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Computer Vision II
Bilddatenanalyse und Computer Vision II
Last Updated: 2026-02-05 15:19:51
Abstract
Introduction into the basic procedures for the interpretation of image content and object recognition. Demonstrating the current capabilities of computer vision systems through selected applications. Gaining own experience through practical computer and programming exercises.
Objective
Overview of the basic concepts of image formation, perception and analysis, and Computer Vision. Gaining own experience through practical computer and programming exercises.
Content
The first part of the course starts off from an overview of existing and emerging applications that need computer vision. It shows that the realm of image processing is no longer restricted to the factory floor, but is entering several fields of our daily life. First it is investigated how the parameters of the electromagnetic waves are related to our perception. Also the interaction of light with matter is considered. The most important hardware components of technical vision systems, such as cameras, optical devices and illumination sources are discussed. The course then turns to the steps that are necessary to arrive at the discrete images that serve as input to algorithms. A separate chapter is devoted to sampling and quantisation. The next part describes necessary preprocessing steps of image analysis, that enhance image quality and/or detect specific features such as edges and corners. Linear and non-linear filters are introduced for that purpose. The course will conclude by analyzing procedures for the analysis of multiple images containing additional types of basic information, with motion and depth as two important examples. The estimation of image velocities (``optical flow\\\\'\\\\') will get due attention. Several techniques are discussed to extract three-dimensional information about objects and scenes.
Resources
Lecture Notes
Course material Script, computer demonstrations, exercises and problem solutions.
General Information
- Language
- English
- Levels
- DS , BSC , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- oral 30 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Bilddatenanalyse und Computer Vision II |
|
4 h weekly |
Offered In
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Application Area (only necessary for MSc in Applied Mathematics)
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