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
Hsu, W., Chua, T.S., Pung, H.K.: Approximating Content-Based Object-Level Image Retrieval. Multimedia Tools and Applications 12, 59–79 (2000)
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)
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)
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)
Wang, J.Z., Li, J.: Learning-Based Linguistic Indexing of Pictures with 2-d Mhmms. In: Proceeding of ACM Multimedia, pp. 436–445 (2002)
Pentland, A.: View-Based and Modular Eigenspaces for Face Recognition. In: Proc. of the IEEE Conf. on Computer Vision & Pattern Recognition, Seattle, WA (1994)
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)
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)
Karnaugh, M.: The Map Method for Synthesis of Combinational Logic Circuits. Trans. AIEE. Part I. 9, 593–599 (1953)
Westermann, U., Klas, W.: An Analysis of XML Database Solutions for Management of MPEG-7 Media Descriptions. ACM Computing Surveys, 331–373 (2003)
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)
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)
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Yang, B., Hurson, A.R. (2006). Multimedia Semantics Integration Using Linguistic Model. In: Ng, WK., Kitsuregawa, M., Li, J., Chang, K. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2006. Lecture Notes in Computer Science(), vol 3918. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11731139_78
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DOI: https://doi.org/10.1007/11731139_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33206-0
Online ISBN: 978-3-540-33207-7
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