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.
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Wu, Q., Zhou, C., Wang, C. (2005). Content-Based Affective Image Classification and Retrieval Using Support Vector Machines. In: Tao, J., Tan, T., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2005. Lecture Notes in Computer Science, vol 3784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573548_31
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DOI: https://doi.org/10.1007/11573548_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29621-8
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