Unit name | Image Processing and Computer Vision (Teaching Unit) |
---|---|
Unit code | COMS30030 |
Credit points | 0 |
Level of study | H/6 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Professor. Mirmehdi |
Open unit status | Not open |
Pre-requisites |
COMS10014 Mathematics for Computer Science A and COMS10013 Mathematics for Computer Science B or equivalent. COMS10016 Imperative and Functional Programming and COMS10017 Object-Oriented Programming and Algorithms I or equivalent programming experience. COMS20010 Algorithms II and COMS20011 Data-Driven Computer Science or equivalent. |
Co-requisites |
EITHER Assessment Units COMS30032 Image Processing and Computer Vision (Exam assessment, 10 credits). OR COMS30031 Image Processing and Computer Vision (Coursework assessment, 20 credits). Please note: COMS30030 is the Teaching Unit for the Image Processing and Computer Vision option. Single Honours Computer Science students can choose to be assessed by either examination (10 credits, COMS30032) or coursework (20 credits, COMS30031) by selecting the appropriate co-requisite assessment unit. Any other students that are permitted to take the Image Processing and Computer Vision option are assessed by examination (10 credits) and should be enrolled on the co-requisite exam assessment unit (COMS30031). |
School/department | School of Computer Science |
Faculty | Faculty of Engineering |
The aim of this unit is to give you an introduction to computational vision: the theory, principles, techniques, algorithms and applications. The unit is structured in terms of topics, each associated to a lecture, a follow-up seminar, laboratory sessions and self-study. For each topic, we will cover the underlying theory, the practical challenges, important algorithms and example applications. Practical implementation work will be conducted individually, with lab support, using C/C++ and OpenCV
On successful completion of this unit, students will be able to:
Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, practical activities supported by drop-in sessions, problem sheets and self-directed exercises.
Teaching will take place over Weeks 1-7, with coursework support in weeks 8-10 and for students assessed by examination, consolidation and revision sessions in Weeks 11 and 12.
Examination details:
January timed assessment (100%, 10 credits)
OR
Coursework details:
Coursework, to be completed over weeks 8-10. (100%, 20 credits)