NDAK12002U Vision and Image Processing

Volume 2013/2014
Education
MSc Programme in Computer Science
MSc Programme in It & Cognition
Content
The objective is to provide students with a general introduction to visual cognitive models and its relevance to modern image processing. The course also provides students with the necessary mathematical background to understand vision and image processing methods and includes programming exercises.
  
This course is mandatory for students enrolled in the It & cognition MSc study programme and is a restricted 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).

We will investigate state of the art methods for solving visual processing tasks such as perception, scene understanding, object recognition,  and content based image search and retrieval.
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
Literature
See Absalon.
Basic programming as obtained on Scientific programming (IT&cognition) or as required by the MSc programme in Computer Science.
Mix of lectures and exercises
  • Category
  • Hours
  • Exam
  • 83
  • Lectures
  • 32
  • Practical exercises
  • 8
  • Preparation
  • 83
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Continuous assessment
Continuous assessment based on assignments throughout the course. Assignments handled electronically in Absalon. Internal Pass / fail grading.
Marking scale
passed/not passed
Censorship form
No external censorship
Re-exam
Resubmission of assignments. Internal Pass / fail grading.
Criteria for exam assesment
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.