The Research of SVM Introjecting Fuzzy Theory in Image Affective Recognition

Junjie Chen, Dawei Zhang, Haifang Li
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Abstract

This paper introduces FSVM, which introjects fuzzy theory to SVM, achieves a classification system which classifies image layer by layer to affective semantic level by FSVM, and proposes one kind of image affective semantics classification method. The difficulty is to establish a mapping from image features to image affective semantics and how to select fitting membership function to test image semantic class. The experimental result shows that the system is simple, fast, effective, and so on, therefore our system is proved to be successful in promoting the image semantic classification to affective semantic level.
基于模糊理论的支持向量机图像情感识别研究
引入模糊支持向量机,将模糊理论引入到支持向量机中,实现了一种将图像逐层分类到情感语义层次的分类系统,并提出了一种图像情感语义分类方法。难点在于如何建立图像特征到图像情感语义的映射关系,以及如何选择拟合的隶属函数来测试图像语义类。实验结果表明,该系统具有简单、快速、有效等特点,能够成功地将图像语义分类提升到情感语义层次。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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