Realistic hair rendering in Autodesk Maya

Tato diplomová práce popisuje real-time zobrazovaní vlasů v 3D modelovacím programu Autodesk Maya. Zobrazovací modul je součást projektu Stubble - zasuvného modulu do programu Maya, který slouží k modelovaní vlasů. Prezentovaný algoritmus poskytuje vysoce kvalitní interaktivní náhled, pomocí kterého je možné modelovat vlasy bez nutnosti zdlouhavého vytváření náhledu v externím programu. Cílem je vytvořit takový náhled, který se bude co nejvíce podobat obrázkům, které produkuje 3Delight - zasuvný modul pro program Maya, který implementuje standardy zobrazovacího rozhraní RenderMan.This thesis describes a real-time hair rendering in 3D animation and modeling software Autodesk Maya. The renderer is part of the Stubble project a - Maya plug-in for hair modeling. The presented renderer provides a high-quality interactive preview that allows fast hair modeling without the need for rendering in slow off-line renderers. The goal of this work is to create a renderer that can generate images in real-time that are as close as possible to the output of the 3Delight renderer - a plug-in for Maya that is based on RenderMan standards.Department of Software and Computer Science EducationKatedra softwaru a výuky informatikyFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult

Real-Time Hair Filtering with Convolutional Neural Networks

Rendering of realistic-looking hair is in general still too costly to do in real-time applications, from simulating the physics to rendering the fine details required for it to look natural, including self-shadowing.We show how an autoencoder network, that can be evaluated in real time, can be trained to filter an image of few stochastic samples, including self-shadowing, to produce a much more detailed image that takes into account real hair thickness and transparency

A framework for real-time physically-based hair rendering

Hair rendering has been a major challenge in computer graphics for several years due to the complex light interactions involved. Complexity mainly stems from two aspects: the number of hair strands, and the resulting complexity of their interaction with light. In general, theoretical approaches towards a realistic hair visualization aim to develop a proper scattering model on a per-strand level, which can be extended in practice to the whole hair volume with ray tracing even though it is usually expensive in computational terms. Aiming at achieving real-time hair rendering, I analyze each component contributing to it from both theoretical and practical points of view in this work. Most approaches, both real- and non-real-time build on top of the Marschner scattering model, such as recent efficient state-of-the-art techniques introduced in Unreal Engine and Frostbite, among others. Interactive applications cannot afford the complexity of ray tracing, and they target efficiency by explicitly dealing with each component involved in both single-strand and inter-strand light interactions, applying the necessary simplifications to match the time budget. I have further implemented a framework, separating the different components, which combines aspects of these approaches towards the best possible quality and performance. The implementation achieves real-time good-looking hair, and its flexibility has allowed to perform experiments on performance, scalability, and contribution to quality of the different components

Real-Time deep image rendering and order independent transparency

In computer graphics some operations can be performed in either object space or image space. Image space computation can be advantageous, especially with the high parallelism of GPUs, improving speed, accuracy and ease of implementation. For many image space techniques the information contained in regular 2D images is limiting. Recent graphics hardware features, namely atomic operations and dynamic memory location writes, now make it possible to capture and store all per-pixel fragment data from the rasterizer in a single pass in what we call a deep image. A deep image provides a state where all fragments are available and gives a more complete image based geometry representation, providing new possibilities in image based rendering techniques. This thesis investigates deep images and their growing use in real-time image space applications. A focus is new techniques for improving fundamental operation performance, including construction, storage, fast fragment sorting and sampling. A core and driving application is order-independent transparency (OIT). A number of deep image sorting improvements are presented, through which an order of magnitude performance increase is achieved, significantly advancing the ability to perform transparency rendering in real time. In the broader context of image based rendering we look at deep images as a discretized 3D geometry representation and discuss sampling techniques for raycasting and antialiasing with an implicit fragment connectivity approach. Using these ideas a more computationally complex application is investigated — image based depth of field (DoF). Deep images are used to provide partial occlusion, and in particular a form of deep image mipmapping allows a fast approximate defocus blur of up to full screen size

Material Recognition Meets 3D Reconstruction : Novel Tools for Efficient, Automatic Acquisition Systems

For decades, the accurate acquisition of geometry and reflectance properties has represented one of the major objectives in computer vision and computer graphics with many applications in industry, entertainment and cultural heritage. Reproducing even the finest details of surface geometry and surface reflectance has become a ubiquitous prerequisite in visual prototyping, advertisement or digital preservation of objects. However, today's acquisition methods are typically designed for only a rather small range of material types. Furthermore, there is still a lack of accurate reconstruction methods for objects with a more complex surface reflectance behavior beyond diffuse reflectance. In addition to accurate acquisition techniques, the demand for creating large quantities of digital contents also pushes the focus towards fully automatic and highly efficient solutions that allow for masses of objects to be acquired as fast as possible. This thesis is dedicated to the investigation of basic components that allow an efficient, automatic acquisition process. We argue that such an efficient, automatic acquisition can be realized when material recognition "meets" 3D reconstruction and we will demonstrate that reliably recognizing the materials of the considered object allows a more efficient geometry acquisition. Therefore, the main objectives of this thesis are given by the development of novel, robust geometry acquisition techniques for surface materials beyond diffuse surface reflectance, and the development of novel, robust techniques for material recognition. In the context of 3D geometry acquisition, we introduce an improvement of structured light systems, which are capable of robustly acquiring objects ranging from diffuse surface reflectance to even specular surface reflectance with a sufficient diffuse component. We demonstrate that the resolution of the reconstruction can be increased significantly for multi-camera, multi-projector structured light systems by using overlappings of patterns that have been projected under different projector poses. As the reconstructions obtained by applying such triangulation-based techniques still contain high-frequency noise due to inaccurately localized correspondences established for images acquired under different viewpoints, we furthermore introduce a novel geometry acquisition technique that complements the structured light system with additional photometric normals and results in significantly more accurate reconstructions. In addition, we also present a novel method to acquire the 3D shape of mirroring objects with complex surface geometry. The aforementioned investigations on 3D reconstruction are accompanied by the development of novel tools for reliable material recognition which can be used in an initial step to recognize the present surface materials and, hence, to efficiently select the subsequently applied appropriate acquisition techniques based on these classified materials. In the scope of this thesis, we therefore focus on material recognition for scenarios with controlled illumination as given in lab environments as well as scenarios with natural illumination that are given in photographs of typical daily life scenes. Finally, based on the techniques developed in this thesis, we provide novel concepts towards efficient, automatic acquisition systems

LEGEND-1000 Preconceptual Design Report

We propose the construction of LEGEND-1000, the ton-scale Large Enriched Germanium Experiment for Neutrinoless $\beta \beta$ Decay. This international experiment is designed to answer one of the highest priority questions in fundamental physics. It consists of 1000 kg of Ge detectors enriched to more than 90% in the $^{76}$Ge isotope operated in a liquid argon active shield at a deep underground laboratory. By combining the lowest background levels with the best energy resolution in the field, LEGEND-1000 will perform a quasi-background-free search and can make an unambiguous discovery of neutrinoless double-beta decay with just a handful of counts at the decay $Q$ value. The experiment is designed to probe this decay with a 99.7%-CL discovery sensitivity in the $^{76}$Ge half-life of $1.3\times10^{28}$ years, corresponding to an effective Majorana mass upper limit in the range of 9-21 meV, to cover the inverted-ordering neutrino mass scale with 10 yr of live time

Warning, patrons ahead! A development assessment framework for public space for landscape architects drawing on lessons from the Festival City of Adelaide, Australia.

A deceptively simple and benign sign placed in a public park states, ‘Warning: You may find event equipment and patrons on the pathway’ (Figure T-2). The sign hints at the complexity and contradictions of public space and poses a curious question that continues to gain currency in multidisciplinary discourse: How public is public space? This thesis poses a further question by asking, Do temporary events pose a threat to public space? To answer both questions, the thesis draws on the historic trajectory of urban public space, culminating in an extensive appraisal of 20th century forms and programs. In doing so, the thesis examines definitions of ‘public space’ and ‘public’, and considers how a more rigorous understanding of these terms can inform the practice of landscape architecture. As a result, the thesis proposes a new definition of public space, focusing on the value of publicly accessible space. It also proposes a new typology of publics—the defined public, the appropriating public, the transitory public and the illegitimate public—to better understand perceived and actual threats to public space. To test these definitions, the thesis critically reviews existing assessment methods, techniques and tools, and their application in landscape architectural assessments. It asks if current approaches adequately depict the typology of publics and the diversity of private use. As a result, the thesis proposes an integrated approach termed the Design Assessment Framework as a guide for alternative design strategies and policy formation for publicly accessible landscapes. The framework measures the degree of ‘publicness’ in public space by comprehensively capturing and assessing public space elements. The perceived conflict between public space and private use is explored through 16 case study sites in Adelaide, Australia. The city is recognised internationally for its urban plan, which includes a generous provision of public space and it is celebrated for the many festivals and events held within the city. The thesis offers an important and timely counter point to the majority voice that laments the future of public space, concluding that publicness is a spectrum, not an absolute. It positions landscape architects in a pivotal role to influence the effective design of public space and create a richer place for publics to interact. The typology of publics and the Design Assessment Framework are presented as new tools for landscape architects to assess public spaces and implement a spectrum of inclusivity. Finally, the thesis argues that events are not a threat to the publicness of public space, and should instead be viewed as opportunities to bring the community together for social exchange. Without social exchange, the question of threats to the publicness of public space may be a moot point.Thesis (Ph.D.) -- University of Adelaide, School of Architecture and Built Environment, 202