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. © Springer-Verlag Berlin Heidelberg 2009.
CITATION STYLE
Messina, A., Montagnuolo, M., & Sapino, M. L. (2009). Characterizing multimedia objects through multimodal content analysis and fuzzy fingerprints. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4879 LNCS, pp. 22–33). https://doi.org/10.1007/978-3-642-01350-8_3
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