Computer Vision and Image Processing
Introduction
The course imparts knowledge about current methods and algorithms in the field of computer vision. Important fundamentals and the latest approaches to image representation, image processing and image analysis are taught. Current models and methods of machine learning and their technical background are presented, and their respective applications in image processing are demonstrated.
Contents
- fundamental methods and techniques that enable a machine to analyse images and videos and understand their content
- fundamentals of image generation, linear filters, image segmentation, object recognition, object categorisation, 3D reconstructio
- application of current methods of machine learning for the topics described above
Learning Objectives
- Students describe current research trends and developments in the field of computer vision
- Students name relevant techniques necessary for image and video analysis tasks
- Students will be able to derive and explain methods and techniques that enable a machine to analyse images and videos and understand their content
- Students select basic computer vision techniques that are necessary for these analysis tasks
- Students independently apply the methods covered to real-world problems
- Students implement the algorithms presented themselves and translate them into a programming language of their choice
Examination Methods
- either a written exam (90-100 minutes)
- or an oral examination (20-30 minutes)
- or a project report (20-30 pages)
Lecture: Computer Vision
SWS: 2 ECTS: 2
Exercise: Computer Vision Exercise
SWS: 2 ECTS: 4
Module Competences
| ID | Description | Disciplines | Prerequisites | Evidence | Author | Source |
|---|---|---|---|---|---|---|
| compiler_tech_1 | apply modelling techniques | Computer Science | develop solutions through technical methods | University of Potsdam | Link | |
| compiler_tech_2 | analyse problems in given software systems | Computer Science | discuss problems in a team | University of Potsdam | Link |