Queen Mary, University of London

Course Introduction

What if your smartphone could recognise that it was you before switching on, and could sense your mood by recognising your facial expressions? What if you could use a real thumbs'up for "liking" things on Facebook? How can you play games on an Xbox using only your body gestures? How can you equip cars with in'vehicle technology that could automatically read road signs? These are just some of the fascinating questions that students will strive to answer on this programme. This programme is intended to respond to a growing skills shortage in research and industry for engineers with a high level of training in the analysis and interpretation of images and video. It covers both low'level image processing and high'level interpretation using state'of'the'art machine learning methodologies. In addition, it offers high'level training in programming languages, tools and methods that are necessary for the design and implementation of practical computer vision systems.

Course Modules

Modules include: advanced transform methods; artificial intelligence; C++ for image processing; introduction to computer vision; machine learning; techniques for computer vision.

Course Additional Entry

Applicants should have a good 2nd class degree in electronic engineering, computer science, mathematics, or a related discipline. Applicants with unrelated degrees will be considered if there is evidence of equivalent industrial experience. Applicants should have good knowledge of computer programming, for example using C/C++, Python, Matlab or Java.

Duration & Attendance Qualification Tuition fees
1 year
Full Time
MSc (Postgraduate)