Welcome to
CEG4520/CEG4520 - Scientific Visualization and
Virtual Environments
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Welcome to
CEG4520/CEG4520 - Scientific Visualization and
Virtual Environments |
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Scientific visualization as a research area has impacted
an enormous number of engineering disciplines. In
particular, it helps users get better insight into their
data. In many areas, it is almost impossible to
reasonably analyze data without an appropriate
visualization due to the overwhelming amount of
information present in the data. Data sets resulting
from simulations or experiments in various application
fields, for example computational fluid dynamics (CFD)
or medical imaging, have to be analyzed and represented
in a way that the user is enabled to easily investigate
and explore the data. Generally, the software
environment becomes more and more illustrative. For
example, the emerging of Google maps and Google Earth
underlines this.
This course will provide you with techniques for
generating visualizations of various different data types,
including scalar, vector, and tensor data. Geometric as
well as volumetric methodologies will be
introduced. Advantages and disadvantages of the
visualization methods are discussed to enable students to
pick the optimal technique for a given type of data
set. Different visualization environments are
illustrated from common desktop environments to
high-end virtual environments. Programming techniques
for these environments are explained, including
rendering techniques and different input
paradigms. Programming examples are provided to enable
students to immediately experience their own
visualization application. Materials in this course are
complementary to those in Computer Graphics I.
The slides used during the lecture can be downloaded here: Proofs for different types of vector fields OpenGL example for using Microsoft's Kinect with the Kinect SDK. Example for getting positional data from a VRPN server Midterm review sample questions
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