course-details-portlet

IDIG4004 - Computer vision and applications

About

Examination arrangement

Examination arrangement: Aggregate score
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Assignment 60/100
Oral exam 40/100 20 minutes C

Course content

Review of vision systems

  • Image formation (light, colour, optics, cameras)
  • Digital images (sampling, quantisation, colour spaces)

Visual data processing

  • Transformations, filtering and feature extraction
  • Feature visualisation techniques
  • Density estimation, clustering and classification

Optimisation

  • Optimisation basics

Computer vision

  • Modeling and optimisation basics
  • Object detection/recognition
  • Tracking
  • Video understanding
  • Imaging with multiple cameras
  • Illuminant invariance

Deep learning for computer vision

  • Overview of state-of-the-art machine learning techniques
  • Explainable AI basics for Computer Vision

Learning outcome

At the end of the semester, a successful student will have knowledge of:

  • Vision systems (basics)
  • Feature extraction and analysis for images and videos
  • Optimisation techniques for model training
  • Classical computer vision techniques for object detection, recognition, tracking and scene understanding.
  • Deep learning for computer vision (basics)

Students will have developed the skills required to design simple machine/robot vision systems and to extract basic knowledge from digital images and videos. Students will also develop Python programming skills through assignments and project work.

Learning methods and activities

Learning activities will be in the form of interactive lectures, programming assignments and project work.

Compulsory assignments

  • Compulsory assignment

Further on evaluation

Assessment for this course is based on:

- 2 assignments (pass/fail). You need to pass both in order to be eligible for the project and exam.

- 1 project report: Students can work in groups of 2 or 3. A list of topics will be provided to choose from.

- 1 oral exam: 20 minutes per student. Questions can pertain to any topic covered in class.

Re-sit for the oral exam only. If not passed grade for the project, the course need to be done next time offered (both assessment parts).

Specific conditions

Admission to a programme of study is required:
Applied Computer Science (MACS)

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  SPRING 2025

Language of instruction: English

Location: Gjøvik

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

Department with academic responsibility
Department of Computer Science

Timetable

List view
Calendar view

Examination

Examination arrangement: Aggregate score

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD Assignment 60/100 INSPERA
Room Building Number of candidates
Spring ORD Oral exam 40/100 C
Room Building Number of candidates
Summer UTS Oral exam 40/100 C
Room Building Number of candidates
  • * 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.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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