course-details-portlet

IMT3017 - Computer Vision

About

Examination arrangement

Examination arrangement: Assignment and Oral examination
Grade: Letters

Evaluation form Weighting Duration Examination aids Grade deviation
Assignment 40/100
Oral examination 60/100

Course content

Image formation and filtering, including:
-Camera and optics
-Light and color
-Image filtering
Image processing
Feature detection and matching
Image compression
Multiple views and stereo
Recognition
Segmentation
Color imaging
Introduction to spectral imaging
Introduction to machine learning
Applications, including for example the following;
-Face detection
-Face recognition
-OCR
-Industrial applications
-Medical imaging
-Image stitching

Learning outcome

Knowledge:
-identify basic concepts, terminology, theories, models and methods in the field of computer vision
-describe basic methods of computer vision related to multi-scale representation, edge detection and detection of other primitives, stereo, motion and object recognition.
-assess which methods to use for solving a given problem, and analyse the accuracy of the methods

Skills:
-develop and apply computer vision techniques for solving practical problems
-choose appropriate image processing methods for image filtering, image restoration, image reconstruction, segmentation, classification and representation,

General competence:
-acquire good and practical skills in computer vision.

Learning methods and activities

-Lectures
-Exercises
-Project and other methods

Compulsory assignments

  • Mandatory assigments

Further on evaluation

Mandatory assignments and project has to be completed in order to be eligible to appear for the main exam.

Mode (written /oral) of the examination will be decided by the course responsible and is depended on the number of students.

The course will run if required, and is subject to availability or capacity.

Specific conditions

Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.

Admission to a programme of study is required:
Engineering - Computer Science (BIDAT)
Engineering - Electrical (BIELE)
Programming (BPROG)

Required previous knowledge

-REA2091 Mathematics 2 for Computer Science or
-REA2081 Mathematics 2 for Electical Engineering or
-REA1121 Mathematics for Programming

Course materials

“Computer Vision: Algorithms and Applications" by Richard Szeliski
“Digital Image Processing“ by Rafael C. Gonzalez and Richard Eugene Woods

More on the course

No

Facts

Version: 1
Credits:  10.0 SP
Study level: Third-year courses, level III

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2020

Language of instruction: English

Location: Gjøvik

Subject area(s)

-

Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Computer Science

Phone:

Examination

Examination arrangement: Assignment and Oral examination

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Autumn ORD Assignment 40/100
Room Building Number of candidates
Autumn ORD Oral examination 60/100 2020-11-30 09:00
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"

More on examinations at NTNU