Constant-Cost Spatio-Angular Prefiltering of Glinty Appearance Using Tensor Decomposition

International audienceThe detailed glinty appearance from complex surface microstructures enhances the level of realism but is both - and time-consuming to render, especially when viewed from far away (large spatial coverage) and/or illuminated by area lights (large angular coverage). In this article, we formulate the glinty appearance rendering process as a spatio-angular range query problem of the Normal Distribution Functions (NDFs), and introduce an efficient spatio-angular prefiltering solution to it. We start by exhaustively precomputing all possible NDFs with differently sized positional coverages. Then we compress the precomputed data using tensor rank decomposition, which enables accurate and fast angular range queries. With our spatio-angular prefiltering scheme, we are able to solve both the storage and performance issues at the same time, leading to efficient rendering of glinty appearance with both constant storage and constant performance, regardless of the range of spatio-angular queries. Finally, we demonstrate that our method easily applies to practical rendering applications that were traditionally considered difficult. For example, efficient bidirectional reflection distribution function evaluation accurate NDF importance sampling, fast global illumination between glinty objects, high-frequency preserving rendering with environment lighting, and tile-based synthesis of glinty appearance

Semi-transparent textures based on opaque and transparent texels augmented with a thickness

Le rendu en temps réel repose sur des compromis entre la performance et le réalisme. Un de ces compromis est de représenter des matériaux plus minces tels que les tissus comme étant infiniment minces pour économiser mémoire et temps de rendu. Par contre, cette perte de dimension prive la surface de propriétés essentielles à certains effets visuels. Dans ce mémoire, nous présentons une méthode pour simuler les effets de l’épaisseur sur des surfaces semi-transparentes en utilisant des textures composées de texels opaques et transparents. Nous analysons les trous formés par les texels transparents et nous conservons de l’information sur les contours des trous dans une structure hiérarchique compatible avec la méthode de filtrage de textures par MIP map. Nous dérivons des équations représentant la proportion de lumière passant dans un trou avec des murs intérieurs en fonction de l’angle incident des rayons de lumière. Nous combinons ces équations avec l’information conservée pour calculer un terme de transparence à différents niveaux de détail en temps réel.Real-time rendering is built upon compromises between performance and realism. One such compromise is to represent thinner materials like textile as infinitely thin in order to save on memory and rendering time. However, this loss of dimension robs the surface of properties key to some visual effects. In this thesis, we present a method to simulate the effects of thickness on semi-transparent surfaces using textures consisting of opaque and transparent texels. We analyze holes formed by transparent texels and store information about the contours of the holes in a hierarchical structure compatible with the filtering method of MIP mapping. We derive equations representing the proportion of light passing through a hole as a function of the incident angle of light. The proportions of texel top, texel side wall, and hole are computed accurately. We combine these equations with the information stored to compute a transparency term at different levels of detail in real time

Efektivní a expresivní mikrofasetové modely

Název: Efektivní a expresivní mikrofasetové modely Autor: Asen Atanasov Katedra: Katedra softwaru a výuky informatiky Vedoucí: doc. Dr. Alexander Wilkie, Katedra softwaru a výuky informatiky Abstrakt: V realistickém modelování vzhledu jsou drsné povrchy, které mají mikroskopické detaily, popsány pomocí tzv. mikrofazetových modelů. Mezi tyto modely patří analytické modely, které statisticky definují fyzikálně založený mikropovrch. Takové modely jsou široce používány v praxi, protože jsou nenáročné na výpočet a nabízejí značnou flexibilitu ve vzhledu, který s nimi lze docílit. Tyto modely mohou být rozšířené o viditelné povrchové prvky prostřednictvím normálové mapy. Stále však existují oblasti, ve kterých lze tento obecný typ modelu vylepšit: důležité funkce, jako je řízení anizotropie, někdy postrádají analytická řešení a účinné vykreslování normálových map vyžaduje přesné a obecné filtrovací algoritmy. Posunujeme předchozí práci v následujících oblastech: odvodíme analytické anizotropní modely, přeformulujeme problém filtrování a navrhneme efektivní filtrační algoritmus založený na nové datové struktuře filtračních dat. Konkrétně odvodíme obecný výsledek v mikrofazetové teorii: na základě libovolného mikropovrchu definovaného pomocí standardní mikrofazetové statistiky ukážeme, jak konstruovat statistiku...Title: Efficient and Expressive Microfacet Models Author: Asen Atanasov Department: Department of Software and Computer Science Education Supervisor: doc. Dr. Alexander Wilkie, Department of Software and Computer Science Education Abstract: In realistic appearance modeling, rough surfaces that have micro- scopic details are described using so-called microfacet models. These include analytical models that statistically define a physically-based microsurface. Such models are extensively used in practice because they are inexpensive to compute and offer considerable flexibility in terms of appearance control. Also, small but visible surface features can easily be added to them through the use of a normal map. However, there are still areas in which this general type of model can be improved: important features like anisotropy control sometimes lack analytic solutions, and the efficient rendering of normal maps requires accurate and general filtering algorithms. We advance the state of the art with regard to such models in these areas: we derive analytic anisotropic models, reformulate the filtering problem and propose an efficient filtering algorithm based on a novel filtering data structure. Specifically, we derive a general result in microfacet theory: given an arbitrary microsurface defined via standard...Katedra softwaru a výuky informatikyDepartment of Software and Computer Science EducationMatematicko-fyzikální fakultaFaculty of Mathematics and Physic

직접 볼륨 렌더링의 전이 함수 설계에 관한 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2017. 2. 신영길.Although direct volume rendering (DVR) has become a commodity, the design of transfer functions still a challenge. Transfer functions which map data values to optical properties (i.e., colors and opacities) highlight features of interests as well as hide unimportant regions, dramatically impacting on the quality of the visualization. Therefore, for the effective rendering of interesting features, the design of transfer functions is very important and challenging task. Furthermore, manipulation of these transfer functions is tedious and time-consuming task. In this paper, we propose a 3D spatial field for accurately identifying and visually distinguishing interesting features as well as a mechanism for data exploration using multi-dimensional transfer function. First, we introduce a 3D spatial field for the effective visualization of constricted tubular structures, called as a stenosis map which stores the degree of constriction at each voxel. Constrictions within tubular structures are quantified by using newly proposed measures (i.e., line similarity measure and constriction measure) based on the localized structure analysis, and classified with a proposed transfer function mapping the degree of constriction to color and opacity. We show the application results of our method to the visualization of coronary artery stenoses. We present performance evaluations using twenty-eight clinical datasets, demonstrating high accuracy and efficacy of our proposed method. Second, we propose a new multi-dimensional transfer function which incorporates texture features calculated from statistically homogeneous regions. This approach employs parallel coordinates to provide an intuitive interface for exploring a new multi-dimensional transfer function space. Three specific ways to use a new transfer function based on parallel coordinates enables the effective exploration of large and complex datasets. We present a mechanism for data exploration with a new transfer function space, demonstrating the practical efficacy of our proposed method. Through a study on transfer function design for DVR, we propose two useful approaches. First method to saliently visualize the constrictions within tubular structures and interactively adjust the visual appearance of the constrictions delivers a substantial aid in radiologic practice. Furthermore, second method to classify objects with our intuitive interface utilizing parallel coordinates proves to be a powerful tool for complex data exploration.Chapter 1 Introduction 1 1.1 Background 1 1.1.1 Volume rendering 1 1.1.2 Computer-aided diagnosis 3 1.1.3 Parallel coordinates 5 1.2 Problem statement 8 1.3 Main contribution 12 1.4 Organization of dissertation 16 Chapter 2 Related Work 17 2.1 Transfer function 17 2.1.1 Transfer functions based on spatial characteristics 17 2.1.2 Opacity modulation techniques 20 2.1.3 Multi-dimensional transfer functions 22 2.1.4 Manipulation mechanism for transfer functions 25 2.2 Coronary artery stenosis 28 2.3 Parallel coordinates 32 Chapter 3 Volume Visualization of Constricted Tubular Structures 36 3.1 Overview 36 3.2 Localized structure analysis 37 3.3 Stenosis map 39 3.3.1 Overview 39 3.3.2 Detection of tubular structures 40 3.3.3 Stenosis map computation 49 3.4 Stenosis-based classification 52 3.4.1 Overview 52 3.4.2 Constriction-encoded volume rendering 52 3.4.3 Opacity modulation based on constriction 54 3.5 GPU implementation 57 3.6 Experimental results 59 3.6.1 Clinical data preparation 59 3.6.2 Qualitative evaluation 60 3.6.3 Quantitative evaluation 63 3.6.4 Comparison with previous methods 66 3.6.5 Parameter study 69 Chapter 4 Interactive Multi-Dimensional Transfer Function Using Adaptive Block Based Feature Analysis 73 4.1 Overview 73 4.2 Extraction of statistical features 74 4.3 Extraction of texture features 78 4.4 Multi-dimensional transfer function design using parallel coordinates 81 4.5 Experimental results 86 Chapter 5 Conclusion 90 Bibliography 92 초 록 107Docto

Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering

The rendering scheme in neural radiance field (NeRF) is effective in rendering a pixel by casting a ray into the scene. However, NeRF yields blurred rendering results when the training images are captured at non-uniform scales, and produces aliasing artifacts if the test images are taken in distant views. To address this issue, Mip-NeRF proposes a multiscale representation as a conical frustum to encode scale information. Nevertheless, this approach is only suitable for offline rendering since it relies on integrated positional encoding (IPE) to query a multilayer perceptron (MLP). To overcome this limitation, we propose mip voxel grids (Mip-VoG), an explicit multiscale representation with a deferred architecture for real-time anti-aliasing rendering. Our approach includes a density Mip-VoG for scene geometry and a feature Mip-VoG with a small MLP for view-dependent color. Mip-VoG encodes scene scale using the level of detail (LOD) derived from ray differentials and uses quadrilinear interpolation to map a queried 3D location to its features and density from two neighboring downsampled voxel grids. To our knowledge, our approach is the first to offer multiscale training and real-time anti-aliasing rendering simultaneously. We conducted experiments on multiscale datasets, and the results show that our approach outperforms state-of-the-art real-time rendering baselines

Towards Predictive Rendering in Virtual Reality

The strive for generating predictive images, i.e., images representing radiometrically correct renditions of reality, has been a longstanding problem in computer graphics. The exactness of such images is extremely important for Virtual Reality applications like Virtual Prototyping, where users need to make decisions impacting large investments based on the simulated images. Unfortunately, generation of predictive imagery is still an unsolved problem due to manifold reasons, especially if real-time restrictions apply. First, existing scenes used for rendering are not modeled accurately enough to create predictive images. Second, even with huge computational efforts existing rendering algorithms are not able to produce radiometrically correct images. Third, current display devices need to convert rendered images into some low-dimensional color space, which prohibits display of radiometrically correct images. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented and their limitations are pointed out. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering. A special focus of this thesis lays on real-time generation of predictive images using bidirectional texture functions (BTFs), i.e., very accurate representations for spatially varying surface materials. The techniques proposed by this thesis enable efficient handling of BTFs by compressing the huge amount of data contained in this material representation, applying them to geometric surfaces using texture and BTF synthesis techniques, and rendering BTF covered objects in real-time. Further approaches proposed in this thesis target inclusion of real-time global illumination effects or more efficient rendering using novel level-of-detail representations for geometric objects. Finally, this thesis assesses the rendering quality achievable with BTF materials, indicating a significant increase in realism but also confirming the remainder of problems to be solved to achieve truly predictive image generation

Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Festschrift zum 60. Geburtstag von Wolfgang Strasser

Die vorliegende Festschrift ist Prof. Dr.-Ing. Dr.-Ing. E.h. Wolfgang Straßer zu seinem 60. Geburtstag gewidmet. Eine Reihe von Wissenschaftlern auf dem Gebiet der Computergraphik, die alle aus der "Tübinger Schule" stammen, haben - zum Teil zusammen mit ihren Schülern - Aufsätze zu dieser Schrift beigetragen. Die Beiträge reichen von der Objektrekonstruktion aus Bildmerkmalen über die physikalische Simulation bis hin zum Rendering und der Visualisierung, vom theoretisch ausgerichteten Aufsatz bis zur praktischen gegenwärtigen und zukünftigen Anwendung. Diese thematische Buntheit verdeutlicht auf anschauliche Weise die Breite und Vielfalt der Wissenschaft von der Computergraphik, wie sie am Lehrstuhl Straßer in Tübingen betrieben wird. Schon allein an der Tatsache, daß im Bereich der Computergraphik zehn Professoren an Universitäten und Fachhochschulen aus Tübingen kommen, zeigt sich der prägende Einfluß Professor Straßers auf die Computergraphiklandschaft in Deutschland. Daß sich darunter mehrere Physiker und Mathematiker befinden, die in Tübingen für dieses Fach gewonnen werden konnten, ist vor allem seinem Engagement und seiner Ausstrahlung zu verdanken. Neben der Hochachtung vor den wissenschaftlichen Leistungen von Professor Straßer hat sicherlich seine Persönlichkeit einen entscheidenden Anteil an der spontanten Bereischaft der Autoren, zu dieser Festschrift beizutragen. Mit außergewöhnlich großem persönlichen Einsatz fördert er Studenten, Doktoranden und Habilitanden, vermittelt aus seinen reichen internationalen Beziehungen Forschungskontakte und schafft so außerordentlich gute Voraussetzungen für selbständige wissenschafliche Arbeit. Die Autoren wollen mit ihrem Beitrag Wolfgang Straßer eine Freude bereiten und verbinden mit ihrem Dank den Wunsch, auch weiterhin an seinem fachlich wie menschlich reichen und bereichernden Wirken teilhaben zu dürfen

Signal processing with Fourier analysis, novel algorithms and applications

Fourier analysis is the study of the way general functions may be represented or approximated by sums of simpler trigonometric functions, also analogously known as sinusoidal modeling. The original idea of Fourier had a profound impact on mathematical analysis, physics and engineering because it diagonalizes time-invariant convolution operators. In the past signal processing was a topic that stayed almost exclusively in electrical engineering, where only the experts could cancel noise, compress and reconstruct signals. Nowadays it is almost ubiquitous, as everyone now deals with modern digital signals. Medical imaging, wireless communications and power systems of the future will experience more data processing conditions and wider range of applications requirements than the systems of today. Such systems will require more powerful, efficient and flexible signal processing algorithms that are well designed to handle such needs. No matter how advanced our hardware technology becomes we will still need intelligent and efficient algorithms to address the growing demands in signal processing. In this thesis, we investigate novel techniques to solve a suite of four fundamental problems in signal processing that have a wide range of applications. The relevant equations, literature of signal processing applications, analysis and final numerical algorithms/methods to solve them using Fourier analysis are discussed for different applications in the electrical engineering/computer science. The first four chapters cover the following topics of central importance in the field of signal processing: • Fast Phasor Estimation using Adaptive Signal Processing (Chapter 2) • Frequency Estimation from Nonuniform Samples (Chapter 3) • 2D Polar and 3D Spherical Polar Nonuniform Discrete Fourier Transform (Chapter 4) • Robust 3D registration using Spherical Polar Discrete Fourier Transform and Spherical Harmonics (Chapter 5) Even though each of these four methods discussed may seem completely disparate, the underlying motivation for more efficient processing by exploiting the Fourier domain signal structure remains the same. The main contribution of this thesis is the innovation in the analysis, synthesis, discretization of certain well known problems like phasor estimation, frequency estimation, computations of a particular non-uniform Fourier transform and signal registration on the transformed domain. We conduct propositions and evaluations of certain applications relevant algorithms such as, frequency estimation algorithm using non-uniform sampling, polar and spherical polar Fourier transform. The techniques proposed are also useful in the field of computer vision and medical imaging. From a practical perspective, the proposed algorithms are shown to improve the existing solutions in the respective fields where they are applied/evaluated. The formulation and final proposition is shown to have a variety of benefits. Future work with potentials in medical imaging, directional wavelets, volume rendering, video/3D object classifications, high dimensional registration are also discussed in the final chapter. Finally, in the spirit of reproducible research we release the implementation of these algorithms to the public using Github