AIS2204 - Machine Vision


This course is no longer taught and is only available for examination.

Course content

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

Learning outcome


  • 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.

General competence

  • The candidate has a good analytic understanding of machine vision, and the relationship between different approach to machine vision, and 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 seminars, lectures, tutorials and lab/project work.

A constructivist and hermeneutic 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. The re-sit exam is an oral exam the following spring.

Required previous knowledge

The course has no prerequisites.

Course materials

An updated course overview, including curriculum, is presented at the start of the semester.

More on the course

Version: 1
Credits:  7.5 SP
Study level: Third-year courses, level III


Language of instruction: English, Norwegian

Location: Ålesund

Subject area(s)
  • Computer and Information Science
  • Engineering Cybernetics
  • Engineering
Contact information
Course coordinator:

Department with academic responsibility
Department of ICT and Natural Sciences


  • * 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"

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