Content area

Abstract

Visual saliency can always persuade the viewer's visual attention to fine-scale mesostructure of 3D complex shapes. Owing to the multi-channel salience measure and salience-domain shape modeling technique, a novel visual saliency based shape depiction scheme is presented to exaggerate salient geometric details of the underlying relief surface. Our multi-channel salience measure is calculated by combining three feature maps, i.e., the 0-order feature map of local height distribution, the 1-order feature map of normal difference, and the 2-order feature map of mean curvature variation. The original relief surface is firstly manipulated by a salience-domain enhancement function, and the detail exaggeration surface can then be obtained by adjusting the surface normals of the original surface as the corresponding final normals of the manipulated surface. The advantage of our detail exaggeration technique is that it can adaptively alter the shading of the original shape to reveal visually salient features whilst keeping the desired appearance unimpaired. The experimental results demonstrate that our non-photorealistic shading scheme can enhance the surface mesostructure effectively and thus improving the shape depiction of the relief surfaces.[PUBLICATION ABSTRACT]

Details

Title
A Multi-Channel Salience Based Detail Exaggeration Technique for 3D Relief Surfaces
Author
Miao, Yong-Wei 1 ; Feng, Jie-Qing 2 ; Wang, Jin-Rong 2 ; Pajarola, Renato 3 

 Zhejiang University of Technology, College of Computer Science and Technology, Hangzhou, China (GRID:grid.413273.0) (ISNI:0000000105748737) 
 Zhejiang University, State Key Lab of CAD & CG, Hangzhou, China (GRID:grid.13402.34) (ISNI:000000041759700X) 
 University of Zürich, Department of Informatics, Zürich, Switzerland (GRID:grid.7400.3) (ISNI:0000000419370650) 
Pages
1100-1109
Publication year
2012
Publication date
Nov 2012
Publisher
Springer Nature B.V.
ISSN
10009000
e-ISSN
18604749
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1266439263
Copyright
© Springer Science+Business Media New York & Science Press, China 2012.