag. Paraskevi, Athens, Greece

    Georgios Paliouras  & Constantine D. Spyropoulos  & 

  2. Biotechnology Center (BIOTEC), TU Dresden, Tatzberg 47-51, 01307, Dresden, Germany

    George Tsatsaronis

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Espinosa, S., Kaya, A., Möller, R. (2011). Logical Formalization of Multimedia Interpretation. In: Paliouras, G., Spyropoulos, C.D., Tsatsaronis, G. (eds) Knowledge-Driven Multimedia Information Extraction and Ontology Evolution. Lecture Notes in Computer Science(), vol 6050. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20795-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-20795-2_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20794-5

  • Online ISBN: 978-3-642-20795-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation