PERCEPTUAL GRAPHICS FOR EFFECTIVE VISUALIZATION

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2005-08-31

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Current trends in 3D graphics point to a near future when our ability to generate 3D content will far surpass our ability to analyze it meaningfully. These trends have inspired us to improve the comprehensibility of 3D graphics rendering using insights from human perception of geometry and illumination. In this dissertation, we develop algorithms and systems to seamlessly integrate the low-level human visual system cues with object modeling and lighting for 3D graphics.

Artists and illustrators have enhanced the perception of shape with discrepant lighting for centuries. Traditional graphics however assumes a model of consistent lighting. We have developed a lighting design system, that by relaxing the constraint of consistent lighting is able to convey a better depiction of shape. Our system for automatic lighting design, Light Collages, segments the objects into local surface patches and uses careful placement of highlights, shadows, and silhouettes on them to enhance shape perception. We have developed a spherical-harmonics-based formulation to achieve a 20-fold improvement in speed.

Geometric processing in graphics has made significant advances over the last decade in defining and using mathematical measures of shape, such as curvature. However, less attention has been paid to the use of perception-inspired metrics for geometric processing. We have brought perception-inspired metrics to bear on the problem of processing and viewing for 3D graphics. We have developed the concept of scale-dependent mesh saliency for graphics. We have also explored how saliency can be used to prioritize operations in applications such as object simplification and to automatically compute desirable viewing parameters for 3D graphics applications.

We believe that Perceptual Graphics could lead us in the direction of more effective graphics applications that not only use computational resources wisely, but also lift the burden of unnecessary rendered detail from the human visual system.

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