Vector offset operators for deformable organic objects.

Many natural materials and most of living tissues exhibit complex deformable behaviours that may be characteriseda s organic. In computer animation, deformable organic material behaviour is needed for the development of characters and scenes based on living creatures and natural phenomena. This study addresses the problem of deformable organic material behaviour in computer animated objects. The focus of this study is concentrated on problems inherent in geometry based deformation techniques, such as non-intuitive interaction and difficulty in achieving realism. Further, the focus is concentrated on problems inherent in physically based deformation techniques, such as inefficiency and difficulty in enforcing spatial and temporal constraints. The main objective in this study is to find a general and efficient solution to interaction and animation of deformable 3D objects with natural organic material properties and constrainable behaviour. The solution must provide an interaction and animation framework suitable for the creation of animated deformable characters. An implementation of physical organic material properties such as plasticity, elasticity and iscoelasticity can provide the basis for an organic deformation model. An efficient approach to stress and strain control is introduced with a deformation tool named Vector Offset Operator. Stress / strain graphs control the elastoplastic behaviour of the model. Strain creep, stress relaxation and hysteresis graphs control the viscoelastic behaviour of the model. External forces may be applied using motion paths equipped with momentum / time graphs. Finally, spatial and temporal constraints are applied directly on vector operators. The suggested generic deformation tool introduces an intermediate layer between user interaction, deformation, elastoplastic and viscoelastic material behaviour and spatial and temporal constraints. This results in an efficient approach to deformation, frees object representation from deformation, facilitates the application of constraints and enables further development

Comparing Features of Three-Dimensional Object Models Using Registration Based on Surface Curvature Signatures

This dissertation presents a technique for comparing local shape properties for similar three-dimensional objects represented by meshes. Our novel shape representation, the curvature map, describes shape as a function of surface curvature in the region around a point. A multi-pass approach is applied to the curvature map to detect features at different scales. The feature detection step does not require user input or parameter tuning. We use features ordered by strength, the similarity of pairs of features, and pruning based on geometric consistency to efficiently determine key corresponding locations on the objects. For genus zero objects, the corresponding locations are used to generate a consistent spherical parameterization that defines the point-to-point correspondence used for the final shape comparison

Template based shape processing

As computers can only represent and process discrete data, information gathered from the real world always has to be sampled. While it is nowadays possible to sample many signals accurately and thus generate high-quality reconstructions (for example of images and audio data), accurately and densely sampling 3D geometry is still a challenge. The signal samples may be corrupted by noise and outliers, and contain large holes due to occlusions. These issues become even more pronounced when also considering the temporal domain. Because of this, developing methods for accurate reconstruction of shapes from a sparse set of discrete data is an important aspect of the computer graphics processing pipeline. In this thesis we propose novel approaches to including semantic knowledge into reconstruction processes using template based shape processing. We formulate shape reconstruction as a deformable template fitting process, where we try to fit a given template model to the sampled data. This approach allows us to present novel solutions to several fundamental problems in the area of shape reconstruction. We address static problems like constrained texture mapping and semantically meaningful hole-filling in surface reconstruction from 3D scans, temporal problems such as mesh based performance capture, and finally dynamic problems like the estimation of physically based material parameters of animated templates.Analoge Signale müssen digitalisiert werden um sie auf modernen Computern speichern und verarbeiten zu können. Für viele Signale, wie zum Beispiel Bilder oder Tondaten, existieren heutzutage effektive und effiziente Digitalisierungstechniken. Aus den so gewonnenen Daten können die ursprünglichen Signale hinreichend akkurat wiederhergestellt werden. Im Gegensatz dazu stellt das präzise und effiziente Digitalisieren und Rekonstruieren von 3D- oder gar 4D-Geometrie immer noch eine Herausforderung dar. So führen Verdeckungen und Fehler während der Digitalisierung zu Löchern und verrauschten Meßdaten. Die Erforschung von akkuraten Rekonstruktionsmethoden für diese groben digitalen Daten ist daher ein entscheidender Schritt in der Entwicklung moderner Verarbeitungsmethoden in der Computergrafik. In dieser Dissertation wird veranschaulicht, wie deformierbare geometrische Modelle als Vorlage genutzt werden können, um semantische Informationen in die robuste Rekonstruktion von 3D- und 4D Geometrie einfließen zu lassen. Dadurch wird es möglich, neue Lösungsansätze für mehrere grundlegenden Probleme der Computergrafik zu entwickeln. So können mit dieser Technik Löcher in digitalisierten 3D Modellen semantisch sinnvoll aufgefüllt, oder detailgetreue virtuelle Kopien von Darstellern und ihrer dynamischen Kleidung zu erzeugt werden