In this dissertation we focus on developing accurate and efficient Monte Carlo methods for synthesizing images containing general participating media. Participating media such as clouds, smoke, and fog are ubiquitous in the world and are responsible for many important visual phenomena which are of interest to computer graphics as well as related fields. When present, the medium participates in lighting interactions by scattering or absorbing photons as they travel through the scene. Though these effects add atmosphere and considerable depth to rendered images they are computationally very expensive to simulate. Most practical solutions make simplifying assumptions about the medium in order to maintain efficiency. Unfortunately, accurate and efficient simulation of light transport in general scattering media is a challenging undertaking. In this dissertation, we address this problem by introducing two complementary techniques. We first turn to the irradiance caching method for surface illumination. Irradiance caching gains efficiency by computing an accurate representation of lighting only at a sparse set of locations and reusing these values through interpolation whenever possible. We derive the mathematical concepts that form the foundation of this approach and analyze its strengths and weaknesses. Drawing inspiration from this algorithm, we then introduce a novel volumetric radiance caching method for efficiently simulating global illumination within participating media. In developing the technique we also introduce efficient methods for evaluating the gradient of the lighting within participating media. Our gradient analysis has immediate applicability for improved interpolation quality in both surface and media-based caching methods. We also develop a novel photon mapping technique for participating media. We present a theoretical reformulation of volumetric photon mapping, which provides significant new insights. This reformulation makes it easier to qualify the error introduced by the radiance estimate but, more importantly, also allows us to develop more efficient rendering techniques. Conventional photon mapping accelerate the computation of lighting at any point in the scene by performing density estimation. In contrast, our reformulation accelerates the computation of accumulated lighting along the length of entire rays. This algorithmic improvement provides for significantly reduced render times and even the potential for real-time visualization of light transport in participating media

We present a new method for efficiently simulating the scattering of light within participating media. Using a theoretical reformulation of volumetric photon mapping, we develop a novel photon gathering technique for participating media. Traditional volumetric photon mapping samples the in-scattered radiance at numerous points along the length of a single ray by performing costly range queries within the photon map. Our technique replaces these multiple point-queries with a single beam-query, which explicitly gathers all photons along the length of an entire ray. These photons are used to estimate the accumulated in-scattered radiance arriving from a particular direction and need to be gathered only once per ray. Our method handles both fixed and adaptive kernels, is faster than regular volumetric photon mapping, and produces images with less noise.

Pre-2018 CSE ID: CS2008-0914

Significance

For people with limited vision, wearable displays hold the potential to digitally enhance visual function. As these display technologies advance, it is important to understand their promise and limitations as vision aids.

Purpose

The aim of this study was to test the potential of a consumer augmented reality (AR) device for improving the functional vision of people with near-complete vision loss.

Methods

An AR application that translates spatial information into high-contrast visual patterns was developed. Two experiments assessed the efficacy of the application to improve vision: an exploratory study with four visually impaired participants and a main controlled study with participants with simulated vision loss (n = 48). In both studies, performance was tested on a range of visual tasks (identifying the location, pose and gesture of a person, identifying objects, and moving around in an unfamiliar space). Participants' accuracy and confidence were compared on these tasks with and without augmented vision, as well as their subjective responses about ease of mobility.

Results

In the main study, the AR application was associated with substantially improved accuracy and confidence in object recognition (all P < .001) and to a lesser degree in gesture recognition (P < .05). There was no significant change in performance on identifying body poses or in subjective assessments of mobility, as compared with a control group.

Conclusions

Consumer AR devices may soon be able to support applications that improve the functional vision of users for some tasks. In our study, both artificially impaired participants and participants with near-complete vision loss performed tasks that they could not do without the AR system. Current limitations in system performance and form factor, as well as the risk of overconfidence, will need to be overcome.

People typically rely heavily on visual information when finding their way to unfamiliar locations. For individuals with reduced vision, there are a variety of navigational tools available to assist with this task if needed. However, for wayfinding in unfamiliar indoor environments the applicability of existing tools is limited. One potential approach to assist with this task is to enhance visual information about the location and content of existing signage in the environment. With this aim, we developed a prototype software application, which runs on a consumer head-mounted augmented reality (AR) device, to assist visually impaired users with sign-reading. The sign-reading assistant identifies real-world text (e.g., signs and room numbers) on command, highlights the text location, converts it to high contrast AR lettering, and optionally reads the content aloud via text-to-speech. We assessed the usability of this application in a behavioral experiment. Participants with simulated visual impairment were asked to locate a particular office within a hallway, either with or without AR assistance (referred to as the AR group and control group, respectively). Subjective assessments indicated that participants in the AR group found the application helpful for this task, and an analysis of walking paths indicated that these participants took more direct routes compared to the control group. However, participants in the AR group also walked more slowly and took more time to complete the task than the control group. The results point to several specific future goals for usability and system performance in AR-based assistive tools.