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 :
بازگشت