摘要
How high-level emotional representation of art paintings can be inferred from percep tual level features suited for the particular classes (dynamic vs. static classification)is presented. The key points are feature selection and classification. According to the strong relationship between notable lines of image and human sensations, a novel feature vector WLDLV (Weighted Line Direction-Length Vector) is proposed, which includes both orientation and length information of lines in an image. Classification is performed by SVM (Support Vector Machine) and images can be classified into dynamic and static. Experimental results demonstrate the effectiveness and superiority of the algorithm.
How high-level emotional representation of art paintings can be inferred from perceptual level features suited for the particular classes (dynamic vs. static classification) is presented. The key points are feature selection and classification. According to the strong relationship between notable lines of image and human sensations, a novel feature vector WLDLV (Weighted Line Direction-Length Vector) is proposed, which includes both orientation and length information of lines in an image. Classification is performed by SVM (Support Vector Machine) and images can be classified into dynamic and static. Experimental results demonstrate the effectiveness and superiority of the algorithm.
基金
SupportedbytheNationalNaturalScienceFoundationofChina(No.60372068)
关键词
SVM
图象分类
支持向量机
WLDLV
图像检索
Image classification
Emotional classification
Support Vector Machine(SVM)
Weighted Line Direction-Length Vector(WLDLV)
