Image emotional classification: static vs. dynamic
Wang Wei-ning
Yu Ying-lin
Zhang Jian-chao
Dept. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China;
This paper appears in: Systems, Man and Cybernetics, 2004 IEEE International Conference on
Publication Date: 10-13 Oct. 2004
Volume: 7,
On page(s): 6407- 6411 vol.7
ISSN: 1062-922X
ISBN: 0-7803-8566-7
INSPEC Accession Number: 8348317
Digital Object Identifier: 10.1109/ICSMC.2004.1401407
Current Version Published: 2005-03-07
Abstract
Grouping images into emotional categories is an important and challenging problem in content-based image retrieval. In this paper, we propose an approach to classify art paintings into emotional categories (dynamic vs. static). The key points are feature selection and classification algorithm. 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, Then classification is performed by SVM (support vector machine) and images can be classified into dynamic vs. static. Experimental results demonstrate the effectiveness and superiority of our approach.
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
