Abstract
Emotion is the most abstract semantic structure of images. This paper overviews recent research on emotion semantics image retrieval. First, the paper introduces the general frame of emotion semantics image retrieval and points out the four main research issues: to exact sensitive features from images, to define users' emotion information, to build emotion user model and to individualize the user model. Then several algorithms to solve these four issues are analyzed in detail. After that, some future research topics, including construction of an emotion database, evaluation of the user model and computation of the user model, are discussed, and some resolved strategies are presented elementarily. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Wang, S., & Wang, X. (2005). Emotion semantics image retrieval: An brief overview. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3784 LNCS, pp. 490–497). Springer Verlag. https://doi.org/10.1007/11573548_63
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