DocumentCode
2094377
Title
Feature Extraction and Analysis for Scientific Understanding of Visual Art
Author
Zhang Yi ; Pu Yuanyuan ; Huang Yaqun ; Xu Dan ; Qian Wenhua
Author_Institution
Sch. of Inf. Sci. & Eng., Yunnan Univ., Kunming, China
fYear
2013
fDate
16-18 Nov. 2013
Firstpage
411
Lastpage
412
Abstract
In this paper, the research of visual art based on the computer and information of paintings, which can be called scientific understanding of visual art, has been brought out. Four features, multi-scale amplitude, non-stationarity of artworks, anisotropy of artworks and correlation of coefficients of the curve let transform between scales, are extracted based on the curve let transform to evaluate the style of different artists. The relations between the style of visual art and these features are also stated, and the similarities of these styles are also qualified by comparing these features. It is apparent that each feature reflects different characteristics of the different school paintings.
Keywords
art; curvelet transforms; feature extraction; artwork anisotropy; artwork nonstationarity; curvelet transform; feature extraction; multiscale amplitude; school paintings; scientific understanding; visual art; Art; Correlation; Educational institutions; Feature extraction; Painting; Transforms; Visualization; Computational Aesthetics; Curvelet transform; Scientific understanding; Styles; Visual art;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer-Aided Design and Computer Graphics (CAD/Graphics), 2013 International Conference on
Conference_Location
Guangzhou
Type
conf
DOI
10.1109/CADGraphics.2013.72
Filename
6815036
Link To Document