Why study this course at Dundee?
Computer vision and imaging is a rapidly expanding field with plenty of real-life applications and opportunities. Here at Dundee, we encourage a professional, inter-disciplinary and user-centred approach to computer systems design and production.
Application areas include:
- controlling processes - e.g. an industrial robot or an autonomous vehicle
- detecting events - e.g. for visual surveillance or people counting
- organising information - e.g. for indexing databases of images and image sequences
- modelling objects or environments - e.g. for industrial inspection
- medical image analysis
- topographical modelling
You will acquire skills in computer vision, inference, algorithmic underpinnings of computer vision systems, how images and signals are formed, filter, compressed and analysed, and how multiple images can be combined.
Throughout this course, you will also develop the necessary skills to undertake independent research and participate in proposal development and innovation - an excellent grounding for many future careers.
What is so good about this course?
Teaching at Dundee is research-led, meaning that the MSc programme benefits from association with cutting-edge research of international standard and its commercial applications.
We also have an active Computer Vision and Image Processing research group. Our Vision and Imaging students are involved in a number of projects, and have been involved with a number of completed research projects like ACTIVE, a project concerning adaptive interfaces for the operation of secondary controls in motor vehicles using pointing gestures and virtual dashboards.
Links with industry
The School of Computing collaborates with, and has links to, companies such as IBM, NCR and Oracle.
You will have 24-hour access to our award winning and purpose-built Queen Mother Building. It has an unusual mixture of lab space and breakout areas, with a range of conventional and special equipment for you to use. It's also easy to work on your own laptop as there is wireless access throughout the building. Our close ties to industry allows us access to facilities such as Windows Azure and Teradata, and university and industry standard software such as Tableau for you to evaluate and use.
The University maintains a friendly, intimate and supportive atmosphere, and we take pride in the fact that we know all of our students. We have a thriving postgraduate department with regular seminars and guest speakers.
The institution's focus on research was highly beneficial throughout the course, as it ensures that students get insight not only into well-known areas of computer science but into newly emerging studies which will shape tomorrow's world.
The start date is September each year. The MSc course lasts for 12 months and the PGDip lasts for 9 months.
We know how important it is to be at the leading edge of computing and so you will learn from research-active staff. Leading researchers teach you and small class sizes mean that they really get to know you, making for an informal and supportive community.
Industrial collaboration is part of our ethos too, so we regularly include guest experts from industry.
You select seven taught modules, three per semester, during the period September-April. You will make module selections with your advisor.
Semester 1 (Sept-Dec)
- Probabilistic Inference and Learning
- Signals and Images
- Plus two from:
- Technology Innovation Management
- Computer Graphics
- Logical Inference & Symbolic Reasoning
- Information Theory
Semester 2 (Jan-Mar)
- Vision and Perception
- Research Methods
- Plus one from:
- Computing Research Frontiers
- Multi-agent Systems & Grid Computing
Subject to examination performance, you then progress to the MSc project which runs from May to September, or to a Diploma project lasting 9 weeks.
Please note that some of the modules in the programme are shared with other masters programmes and some of the teaching and resources may be shared with our BSc programme. These joint classes offer a valuable opportunity to learn from, and discuss the material with, other groups of students with different backgrounds and perspectives.
The taught modules are assessed by continuous assessment plus end of semester examinations in December and March/April. The project is assessed by dissertation.
Computing coursework is often very practical, e.g. writing computer programs, designing interfaces, writing reports, constructing web sites, testing software, implementing databases, analysing problems or presenting solutions to clients.
The knowledge, skills and understanding that you will gain in the areas of computer vision, inference and learning will enable you to work effectively in the application of video and image-based computing - whether you choose industry, commerce or research.