Course - Machine Vision - AIS2204
AIS2204 - Machine Vision
The course contains the following topics:
- Fundamental image analysis
- Fundamental 3D modelling
- Practical use of standard libraries for machine vision
- Object recognition and tracking
- 3D reconstruction from stereo views
- Other topics required for achieving intended learning outcomes
- The candidate can explain fundamental mathematical models for digital imaging, 3D models, and machine vision.
- The candidate are aware of the principles of digital cameras and image capture.
- The candidate can implement selected techniques for object recognition, tracking and 3D reconstruction.
- The candidate has a good analytic understanding of machine vision and of the collaboration between machine vision and other systems in robotics.
- The candidate can exploit the connection between theory and application for presenting and discussing engineering problems and solutions.
Learning methods and activities
Learning activities include lectures, tutorials and lab/project work.
A constructivist approach for learning is endorsed, with focus on problem solving and practical application of theory.
Further on evaluation
Assessment guidelines for the oral exam will be discussed with the reference group and published before the end of the teaching term.
Admission to a programme of study is required:
Automation and Intelligent Systems (BIAIS)
Recommended previous knowledge
- ISTA1002 Statistikk
- IMA2011 Matematiske metoder 2
- IMA1001 Matematiske metoder 1
Required previous knowledge
The course has no prerequisites.
It is a requirement that students are enrolled in the study programme to which the course belongs.
An updated course overview, including curriculum, is presented at the start of the semester and will typically also include English material.
Credits: 7.5 SP
Study level: Third-year courses, level III
Term no.: 1
Teaching semester: AUTUMN 2022
Language of instruction: English, Norwegian
- Computer and Information Science
- Engineering Cybernetics
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"