Processing mesh animations: from static to dynamic geometry and back

Static triangle meshes are the representation of choice for artificial objects, as well as for digital replicas of real objects. They have proven themselves to be a solid foundation for further processing. Although triangle meshes are handy in general, it may seem that their discrete approximation of reality is a downside. But in fact, the opposite is true. The approximation of the real object's shape remains the same, even if we willfully change the vertex positions in the mesh, which allows us to optimize it in this way. Due to modern acquisition methods, such a step is always beneficial, often even required, prior to further processing of the acquired triangle mesh. Therefore, we present a general framework for optimizing surface meshes with respect to various target criteria. Because of the simplicity and efficiency of the setup it can be adapted to a variety of applications. Although this framework was initially designed for single static meshes, the application to a set of meshes is straightforward. For example, we convert a set of meshes into compatible ones and use them as basis for creating dynamic geometry. Consequently, we propose an interpolation method which is able to produce visually plausible interpolation results, even if the compatible input meshes differ by large rotations. The method can be applied to any number of input vertex configurations and due to the utilization of a hierarchical scheme, the approach is fast and can be used for very large meshes. Furthermore, we consider the opposite direction. Given an animation sequence, we propose a pre-processing algorithm that considerably reduces the number of meshes required to describe the sequence, thus yielding a compact representation. Our method is based on a clustering and classification approach, which can be utilized to automatically find the most prominent meshes of the sequence. The original meshes can then be expressed as linear combinations of these few representative meshes with only small approximation errors. Finally, we investigate the shape space spanned by those few meshes and show how to apply different interpolation schemes to create other shape spaces, which are not based on vertex coordinates. We conclude with a careful analysis of these shape spaces and their usability for a compact representation of an animation sequence

Analysis and Manipulation of Repetitive Structures of Varying Shape

Self-similarity and repetitions are ubiquitous in man-made and natural objects. Such structural regularities often relate to form, function, aesthetics, and design considerations. Discovering structural redundancies along with their dominant variations from 3D geometry not only allows us to better understand the underlying objects, but is also beneficial for several geometry processing tasks including compact representation, shape completion, and intuitive shape manipulation. To identify these repetitions, we present a novel detection algorithm based on analyzing a graph of surface features. We combine general feature detection schemes with a RANSAC-based randomized subgraph searching algorithm in order to reliably detect recurring patterns of locally unique structures. A subsequent segmentation step based on a simultaneous region growing is applied to verify that the actual data supports the patterns detected in the feature graphs. We introduce our graph based detection algorithm on the example of rigid repetitive structure detection. Then we extend the approach to allow more general deformations between the detected parts. We introduce subspace symmetries whereby we characterize similarity by requiring the set of repeating structures to form a low dimensional shape space. We discover these structures based on detecting linearly correlated correspondences among graphs of invariant features. The found symmetries along with the modeled variations are useful for a variety of applications including non-local and non-rigid denoising. Employing subspace symmetries for shape editing, we introduce a morphable part model for smart shape manipulation. The input geometry is converted to an assembly of deformable parts with appropriate boundary conditions. Our method uses self-similarities from a single model or corresponding parts of shape collections as training input and allows the user also to reassemble the identified parts in new configurations, thus exploiting both the discrete and continuous learned variations while ensuring appropriate boundary conditions across part boundaries. We obtain an interactive yet intuitive shape deformation framework producing realistic deformations on classes of objects that are difficult to edit using repetition-unaware deformation techniques

Enriquecendo animações em quadros-chaves espaciais com movimento capturado

While motion capture (mocap) achieves realistic character animation at great cost, keyframing is capable of producing less realistic but more controllable animations. In this work we show how to combine the Spatial Keyframing (SK) Framework of IGARASHI et al. [1] and multidimensional projection techniques to reuse mocap data in several ways. Additionally, we show that multidimensional projection also can be used for visualization and motion analysis. We also propose a method for mocap compaction with the help of SK’s pose reconstruction (backprojection) algorithm. Finally, we present a novel multidimensional projection optimization technique that significantly enhances SK-based reconstruction and can also be applied to other contexts where a backprojection algorithm is available.Movimento capturado (mocap) produz animacões de personagens com grande realismo mas a um custo alto. A utilização de quadros-chave torna mais difícil um resultado com realismo mas torna mais fácil o controle da animacão. Neste trabalho, mostramos como combinar o uso de quadros-chaves espaciais – Spatial Keyframing (SK) Framework – de IGARASHI et al. [1] e técnicas de projeção multidimensional para reutilizar dados de movimento capturado de várias maneiras. Mostramos também como projeções multidimensionais podem ser utilizadas para visualização e análise de movimento. Propomos um método de compactação de dados de mocap utilizando a reconstrução de poses por meio do algoritmo de quadros-chaves espaciais. Também apresentamos uma técnica de otimização para as projeções multidimensionais que melhora a reconstrução do movimento e que pode ser aplicada em outros casos onde um algoritmo de retroprojecão esteja dad

Realistic Visualization of Animated Virtual Cloth

Photo-realistic rendering of real-world objects is a broad research area with applications in various different areas, such as computer generated films, entertainment, e-commerce and so on. Within photo-realistic rendering, the rendering of cloth is a subarea which involves many important aspects, ranging from material surface reflection properties and macroscopic self-shadowing to animation sequence generation and compression. In this thesis, besides an introduction to the topic plus a broad overview of related work, different methods to handle major aspects of cloth rendering are described. Material surface reflection properties play an important part to reproduce the look & feel of materials, that is, to identify a material only by looking at it. The BTF (bidirectional texture function), as a function of viewing and illumination direction, is an appropriate representation of reflection properties. It captures effects caused by the mesostructure of a surface, like roughness, self-shadowing, occlusion, inter-reflections, subsurface scattering and color bleeding. Unfortunately a BTF data set of a material consists of hundreds to thousands of images, which exceeds current memory size of personal computers by far. This work describes the first usable method to efficiently compress and decompress a BTF data for rendering at interactive to real-time frame rates. It is based on PCA (principal component analysis) of the BTF data set. While preserving the important visual aspects of the BTF, the achieved compression rates allow the storage of several different data sets in main memory of consumer hardware, while maintaining a high rendering quality. Correct handling of complex illumination conditions plays another key role for the realistic appearance of cloth. Therefore, an upgrade of the BTF compression and rendering algorithm is described, which allows the support of distant direct HDR (high-dynamic-range) illumination stored in environment maps. To further enhance the appearance, macroscopic self-shadowing has to be taken into account. For the visualization of folds and the life-like 3D impression, these kind of shadows are absolutely necessary. This work describes two methods to compute these shadows. The first is seamlessly integrated into the illumination part of the rendering algorithm and optimized for static meshes. Furthermore, another method is proposed, which allows the handling of dynamic objects. It uses hardware-accelerated occlusion queries for the visibility determination. In contrast to other algorithms, the presented algorithm, despite its simplicity, is fast and produces less artifacts than other methods. As a plus, it incorporates changeable distant direct high-dynamic-range illumination. The human perception system is the main target of any computer graphics application and can also be treated as part of the rendering pipeline. Therefore, optimization of the rendering itself can be achieved by analyzing human perception of certain visual aspects in the image. As a part of this thesis, an experiment is introduced that evaluates human shadow perception to speedup shadow rendering and provides optimization approaches. Another subarea of cloth visualization in computer graphics is the animation of the cloth and avatars for presentations. This work also describes two new methods for automatic generation and compression of animation sequences. The first method to generate completely new, customizable animation sequences, is based on the concept of finding similarities in animation frames of a given basis sequence. Identifying these similarities allows jumps within the basis sequence to generate endless new sequences. Transmission of any animated 3D data over bandwidth-limited channels, like extended networks or to less powerful clients requires efficient compression schemes. The second method included in this thesis in the animation field is a geometry data compression scheme. Similar to the BTF compression, it uses PCA in combination with clustering algorithms to segment similar moving parts of the animated objects to achieve high compression rates in combination with a very exact reconstruction quality.Realistische Visualisierung von animierter virtueller Kleidung Das photorealistisches Rendering realer Gegenstände ist ein weites Forschungsfeld und hat Anwendungen in vielen Bereichen. Dazu zählen Computer generierte Filme (CGI), die Unterhaltungsindustrie und E-Commerce. Innerhalb dieses Forschungsbereiches ist das Rendern von photorealistischer Kleidung ein wichtiger Bestandteil. Hier reichen die wichtigen Aspekte, die es zu berücksichtigen gilt, von optischen Materialeigenschaften über makroskopische Selbstabschattung bis zur Animationsgenerierung und -kompression. In dieser Arbeit wird, neben der Einführung in das Thema, ein weiter Überblick über ähnlich gelagerte Arbeiten gegeben. Der Schwerpunkt der Arbeit liegt auf den wichtigen Aspekten der virtuellen Kleidungsvisualisierung, die oben beschrieben wurden. Die optischen Reflektionseigenschaften von Materialoberflächen spielen eine wichtige Rolle, um das so genannte look & feel von Materialien zu charakterisieren. Hierbei kann ein Material vom Nutzer identifiziert werden, ohne dass er es direkt anfassen muss. Die BTF (bidirektionale Texturfunktion)ist eine Funktion die abhängig von der Blick- und Beleuchtungsrichtung ist. Daher ist sie eine angemessene Repräsentation von Reflektionseigenschaften. Sie enthält Effekte wie Rauheit, Selbstabschattungen, Verdeckungen, Interreflektionen, Streuung und Farbbluten, die durch die Mesostruktur der Oberfläche hervorgerufen werden. Leider besteht ein BTF Datensatz eines Materials aus hunderten oder tausenden von Bildern und sprengt damit herkömmliche Hauptspeicher in Computern bei weitem. Diese Arbeit beschreibt die erste praktikable Methode, um BTF Daten effizient zu komprimieren, zu speichern und für Echtzeitanwendungen zum Visualisieren wieder zu dekomprimieren. Die Methode basiert auf der Principal Component Analysis (PCA), die Daten nach Signifikanz ordnet. Während die PCA die entscheidenen visuellen Aspekte der BTF erhält, können mit ihrer Hilfe Kompressionsraten erzielt werden, die es erlauben mehrere BTF Materialien im Hauptspeicher eines Consumer PC zu verwalten. Dies erlaubt ein High-Quality Rendering. Korrektes Verwenden von komplexen Beleuchtungssituationen spielt eine weitere, wichtige Rolle, um Kleidung realistisch erscheinen zu lassen. Daher wird zudem eine Erweiterung des BTF Kompressions- und Renderingalgorithmuses erläutert, die den Einsatz von High-Dynamic Range (HDR) Beleuchtung erlaubt, die in environment maps gespeichert wird. Um die realistische Erscheinung der Kleidung weiter zu unterstützen, muss die makroskopische Selbstabschattung integriert werden. Für die Visualisierung von Falten und den lebensechten 3D Eindruck ist diese Art von Schatten absolut notwendig. Diese Arbeit beschreibt daher auch zwei Methoden, diese Schatten schnell und effizient zu berechnen. Die erste ist nahtlos in den Beleuchtungspart des obigen BTF Renderingalgorithmuses integriert und für statische Geometrien optimiert. Die zweite Methode behandelt dynamische Objekte. Dazu werden hardwarebeschleunigte Occlusion Queries verwendet, um die Sichtbarkeitsberechnung durchzuführen. Diese Methode ist einerseits simpel und leicht zu implementieren, anderseits ist sie schnell und produziert weniger Artefakte, als vergleichbare Methoden. Zusätzlich ist die Verwendung von veränderbarer, entfernter HDR Beleuchtung integriert. Das menschliche Wahrnehmungssystem ist das eigentliche Ziel jeglicher Anwendung in der Computergrafik und kann daher selbst als Teil einer erweiterten Rendering Pipeline gesehen werden. Daher kann das Rendering selbst optimiert werden, wenn man die menschliche Wahrnehmung verschiedener visueller Aspekte der berechneten Bilder analysiert. Teil der vorliegenden Arbeit ist die Beschreibung eines Experimentes, das menschliche Schattenwahrnehmung untersucht, um das Rendern der Schatten zu beschleunigen. Ein weiteres Teilgebiet der Kleidungsvisualisierung in der Computergrafik ist die Animation der Kleidung und von Avataren für Präsentationen. Diese Arbeit beschreibt zwei neue Methoden auf diesem Teilgebiet. Einmal ein Algorithmus, der für die automatische Generierung neuer Animationssequenzen verwendet werden kann und zum anderen einen Kompressionsalgorithmus für eben diese Sequenzen. Die automatische Generierung von völlig neuen, anpassbaren Animationen basiert auf dem Konzept der Ähnlichkeitssuche. Hierbei werden die einzelnen Schritte von gegebenen Basisanimationen auf Ähnlichkeiten hin untersucht, die zum Beispiel die Geschwindigkeiten einzelner Objektteile sein können. Die Identifizierung dieser Ähnlichkeiten erlaubt dann Sprünge innerhalb der Basissequenz, die dazu benutzt werden können, endlose, neue Sequenzen zu erzeugen. Die Übertragung von animierten 3D Daten über bandbreitenlimitierte Kanäle wie ausgedehnte Netzwerke, Mobilfunk oder zu sogenannten thin clients erfordert eine effiziente Komprimierung. Die zweite, in dieser Arbeit vorgestellte Methode, ist ein Kompressionsschema für Geometriedaten. Ähnlich wie bei der Kompression von BTF Daten wird die PCA in Verbindung mit Clustering benutzt, um die animierte Geometrie zu analysieren und in sich ähnlich bewegende Teile zu segmentieren. Diese erkannten Segmente lassen sich dann hoch komprimieren. Der Algorithmus arbeitet automatisch und erlaubt zudem eine sehr exakte Rekonstruktionsqualität nach der Dekomprimierung

Representations for Cognitive Vision : a Review of Appearance-Based, Spatio-Temporal, and Graph-Based Approaches

The emerging discipline of cognitive vision requires a proper representation of visual information including spatial and temporal relationships, scenes, events, semantics and context. This review article summarizes existing representational schemes in computer vision which might be useful for cognitive vision, a and discusses promising future research directions. The various approaches are categorized according to appearance-based, spatio-temporal, and graph-based representations for cognitive vision. While the representation of objects has been covered extensively in computer vision research, both from a reconstruction as well as from a recognition point of view, cognitive vision will also require new ideas how to represent scenes. We introduce new concepts for scene representations and discuss how these might be efficiently implemented in future cognitive vision systems

Geometric Expression Invariant 3D Face Recognition using Statistical Discriminant Models

Currently there is no complete face recognition system that is invariant to all facial expressions. Although humans find it easy to identify and recognise faces regardless of changes in illumination, pose and expression, producing a computer system with a similar capability has proved to be particularly di cult. Three dimensional face models are geometric in nature and therefore have the advantage of being invariant to head pose and lighting. However they are still susceptible to facial expressions. This can be seen in the decrease in the recognition results using principal component analysis when expressions are added to a data set. In order to achieve expression-invariant face recognition systems, we have employed a tensor algebra framework to represent 3D face data with facial expressions in a parsimonious space. Face variation factors are organised in particular subject and facial expression modes. We manipulate this using single value decomposition on sub-tensors representing one variation mode. This framework possesses the ability to deal with the shortcomings of PCA in less constrained environments and still preserves the integrity of the 3D data. The results show improved recognition rates for faces and facial expressions, even recognising high intensity expressions that are not in the training datasets. We have determined, experimentally, a set of anatomical landmarks that best describe facial expression e ectively. We found that the best placement of landmarks to distinguish di erent facial expressions are in areas around the prominent features, such as the cheeks and eyebrows. Recognition results using landmark-based face recognition could be improved with better placement. We looked into the possibility of achieving expression-invariant face recognition by reconstructing and manipulating realistic facial expressions. We proposed a tensor-based statistical discriminant analysis method to reconstruct facial expressions and in particular to neutralise facial expressions. The results of the synthesised facial expressions are visually more realistic than facial expressions generated using conventional active shape modelling (ASM). We then used reconstructed neutral faces in the sub-tensor framework for recognition purposes. The recognition results showed slight improvement. Besides biometric recognition, this novel tensor-based synthesis approach could be used in computer games and real-time animation applications

A system for advanced facial animation

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 35-36).by Kenneth D. Miller, III.M.Eng