Lightweight Face Relighting

In this paper we present a method to relight human faces in real time, using consumer-grade graphics cards even with limited 3D capabilities. We show how to render faces using a combination of a simple, hardware-accelerated parametric model simulating skin shading and a detail texture map, and provide robust procedures to estimate all the necessary parameters for a given face. Our model strikes a balance between the difficulty of realistic face rendering (given the very specific reflectance properties of skin) and the goal of real-time rendering with limited hardware capabilities. This is accomplished by automatically generating an optimal set of parameters for a simple rendering model. We offer a discussion of the issues in face rendering to discern the pros and cons of various rendering models and to generalize our approach to most of the current hardware constraints. We provide results demonstrating the usability of our approach and the improvements we introduce both in the performance and in the visual quality of the resulting faces

Perceptually-Driven Decision Theory for Interactive Realistic Rendering

this paper we introduce a new approach to realistic rendering at interactive rates on commodity graphics hardware. The approach uses efficient perceptual metrics within a decision theoretic framework to optimally order rendering operations, producing images of the highest visual quality within system constraints. We demonstrate the usefulness of this approach for various applications such as diffuse texture caching, environment map prioritization and radiosity mesh simplification. Although here we address the problem of realistic rendering at interactive rates, the perceptually-based decision theoretic methodology we introduce can be usefully applied in many areas of computer graphic

Interactive global illumination on the CPU

Computing realistic physically-based global illumination in real-time remains one of the major goals in the fields of rendering and visualisation; one that has not yet been achieved due to its inherent computational complexity. This thesis focuses on CPU-based interactive global illumination approaches with an aim to develop generalisable hardware-agnostic algorithms. Interactive ray tracing is reliant on spatial and cache coherency to achieve interactive rates which conflicts with needs of global illumination solutions which require a large number of incoherent secondary rays to be computed. Methods that reduce the total number of rays that need to be processed, such as Selective rendering, were investigated to determine how best they can be utilised. The impact that selective rendering has on interactive ray tracing was analysed and quantified and two novel global illumination algorithms were developed, with the structured methodology used presented as a framework. Adaptive Inter- leaved Sampling, is a generalisable approach that combines interleaved sampling with an adaptive approach, which uses efficient component-specific adaptive guidance methods to drive the computation. Results of up to 11 frames per second were demonstrated for multiple components including participating media. Temporal Instant Caching, is a caching scheme for accelerating the computation of diffuse interreflections to interactive rates. This approach achieved frame rates exceeding 9 frames per second for the majority of scenes. Validation of the results for both approaches showed little perceptual difference when comparing against a gold-standard path-traced image. Further research into caching led to the development of a new wait-free data access control mechanism for sharing the irradiance cache among multiple rendering threads on a shared memory parallel system. By not serialising accesses to the shared data structure the irradiance values were shared among all the threads without any overhead or contention, when reading and writing simultaneously. This new approach achieved efficiencies between 77% and 92% for 8 threads when calculating static images and animations. This work demonstrates that, due to the flexibility of the CPU, CPU-based algorithms remain a valid and competitive choice for achieving global illumination interactively, and an alternative to the generally brute-force GPU-centric algorithms

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

From Image-based Motion Analysis to Free-Viewpoint Video

The problems of capturing real-world scenes with cameras and automatically analyzing the visible motion have traditionally been in the focus of computer vision research. The photo-realistic rendition of dynamic real-world scenes, on the other hand, is a problem that has been investigated in the field of computer graphics. In this thesis, we demonstrate that the joint solution to all three of these problems enables the creation of powerful new tools that are benecial for both research disciplines. Analysis and rendition of real-world scenes with human actors are amongst the most challenging problems. In this thesis we present new algorithmic recipes to attack them. The dissertation consists of three parts: In part I, we present novel solutions to two fundamental problems of human motion analysis. Firstly, we demonstrate a novel hybrid approach for markerfree human motion capture from multiple video streams. Thereafter, a new algorithm for automatic non-intrusive estimation of kinematic body models of arbitrary moving subjects from video is detailed. In part II of the thesis, we demonstrate that a marker-free motion capture approach makes possible the model-based reconstruction of free-viewpoint videos of human actors from only a handful of video streams. The estimated 3D videos enable the photo-realistic real-time rendition of a dynamic scene from arbitrary novel viewpoints. Texture information from video is not only applied to generate a realistic surface appearance, but also to improve the precision of the motion estimation scheme. The commitment to a generic body model also allows us to reconstruct a time-varying reflectance description of an actor`s body surface which allows us to realistically render the free-viewpoint videos under arbitrary lighting conditions. A novel method to capture high-speed large scale motion using regular still cameras and the principle of multi-exposure photography is described in part III. The fundamental principles underlying the methods in this thesis are not only applicable to humans but to a much larger class of subjects. It is demonstrated that, in conjunction, our proposed algorithmic recipes serve as building blocks for the next generation of immersive 3D visual media.Die Entwicklung neuer Algorithmen zur optischen Erfassung und Analyse der Bewegung in dynamischen Szenen ist einer der Forschungsschwerpunkte in der computergestützten Bildverarbeitung. Während im maschinellen Bildverstehen das Augenmerk auf der Extraktion von Informationen liegt, konzentriert sich die Computergrafik auf das inverse Problem, die fotorealistische Darstellung bewegter Szenen. In jüngster Vergangenheit haben sich die beiden Disziplinen kontinuierlich angenähert, da es eine Vielzahl an herausfordernden wissenschaftlichen Fragestellungen gibt, die eine gemeinsame Lösung des Bilderfassungs-, des Bildanalyse- und des Bildsyntheseproblems verlangen. Zwei der schwierigsten Probleme, welche für Forscher aus beiden Disziplinen eine große Relevanz besitzen, sind die Analyse und die Synthese von dynamischen Szenen, in denen Menschen im Mittelpunkt stehen. Im Rahmen dieser Dissertation werden Verfahren vorgestellt, welche die optische Erfassung dieser Art von Szenen, die automatische Analyse der Bewegungen und die realistische neue Darstellung im Computer erlauben. Es wid deutlich werden, dass eine Integration von Algorithmen zur Lösung dieser drei Probleme in ein Gesamtsystem die Erzeugung völlig neuartiger dreidimensionaler Darstellungen von Menschen in Bewegung ermöglicht. Die Dissertation ist in drei Teile gegliedert: Teil I beginnt mit der Beschreibung des Entwurfs und des Baus eines Studios zur zeitsynchronen Erfassung mehrerer Videobildströme. Die im Studio aufgezeichneten Multivideosequenzen dienen als Eingabedaten für die im Rahmen dieser Dissertation entwickelten videogestützten Bewegunsanalyseverfahren und die Algorithmen zur Erzeugung dreidimensionaler Videos. Im Anschluß daran werden zwei neu entwickelte Verfahren vorgestellt, die Antworten auf zwei fundamentale Fragen in der optischen Erfassung menschlicher Bewegung geben, die Messung von Bewegungsparametern und die Erzeugung von kinematischen Skelettmodellen. Das erste Verfahren ist ein hybrider Algorithmus zur markierungslosen optischen Messung von Bewegunsgparametern aus Multivideodaten. Der Verzicht auf optische Markierungen wird dadurch ermöglicht, dass zur Bewegungsanalyse sowohl aus den Bilddaten rekonstruierte Volumenmodelle als auch leicht zu erfassende Körpermerkmale verwendet werden. Das zweite Verfahren dient der automatischen Rekonstruktion eines kinematischen Skelettmodells anhand von Multivideodaten. Der Algorithmus benötigt weder optischen Markierungen in der Szene noch a priori Informationen über die Körperstruktur, und ist in gleicher Form auf Menschen, Tiere und Objekte anwendbar. Das Thema das zweiten Teils dieser Arbeit ist ein modellbasiertes Verfahrenzur Rekonstruktion dreidimensionaler Videos von Menschen in Bewegung aus nur wenigen zeitsynchronen Videoströmen. Der Betrachter kann die errechneten 3D Videos auf einem Computer in Echtzeit abspielen und dabei interaktiv einen beliebigen virtuellen Blickpunkt auf die Geschehnisse einnehmen. Im Zentrum unseres Ansatzes steht ein silhouettenbasierter Analyse-durch-Synthese Algorithmus, der es ermöglicht, ohne optische Markierungen sowohl die Form als auch die Bewegung eines Menschen zu erfassen. Durch die Berechnung zeitveränderlicher Oberächentexturen aus den Videodaten ist gewährleistet, dass eine Person aus jedem beliebigen Blickwinkel ein fotorealistisches Erscheinungsbild besitzt. In einer ersten algorithmischen Erweiterung wird gezeigt, dass die Texturinformation auch zur Verbesserung der Genauigkeit der Bewegunsgssch ätzung eingesetzt werden kann. Zudem ist es durch die Verwendung eines generischen Körpermodells möglich, nicht nur dynamische Texturen sondern sogar dynamische Reektionseigenschaften der Körperoberäche zu messen. Unser Reektionsmodell besteht aus einer parametrischen BRDF für jeden Texel und einer dynamischen Normalenkarte für die gesamte Körperoberäche. Auf diese Weise können 3D Videos auch unter völlig neuen simulierten Beleuchtungsbedingungen realistisch wiedergegeben werden. Teil III dieser Arbeit beschreibt ein neuartiges Verfahren zur optischen Messung sehr schneller Bewegungen. Bisher erforderten optische Aufnahmen von Hochgeschwindigkeitsbewegungen sehr teure Spezialkameras mit hohen Bildraten. Im Gegensatz dazu verwendet die hier beschriebene Methode einfache Digitalfotokameras und das Prinzip der Multiblitzfotograe. Es wird gezeigt, dass mit Hilfe dieses Verfahrens sowohl die sehr schnelle artikulierte Handbewegung des Werfers als auch die Flugparameter des Balls während eines Baseballpitches gemessen werden können. Die hochgenau erfaßten Parameter ermöglichen es, die gemessene Bewegung in völlig neuer Weise im Computer zu visualisieren. Obgleich die in dieser Dissertation vorgestellten Verfahren vornehmlich der Analyse und Darstellung menschlicher Bewegungen dienen, sind die grundlegenden Prinzipien auch auf viele anderen Szenen anwendbar. Jeder der beschriebenen Algorithmen löst zwar in erster Linie ein bestimmtes Teilproblem, aber in Ihrer Gesamtheit können die Verfahren als Bausteine verstanden werden, welche die nächste Generation interaktiver dreidimensionaler Medien ermöglichen werden

Development of the components of a low cost, distributed facial virtual conferencing system

This thesis investigates the development of a low cost, component based facial virtual conferencing system. The design is decomposed into an encoding phase and a decoding phase, which communicate with each other via a network connection. The encoding phase is composed of three components: model acquisition (which handles avatar generation), pose estimation and expression analysis. Audio is not considered part of the encoding and decoding process, and as such is not evaluated. The model acquisition component is implemented using a visual hull reconstruction algorithm that is able to reconstruct real-world objects using only sets of images of the object as input. The object to be reconstructed is assumed to lie in a bounding volume of voxels. The reconstruction process involves the following stages: - Space carving for basic shape extraction; - Isosurface extraction to remove voxels not part of the surface of the reconstruction; - Mesh connection to generate a closed, connected polyhedral mesh; - Texture generation. Texturing is achieved by Gouraud shading the reconstruction with a vertex colour map; - Mesh decimation to simplify the object. The original algorithm has complexity O(n), but suffers from an inability to reconstruct concave surfaces that do not form part of the visual hull of the object. A novel extension to this algorithm based on Normalised Cross Correlation (NCC) is proposed to overcome this problem. An extension to speed up traditional NCC evaluations is proposed which reduces the NCC search space from a 2D search problem down to a single evaluation. Pose estimation and expression analysis are performed by tracking six fiducial points on the face of a subject. A tracking algorithm is developed that uses Normalised Cross Correlation to facilitate robust tracking that is invariant to changing lighting conditions, rotations and scaling. Pose estimation involves the recovery of the head position and orientation through the tracking of the triangle formed by the subject's eyebrows and nose tip. A rule-based evaluation of points that are tracked around the subject's mouth forms the basis of the expression analysis. A user assisted feedback loop and caching mechanism is used to overcome tracking errors due to fast motion or occlusions. The NCC tracker is shown to achieve a tracking performance of 10 fps when tracking the six fiducial points. The decoding phase is divided into 3 tasks, namely: avatar movement, expression generation and expression management. Avatar movement is implemented using the base VR system. Expression generation is facilitated using a Vertex Interpolation Deformation method. A weighting system is proposed for expression management. Its function is to gradually transform from one expression to the next. The use of the vertex interpolation method allows real-time deformations of the avatar representation, achieving 16 fps when applied to a model consisting of 7500 vertices. An Expression Parameter Lookup Table (EPLT) facilitates an independent mapping between the two phases. It defines a list of generic expressions that are known to the system and associates an Expression ID with each one. For each generic expression, it relates the expression analysis rules for any subject with the expression generation parameters for any avatar model. The result is that facial expression replication between any subject and avatar combination can be performed by transferring only the Expression ID from the encoder application to the decoder application. The ideas developed in the thesis are demonstrated in an implementation using the CoRgi Virtual Reality system. It is shown that the virtual-conferencing application based on this design requires only a bandwidth of 2 Kbps.Adobe Acrobat Pro 9.4.6Adobe Acrobat 9.46 Paper Capture Plug-i

Virtual light fields for global illumination in computer graphics

This thesis presents novel techniques for the generation and real-time rendering of globally illuminated environments with surfaces described by arbitrary materials. Real-time rendering of globally illuminated virtual environments has for a long time been an elusive goal. Many techniques have been developed which can compute still images with full global illumination and this is still an area of active flourishing research. Other techniques have only dealt with certain aspects of global illumination in order to speed up computation and thus rendering. These include radiosity, ray-tracing and hybrid methods. Radiosity due to its view independent nature can easily be rendered in real-time after pre-computing and storing the energy equilibrium. Ray-tracing however is view-dependent and requires substantial computational resources in order to run in real-time. Attempts at providing full global illumination at interactive rates include caching methods, fast rendering from photon maps, light fields, brute force ray-tracing and GPU accelerated methods. Currently, these methods either only apply to special cases, are incomplete exhibiting poor image quality and/or scale badly such that only modest scenes can be rendered in real-time with current hardware. The techniques developed in this thesis extend upon earlier research and provide a novel, comprehensive framework for storing global illumination in a data structure - the Virtual Light Field - that is suitable for real-time rendering. The techniques trade off rapid rendering for memory usage and precompute time. The main weaknesses of the VLF method are targeted in this thesis. It is the expensive pre-compute stage with best-case O(N^2) performance, where N is the number of faces, which make the light propagation unpractical for all but simple scenes. This is analysed and greatly superior alternatives are presented and evaluated in terms of efficiency and error. Several orders of magnitude improvement in computational efficiency is achieved over the original VLF method. A novel propagation algorithm running entirely on the Graphics Processing Unit (GPU) is presented. It is incremental in that it can resolve visibility along a set of parallel rays in O(N) time and can produce a virtual light field for a moderately complex scene (tens of thousands of faces), with complex illumination stored in millions of elements, in minutes and for simple scenes in seconds. It is approximate but gracefully converges to a correct solution; a linear increase in resolution results in a linear increase in computation time. Finally a GPU rendering technique is presented which can render from Virtual Light Fields at real-time frame rates in high resolution VR presentation devices such as the CAVETM