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Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connections between features and video events. Provided that this structure is given as input, the parameters are then estimated from training data. Bayesian networks offer an additional feature, namely structure learning, which allows...
This paper discusses a methodology for the semantic characterization of the animation movie color content in the video indexing framework. Color is a major feature of animation movies: almost each movie uses a particular color palette which is related to its artistic content. To characterize the color content we use a fuzzy symbolic representation of several low-level statistical parameters which...
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