[robotics-worldwide] [news] New MSc in Computer Vision - Oxford Brookes University

Fabio Cuzzolin fabio.cuzzolin at brookes.ac.uk
Tue Jun 2 09:21:55 PDT 2015

The Department of Computing and Communication Technologies of Oxford
Brookes University, Oxford, UK is launching a new MSc programme in Computer


A strong trend towards the commercial diffusion of Computer Vision
algorithms is becoming increasingly marked in recent years. Autonomous cars
endowed with smart visual sensors are at the forefront of the research
effort of R&D giants such as Goggle and Apple. In the entertainment
industry computer vision is intensively employed to create animated
characters via motion capture techniques.  Next generation robots are
designed to naturally interact with their human counterparts, and assist
surgeons in complex procedures. In surveillance, action recognition is used
to understand people’s behaviour, while their identity can be ascertained
by observing their walking gait. Computer vision apps for tablets and smart
phones which make face tracking or gestural interaction possible are
already available, while novel semantic approaches to image and video
retrieval over the internet are being researched.

Oxford is at the heart of the UK’s high-tech business community. The
Department of Computing and Communication Technologies has a world-class
reputation for research in the field. The Oxford Brookes Computer Vision
research group has in the past won numerous international prizes and awards
for the quality of its work. The new Artificial Intelligence and Vision
Research group led by Dr Fabio Cuzzolin


has links with world-class companies such as Google, Microsoft Research and
Magna International, and closely collaborates with other top research
groups in Oxford University, INRIA, UCL among others. Dr Cuzzolin is also
the Subject Coordinator for the MSc in Computer Vision.

This Master's programme is designed to teach core techniques and concepts
used in Computer Vision, whilst taking on board the exciting cutting-edge
approaches devised by the ongoing research work. The MSc is heavily
research-oriented, with Master’s students seen as an integral part of the
research activities. Links forged between the taught programme and the
research group are meant to enable them to produce research papers to
submit to top conferences and to feel part of the group's research efforts,
so enhancing their career prospects.

Students on the course are mentored by PhD students, Research Assistants
and other members of the Artificial Intelligence and Computer Vision
Research Group throughout their dissertation. They have access to highly
specialised equipment (including range and traditional cameras, NAO robots,
GPUs for heavily parallelised computation, a High Performance PC and a
motion capture suite), and to computer laboratories where they can learn
the practical application of the techniques they are taught.

Course description

To qualify for the MSc students need to pass three compulsory modules in
Semester 1 and three compulsory modules in Semester 2, as well as a final

Semester 1 covers the following modules:

Research and Scholarship Methods - designed to equip students with the
necessary research skills as well as the professional skills and outlook
needed for a lifelong career in the computer vision industry.

Principles of Computer Vision - introduces students to image formation,
image processing and basic methods for feature extraction and recognition.
These form the basis for further study of methodology and algorithms in
Advanced Computer Vision.

Mathematical Methods for Computer Vision - introduces students to the most
common mathematical tools used in computer vision and machine learning,
broadly spanning topics from linear algebra, calculus, geometry,
probability and statistics and optimisation.

Semester 2 is composed by the following modules:

Software Production - studies the current practices, skills and techniques
applied to managing software development related projects, individually and
in teams. The module combines theory with pragmatic and professional
insights and considers project management, risk, quality assurance,
usability and HCI issues.

Machine Learning – builds on Mathematical Methods to equip students with
the necessary instruments derived from machine learning. It covers a broad
spectrum of topics, such as: clustering and k-nearest neighbour, Bayesian
classification, maximum-entropy classifiers and MLE estimation,
Expectation-Maximisation, the perceptron model, linear SVMs, statistical

Advanced Computer Vision - is the end point of the MSc in Computer Vision.
The module is structured as a series of four seminars centred around a
number of real-world application scenarios: surveillance, gaming and
entertainment, cognitive robotics and navigation, semantic video retrieval,
and human-robot interaction. Students work in teams to explore and present
to their peers the state of the art in one of these scenarios, and tackle a
live project within the portfolio of the Computer Vision group.

During the summer period students undertake the MSc Dissertation, an
individual research and development project on a topic of their choice
within the portfolio of research interest of the Artificial intelligence
 and Vision Research group. Students are mentored by an individual
supervisor. The work may be undertaken in close co-operation with a
research, industrial or commercial organisation.

Students undertaking an MSc with placement will have the opportunity to
undertake a 1 year placement in industry. Placements are not guaranteed,
although the department will support students in finding a placement.
Students who successfully do so will undertake the placement after the
taught component and before working on the dissertation.

More info and how to
apply ----------------------------------------------------------------------------------------------------

For additional information and resources on the MSc course in Computer
Vision, including a short video introduction to the course please consult:


For entry requirements, fees and instructions on how to apply please
consult the official University web site:


You are also encouraged to browse through Dr Fabio Cuzzolin’s web page for
more information on the live research projects of the Artificial
Intelligence and Vision Research group here:


For any informal enquiries feel free to contact the subject coordinator at
fabio.cuzzolin at brookes.ac.uk


Dr Fabio Cuzzolin
Head of Artificial Intelligence and Vision
Department of Computing and Communication Technologies
Oxford Brookes University
Oxford, UK

+44 (0)1865 484526

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