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Perception-Augmenting Illumination

Veronika Šoltészová

PHDTHESIS, Aug, 2012

Abstract

At each stage of the visualization pipeline, the information is impeded by loss or by noise because of imprecise acquisition, storage limitations, and processing. Furthermore, it passes through the complex and not yet well understood pathways in the human visual system and finally to result into a mental image. Due to the noise that impedes the information in the visualization pipeline and the processes in the human visual system, the mental image and the real-world phenomenon do not match. From the aspect of physics, the input of the visual system is confined only to patterns of light. Illumination is therefore essential in 3D visualization for perception of visualized objects. In this thesis, several advancements for advanced volumetric lighting are presented. First, a novel lighting model that supports interactive light source placement and yields a high-quality soft shadowing effect, is proposed. The light transport is represented by conical functions and approximated with an incremental blurring operation of the opacity buffer during front-to-back slicing of the volume. Furthermore, a new perceptuallyfounded model for expressing shadows that gives a full control over the appearance of shadows in terms of color and opacity, is presented. Third, a systematic error in perception of surface slant is modeled. This knowledge is then applied to adjust an existing shading model in a manner that compensates for the error in perception. These new visualization methodologies are linked to the knowledge of perceptual psychology and the craft of illustrators, who experimented with visual-presentation techniques for centuries. The new methodologies are showcased on challenging acoustic modalities such as 3D medical ultrasound and sonar imaging.

Published

  • ISBN: 978-82-308-2118-3
  • School: Department of Informatics, University of Bergen, Norway
  • Date: Aug 2012

Media

  • paper
  • Click to view

BibTeX

@phdthesis{solteszova12thesis,
  title = {Perception-Augmenting Illumination},
  author = {Veronika \v{S}olt{\'e}szov{\'a}},
  year = {2012},
  month = {Aug},
  abstract = {At each stage of the visualization pipeline, the information is impeded 
  by loss or by noise because of imprecise acquisition, storage limitations, and 
  processing. Furthermore, it passes through the complex and not yet well understood 
  pathways in the human visual system and finally to result into a mental image. Due 
  to the noise that impedes the information in the visualization pipeline and the 
  processes in the human visual system, the mental image and the real-world phenomenon
  do not match. From the aspect of physics, the input of the visual system is confined 
  only to patterns of light. Illumination is therefore essential in 3D visualization 
  for perception of visualized objects. In this thesis, several advancements for advanced 
  volumetric lighting are presented. First, a novel lighting model that supports 
  interactive light source placement and yields a high-quality soft shadowing effect, 
  is proposed. The light transport is represented by conical functions and approximated 
  with an incremental blurring operation of the opacity buffer during front-to-back 
  slicing of the volume. Furthermore, a new perceptuallyfounded model for expressing 
  shadows that gives a full control over the appearance of shadows in terms of color 
  and opacity, is presented. Third, a systematic error in perception of surface slant 
  is modeled. This knowledge is then applied to adjust an existing shading model in a 
  manner that compensates for the error in perception. These new visualization
  methodologies are linked to the knowledge of perceptual psychology and the
  craft of illustrators, who experimented with visual-presentation techniques for centuries.
  The new methodologies are showcased on challenging acoustic modalities such as 3D
  medical ultrasound and sonar imaging.},
  school = {Department of Informatics, University of Bergen, Norway},
  ISBN = {978-82-308-2118-3},



}






 Last Modified: Jean-Paul Balabanian, 2014-11-06