A perceptual-statistics shading model

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

Perceptual effects of volumetric shading models in stereoscopic desktop-based environments

Throughout the years, many shading techniques have been developed to improve the conveying of information in Volume Visualization. Some of these methods, usually referred to as realistic, are supposed to provide better cues for the understanding of volume data sets. While shading approaches are heavily exploited in traditional monoscopic setups, no previous study has analyzed the effect of these techniques in Virtual Reality. To further explore the influence of shading on the understanding of volume data in such environments, we carried out a user study in a desktop-based stereoscopic setup. The goals of the study were to investigate the impact of well-known shading approaches and the influence of real illumination on depth perception. Participants had to perform three different perceptual tasks when exposed to static visual stimuli. 45 participants took part in the study, giving us 1152 trials for each task. Results show that advanced shading techniques improve depth perception in stereoscopic volume visualization. As well, external lighting does not affect depth perception when these shading methods are applied. As a result, we derive some guidelines that may help the researchers when selecting illumination models for stereoscopic rendering.Peer ReviewedPostprint (author's final draft

Perceptually Uniform Motion Space

Flow data is often visualized by animated particles inserted into a flow field. The velocity of a particle on the screen is typically linearly scaled by the velocities in the data. However, the perception of velocity magnitude in animated particles is not necessarily linear. We present a study on how different parameters affect relative motion perception. We have investigated the impact of four parameters. The parameters consist of speed multiplier, direction, contrast type and the global velocity scale. In addition, we investigated if multiple motion cues, and point distribution, affect the speed estimation. Several studies were executed to investigate the impact of each parameter. In the initial results, we noticed trends in scale and multiplier. Using the trends for the significant parameters, we designed a compensation model, which adjusts the particle speed to compensate for the effect of the parameters. We then performed a second study to investigate the performance of the compensation model. From the second study we detected a constant estimation error, which we adjusted for in the last study. In addition, we connect our work to established theories in psychophysics by comparing our model to a model based on Stevens’ Power Law

Shape Perception of Clear Water in Photo-Realistic Images

Light plays a vital role in the perception of transparency, depth and shape of liquids. The perception of the surfaces of liquids is made possible with an understanding of refraction of light and knowledge of the underlying texture geometry. Given this, what specific characteristics of the natural optical environment are essential to the perception of transparent liquids, specifically with respect to efficiency and realism? In this thesis, a light path triangulation method for the recovery of transparent surface shape and a system to estimate the perceived shape of any arbitrary-shaped object with a refractive surface are proposed. A psycho-physical experiment was conducted to investigate this using the perceived shape of water from stereo images using a real time stereoscopic 3-D depth gauge. The results suggest that people are able to consistently perceive shape of liquids from photo-realistic images and that regularity in underlying texture facilitates human judgement of surface shape