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Computer Vision
Last Updated: 2026-02-05 16:15:43
Abstract
The goal of this course is to provide students with a good understanding of computer vision and image analysis techniques. The main concepts and techniques will be studied in depth and practical algorithms and approaches will be discussed and explored through the exercises.
Objective
The objectives of this course are: 1. To introduce the fundamental problems of computer vision. 2. To introduce the main concepts and techniques used to solve those. 3. To enable participants to implement solutions for reasonably complex problems. 4. To enable participants to make sense of the computer vision literature.
Content
Camera models and calibration, invariant features, Multiple-view geometry, Model fitting, Stereo Matching, Segmentation, 2D Shape matching, Shape from Silhouettes, Optical flow, Structure from motion, Tracking, Object recognition, Object category recognition
Resources
Learning Materials (Links)
- Main link
- Information
General Information
- Language
- English
- Levels
- BSC , MSC , WBZ
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 120 minutes
- Aids
- None
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Computer Vision |
|
3 h weekly |
| exercise | Computer Vision |
|
1 h weekly |
| independent project | Computer Vision | No time listed | 3 h weekly |
Offered In
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Robotics (continued) (Only one of the two course units 263-5902-00L Computer Vision resp. 227-0447-00L Image Analysis and Computer Vision may be recognised for credits for the overall (CSE Bachelor and Master) study programmes. Only one of the two course units 263-5210-00L Probabilistic Artificial Intelligence resp. 252-0535-00L Advanced Machine Learning may be recognised for credits in the field of specialisation `Robotics' for the overall (CSE Bachelor and Master) study programmes. However, the other course unit may be recognised for a different category. For the category assignment take contact with the Study Administration ( ).)
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Robotics, Systems and Control (The courses listed in this category “Core Courses” are recommended. Alternative courses can be chosen in agreement with the tutor.)
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Robotics (continued) (Only one of the two course units 263-5902-00L Computer Vision resp. 227-0447-00L Image Analysis and Computer Vision may be recognised for credits for the overall (CSE Bachelor and Master) study programmes. Only one of the two course units 263-5210-00L Probabilistic Artificial Intelligence resp. 252-0535-00L Advanced Machine Learning may be recognised for credits in the field of specialisation `Robotics' for the overall (CSE Bachelor and Master) study programmes. However, the other course unit may be recognised for a different category. For the category assignment take contact with the Study Administration ( ).)
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Recommended Elective Courses (These courses are particularly recommended for the Bioelectronics track. Please consult your track advisor if you wish to select other subjects.)
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