Depth-Enhanced Tag Cloud Maps
Yasuto Murakami, Takamasa Kawagoe, Michael M. Cohen, Shigeo Takahashi · 2018
We present an approach to synthesizing tag cloud ("wordle"s) maps that produce illusionary visual depth fields based on stereoscopic imaging. By using a 3D scalar field (such as elevation or weather data) as input, the synthesized map yields a visual illusion that suitably simulates the 3D shape of the field; this is done by applying stereoscopic rendering effects to individual word tags. In the generated tag cloud maps, we employed chromastereoptic rendering as a mechanism for controlling the rendering styles of respective place names. Our technical contribution also lies in the formulation for optimizing the layout of place names in a tag cloud by using a genetic algorithm, which effectively simulates the 3D visual depth illusion of a given scalar field over the map domain. Design examples are presented to demonstrate the capability of the proposed approach followed by a discussion of the possible limitations.