Using Color to Improve the Discrimination and Aesthetics of Treemaps

Summary form only given. Existing treemap tiling algorithms are not able to readily discriminate data with similar sizes or generate aesthetically pleasing treemaps. We propose novel solutions to overcome these two limitations. For better the degree of data discrimination, based on the principle of expansive and contractive colors, we propose a novel quantitative color-visually perceived area (C-VPA) model via experimental methods. To improve the aesthetic value of a treemap, we firstly apply the color aesthetic model to treemap generation. Moreover, we combine these two models to derive a genetic algorithm based treemap tiling method.