Kursussøgning, efter- og videreuddannelse – Københavns Universitet

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Kursussøgning, efter- og videreuddannelse

Vision and Image Processing (VIP)

Practical information
Study year 2016/2017
Time
Block 2
Programme level Full Degree Master
ECTS 7,5 ECTS
Course responsible
  • Søren Ingvor Olsen (6-6c716a79727543676c316e7831676e)
  • Department of Computer Science
Course number: NDAK12002U

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 solving visual processing tasks such as object recognition, content based image search and retrieval, and structure from motion.


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 & 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).

Learning outcome

The student will obtain the following from this course:

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

 

Recommended prerequisites

Basic programming as obtained on Scientific programming (IT&cognition) or as required by the BSc or MSc programme in Computer Science.

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Education

MSc Programme in IT and Cognition

Studyboard

Study Board of Mathematics and Computer Science

Course type

Single subject courses (day)

Duration

1 block

Schedulegroup

C
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Teaching and learning methods

Mix of lectures and exercises

Capacity

No limit

Language

English

Literature

See Absalon.

Workload

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

Exam

Type of assessment

Continuous assessment
Continuous assessment based on 4-6 assignments throughout the course. Assignments handled electronically in Absalon.

Marking scale

passed/not passed

Criteria for exam assessment

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

  • 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.

 

Censorship form

No external censorship
Several internal examiners

Re-exam

Resubmission of assignments.

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