Multimedia Semantics Integration Using Linguistic Model

  • Bo Yang
  • Ali R. Hurson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3918)

Abstract

The integration of multimedia semantics is challenging due to the feature-based representation of multimedia data and the heterogeneity among data sources. From human viewpoint, multimedia data objects are often considered as perceptions of the real world, and therefore can be represented at a semantic-entity level in the linguistic domain. This paper proposes a paradigm that facilitates the integration of multimedia semantics in heterogeneous distributed database environments with the help of linguistic analysis. Specifically, we derive a closed set of logic-based form expressions for the efficient computation of multimedia semantic contents, which include conceptual attributes and linguistic relationships into the consideration. In the expression set, the logic terms give a convenient way to describe semantic contents concisely and precisely, providing a representation of multimedia data that is closer to human perception. The space utilization is also improved through the collective representation of similar semantic contents and feature values. In addition, the optimization can be easily performed on logic expressions using mathematical analysis. By replacing long terms with equivalent terms of shorter lengths, the image representation can be automatically optimized. Using a heterogeneous database infrastructure, the proposed method has been simulated and analyzed.

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References

  1. 1.
    Hsu, W., Chua, T.S., Pung, H.K.: Approximating Content-Based Object-Level Image Retrieval. Multimedia Tools and Applications 12, 59–79 (2000)CrossRefMATHGoogle Scholar
  2. 2.
    Kim, J.B., Kim, H.J.: Unsupervised Moving Object Segmentation and Recognition Using Clustering and A Neural Network. In: Proc. of the Intl. Joint Conf. on Neural Networks, pp. 1240–1245 (2002)Google Scholar
  3. 3.
    Huang, Y.P., Chang, T.W., Huang, C.-Z.: A Fuzzy Feature Clustering with Relevance Feedback Approach to Content-Based Image Retrieval. In: Proc. of the IEEE Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems, pp. 57–62 (2003)Google Scholar
  4. 4.
    Kwon, T., Choi, Y., Bisdikian, C., Naghshineh, M.: QoS Provisioning in Wireless/Mobile Multimedia Networks Using An Adaptive Framework. In: Wireless Networks, pp. 51–59 (2003)Google Scholar
  5. 5.
    Wang, J.Z., Li, J.: Learning-Based Linguistic Indexing of Pictures with 2-d Mhmms. In: Proceeding of ACM Multimedia, pp. 436–445 (2002)Google Scholar
  6. 6.
    Pentland, A.: View-Based and Modular Eigenspaces for Face Recognition. In: Proc. of the IEEE Conf. on Computer Vision & Pattern Recognition, Seattle, WA (1994)Google Scholar
  7. 7.
    Naphade, M.R.: Detecting Semantic Concepts Using Context and Audiovisual Features. In: IEEE Workshop on Detection and Recognition of Events in Video, pp. 92–98 (2001)Google Scholar
  8. 8.
    Li, D., Dimitrova, N., Li, M., Sethi, I.K.: Multimedia Content Processing through Cross-Modal Association. In: Proc. of the ACM Conference on Multimedia, pp. 604–611 (2003)Google Scholar
  9. 9.
    Karnaugh, M.: The Map Method for Synthesis of Combinational Logic Circuits. Trans. AIEE. Part I. 9, 593–599 (1953)MathSciNetGoogle Scholar
  10. 10.
    Westermann, U., Klas, W.: An Analysis of XML Database Solutions for Management of MPEG-7 Media Descriptions. ACM Computing Surveys, 331–373 (2003)Google Scholar
  11. 11.
    Naphade, M.R., Huang, T.S.: Recognizing High-Level Audio-Visual Concepts Using Context. In: Proc. of the IEEE Intl. Conf. on Image Processing., pp. 46–49 (2001)Google Scholar
  12. 12.
    Li, M., Li, D., Dimitrova, N., Sethi, I.K.: Audio-Visual Talking Face Detection. In: Proc. of IEEE Intl. Conf. on Multimedia and Expo., pp. 473–476 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bo Yang
    • 1
  • Ali R. Hurson
    • 1
  1. 1.Department of Computer Science and EngineeringThe Pennsylvania State UniversityUniversity ParkUSA

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