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In this demonstration, a collaborative personalized affective video retrieval is introduced. A dataset of 155 video clips extracted from Hollywood movies were annotated by the emotion felt by participants. More than 1300 annotations from 40 participants were gathered in a database to be used for affective retrieval system. The retrieval system is able to retrieve videos based on emotional keyword...
Emotions that are elicited in response to a video scene contain valuable information for multimedia tagging and indexing. The novelty of this paper is to introduce a Bayesian classification framework for affective video tagging that allows taking contextual information into account. A set of 21 full length movies was first segmented and informative content-based features were extracted from each shot...
An approach for implementing affective information as tags for multimedia content indexing and retrieval is presented. The approach can be used for implicit as well as explicit tags and is presented here using data recorded during the viewing of movie fragments containing annotations and physiological signal recordings. For retrieval based on affective queries, a representation of the query-words...
In this paper, we propose an approach for affective representation of movie scenes based on the emotions that are actually felt by spectators. Such a representation can be used for characterizing the emotional content of video clips for e.g. affective video indexing and retrieval, neuromarketing studies, etc. A dataset of 64 different scenes from eight movies was shown to eight participants. While...
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