Fuzzy mining of multimedia genre applied to television archives

The quantity of multimedia content available either through the traditional distribution channels, such as broadcast television, or through new platforms like the Internet, is continuously increasing. Tools for user-oriented access to desired information are thus needed. In this paper, we illustrate a novel fuzzy multimedia mining technique for genre characterisation, aimed at overcoming limitations of conventional crisp classification systems. Effective results in genre classification and characterisation are presented based on the extraction of structural and cognitive properties of the content.

[1]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[2]  Gu Jianhua,et al.  Fuzzy clustering for TV program classification , 2004, International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004..

[3]  Alberto Messina,et al.  Characterizing Multimedia Objects through Multimodal Content Analysis and Fuzzy Fingerprints , 2009, SITIS.

[4]  Yannis Avrithis,et al.  Handling Uncertainty in Video Analysis with Spatiotemporal Visual Attention , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[5]  Alberto Messina,et al.  Multimedia genre characterisation with fuzzy embedding classifiers , 2008, AMDIT '08.

[6]  Qi Tian,et al.  News video search with fuzzy event clustering using high-level features , 2006, MM '06.

[7]  B. Yegnanarayana,et al.  Combining multiple evidence for video classification , 2005, Proceedings of 2005 International Conference on Intelligent Sensing and Information Processing, 2005..

[8]  Chng Eng Siong,et al.  Automatic Sports Video Genre Classification using Pseudo-2D-HMM , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[9]  Xingbo Wang,et al.  A Rough Set Approach to Video Genre Classification , 2006, ACIVS.

[10]  Tao Mei,et al.  Automatic Video Genre Categorization using Hierarchical SVM , 2006, 2006 International Conference on Image Processing.