Computer Vision, Robotics and Machine Learning MSc

This MSc programme is offered by Surrey's Department of Electronic Engineering, recognised for internationally leading research in multimedia signal processing and artificial intelligence. Our course provides you with up-to-date training in emerging technologies, and is highly valued by industry.

Why Surrey?

If you are intrigued by the acquisition, processing, analysis and understanding of computer vision, then our programme will suit you.

Computer vision is a fascinating and fast-moving field: the rate at which visual data (images and videos) grow on the internet and home computers is unprecedented and incomparable to any other type of data.

Computer vision is a key development area for creative industries, rapidly growing in importance and visibility to our global economy - and demand continues to rise for experts who will create solutions for generating, managing and analysing visual data.

Programme overview

Our MSc degree provides in-depth training for students interested in a career in industry, as well as research-oriented institutions focused on image and video analysis. State-of-the-art computer vision and machine learning approaches for image and video analysis are included in the course as well as low-level image processing methods.

We also offer training in programming languages, software tools and methods for the design and implementation of computer vision systems.

Why not read about past and present student experiences of our electronic engineering programmes, including Christopher Lord, Christos Merkouris and Prashant Butani?

Module overview

Programme structure

C - Compulsory, O - Optional
Modules Credits MSc
Image Processing and Vision 15 C
Space Robotics and Autonomy 15 C
Artificial Intelligence and AI Programming 15 C
Computer Vision and Pattern Recognition 15 C
Image and Vision Compression 15 C
Advanced Signal Processing 15 C
Object-Oriented Design and C++ Programming 15 O
Satellite Remote Sensing 15 O
Fundamentals of Digital Signal Processing 15 O

Compulsory modules

Advanced Signal Processing

You will be taught about the concepts of statistical and adaptive techniques in the detecting, filtering and matching of signals in noise. By the end of this module, you will be able to manipulate mathematical models to solve problems and predict effects, and you will learn to appreciate how these techniques apply to machine perception.

Computer Vision and Pattern Recognition

You will learn about the mathematical principles and concepts of computer vision alongside its practical applications. This module aims to provide you with an introduction to computer vision; encompassing; image formatting and processing; mid-level scene representation; as well as model-based description and tracking.

Image Processing and Vision

This module will be of interest to any student curious about the science and technology behind machine vision. You will gain a good background in how to build artificial systems that manipulate videos and images to alter or analyse information content.

Optional modules

Object-Oriented Design and C++

This module will provide you with the fundamentals of programming in the C++ language. You will study object-oriented design, the C++ class and look at design issues and planning.

Artificial Intelligence and AI Programming 

The aim of this module is to introduce the ideas and concepts which underlie the development of artificially intelligent machine systems and to teach the programming language suited to the implementation of such systems.

Image and Video Compression

By taking this module, you will learn about principles underlying the compression of video signals and you will come away with an in-depth knowledge of state-of-the-art coding techniques, internationally standardised compression algorithms, error resilience issues and related systems and technology.

Mobile Applications and Web Services

This module’s main aim is to introduce you to the basics of mobile web service development, discussing web service technologies and introducing the mechanisms for representing, manipulating and querying structured data (XML).

Dissertation and projects

The summer dissertation projects provide an opportunity for you to apply material learnt during the previous two semesters and to develop a detailed knowledge of a particular area.

The dissertation projects have strong industrial relevance by drawing on EU- or industry-funded research and development carried out in the Centre for Vision, Speech and Signal Processing (CVSSP).

They will cover various applications areas, including 3D broadcast production, biometrics, video archive restoration, security and surveillance systems, image and video database retrieval, speech recognition, machine audio perception, biomedical image processing and robotics.

The projects may be based at the university or in industry. There are also opportunities for carrying out the project work at collaborating academic institutions in the EU under the Erasmus programme.

Teaching and assessment

Our taught programme structure provides a judicious mix of theoretical and applied topics delivered over two semesters through lectures, assignments and laboratory exercises. The assessment of these taught modules is through formal examinations at the end of Semesters 1 and 2.

The pass mark is set at 50 per cent for each module, representing a combination of the formal examination and any associated coursework or lab marks. An overall average, aggregated over all of the assessed modules, in excess of 70 per cent achieves a Pass with Distinction.

Projects are selected during the first semester from a broad list and are primarily undertaken between June and September. Following the spring examinations, usually staggered over May and June, you will concentrate on your MSc project.

You will usually meet with your project supervisor either weekly or fortnightly to discuss your project. There is a mid-term assessment based at the university where you will orally present your project to an assessment panel. This provides you with feedback on your progress and suggestions for ongoing development.

You will produce a formal MSc dissertation and will also be assessed at a viva voce examination in late August or early September.

Facilities, equipment and support

To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.

We provide computing support with any specialised software required during the programme, for example, Matlab. The Faculty’s student common room is also covered by the University’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices.

Specialist experimental and research facilities, for computationally demanding projects or those requiring specialist equipment, are provided by the Centre for Vision, Speech and Signal Processing (CVSSP).

Skills and knowledge

The study of Computer Vision at this level develops a unique set of skills and knowledge, including:

  • Theoretical knowledge and practical application of methods in computer vision
  • Programming skills in Matlab or C/C++
  • Data collection and analysis techniques
  • Logical and critical thinking
  • Communication and presentation skills

Job opportunities

Computer vision specialists are be valuable in all industries that require intelligent processing and interpretation of image and video.

This includes industries in directly related fields such as:

  • Multimedia indexing and retrieval (Google, Microsoft, Apple)
  • Motion capture (Foundry)
  • Media production (BBC, Foundry)
  • Medical Imaging (Siemens)
  • Security and Defence (BAE, EADS, Qinetiq)
  • Robotics (SSTL)

and industries in related areas that require good knowledge of machine learning, signal processing and programming.

Studying for Msc degree in Computer Vision offers variety, challenge and stimulation. It is not just the introduction to a rewarding career, but also offers an intellectually demanding and exciting opportunity to break through boundaries in research.

Many of the most remarkable advancements in the past 60 years have only been possible through the curiosity and ingenuity of engineers. Our graduates have a consistently strong record of gaining employment with leading companies. Employers value the skills and experience that enable our graduates to make a positive contribution in their jobs from day one.

Our graduates are employed by companies across the electronics, information technology and communications industries. Recent employers include BAE Systems, BT, Philips, Hewlett Packard, Logica, Lucent Technologies, the BBC, Motorola, NEC Technologies, Nokia, Nortel Networks and Red Hat.

Industrial collaborations

We draw on our industry experience to inform and enrich our teaching, bringing theoretical subjects to life. Our industrial collaborations include:

  • Research and technology transfer projects with industrial partners such as the BBC, Foundry, LionHead and BAE
  • A number of our academics offer MSc projects in collaboration with our industrial partners

Research perspectives

This course gives an excellent preparation for continuing onto PhD studies in computer vision related domains.

Professional recognition

Our MSc in Computer Vision is awaiting accreditation by the IET.

Related programmes

Postgraduate (Taught)

Professional development

Related departments/schools

Related research areas

Programme leader

Dr John Collomosse

Find out more

General enquiries:

+44 (0)1483 681 681

Admissions enquiries:

+44-(0)1483-682-222

admissions@surrey.ac.uk

Programme facts

Type of programme:

MSc

Programme length:

  • Full-time: 12 months
  • Part-time: 60 months

Start date:

Sep 2016

Entry Requirements

An undergraduate degree in electronic engineering, computer science, maths, physics or a related discipline. Computer programming skills C/C++, Python, Matlab or Java. Our minimum entry level is a 2.2 from a good UK university, or overseas equivalent. Relevant industrial experience will also be considered.

View entry requirements by country

English language requirements

We offer intensive English language pre-sessional courses, designed to take you to the level of English ability and skill required for your studies here.

Fees

Study mode Start date UK/EU fees Overseas fees
Full-time Sep 2016 £8,000 £18,000
Part-time Sep 2016 £900 per 15 credits £2,000 per 15 credits

Please note these fees are for the academic year 2016/2017 only. Annual fees will rise by four per cent (rounded up to the nearest £100) for each year of study.

A complete list of all fees for our Masters Programmes

Funding

Discounts for Surrey graduates

Thinking of continuing your education at Surrey? As an alumnus of Surrey you may be eligible for a ten per cent discount on our taught Masters programme fees. Learn more.

For more details

GREAT Surrey Scholarships India

For for all postgraduate taught courses starting in February 2017 within the Faculty of Engineering and Physical Sciences, the University is offering graduates from India the opportunity to apply for one of three scholarships worth £5,000 through the GREAT Scholarships - India programme. 

For more details

Admissions Information

Our Admissions Policy provides the basis for admissions practice across the University and gives a framework for how we encourage, consider applications and admit students.

Further information for applicants

Postgraduate Study Advice

Steps to Postgraduate Study is an official, independent guide for anyone considering a taught postgraduate course. The guide is produced by the Higher Education Funding Council for England (HEFCE), the Higher Education Funding Council for Wales, the Scottish Funding Council and the Department for Employment and Learning, Northern Ireland.

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Disclaimer

Modules listed are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.

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