Christopher G. Healey - Engaging viewers through nonphotorealistic

Conference

L. Tateosian, C. G. Healey, J. T. Enns
5th International Symposium on Non-Photorealistic Animation and Rendering (NPR '07), 2007, pp. 93-102

View PDF Semantic Scholar DBLP DOI

Cite

APA Click to copy
Tateosian, L., Healey, C. G., & Enns, J. T. (2007). Engaging viewers through nonphotorealistic visualizations. In 5th International Symposium on Non-Photorealistic Animation and Rendering (NPR '07) (pp. 93–102).

Chicago/Turabian Click to copy
Tateosian, L., C. G. Healey, and J. T. Enns. “Engaging Viewers through Nonphotorealistic Visualizations.” In 5th International Symposium on Non-Photorealistic Animation and Rendering (NPR '07), 93–102, 2007.

MLA Click to copy
Tateosian, L., et al. “Engaging Viewers through Nonphotorealistic Visualizations.” 5th International Symposium on Non-Photorealistic Animation and Rendering (NPR '07), 2007, pp. 93–102.

BibTeX Click to copy

@conference{l2007a,
  title = {Engaging viewers through nonphotorealistic visualizations},
  year = {2007},
  pages = {93-102},
  author = {Tateosian, L. and Healey, C. G. and Enns, J. T.},
  booktitle = {5th International Symposium on Non-Photorealistic Animation and Rendering (NPR '07)}
}

Abstract

[Picture]

A nonphotorealistic visualization of flow through a simulated supernova collapse, showing flow direction with stroke orientation, flow velocity with colour, and flow pressure with stroke size

Research in human visual cognition suggests that beautiful images can engage the visual system, encouraging it to linger in certain locations in an image and absorb subtle details. By developing aesthetically pleasing visualizations of data, we aim to engage viewers and promote prolonged inspection, which can lead to new discoveries within the data. We present three new visualization techniques that apply painterly rendering styles to vary interpretational complexity (IC), indication and detail (ID), and visual complexity (VC), image properties that are important to aesthetics. Knowledge of human visual perception and psychophysical models of aesthetics provide the theoretical basis for our designs. Computational geometry and nonphotorealistic algorithms are used to preprocess the data and render the visualizations. We demonstrate the techniques with visualizations of real weather and supernova data.