Content-based affective image classification and retrieval using support vector machines

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Abstract

In this paper a new method to classify and retrieve affective images is proposed. First users express the affective semantics of the images with adjective words; process the data got by Semantic Differential method to obtain main factors of affection and establish affective space; extract low-level visual features of image to construct visual feature space; calculate the correlation between affective space and visual feature space with SVMs. The prototype system that embodies trained SVMs has been implemented. The system can classify the images automatically and support the affective image retrieval. The experimental results prove the effectiveness of this method. © Springer-Verlag Berlin Heidelberg 2005.

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Wu, Q., Zhou, C., & Wang, C. (2005). Content-based affective image classification and retrieval using support vector machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3784 LNCS, pp. 239–247). Springer Verlag. https://doi.org/10.1007/11573548_31

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