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A Perceptual-Statistics Shading Model

Veronika Šoltészová, Cagatay Turkay, Mark Price, Ivan Viola

ARTICLE, Visualization and Computer Graphics, IEEE Transaction on, Dec, 2012

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.

Published

Visualization and Computer Graphics, IEEE Transaction on

  • Volume: 18
  • Number: 12
  • Pages: 2265 -2274
  • ISSN: 1077--2626
  • Event: IEEE Scientific Visualization Conference 2012
  • Location: Seattle, WA, USA
  • Date: Dec 2012
  • Project: IllustraSound, MedViz, Illustrative Visualization

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BibTeX

@article{Solteszova12APerceptual,
 title = {A Perceptual-Statistics Shading Model},
 author = {Veronika \v{S}olt{\'e}szov{\'a} and Cagatay Turkay and Mark Price and Ivan Viola},
 year = {2012},
 month = {Dec},
 journal = {Visualization and Computer Graphics, IEEE Transaction on},
 event = {IEEE Scientific Visualization Conference 2012},
 location = {Seattle, WA, USA},
 volume={18},
 number={12},
 pages={2265 -2274},
 doi={10.1109/TVCG.2012.188},
 ISSN={1077--2626}, 
 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.},


}






 Last Modified: Jean-Paul Balabanian, 2014-11-25