Daniel Beauchêne

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Multimedia documents are increasingly numerous. Their efficient management requires tools to provide services that measure up to users' expectations, based on the contents of these voluminous document databases. This implies a number of challenges. Although we can extract highly symbolic concepts from texts, a wide semantic gap appears when processing(More)
In the context of animated movie characterization, we present an information fusion approach mixing very different types of data related to the activity within a movie. These data are the features extracted from images, words extracted from the synopses and expert knowledge. The difficulty of this fusion is due to the very different semantic level of these(More)
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