Color design for illustrative visualization.
Professional designers and artists are quite cognizant of the rules that guide the design of effective color palettes, from both aesthetic and attention-guiding points of view. In the field of visualization, however, the use of systematic rules embracing these aspects has received less attention. The situation is further complicated by the fact that visualization often uses semi-transparencies to reveal occluded objects, in which case the resulting color mixing effects add additional constraints to the choice of the color palette. Color design forms a crucial part in visual aesthetics. Thus, the consideration of these issues can be of great value in the emerging field of illustrative visualization. We describe a knowledge-based system that captures established color design rules into a comprehensive interactive framework, aimed to aid users in the selection of colors for scene objects and incorporating individual preferences, importance functions, and overall scene composition. Our framework also offers new knowledge and solutions for the mixing, ordering and choice of colors in the rendering of semi-transparent layers and surfaces. All design rules are evaluated via user studies, for which we extend the method of conjoint analysis to task-based testing scenarios. Our framework's use of principles rooted in color design with application for the illustration of features in pre-classified data distinguishes it from existing systems which target the exploration of continuous-range density data via perceptual color maps.
Wang
Lujin
L
Center for Visual Computing, Stony Brook University. lujin@cs.sunysb.edu
Giesen
Joachim
J
McDonnell
Kevin T
KT
Zolliker
Peter
P
Mueller
Klaus
K