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227-0448-00L 6 Credits DS , BSC , MSC D-HEST , D-INFK , D-PHYS , D-ITET , D-BAUG , D-MAVT , D-MATH
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Computer Vision II

Bilddatenanalyse und Computer Vision II

4 credit points under the programme regulations 2001
VVZ CR n/a

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
  • Thu 13:15-15:00 (ETZ E 6)
  • Thu 15:15-17:00 (ETL E 11.1)
4 h weekly

Offered In