The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.12 - Dec. (2012 vol.18)
pp: 2265-2274
V. Solteszova , Dept. of Inf., Univ. of Bergen, Bergen, Norway
C. Turkay , Dept. of Inf., Univ. of Bergen, Bergen, Norway
M. C. Price , Psychol. Fac., Univ. of Bergen, Bergen, Norway
I. Viola , Dept. of Inf., Univ. of Bergen, Bergen, Norway and Christian Michelsen Research, Norway
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.
INDEX TERMS
visual perception, data visualisation, statistics, publicly-available datasets, perceptual-statistics shading model, surface perception, influencing factors, perception error, visualization technique, distal stimulus, proximal stimulus, 3D surface visualization, 2D screens, Rendering (computer graphics), Shape analysis, Observers, Mathematical model, Computational modeling, Surface reconstruction, statistical analysis, Shading, perception, evaluation, surface slant
CITATION
V. Solteszova, C. Turkay, M. C. Price, I. Viola, "A Perceptual-Statistics Shading Model", IEEE Transactions on Visualization & Computer Graphics, vol.18, no. 12, pp. 2265-2274, Dec. 2012, doi:10.1109/TVCG.2012.188
REFERENCES
[1] Adobe. Adobe Photoshop CS4 - The “Curves...” tool. http://www. adobe.com/productsphotoshopfamily.html, 2008.
[2] P. Belhumeur, D. Kriegman, and A. Yuille, The bas-relief ambiguity International Journal of Computer Vision, 35(1): 33-44, 1999.
[3] S. Belia, F. Fidler, J. William,, and G. Cumming., Researchers misunder-stand confidence intervals and standard error bars. Psychological Methods, 10(4): 389-396, 2005.
[4] J. Cohen., Statistical power analysis for the behavioral sciences. Routledge Academic Press, New York, 2ndedition, 1988.
[5] J. Cohen, A power primer Psychological Bulletin, 112(1): 155-159, 1992.
[6] F. Cole, K. Sanik, D. DeCarlo., A. Finkelstein, T. Funkhouser., S. Rusinkiewicz, and M. Singh., How well do line drawings depict shape? ACM Transactions on Graphics, 28(3): 28:1-28:9, 2009.
[7] E. De Haan, R. Erens, and A. Noest, Shape from shaded random surfaces Vision Research, 35(21): 2985-3001, 1995.
[8] R. Fleming, A. Torralba, and E. Adelson, Specular reflections and the perception of shape Journal of Vision, 4: 798-820, 2004.
[9] A. Gallardo., Lambertian shading. In 3D Lighting: History, Concepts and Techniques, page 117. Charles River Media, Inc., Massachusetts, 2001.
[10] S. Geisser and S. W, Greenshouse. On methods in the analysis of profile data Psychometrika, 24: 95-112, 1959.
[11] J. J, Gibson The ecological approach to visual perception. Houghton Mifflin, Boston, 1979.
[12] B. Gooch, E. Reinhard, and A. Gooch, Human facial illustration: Creation and psychophysical evaluation ACM Transactions on Graphics, 23(1): 17-44, 2004.
[13] D. H. House,A. S. Bair,, and C. Ware., An approach to the perceptual optimization of complex visualizations IEEE Transactions on Visualization and Computer Graphics, 12(4): 509-521, 2006.
[14] A. Johnston and P. Passmore, Shape from shading. I: Surface curvature and orientation Perception, 23: 169-189, 1994.
[15] Y. Kim and A. Varshney, Persuading visual attention through geometry IEEE Transactions on Visualization and Computer Graphics, 14(4): 772-782, 2008.
[16] J. Koenderink,A. van Doorn,, and A. Kappers., Surface perception in pictures. Perception and & Psychophysics, 52(5): 487-496, 1992.
[17] J. Koenderink,A. van Doorn,, and A. Kappers., Ambiguity and the mental eye in pictorial relief. Perception, 30: 431-448, 2001.
[18] F. Lindemann and T. Ropinski, About the influence of illumination models on image comprehension in direct volume rendering IEEE Transactions on Visualization and Computer Graphics, 17(12): 1922-1931, 2011.
[19] M. Livingstone., Vision and art – the biology of seeing. Abrams, paper-back edition, 2008.
[20] P. Mamassian and R. Goutcher, Prior knowledge on the illumination position Cognition, 81: Bl-9, 2001.
[21] P. Mamassian and D. Kersten, Illumination, shading and the perception of local orientation Vision Research, 36(15): 2351-2367, 1996.
[22] Math Works. Matlab: The language of technical computing. www.mathworks.com, 2012.
[23] J. W. Mauchly., Significance test for sphericity of a normal n-variate distribution The Annals of Mathematical Statistics, 11(2): 204-209, 1940.
[24] E. Mingolla and J. Todd, Perception of solid shape from shading Biological Cybernetics, 53: 137-151, 1986.
[25] J. F. Norman, J. Todd, H. Norman,A. M. Clayton,, and T. R. McBride., Visual discrimination of local surface structure: Slant, tilt, and curvedness Vision Research, 46: 1057-1069, 2006.
[26] J. P., O’Shea, M. S. Banks, and M. Agrawala. The assumed light direction for perceiving shape from shading. In Proceedings of the 5th symposium on Applied perception in graphics and visualization, pages 135-142, 2008.
[27] D. Pineo and C. Ware, Data visualization optimization via computational modeling of perception IEEE Transactions on Visualization and Computer Graphics, 18(2): 309-320, 2012.
[28] Z. Pizlo and M. Salach-Golyska., 3-D shape perception. Perception and Psychophysics, 57(5): 695-714, 1995.
[29] S. Rusinkiewicz, M. Burns, and D. DeCarlo, Exaggerated shading for depicting shape and detail ACM Transactions on Graphics, 25(3): 1199-1205, 2006.
[30] S. S. Shapiro and M. B. Wilk., An analysis of variance test for normality (complete samples) Biometrika, 52(3-4): 591-611, 1965.
[31] V. Soltészová. Perceptual-statistics web. www.ii.uib.no/vis/publications/publication/ 2012Solteszova12APerceptual, 2012.
[32] V. Solteszova, D. Patel, and I. Viola., Chromatic shadows for improved perception. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Non-Photorealistic Animation and Rendering, pages 105-116, 2011.
[33] J. Sun and P. Perona., Where is the sun? Nature Neuroscience, 1: 183-184, 1998.
[34] J. Todd, The visual perception of 3D shape Trends in Cognitive Science, 8(3): 115-121, 2004.
[35] J. Todd and E. Mingolla, Perception of surface curvature and direction of illumination from patterns of shading Journal of Experimental Psychology, 9(4): 583-595, 1983.
[36] A. J. van Doorn and J. Koenderink., The influence of environmental cues on pictorial relief Perception - ECVP Abstract Supplement, 29, 2000.
[37] R. Vergne, R. Pacanowski, P. Barla., X. Granier, and C. Schlick, Light warping for enhanced surface depiction ACM Transactions on Graphics, 28(3): 25:1-25:8, 2009.
[38] R. Vergne, R. Pacanowski, P. Barla., X. Granier, and C. Shlick, Improving shape depiction under arbitrary rendering IEEE Transactions on Visualization and Computer Graphics, 17(8): 1071-1081, 2011.
[39] F. Wilcoxon, Individual comparisons by ranking methods Biometrics bulletin, 1(6): 80-83, 1945.
[40] Yafa Ray. Yafaray 0.0.9: Yet another free raycaster. www.yafaray.org, 2008.
15 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool