Foveated Path Tracing with Fast Reconstruction and Efficient Sample Distribution

Polunseuranta on tietokonegrafiikan piirtotekniikka, jota on käytetty pääasiassa ei-reaaliaikaisen realistisen piirron tekemiseen. Polunseuranta tukee luonnostaan monia muilla tekniikoilla vaikeasti saavutettavia todellisen valon ilmiöitä kuten heijastuksia ja taittumista. Reaaliaikainen polunseuranta on hankalaa polunseurannan suuren laskentavaatimuksen takia. Siksi nykyiset reaaliaikaiset polunseurantasysteemi tuottavat erittäin kohinaisia kuvia, jotka tyypillisesti suodatetaan jälkikäsittelykohinanpoisto-suodattimilla. Erittäin immersiivisiä käyttäjäkokemuksia voitaisiin luoda polunseurannalla, joka täyttäisi laajennetun todellisuuden vaatimukset suuresta resoluutiosta riittävän matalassa vasteajassa. Yksi mahdollinen ratkaisu näiden vaatimusten täyttämiseen voisi olla katsekeskeinen polunseuranta, jossa piirron resoluutiota vähennetään katseen reunoilla. Tämän johdosta piirron laatu on katseen reunoilla sekä harvaa että kohinaista, mikä asettaa suuren roolin lopullisen kuvan koostavalle suodattimelle. Tässä työssä esitellään ensimmäinen reaaliajassa toimiva regressionsuodatin. Suodatin on suunniteltu kohinaisille kuville, joissa on yksi polunseurantanäyte pikseliä kohden. Nopea suoritus saavutetaan tiileissä käsittelemällä ja nopealla sovituksen toteutuksella. Lisäksi työssä esitellään Visual-Polar koordinaattiavaruus, joka jakaa polunseurantanäytteet siten, että niiden jakauma seuraa silmän herkkyysmallia. Visual-Polar-avaruuden etu muihin tekniikoiden nähden on että se vähentää työmäärää sekä polunseurannassa että suotimessa. Nämä tekniikat esittelevät toimivan prototyypin katsekeskeisestä polunseurannasta, ja saattavat toimia tienraivaajina laajamittaiselle realistisen reaaliaikaisen polunseurannan käyttöönotolle.Photo-realistic offline rendering is currently done with path tracing, because it naturally produces many real-life light effects such as reflections, refractions and caustics. These effects are hard to achieve with other rendering techniques. However, path tracing in real time is complicated due to its high computational demand. Therefore, current real-time path tracing systems can only generate very noisy estimate of the final frame, which is then denoised with a post-processing reconstruction filter. A path tracing-based rendering system capable of filling the high resolution in the low latency requirements of mixed reality devices would generate a very immersive user experience. One possible solution for fulfilling these requirements could be foveated path tracing, wherein the rendering resolution is reduced in the periphery of the human visual system. The key challenge is that the foveated path tracing in the periphery is both sparse and noisy, placing high demands on the reconstruction filter. This thesis proposes the first regression-based reconstruction filter for path tracing that runs in real time. The filter is designed for highly noisy one sample per pixel inputs. The fast execution is accomplished with blockwise processing and fast implementation of the regression. In addition, a novel Visual-Polar coordinate space which distributes the samples according to the contrast sensitivity model of the human visual system is proposed. The specialty of Visual-Polar space is that it reduces both path tracing and reconstruction work because both of them can be done with smaller resolution. These techniques enable a working prototype of a foveated path tracing system and may work as a stepping stone towards wider commercial adoption of photo-realistic real-time path tracing

Inattentional Blindness for Redirected Walking Using Dynamic Foveated Rendering

Redirected walking is a Virtual Reality(VR) locomotion technique which enables users to navigate virtual environments (VEs) that are spatially larger than the available physical tracked space. In this work we present a novel technique for redirected walking in VR based on the psychological phenomenon of inattentional blindness. Based on the user's visual fixation points we divide the user's view into zones. Spatially-varying rotations are applied according to the zone's importance and are rendered using foveated rendering. Our technique is real-time and applicable to small and large physical spaces. Furthermore, the proposed technique does not require the use of stimulated saccades but rather takes advantage of naturally occurring saccades and blinks for a complete refresh of the framebuffer. We performed extensive testing and present the analysis of the results of three user studies conducted for the evaluation

Fast and interactive ray-based rendering

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonDespite their age, ray-based rendering methods are still a very active field of research with many challenges when it comes to interactive visualization. In this thesis, we present our work on Guided High-Quality Rendering, Foveated Ray Tracing for Head Mounted Displays and Hash-based Hierarchical Caching and Layered Filtering. Our system for Guided High-Quality Rendering allows for guiding the sampling rate of ray-based rendering methods by a user-specified Region of Interest (RoI). We propose two interaction methods for setting such an RoI when using a large display system and a desktop display, respectively. This makes it possible to compute images with a heterogeneous sample distribution across the image plane. Using such a non-uniform sample distribution, the rendering performance inside the RoI can be significantly improved in order to judge specific image features. However, a modified scheduling method is required to achieve sufficient performance. To solve this issue, we developed a scheduling method based on sparse matrix compression, which has shown significant improvements in our benchmarks. By filtering the sparsely sampled image appropriately, large brightness variations in areas outside the RoI are avoided and the overall image brightness is similar to the ground truth early in the rendering process. When using ray-based methods in a VR environment on head-mounted display de vices, it is crucial to provide sufficient frame rates in order to reduce motion sickness. This is a challenging task when moving through highly complex environments and the full image has to be rendered for each frame. With our foveated rendering sys tem, we provide a perception-based method for adjusting the sample density to the user’s gaze, measured with an eye tracker integrated into the HMD. In order to avoid disturbances through visual artifacts from low sampling rates, we introduce a reprojection-based rendering pipeline that allows for fast rendering and temporal accumulation of the sparsely placed samples. In our user study, we analyse the im pact our system has on visual quality. We then take a closer look at the recorded eye tracking data in order to determine tracking accuracy and connections between different fixation modes and perceived quality, leading to surprising insights. For previewing global illumination of a scene interactively by allowing for free scene exploration, we present a hash-based caching system. Building upon the concept of linkless octrees, which allow for constant-time queries of spatial data, our frame work is suited for rendering such previews of static scenes. Non-diffuse surfaces are supported by our hybrid reconstruction approach that allows for the visualization of view-dependent effects. In addition to our caching and reconstruction technique, we introduce a novel layered filtering framework, acting as a hybrid method between path space and image space filtering, that allows for the high-quality denoising of non-diffuse materials. Also, being designed as a framework instead of a concrete filtering method, it is possible to adapt most available denoising methods to our layered approach instead of relying only on the filtering of primary hitpoints

Beyond blur: real-time ventral metamers for foveated rendering

To peripheral vision, a pair of physically different images can look the same. Such pairs are metamers relative to each other, just as physically-different spectra of light are perceived as the same color. We propose a real-time method to compute such ventral metamers for foveated rendering where, in particular for near-eye displays, the largest part of the framebuffer maps to the periphery. This improves in quality over state-of-the-art foveation methods which blur the periphery. Work in Vision Science has established how peripheral stimuli are ventral metamers if their statistics are similar. Existing methods, however, require a costly optimization process to find such metamers. To this end, we propose a novel type of statistics particularly well-suited for practical real-time rendering: smooth moments of steerable filter responses. These can be extracted from images in time constant in the number of pixels and in parallel over all pixels using a GPU. Further, we show that they can be compressed effectively and transmitted at low bandwidth. Finally, computing realizations of those statistics can again be performed in constant time and in parallel. This enables a new level of quality for foveated applications such as such as remote rendering, level-of-detail and Monte-Carlo denoising. In a user study, we finally show how human task performance increases and foveation artifacts are less suspicious, when using our method compared to common blurring

Perception-driven approaches to real-time remote immersive visualization

In remote immersive visualization systems, real-time 3D perception through RGB-D cameras, combined with modern Virtual Reality (VR) interfaces, enhances the user’s sense of presence in a remote scene through 3D reconstruction rendered in a remote immersive visualization system. Particularly, in situations when there is a need to visualize, explore and perform tasks in inaccessible environments, too hazardous or distant. However, a remote visualization system requires the entire pipeline from 3D data acquisition to VR rendering satisfies the speed, throughput, and high visual realism. Mainly when using point-cloud, there is a fundamental quality difference between the acquired data of the physical world and the displayed data because of network latency and throughput limitations that negatively impact the sense of presence and provoke cybersickness. This thesis presents state-of-the-art research to address these problems by taking the human visual system as inspiration, from sensor data acquisition to VR rendering. The human visual system does not have a uniform vision across the field of view; It has the sharpest visual acuity at the center of the field of view. The acuity falls off towards the periphery. The peripheral vision provides lower resolution to guide the eye movements so that the central vision visits all the interesting crucial parts. As a first contribution, the thesis developed remote visualization strategies that utilize the acuity fall-off to facilitate the processing, transmission, buffering, and rendering in VR of 3D reconstructed scenes while simultaneously reducing throughput requirements and latency. As a second contribution, the thesis looked into attentional mechanisms to select and draw user engagement to specific information from the dynamic spatio-temporal environment. It proposed a strategy to analyze the remote scene concerning the 3D structure of the scene, its layout, and the spatial, functional, and semantic relationships between objects in the scene. The strategy primarily focuses on analyzing the scene with models the human visual perception uses. It sets a more significant proportion of computational resources on objects of interest and creates a more realistic visualization. As a supplementary contribution, A new volumetric point-cloud density-based Peak Signal-to-Noise Ratio (PSNR) metric is proposed to evaluate the introduced techniques. An in-depth evaluation of the presented systems, comparative examination of the proposed point cloud metric, user studies, and experiments demonstrated that the methods introduced in this thesis are visually superior while significantly reducing latency and throughput

Inattentional Blindness for Redirected Walking Using Dynamic Foveated Rendering

Redirected walking is a Virtual Reality(VR) locomotion technique which enables users to navigate virtual environments (VEs) that are spatially larger than the available physical tracked space. In this work we present a novel technique for redirected walking in VR based on the psychological phenomenon of inattentional blindness. Based on the user's visual fixation points we divide the user's view into zones. Spatially-varying rotations are applied according to the zone's importance and are rendered using foveated rendering. Our technique is real-time and applicable to small and large physical spaces. Furthermore, the proposed technique does not require the use of stimulated saccades but rather takes advantage of naturally occurring saccades and blinks for a complete refresh of the framebuffer. We performed extensive testing and present the analysis of the results of three user studies conducted for the evaluation

Blickpunktabhängige Computergraphik

Contemporary digital displays feature multi-million pixels at ever-increasing refresh rates. Reality, on the other hand, provides us with a view of the world that is continuous in space and time. The discrepancy between viewing the physical world and its sampled depiction on digital displays gives rise to perceptual quality degradations. By measuring or estimating where we look, gaze-contingent algorithms aim at exploiting the way we visually perceive to remedy visible artifacts. This dissertation presents a variety of novel gaze-contingent algorithms and respective perceptual studies. Chapter 4 and 5 present methods to boost perceived visual quality of conventional video footage when viewed on commodity monitors or projectors. In Chapter 6 a novel head-mounted display with real-time gaze tracking is described. The device enables a large variety of applications in the context of Virtual Reality and Augmented Reality. Using the gaze-tracking VR headset, a novel gaze-contingent render method is described in Chapter 7. The gaze-aware approach greatly reduces computational efforts for shading virtual worlds. The described methods and studies show that gaze-contingent algorithms are able to improve the quality of displayed images and videos or reduce the computational effort for image generation, while display quality perceived by the user does not change.Moderne digitale Bildschirme ermöglichen immer höhere Auflösungen bei ebenfalls steigenden Bildwiederholraten. Die Realität hingegen ist in Raum und Zeit kontinuierlich. Diese Grundverschiedenheit führt beim Betrachter zu perzeptuellen Unterschieden. Die Verfolgung der Aug-Blickrichtung ermöglicht blickpunktabhängige Darstellungsmethoden, die sichtbare Artefakte verhindern können. Diese Dissertation trägt zu vier Bereichen blickpunktabhängiger und wahrnehmungstreuer Darstellungsmethoden bei. Die Verfahren in Kapitel 4 und 5 haben zum Ziel, die wahrgenommene visuelle Qualität von Videos für den Betrachter zu erhöhen, wobei die Videos auf gewöhnlicher Ausgabehardware wie z.B. einem Fernseher oder Projektor dargestellt werden. Kapitel 6 beschreibt die Entwicklung eines neuartigen Head-mounted Displays mit Unterstützung zur Erfassung der Blickrichtung in Echtzeit. Die Kombination der Funktionen ermöglicht eine Reihe interessanter Anwendungen in Bezug auf Virtuelle Realität (VR) und Erweiterte Realität (AR). Das vierte und abschließende Verfahren in Kapitel 7 dieser Dissertation beschreibt einen neuen Algorithmus, der das entwickelte Eye-Tracking Head-mounted Display zum blickpunktabhängigen Rendern nutzt. Die Qualität des Shadings wird hierbei auf Basis eines Wahrnehmungsmodells für jeden Bildpixel in Echtzeit analysiert und angepasst. Das Verfahren hat das Potenzial den Berechnungsaufwand für das Shading einer virtuellen Szene auf ein Bruchteil zu reduzieren. Die in dieser Dissertation beschriebenen Verfahren und Untersuchungen zeigen, dass blickpunktabhängige Algorithmen die Darstellungsqualität von Bildern und Videos wirksam verbessern können, beziehungsweise sich bei gleichbleibender Bildqualität der Berechnungsaufwand des bildgebenden Verfahrens erheblich verringern lässt

Efficient image-based rendering

Recent advancements in real-time ray tracing and deep learning have significantly enhanced the realism of computer-generated images. However, conventional 3D computer graphics (CG) can still be time-consuming and resource-intensive, particularly when creating photo-realistic simulations of complex or animated scenes. Image-based rendering (IBR) has emerged as an alternative approach that utilizes pre-captured images from the real world to generate realistic images in real-time, eliminating the need for extensive modeling. Although IBR has its advantages, it faces challenges in providing the same level of control over scene attributes as traditional CG pipelines and accurately reproducing complex scenes and objects with different materials, such as transparent objects. This thesis endeavors to address these issues by harnessing the power of deep learning and incorporating the fundamental principles of graphics and physical-based rendering. It offers an efficient solution that enables interactive manipulation of real-world dynamic scenes captured from sparse views, lighting positions, and times, as well as a physically-based approach that facilitates accurate reproduction of the view dependency effect resulting from the interaction between transparent objects and their surrounding environment. Additionally, this thesis develops a visibility metric that can identify artifacts in the reconstructed IBR images without observing the reference image, thereby contributing to the design of an effective IBR acquisition pipeline. Lastly, a perception-driven rendering technique is developed to provide high-fidelity visual content in virtual reality displays while retaining computational efficiency.Jüngste Fortschritte im Bereich Echtzeit-Raytracing und Deep Learning haben den Realismus computergenerierter Bilder erheblich verbessert. Konventionelle 3DComputergrafik (CG) kann jedoch nach wie vor zeit- und ressourcenintensiv sein, insbesondere bei der Erstellung fotorealistischer Simulationen von komplexen oder animierten Szenen. Das bildbasierte Rendering (IBR) hat sich als alternativer Ansatz herauskristallisiert, bei dem vorab aufgenommene Bilder aus der realen Welt verwendet werden, um realistische Bilder in Echtzeit zu erzeugen, so dass keine umfangreiche Modellierung erforderlich ist. Obwohl IBR seine Vorteile hat, ist es eine Herausforderung, das gleiche Maß an Kontrolle über Szenenattribute zu bieten wie traditionelle CG-Pipelines und komplexe Szenen und Objekte mit unterschiedlichen Materialien, wie z.B. transparente Objekte, akkurat wiederzugeben. In dieser Arbeit wird versucht, diese Probleme zu lösen, indem die Möglichkeiten des Deep Learning genutzt und die grundlegenden Prinzipien der Grafik und des physikalisch basierten Renderings einbezogen werden. Sie bietet eine effiziente Lösung, die eine interaktive Manipulation von dynamischen Szenen aus der realen Welt ermöglicht, die aus spärlichen Ansichten, Beleuchtungspositionen und Zeiten erfasst wurden, sowie einen physikalisch basierten Ansatz, der eine genaue Reproduktion des Effekts der Sichtabhängigkeit ermöglicht, der sich aus der Interaktion zwischen transparenten Objekten und ihrer Umgebung ergibt. Darüber hinaus wird in dieser Arbeit eine Sichtbarkeitsmetrik entwickelt, mit der Artefakte in den rekonstruierten IBR-Bildern identifiziert werden können, ohne das Referenzbild zu betrachten, und die somit zur Entwicklung einer effektiven IBR-Erfassungspipeline beiträgt. Schließlich wird ein wahrnehmungsgesteuertes Rendering-Verfahren entwickelt, um visuelle Inhalte in Virtual-Reality-Displays mit hoherWiedergabetreue zu liefern und gleichzeitig die Rechenleistung zu erhalten

Towards Understanding and Expanding Locomotion in Physical and Virtual Realities

Among many virtual reality interactions, the locomotion dilemma remains a significant impediment to achieving an ideal immersive experience. The physical limitations of tracked space make it impossible to naturally explore theoretically boundless virtual environments with a one-to-one mapping. Synthetic techniques like teleportation and flying often induce simulator sickness and break the sense of presence. Therefore, natural walking is the most favored form of locomotion. Redirected walking offers a more natural and intuitive way for users to navigate vast virtual spaces efficiently. However, existing techniques either lead to simulator sickness due to visual and vestibular mismatch or detract users from the immersive experience that virtual reality aims to provide. This research presents innovative techniques and applications to enhance the user experience by expanding walkable, physical space in Virtual Reality. The thesis includes three main contributions. The first contribution proposes a mobile application that uses markerless Augmented Reality to allow users to explore a life-sized virtual library through a divide-and-rule approach. The second contribution presents a subtle redirected walking technique based on inattentional blindness, using dynamic foveated rendering and natural visual suppressions like blinks and saccades. Finally, the third contribution introduces a novel redirected walking solution that leverages a deep neural network, to predict saccades in real-time and eliminate the hardware requirements for eye-tracking. Overall, this thesis offers valuable contributions to human-computer interaction, investigating novel approaches to solving the locomotion dilemma. The proposed solutions were evaluated through extensive user studies, demonstrating their effectiveness and applicability in real-world scenarios like training simulations and entertainment