I.3.7 Three-Dimensional Graphics and Realism
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- visualization (2)
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This thesis discusses several applications of computational topology to the visualization
of scalar fields. Scalar field data come from different measurements and simulations. The
intrinsic properties of this kind of data, which make the visualization of it to a complicated
task, are the large size and presence of noise. Computational topology is a powerful tool
for automatic feature extraction, which allows the user to interpret the information contained
in the dataset in a more efficient way. Utilizing it one can make the main purpose of
scientific visualization, namely extracting knowledge from data, a more convenient task.
Volume rendering is a class of methods designed for realistic visual representation of 3D
scalar fields. It is used in a wide range of applications with different data size, noise
rate and requirements on interactivity and flexibility. At the moment there is no known
technique which can meet the needs of every application domain, therefore development
of methods solving specific problems is required. One of such algorithms, designed for
rendering of noisy data with high frequencies is presented in the first part of this thesis.
The method works with multidimensional transfer functions and is especially suited for
functions exhibiting sharp features. Compared with known methods the presented algorithm
achieves better visual quality with a faster performance in presence of mentioned
features. An improvement on the method utilizing a topological theory, Morse theory, and
a topological construct, Morse-Smale complex, is also presented in this part of the thesis.
The improvement allows for performance speedup at a little precomputation and memory
cost.
The usage of topological methods for feature extraction on a real world dataset often
results in a very large feature space which easily leads to information overflow. Topology
simplification is designed to reduce the number of features and allow a domain expert
to concentrate on the most important ones. In the terms of Morse theory features are
represented by critical points. An importance measure which is usually used for removing
critical points is called homological persistence. Critical points are cancelled pairwise
according to their homological persistence value. In the presence of outlier-like noise
homological persistence has a clear drawback: the outliers get a high importance value
assigned and therefore are not being removed. In the second part of this thesis a new
importance measure is presented which is especially suited for data with outliers. This
importance measure is called scale space persistence. The algorithm for the computation
of this measure is based on the scale space theory known from the area of computer
vision. The development of a critical point in scale space gives information about its
spacial extent, therefore outliers can be distinguished from other critical points. The usage
of the presented importance measure is demonstrated on a real world application, crater
identification on a surface of Mars.
The third part of this work presents a system for general interactive topology analysis
and exploration. The development of such a system is motivated by the fact that topological
methods are often considered to be complicated and hard to understand, because
application of topology for visualization requires deep understanding of the mathematical
background behind it. A domain expert exploring the data using topology for feature
extraction needs an intuitive way to manipulate the exploration process. The presented
system is based on an intuitive notion of a scene graph, where the user can choose and
place the component blocks to achieve an individual result. This way the domain expert
can extract more knowledge from given data independent on the application domain. The
tool gives the possibility for calculation and simplification of the underlying topological
structure, Morse-Smale complex, and also the visualization of parts of it. The system also
includes a simple generic query language to acquire different structures of the topological
structure at different levels of hierarchy.
The fourth part of this dissertation is concentrated on an application of computational
geometry for quality assessment of a triangulated surface. Quality assessment of a triangulation
is called surface interrogation and is aimed for revealing intrinsic irregularities
of a surface. Curvature and continuity are the properties required to design a visually
pleasing geometric object. For example, a surface of a manufactured body usually should
be convex without bumps of wiggles. Conventional rendering methods hide the regions
of interest because of smoothing or interpolation. Two new methods which are presented
here: curvature estimation using local fitting with B´ezier patches and computation of reflection
lines for visual representation of continuity, are specially designed for assessment
problems. The examples and comparisons presented in this part of the thesis prove the
benefits of the introduced algorithms. The methods are also well suited for concurrent visualization
of the results from simulation and surface interrogation to reveal the possible
intrinsic relationship between them.
Sound surrounds us all the time and in every place in our daily life, may it be pleasant music in a concert hall or disturbing noise emanating from a busy street in front of our home. The basic properties are the same for both kinds of sound, namely sound waves propagating from a source, but we perceive it in different ways depending on our current mood or if the sound is wanted or not. In this thesis both pleasant sound as well as disturbing noise is examined by means of simulating the sound and visualizing the results thereof. However, although the basic properties of music and traffic noise are the same, one is interested in different features. For example, in a concert hall, the reverberation time is an important quality measure, but if noise is considered only the resulting sound level, for example on ones balcony, is of interest. Such differences are reflected in different methods of simulation and required visualizations, therefore this thesis is divided into two parts. The first part about room acoustics deals with the simulation and novel visualizations for indoor sound and acoustic quality measures, such as definition (original "Deutlichkeit") and clarity index (original "Klarheitsmaß"). For the simulation two different methods, a geometric (phonon tracing) and a wave based (FEM) approach, are applied and compared. The visualization techniques give insight into the sound behaviour and the acoustic quality of a room from a global as well as a listener based viewpoint. Furthermore, an acoustic rendering equation is presented, which is used to render interference effects for different frequencies. Last but not least a novel visualization approach for low frequency sound is presented, which enables the topological analysis of pressure fields based on room eigenfrequencies. The second part about environmental noise is concerned with the simulation and visualization of outdoor sound with a focus on traffic noise. The simulation instruction prescribed by national regulations is discussed in detail, and an approach for the computation of noise volumes, as well as an extension to the simulation, allowing interactive noise calculation, are presented. Novel visualization and interaction techniques for the calculated noise data, incorporated in an interactive three dimensional environment, enabling the easy comprehension of noise problems, are presented. Furthermore additional information can be integrated into the framework to enhance the visualization of noise and the usability of the framework for different usages.
Feature Based Visualization
(2007)
In this thesis we apply powerful mathematical tools such as interval arithmetic for applications in computational geometry, visualization and computer graphics, leading to robust, general and efficient algorithms. We present a completely novel approach for computing the arrangement of arbitrary implicit planar curves and perform ray casting of arbitrary implicit functions by jointly achieving, for the first time, robustness, efficiency and flexibility. Indeed we are able to render even the most difficult implicits in real-time with guaranteed topology and at high resolution. We use subdivision and interval arithmetic as key-ingredients to guarantee robustness. The presented framework is also well-suited for applications to large and unstructured data sets due to the inherent adaptivity of the techniques that are used. We also approach the topic of tensors by collaborating with mechanical engineers on comparative tensor visualization and provide them with helpful visualization paradigms to interpret the data.