Image Analysis and Computer Vision

Image Analysis and Computer Vision

Professor

Prof. Dr. Bastian Goldlücke

Dates (Lecture)

Abstract

The lecture addresses the basic topics and methodology in image analysis and computer vision:

• Image filtering, frequency and scale
• Image features
• Coordinate transformations and image alignment
• Camera models and calibration
• Multiple views and motion
• Reconstruction of 3D scene geometry

Besides learning the fundamental theoretical building blocks, students will attain working knowledge of important practical algorithms, in particular via programming exercises in Matlab. During the semester, a number of programming assignments will be handed out, which can be done in groups. In the end, everyone should have a nice little code library for basic image analysis tasks. 

The lecture will continue in the next semester with Part II, which covers mostly Probabilistic Graphical Models.

For further details about the lecture see the LSF and the accompanying webpage, and ILIAS.

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