A perceptual-statistics shading model

Šoltészová, V., Turkay, C., Price, M. C. & Viola, I. (2012). A perceptual-statistics shading model. IEEE Transactions on Visualization and Computer Graphics, 18(12), pp. 2265-2274. doi: 10.1109/TVCG.2012.188

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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.

Item Type: Article
Additional Information: (c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Uncontrolled Keywords: Shading, perception, evaluation, surface slant, statistical analysis
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Informatics > Department of Computing
URI: http://openaccess.city.ac.uk/id/eprint/3643

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