Lecture Computer Vision, SS 2015
Group A: July 20-24, 2015
Group B: July 27-31, 2015
: OH 16, R.U09
For the majority of living beeings vision is the most important perception
mechanism for orienting themselves in the environment. Therefore, there exists
a multitude of attempts to recreate this capability in artificial systems.
In contrast to image processing techniques found in industrial applications
the aim of such advanced systems for machine vision is to obtain a task-oriented
interpretation of a complex scene with as few restrictions as possible
concerning the context and the recording conditions.
In this lecture advanced techniques of machine vision are covered
which to some extent are inspired by cognitive processes known from human
visual perception. First, important aspects of imaging processes are introduced
with an emphasis on the perception of colors. Afterwards, methods for the
extraction of image primitives (e.g. regions and edges) and for the calculation
of feature representations (e.g. texture, depth, or motion) are presented.
Finally, the lecture focusses on visual perception processes at the boundary
between image processing and scene interpretation. Especially, appearance based
object recognition techniques and methods for tracking objects in image
sequences will be covered.
The accompanying tutorials will give students the opportunity to deepen
their knowledge of the theoretical concepts presented in the lecture
by working on relevant practical problems.
Specialization Module (Vertiefungsmodul INF-MSc-502)
for Master (Applied) Computer Science
Topical focus areas (Schwerpunktgebiete):
2 (..., Embedded Systems, ...),
7 (Intelligent Systems)
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