Measuring and predicting visual fidelity

  • Authors:
  • Benjamin Watson;Alinda Friedman;Aaron McGaffey

  • Affiliations:
  • Dept. Computer Science, Northwestern University, 1890 Maple Ave, Evanston, IL;Dept. of Psychology, University of Alberta, Edmonton, Alberta, Canada T6G2E9;Dept. of Psychology, University of Alberta, Edmonton, Alberta, Canada T6G2E9

  • Venue:
  • Proceedings of the 28th annual conference on Computer graphics and interactive techniques
  • Year:
  • 2001

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Abstract

This paper is a study of techniques for measuring and predicting visual fidelity. As visual stimuli we use polygonal models, and vary their fidelity with two different model simplification algorithms. We also group the stimuli into two object types: animals and man made artifacts. We examine three different experimental techniques for measuring these fidelity changes: naming times, ratings, and preferences. All the measures were sensitive to the type of simplification and level of simplification. However, the measures differed from one another in their response to object type. We also examine several automatic techniques for predicting these experimental measures, including techniques based on images and on the models themselves. Automatic measures of fidelity were successful at predicting experimental ratings, less successful at predicting preferences, and largely failures at predicting naming times. We conclude with suggestions for use and improvement of the experimental and automatic measures of visual fidelity.