Vision and Image Processing (VIP)

Course content

Vision and Image Processing (VIP) gives a overview of modern vision techniques used in man and machine.  Focus is both on conceptual understanding of the models and methods and on practical experience. The course covers state of the art methods for image analysis including how to solve visual processing tasks such as object recognition and content based image search and retrieval.


The course is not focused on providing a deep mathematical understanding of the techniques, but will include the  mathematical background necessary to understand vision and image processing.


Through a number of mandatory programming exercises the students will develop simple programs and obtain solutions to non-trivial vision tasks.  After the course, the students will be able to understand the models and principles of vision technologies used in new products and applications.

 

This course is mandatory for students enrolled in the IT and Cognition MSc study programme and is an elective course for students enrolled in the MSc programme in Computer Science. The course content does not overlap with Signal and image Processing (MSc in Computer Science).

Education

MSc Programme in IT and Cognition

Learning outcome

In order to pass, the student must document knowledge of the most common problems, methods and results in vision and image processing, specifically:

 

Knowledge:

  • Theoretical and practical knowledge of the current research within computer vision and image analysis.
  • Knowledge of common application areas.


Skills:

  • The ability to read and apply the knowledge obtained by reading scientific papers.
  • The ability to convert a theoretical algorithmic description into a concrete program implementation.
  • The ability to compare computer vision and image analysis algorithms and assess their ability to solve a specific task.


Competences:

  • Understanding and analyzing the main challenges in vision and image processing today.
  • Describing common applications of importance to society.
  • Describing and applying feature extraction methods and modeling techniques in image and vision processing.
  • Analyzing the main challenges in vision and image processing today.
  • Implementation of selected methods.
  • Comparative evaluation of the studied methods.

 

Mix of lectures and exercises

See Absalon.

Basic programming and linear algebra as obtained on Scientific Programming (IT and Cognition) or as required by the BSc or MSc programme in Computer Science.

ECTS
7,5 ECTS
Type of assessment
Continuous assessment
Continuous assessment based on 4-6 assignments throughout the course. Assignments are handled electronically in Absalon. All assignments must be passed.
Aid
All aids allowed
Marking scale
passed/not passed
Censorship form
No external censorship
Several internal examiners
Criteria for exam assessment

See "Learning outcome".

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 32
  • Practical exercises
  • 16
  • Preparation
  • 75
  • Exam
  • 83
  • English
  • 206