A Perceptual-Statistics Shading Model

Veronika Solteszova*, Cagatay Turkay, Mark C. Price, Ivan Viola

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The process of surface perception is complex and based on several influencing factors, e.g., shading, silhouettes, occluding contours, and top down cognition. The accuracy of surface perception can be measured and the influencing factors can be modified in order to decrease the error in perception. This paper presents a novel concept of how a perceptual evaluation of a visualization technique can contribute to its redesign with the aim of improving the match between the distal and the proximal stimulus. During analysis of data from previous perceptual studies, we observed that the slant of 3D surfaces visualized on 2D screens is systematically underestimated. The visible trends in the error allowed us to create a statistical model of the perceived surface slant. Based on this statistical model we obtained from user experiments, we derived a new shading model that uses adjusted surface normals and aims to reduce the error in slant perception. The result is a shape-enhancement of visualization which is driven by an experimentally-founded statistical model. To assess the efficiency of the statistical shading model, we repeated the evaluation experiment and confirmed that the error in perception was decreased. Results of both user experiments are publicly-available datasets.

Original languageEnglish
Pages (from-to)2265-2274
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Volume18
Issue number12
DOIs
StatePublished - Dec 2012
Externally publishedYes

Keywords

  • Shading
  • perception
  • evaluation
  • surface slant
  • statistical analysis
  • SURFACE CURVATURE
  • SHAPE
  • ILLUMINATION
  • ORIENTATION
  • AMBIGUITY
  • RELIEF

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