IKT452 Computer Vision

The course is connected to the following study programs

• Artificial Intelligence and The Internet of Things, Master's Programme
• Artificial Intelligence, 5-year master programme

Teaching language

English

Recommended prerequisites

IKT213 - Machine Vision

Course contents

How can computers represent the visual world of humans? As a subfield of Artificial Intelligence, Computer Vision aims to answer this fundamental question at different fronts by deriving and harnessing meaningful information from visual data such as digital images. One may think of Computer Vision as an enabling instrument for AI to observe and interpret the visual world of humans. This course provides a comprehensive introduction to computer vision, including fundamentals of image formation, camera imaging geometry, feature detection and matching, stereo, motion estimation and tracking, image classification, scene understanding, and deep neural networks. Students will learn some advanced computer vision concepts and gain hands-on experience to solve real-life vision problems.

Learning outcomes

After completion of this course, students will be able to:

• Recognize and explain both the theoretical and practical aspects of computing with images to relate computer vision to human vision;
• Describe the foundation of image formation, measurement, and analysis;
• Discuss the geometric relationships between 2D and 3D computer vision;
• Select and implement appropriate image matching and alignment methods;
• Explain object and scene recognition and categorization from images;
• Identify and use the state-of-the-art deep neural networks for computer vision tasks;
• Develop the practical skills necessary to design and implement computer vision applications.

Teaching methods

The course is organized with a combination of lectures, assignments and projects.

The workload for the average student is approximately 200 hours.

Evaluation

The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.

Offered as Single Standing Module

Yes, if there are places available

Admission Requirement if given as Single Standing Module

Admission requirements for the course are the same as for the master’s programme in ICT.

Assessment methods and criteria

Homework Assignments (60%)

Class Project (40%).