Effective text input in VR is an ongoing problem with no best-agreed-upon solution. One effective solution for this is a word-gesture keyboard implemented in VR. These keyboards work by matching the user-drawn gestures to predefined gestures of all words that connect consecutive letters of the word with straight lines. We investigate matching the user input with gestures comprising of Bézier curves. We found a small improvement in writing speed and a reduction in errors while writing. The method of using complex curves for matching gestures seems promising with many possible ways for further extension.

Virtual Reality's uniquely immersive nature can facilitate skill transfer between an instructor and a student. Through the use of statically transparent ghost instructors that are superimposed on the student avatar, the student can learn skills by observing the ghost instructor's movements from a first-person perspective.

This paper aims to investigate the effect that changing the transparency values of the ghost avatar based on student performance has on learning and retaining skills. A small-scale user study has been conducted to contrast these dynamically and statically transparent ghost instructors. While the group taught by statically transparent ghost instructors displayed better performance improvement between training trials, the performance drop between the training and test trials was much smaller for the group taught by dynamically transparent ghost instructors.

Social uses of virtual reality, such as collaborative virtual environments (CVEs), are showing significant increases in general adoption. In these CVEs, it is desirable for users to feel a high level of presence, which can increase collaboration effectiveness. This study investigated the effect of facial realism on presence in CVEs. Facial realism was implemented through including eye- and mouth-tracked facial expressions in an avatar representation. A controlled within-dyad experiment was performed, consisting of a dyadic interaction between participants in a CVE. We found no significant difference between a Static Face condition and either Eye Tracked or Full Tracked (eye- and mouth) facial expression conditions. Some individual items on the questionnaire were significant or marginally significant, suggesting some positive impact on the assessment of partner reactions in the Full Tracked condition, compared to Static Face. Participants also reported a lower feeling of correspondence between virtual experiences and their physical body in the Full Tracked and Eye Tracked conditions. Some evidence has been found that this experiment warrants repetition with changes discussed in this paper, which may yield significant differences with a higher sample size.

Lag in Virtual Reality can be devastating to the enjoyment of participants. This paper reduces the lag in a physics system by implementing a subset of the architecture proposed by Loren Peitso and Don Brutzman. This subset contains an event based physics system together with a networking system. The collision system of the physics system has been heavily reduced in size, as to speedup development of the architecture.

This architecture seems promising and handles predictable cases with almost no noticeable lag. This architecture does not handle external events well, as the lag is noticeable. The `healing' process for unexpected external events should be researched further to make this architecture viable.

In this thesis, we investigate a CPU-based ray tracer tailored for semiconductor structures. This ray tracer addresses the need for high-quality visualization in environments where GPU acceleration is unavailable. Our primary objective is to achieve interactive visualization performance with quality levels on par with a basic triangle rasterizer employing a flat-shaded lighting model. The research focuses on identifying optimal BVH configurations and developing efficient Oriented Bounding Box (OBB) ray tracing methods. By leveraging OBB clustering and pre-cached ray directions, we aim to mitigate the computational overhead associated with OBB tracing. The result is a prototype that demonstrates the feasibility of CPU-based ray tracing for real-time applications. This work contributes to the broader discourse on rendering techniques in GPU-limited scenarios, offering valuable insights and laying the groundwork for future research and development.

Creating photorealistic images is one of the ultimate goals of computer graphics. Previous work has shown that a material's microstructure plays a crucial role when trying to achieve photorealism. This is because a material's appearance depends on the roughness of its microstructure. Due to this dependence, effects such as masking and shadowing have to be taken into account, as these are capable of altering the effective reflectance of a material. Render engines typically use a mathematical expression, known as a visibility function, that aims to calculate the impact of these effects. However, even the best visibility function known is still an approximation; an exact solution doesn't exist. In order to evaluate the accuracy of visibility functions, an algorithm can be created that computes the correct output, such that the output of a given visibility function can be compared against it. Such an algorithm can be one of two types: approximative or exact. In this paper, we show that approximative algorithms are very capable and come close to their exact counterparts. However, there is still a non-negligible difference between them, meaning they aren't suitable for applications that demand very high levels of accuracy.

This research proposes a new algorithm for mapping Normal Distribution Functions to Heightfields in order to answer its research question: ”Given an NDF, how can we generate a corresponding Heightfield using simple optimization algorithms?”. This research is important, as it helps us to gain a better understanding of how limited statistics-based representations of 3D surfaces are. To this end, we have produced an algorithm using the Simulated Annealing optimization technique, a technique that randomly explores possible solutions of a problem until it finds the optimal solution. The algorithm begins with a flat Heightfield (a 2D representation of a surface that shows the relative altitude of a discrete plane of points), iteratively changes points on the Heightfield and compares its measured NDF (Normal Distribution Function, a function to denote the area distribution along a given direction in a Heightfield) to the target NDF that we want to map. Once the target NDF is reached, or once the pre-determined number of iterations has been reached, the algorithm concludes and the NDF-to-Heightfield mapping has been completed. Three different variations are tried, one na¨ıve implementation which changes points on the Heightfield completely at random, another where the angle of the normal vector of a random surrounding facet of a chosen point is used as guidance for randomization, and finally one where this angle is guided using the relative position of the chosen point to the centre of the Heightfield. The conclusion the proposed algorithm provides is that, while possible, the process of mapping NDFs to Heightfields is a costly and complex operation, and leaves a lot of room for ambiguity. While the research cannot provide a case of an exact match of a target NDF and measured NDF of a Heightfield created through the algorithm, we do show it is without a doubt possible given time.

The micro detail on surfaces can have a profound effect on how rays bounce of it. In ray tracing, this micro-surface is normally approximated with statistical models. We wish to figure out what the effect of normal interpolation and Phong tessellation is on how rays reflect on the surface. This has been Done by creating a ray tracers from scratch, that uses height fields, with normal interpolation and Phong tessellation. This ray tracer has then been used to render 3 different micro-surfaces, which were compared in order to understand the difference. The conclusion of this research was that both smoothing techniques had little to no effect on the reflection of rays on micro-surfaces with a high triangle density. However on micro-surfaces with a low triangle density, there was a much more pronounced difference with the smoothing techniques. A second conclusion was made which was that rougher surfaces have a more spread out distribution of rays than smoother surfaces.

Bidirectional Reflectance Distribution Functions, BRDFs, describe the reflectance of light on a ma-terial, and are widely used in computer graphics to render materials. Acquiring a full measured BRDF can be costly and time consuming, so this research aims to answer the question ”How can we approx-imate a full BRDF from a single slice (in-plane BRDF)?”. Outlined in this paper is an algorithm that uses solids of revolution to approximate a full BRDF from a single slice. The algorithm finds sub-curves of the slice, creates solids of revolution for each, normalizes the data, and merges the solids while removing overlapping data. The resulting solid, described by a list of points using a Carte-sian coordinate system, represents the full, three-dimensional BRDF.

Rendering accurate water reflections is crucial for achieving realism in computer graphics. Their integration with VR and AR technologies can further elevate experiences in sectors like education, engineering, and medicine. Even though various monoscopic reflection techniques exist they either demand substantial computational resources or cannot be straightforwardly adapted to stereoscopic media, leaving a big hole in research concerning stereo-aware reflections and their applications. This thesis researches and analyses the different techniques for water reflections. Further, it makes significant strides in the development of stereo-consistent real-time water reflections for XR platforms. This is achieved by combining implicit functions and bounding volume hierarchies (BVH) into a unified system called Adaptive Hierarchical Signed Distance Fields Reflections (AH-SDFR). It was found that AH-SDF outperforms leading methods such as Hierarchical Screen Space Reflections (HSSR) and Reflection Probes in both visual quality and performance, and as a result, it offers a promising solution for XR applications. However, challenges persist, mainly due to the large memory demands of intricate 3D scenes and perceptual errors from inaccuracies in volume textures.

This research investigates the efficacy and reliability of geometric matching for the specific case of aligning non-exact copies of artistic works with the original from which they were derived. The purpose of which is to provide a foundation for comparison in any further analysis conducted by conservators and art historians. An overview of the image alignment field as a whole is provided as well as a discussion of the particulars of aligning artworks. A variety of demonstrative results indicate the strengths and weaknesses of the technique in this domain and are accompanied by a discussion of the headline conclusions.

Image registration is the process that overlays two or more images from different sources taken at different times and angles. Art conservators take various scans of paintings and then register them against the original in order to learn more about the working style of the artist, materials used and physical changes throughout time. This paper describes how scale space theory could be applied with a variant of cross-correlation to find the right scale at which to register the input images. From there, the standard state-of-the-art approach is used to register the images. This added step allows automatically registering a wider range of images.

The current state-of-the-art image alignment techniques and their input parameters are often unintuitive to those without the required background knowledge.
This work aims to provide users with a graphical user interface through which they can intuitively influence the parameters and results of the algorithm by excluding certain areas from the images.
The application is also capable of automatically optimizing the parameters of the underlying registration algorithm.
Experimental results indicate that the automatic parameter optimization results in alignments at least as good as the default parameters, but that the introduced user interaction does not provide any major benefits.

Multimodal imaging is used by conservators and scientists to study the composition of paintings. To aid the combined analysis of these scans, such images must first be aligned. Rather than proposing a new domain-specific descriptor, we explore and evaluate how existing feature descriptors from related fields can improve the performance of feature-based painting scan registration. We benchmark these descriptors on pixel-precise, manually aligned scans of “Girl with a Pearl Earring” by Johannes Vermeer (c. 1665, Mauritshuis) and of “18th Century Portrait of a Woman”. As a baseline we compare against the well-established classical SIFT descriptor. We consider two recent descriptors: the handcrafted multimodal MFD descriptor, and the learned unimodal SuperPoint descriptor. Experiments show that SuperPoint starkly increases description matching accuracy by 40% for modalities with little modality-specific artefacts. Further, performing craquelure segmentation and using the MFD descriptor results in significant description matching accuracy improvements for modalities with many modality-specific artefacts.

Surface Registration is a registration problem that handles the registration of two similar surfaces. In most research that utilises Deep Learning (DL) models to handle surface registration two theories are investigated; the first being whether surfaces sampled from the same origin can be registered together, and the second theory being whether the models can register Point Clouds with low overlapping data for utilisation in Simultaneous Localisation and Mapping (SLAM) applications. However, the surface registration to be utilised in the HoloNav Augmented Reality (AR) navigation system will utilise Point Clouds sampled from different origins with a high overlap ratio. This research, therefore, aims to determine the viability of DL methods for surface registration in HoloNav data. To determine the viability, rotation and translation errors in the match were used, with the aforementioned metrics later being evaluated manually with the utilisation of a visualiser. The results indicate that the models can generalise on the navigator data for an initial Euler angle difference of 45 degrees, but due to the difference in sampling density on the utilised point clouds can not provide accurate matches. Therefore, the utilisation of DL models can be considered to be viable if the navigator data has a sampling density similar to the pre-operative model.

In order to be able to use the Microsoft HoloLens for surgical navigation purposes, performing good patient alignment is of utmost importance. This paper will discuss how this patient alignment can be done using different point cloud registration algorithms.
A lot of research is being conducted on point cloud registration algorithms. However, most research assumes that the point clouds to be aligned are almost identical, while patient alignment aims at aligning a very detailed pre-operative scan with a very sparse point cloud obtained by the surgeon using an optical marker.
In order to get around this problem, the HoloLens' depth camera is used to obtain a detailed point cloud so that registration algorithms can be used. Then the performance of different point cloud registration algorithms is tested on this depth sensor data to see whether using the HoloLens' depth sensor is a viable option for patient alignment.
From the results, it appears that algorithmic approaches for performing patient alignment are feasible, but the performance of these algorithms is very dependent on the quality of the input data.

Patient and instrument tracking are fundamental parts of surgical navigation systems. Traditional surgical navigation systems rely on stationary cameras for tracking and stationary screens for presenting information. An increased mental load is exerted by surgeons as they switch focus between the surgical site and the presented data. By projecting the required data on the patients anatomy, augmented reality surgical navigation would allow surgeons to navigate seamlessly during surgical procedures. In this paper, an augmented reality tracking algorithm for the Hololens 2 will be presented and tested against state of the art optical tracking. The algorithm is based on the use of reflective markers, which are extensively used in medical applications. An accuracy of 1.04mm was found in optimal conditions using the presented method. The presented tracking method is less accurate and less consistent than state of the art optical tracking methods with a minimum median accuracy of 25mm.

Surgical navigation is a tool that surgeons rely on everyday to perform accurate surgeries all over the world. However, this technology requires good hand-eye coordination and a high level of concentration. HoloNav is a project that inquires to see if using the HoloLens and augmented reality can replace the current surgical navigation methods. To do so, the HoloLens must be able to identify the patient and the location of the surgery instruments, which uses optical reflective spheres. This study focuses on using the grayscale cameras of the HoloLens and a deep learning algorithm YOLOv5 to test if it is possible to precisely detect optical reflective spheres. 3 models were trained with two different data sets, where the results show that the model trained on a data set would perform well on the validation set. However, they would perform far worse when exposed to a data set it was not trained on.

The way that surgeons currently use surgical navigation technology impacts their hand-eye coordination and their ability to view images and data critically. To tackle this issue Augmented Reality goggles, built from the HoloLens 2, have been developed specifically for the purpose of aiding surgeons during surgery and it is called: The HoloNav. Optical reflective spheres are commonly used to track surgical instruments. This research aims to find out if grayscale cameras could contribute to locating these spheres more accurately with the HoloNav. This is done by finding the spheres on the infrared images, reducing the search space on the grayscale images and finding the spheres on the reduced search spaces of the grayscale images. By triangulating those retrieved coordinates and comparing them with the optically tracked coordinates a conclusion can be drawn about the accuracy. The accuracy measured in this research is between 0.66 mm and 10.64 mm (mostly between 1.8 mm and 6.4 mm) depending on the frame. This is quite accurate and similar to the results from related work. With better image quality or different input conditions the accuracy could be improved even more.

To design more efficient sailing boat sails and to analyze the efficiency of a sail trim on the water, it is very helpful to have the ability to obtain a digital copy of real-life sail configurations. As a step towards obtaining such digital copies, the Sailing Innovation Centre in collaboration with GeoDelta has created point cloud measurements from sails by placing physical markers on them. This paper introduces a physics-based reconstruction method that uses a known sail rest shape combined with this point cloud data to reconstruct the sail configuration at the time that the measurement was taken. By using a physics-based sail model and the knowledge that the sail is subject to gravity and wind forces together with a known sail rest shape, we can create plausible reconstructions even for areas in the sail where fewer to no markers are placed. Using measurements that were taken before this reconstruction method was proposed in combination with an approximated sail rest shape and material properties, our reconstruction method was approximated to have an average reconstruction distance below 1cm for a 2.5m by 4.5m sail. Taking new measurements following our proposed guidelines in combination with having a more correct sail rest shape and better knowing the sail material properties is very likely to yield even better results.