Modeling believable lighting is a crucial component of computer graphics applications, including games and modeling programs. Physically accurate lighting is complex and is not currently feasible to compute in real-time situations. Therefore, much research is focused on investigating efficient ways to approximate light behavior within these real-time constraints. In this thesis, we implement a general purpose algorithm for real-time applications to approximate indirect lighting. Based on voxel cone tracing, we use a filtered representation of a scene to efficiently sample ambient light at each point in the scene. We present an approach to scene voxelization using hardware tessellation and compare it with an approach utilizing hardware rasterization. We also investigate possible methods of warped voxelization. Our contributions include a complete and open-source implementation of voxel cone tracing along with both voxelization algorithms. We find similar performance and quality with both voxelization algorithms.

Virtual Reality is a technology that has long held society's interest, but has only recently began to reach a critical mass of everyday consumers. The idea of modern VR can be traced back decades, but because of the limitations of the technology (both hardware and software), we are only now exploring its potential. At present, VR can be used for tele-surgery, PTSD therapy, social training, professional meetings, conferences, and much more. It is no longer just an expensive gimmick to go on a momentary field trip; it is a tool, and as with the automobile, personal computer, and smartphone, it will only evolve as more and more adopt and utilize it in various ways. It can provide a three dimensional interface where only two dimensions were previously possible. It can allow us to express ourselves to one another in new ways regardless of the distance between individuals. It has astronomical potential, but with this potential we must first understand what makes it adoptable and attractive to the average consumer. The interaction with technology is often times the bottleneck through which the public either adopts or abandons that technology. The goal of this project is to explore user immerision and emotion during a VR experience centered around creating a virtual world. We also aimed to explore if the naturality of the user interface had any effect on user experience. Very limited user testing was available, however a small user group conducted in depth testing and feedback. While our sample size is small, the users were able to test the system and show that there is a positive correlation between influence on the virtual environment and a positive user emotional experience (immersion, empowerment, etc.), along with a few unexpected emotions (anxiety). We present the system developed, the user study, and proposed extensions for fruitful directions for this work by which a future project may continue the study.

Within computational continuum mechanics there exists a large category of simulation methods which operate by tracking Lagrangian particles over an Eulerian background grid. These Lagrangian/Eulerian hybrid methods, descendants of the Particle-In-Cell method (PIC), have proven highly effective at simulating a broad range of materials and mechanics including fluids, solids, granular materials, and plasma. These methods remain an area of active research after several decades, and their applications can be found across scientific, engineering, and entertainment disciplines. This thesis presents a GPU driven PIC-like simulation framework created using the Vulkan® API. Vulkan is a cross-platform and open-standard explicit API for graphics and GPU compute programming. Compared to its predecessors, Vulkan offers lower overhead, support for host parallelism, and finer grain control over both device resources and scheduling. This thesis harnesses those advantages to create a programmable GPU compute pipeline backed by a Vulkan adaptation of the SPgrid data-structure and multi-buffered particle arrays. The CPU host system works asynchronously with the GPU to maximize utilization of both the host and device. The framework is demonstrated to be capable of supporting Particle-in-Cell like simulation methods, making it viable for GPU acceleration of many Lagrangian particle on Eulerian grid hybrid methods. This novel framework is the first of its kind to be created using Vulkan® and to take advantage of GPU sparse memory features for grid sparsity.

A field guide is a tool to identify an object of natural history. Field guidescover a wide range of topics from plants to fungi, birds to mammals, and shells to minerals. Traditionally, field guides are books, usually small enough to be carried outdoors . They enjoy wide popularity in modern life; almost every American home and library owns at least one field guide, and the same is also true for other areas of the world. At this time, companies, non-profits, and universities are developing computertechnologies to replace printed field guides for identifying plants. This thesisexamines the state of the art in field guides for plants. First, a framework isestablished for evaluating both printed and digital field guides. Second, fourprint and three digital field guides are evaluated against the criteria. Third, anovel digital field guide is presented and evaluated.

We present a technique for out-of-core GPU path tracing of arbitrarily large scenes that is compatible with hardware-accelerated ray-tracing. Our technique improves upon previous works by subdividing the scene spatially into streamable chunks that are loaded using a priority system that maximizes ray throughput and minimizes GPU memory usage. This allows for arbitrarily large scaling of scene complexity. Our system required under 19 minutes to render a solid color version of Disney's Moana Island scene (39.3 million instances, 261.1 million unique quads, and 82.4 billion instanced quads at a resolution of 1024x429 and 1024spp on an RTX 5000 (24GB memory total, 22GB used, 13GB geometry cache, with the remainder for temporary buffers and storage) (Wald et al.). As a scalability test, our system rendered 26 Moana Island scenes without multi-level instancing (1.02 billion instances, 2.14 trillion instanced quads, ~230GB if all resident) in under 1h:28m. Compared to state-of-the-art hardware-accelerated renders of the Moana Island scene, our system can render larger scenes on a single GPU. Our system is faster than the previous out-of-core approach and is able to render larger scenes than previous in-core approaches given the same memory constraints (Hellmuth, Zellman et al, Wald).

We have designed a simulation that can be used to train police officers. Digital simulations are more cost-effective than a human role play. Use of force decisions are complex and made quickly, so there is a need for better training and innovative methods. Using this simulation, we are measuring the degree of presence that a human experience in a virtual environment. More presence implies better training. Participants are divided into two groups in which one group performs the experiment using a screen, keyboard, and mouse, and another uses virtual reality controls. In this experiment, we use subjective measurements and physiological measurements. We offer a questionnaire to participants before and after play. We also record the participants change in heart rate, skin conductivity and skin temperature using Empatica device. By comparing the data collected from both groups, we prove that people experience more presence in the virtual environment.

Context Free Design Grammar (CFDG) is a programming language for defining recursive structures that can be used to create art. I use CFDG as a design space for genetic programming, experimenting with various options for crossover, mutation, and fitness. In this exploratory work, multiple generations are manually assessed to determine the usefulness of the mutation strategies and fitness functions. I find that simple value mutation and fitness that alters general program structure is not enough to produce an increase of interesting images in CFDG. I discuss these findings as well as future avenues of inquiry for genetic programming in artistic domains.

A robust evaluation toolset has been designed for Naval Research Laboratory’s Real-Time Ocean Forecasting System RELO with the purpose of facilitating an adaptive sampling strategy and providing a more educated guidance for routing underwater gliders. The major challenges are to integrate into the existing operational system, and provide a bridge between the modeling and operative environments. Visualization is the selected approach and the developed software is divided into 3 packages: The first package is to verify that the glider is actually following the waypoints and to predict the position of the glider for the next cycle’s instructions. The second package helps ensures that the delivered waypoints are both useful and feasible. The third package provides the confidence levels for the suggested path. This software’s implementation is in Python for portability and modularity to allow for easy expansion for new visuals.

The visualization of data helps to provide faster and deeper insight into the data. In this work, a system for visualizing and analyzing big data in an interactive mixed reality environment is proposed. Such a system can be used for representing different types of data such as temporal, geospatial, network graph, and high dimensional. Also, an implementation of this system for four different data types are created. The data types include network data, volumetric data, high dimensional, and spectral data for different mixed reality devices such as Microsoft HoloLens, Oculus Rift, Samsung Gear VR, and Android ARCore were created. It was shown that such a system could store and use billions of samples and represent millions of them at once.

The field of computer user interface design is rapidly changing and diversifying as new devices are developed every day. Technology has risen to become an integral part of life for people of all ages around the world. Modern life as we know it depends on computers, and understanding the interfaces through which we communicate with them is critically important in an increasingly digital age. The first part of this paper examines the technological origins and historical background driving the development of graphical user interfaces from its earliest incarnations to today. Hardware advancements and key turning points are presented and discussed. In the second part of this paper, skeuomorphism and flat design, two of the most common design trends today, are analyzed and explained. Finally, the future course of user interface is predicted based off of emergent technologies such as the Apple Watch, Google Glass, Microsoft HoloLens, and Microsoft PixelSense. Through understanding the roots and current state of computer user interface design, engineers, designers, and scientists can help us get the most out of our ever-changing world of advanced technology as it becomes further intertwined with our existence.