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- W2391528571 abstract "Semantics image retrieval is the key issue to solve the semantic gap between users’ complex semantics and visual features. Emotion is the most abstract semantic structure of images. This paper first introduces the general frame of emotion image retrieval and points out the four main research issues: to exact kansei features from images, to describe users’ emotion information, to build affective user model and to individualize the model. Then some algorithms to solve these four issues are analyzed in detail. After that, three typical archetypal systems are presented. Finally, three critical problems, including emotion database, evaluation of user mode and computation of user model, faced in emotion image retrieval are explained, and some resolved strategies are presented elementarily." @default.
- W2391528571 created "2016-06-24" @default.
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- W2391528571 date "2005-01-01" @default.
- W2391528571 modified "2023-09-26" @default.
- W2391528571 title "Development and prospect on emotion image retrieval" @default.
- W2391528571 hasPublicationYear "2005" @default.
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