Computer Vision course

A course in computer science focusing on basic theory, models, and methods for computer vision, image analysis and image processing.

Grades received in the labs

• Lab 1: A
• Lab 2: B
• Lab 3: A

Intended learning outcomes

After completing the course with a passing grade the student should be able to:

• identify basic concepts, terminology, models and methods in computer vision and image processing-
• develop and evaluate a number of basic methods in computer vision and image processing systematically
• choose and apply methods for processing of image data related to image filtrering, image enhancement, segmentation, classification and representation,
• account for basic methods in computer vision as multiscale representation, detection of edges and other distinctive features, stereo, movement and object recognition to
• later as a working professional be able to decide how basic possibilities and limitations influence the choice of methods in image processing and computer vision for specific applications
• independently be able to implement, analyse and evaluate simple methods for computer vision and image processing
• be able to read and apply professional literature in the area.