3 research outputs found
Compression, Modeling, and Real-Time Rendering of Realistic Materials and Objects
The realism of a scene basically depends on the quality of the geometry, the
illumination and the materials that are used. Whereas many sources for
the creation of three-dimensional geometry exist and numerous algorithms
for the approximation of global illumination were presented, the acquisition
and rendering of realistic materials remains a challenging problem.
Realistic materials are very important in computer graphics, because
they describe the reflectance properties of surfaces, which are based on the
interaction of light and matter. In the real world, an enormous diversity of
materials can be found, comprising very different properties. One important
objective in computer graphics is to understand these processes, to formalize
them and to finally simulate them.
For this purpose various analytical models do already exist, but their
parameterization remains difficult as the number of parameters is usually
very high. Also, they fail for very complex materials that occur in the real
world. Measured materials, on the other hand, are prone to long acquisition
time and to huge input data size. Although very efficient statistical
compression algorithms were presented, most of them do not allow for editability,
such as altering the diffuse color or mesostructure. In this thesis,
a material representation is introduced that makes it possible to edit these
features. This makes it possible to re-use the acquisition results in order to
easily and quickly create deviations of the original material. These deviations
may be subtle, but also substantial, allowing for a wide spectrum of
material appearances.
The approach presented in this thesis is not based on compression, but on
a decomposition of the surface into several materials with different reflection
properties. Based on a microfacette model, the light-matter interaction is
represented by a function that can be stored in an ordinary two-dimensional
texture. Additionally, depth information, local rotations, and the diffuse
color are stored in these textures. As a result of the decomposition, some
of the original information is inevitably lost, therefore an algorithm for the
efficient simulation of subsurface scattering is presented as well.
Another contribution of this work is a novel perception-based simplification
metric that includes the material of an object. This metric comprises
features of the human visual system, for example trichromatic color
perception or reduced resolution. The proposed metric allows for a more
aggressive simplification in regions where geometric metrics do not simplif
Pattern Recognition
Pattern recognition is a very wide research field. It involves factors as diverse as sensors, feature extraction, pattern classification, decision fusion, applications and others. The signals processed are commonly one, two or three dimensional, the processing is done in real- time or takes hours and days, some systems look for one narrow object class, others search huge databases for entries with at least a small amount of similarity. No single person can claim expertise across the whole field, which develops rapidly, updates its paradigms and comprehends several philosophical approaches. This book reflects this diversity by presenting a selection of recent developments within the area of pattern recognition and related fields. It covers theoretical advances in classification and feature extraction as well as application-oriented works. Authors of these 25 works present and advocate recent achievements of their research related to the field of pattern recognition