Abstract
In this paper we introduce a new approach to multimedia data semantic characterisation and in particular television programmes fingerprinting, based on multimodal content analysis and fuzzy clustering. The definition of the fingerprints can be seen as a space transformation process, which maps each programme description from the surrogate vector space to a new vector space, defined through a fuzzy clustering method. The fuzzy fingerprint model is well suited for similarity based information retrieval, and it captures ”semantic” similarities coming from common pattern in the programme data, at different semantic levels.
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References
Battiato, S., Gallo, G., Nicotra, S.: Perceptive Visual Texture Classification and Retrieval. In: ICIAP 2003 (2003)
Bertini, M., Del Bimbo, A., Torniai, C.: Enhanced Ontologies for Video Annotation and Retrieval. In: ACM MIR (Multimedia Information Retrieval) Workshop (2005)
Dasiopoulou, S., Papastathis, V.K., Mezaris, V., Kompatsiaris, I., Strintzis, M.G.: An Ontology Framework For Knowledge-Assisted Semantic Video Analysis and Annotation. In: Proc. SemAnnot 2004 (2004)
Dimitrova, N., Agnihotri, L., Wei, G.: Video classification based on HMM using text and faces. In: Proc. European Signal Processing Conference (2000)
Dorado, A., Calic, J., Izquierdo, E.: A rule-based video annotation system. IEEE Transactions on Circuits and Systems for Video Technology 14(5), 622–633 (2004)
Doulamis, A., Avrithis, Y., Doulamis, N., Kollias, S.: Interactive Content-Based Retrieval in Video Databases Using Fuzzy Classification and Relevance Feedback. In: Proc. IEEE ICMSC 1999 (1999)
Ferman, A.M., Tekalp, A.M.: A fuzzy framework for unsupervised video content characterization and shot classification. J. of Electronic Imaging 10(4), 917–929 (2001)
Fischer, S., Lienhart, R., Effelsberg, W.: Automatic recognition of film genres. In: Proc. ACM Multimedia (1995)
Guerrini, F., Leonardi, R., Migliorati, P., Benini, S.: Effective Image Fingerprint Extraction Based on Random Bubble Sampling. In: WIAMIS 2004 (2004)
Höppner, F., Klawonn, F., Kruse, K., Runkler, T.: Fuzzy Cluster Analysis. Wiley, Chichester (1999)
Jadon, R.S., Chaudhury, S., Biswas, K.K.: Generic Video Classification: An Evolutionary Learning based Fuzzy Theoretic Approach. In: Proc. of the ICVGIP 2002 (2002)
Long, F., Zhang, H.J., Feng, D.D.: Fundamentals of Content-Based Image Retrieval. In: Multimedia Information Retrieval and Management- Technological Fundamentals and Applications. Springer, Heidelberg (2003)
Mezei, M.: A novel fingerprint for the characterization of protein folds. Protein Eng. 16(10), 713–715 (2003)
Montagnuolo, M., Messina, A.: Multimedia Knowledge Representation for Automatic Annotation of Broadcast TV Archives. In: Proceedings of the 4th Special Workshop on Multimedia Semantics (WMS 2006), pp. 80–94 (June 2006)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers Inc., San Francisco (1993)
Rabiner, L., Juang, B.: An introduction to hidden Markov models. IEEE ASSP Magazine, 4–16 (1986)
Seymore, K., McCallum, A., Rosenfeld, R.: Learning hidden markov model structure for information extraction. In: AAAI 1999 Workshop on Machine Learning for Information Extraction (1999)
Sharan, R., Elkon, R., Shamir, R.: Cluster analysis and its applications to gene expression data. In: Ernst Schering workshop on Bioinformatics and Genome Analysis (2001)
Sharan, R., Maron-Katz, A., Shamir, R.: Click and expander:A system for clustering and visualizing gene expression data. Bioinformatics 19(14), 1787–1799 (2003)
Snoek, C.G., Worring, M.: Multimodal video indexing: A review of the state-of-the-art. In: Proc. Multimedia Tools and Applications (2003)
Takagi, S., Hattori, S., Yokoyama, Y., Kodate, A., Tominaga, H.: Sports video categorizing method using camera motion parameters. In: Proc. of the Visual Communications and Image Processing 2003 (2003)
Tamura, H., Mori, S., Yamawaki, T.: Texture features corresponding to visual perception. IEEE Trans. on Systems Man Cybernet 8(6), 460–473 (1978)
Tang, S., Li, J.T., Zhang, Y.D.: Compact and Robust Fingerprints Using DCT Coefficients of Key Blocks. LNCS. Springer, Heidelberg (2005)
Truong, B.T., Dorai, C.: Automatic genre identification for content-based videocategorization. In: Proc. Int. ICPR 2000, Barcelona, Spain (2000)
Venkatachalam, V., Cazzanti, L., Dhillon, N., Wells, M.: Automatic identification of sound recordings. IEEE Signal Processing Magazine 21(2), 92–99 (2004)
Xu, L.Q., Li, Y.: Video classification using spatial-temporal features and PCA, Proc. IEEE Inter. In: Conf. on Multimedia and Expo (ICME 2003) (2003)
Zadeh, L.A.: Fuzzy Sets as a Basis for a Theory of Probability. Fuzzy Sets and Systems (1978)
Pal, N.R., Bezdek, J.C.: On cluster validity for the fuzzy c-means model. IEEE Trans. on Fuzzy Systems 3(3), 370–379 (1995)
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Messina, A., Montagnuolo, M., Sapino, M.L. (2009). Characterizing Multimedia Objects through Multimodal Content Analysis and Fuzzy Fingerprints. In: Damiani, E., Yetongnon, K., Chbeir, R., Dipanda, A. (eds) Advanced Internet Based Systems and Applications. SITIS 2006. Lecture Notes in Computer Science, vol 4879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01350-8_3
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DOI: https://doi.org/10.1007/978-3-642-01350-8_3
Publisher Name: Springer, Berlin, Heidelberg
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