Funded PhD Studentship in Learning to Recognise Dynamic Visual Content from Broadcast Footage

Funded PhD Studentship in Learning to Recognise Dynamic Visual Content from Broadcast Footage

Posted by Rebecca Martin on Fri, 19/08/2011 - 12:10

This is your opportunity to study for a PhD at the Centre for Vision, Speech and Signal Processing, one of the UK 's premier research centres in Computer Vision. The studentship is available from Oct and covers both tuition fees and a maintenance grant for 3.5 years. The funding is available to UK or EU students.

Successful applicants will join an expanding research group within the Centre for Vision Speech and Signal Processing which has over 120 people working in vision, machine learning and related disciplines. It has an international reputation for the excellence of its research and, in the last Research Assessment Exercise; the Department (of Electronic Engineering) was rated as second in the country with the highest return of staff for any institution.

The project is collaboration between the University of Surrey (Prof Bowden), the University of Oxford (Prof Zisserman) and the University of Leeds (Dr Everingham). The objective of this project is to develop automated tools that allow temporal visual content, such as a human gesturing, using sign language, or interacting with objects or other humans, to be learnt from standard TV broadcast signals using the transmitted annotation in the form of subtitles, scripts and annotation for the visually impaired as supervision.

Candidates should hold a 1st or strong 2.1 honours degree or Masters degree or equivalent in a scientific discipline (e.g., Engineering, Physics, Mathematics or Computing), and should have good written/spoken English and demonstrate an aptitude for the research area. Prior experience in computer vision, image processing or machine learning would be advantageous.

The studentship includes tuition fees for UK or EU candidates and a tax free maintenance grant of £13,920 for 3.5 years.

The post will remain open until filled. For further information please contact Prof Richard Bowden. Applicants should send a CV and covering letter to Prof Bowden - r.bowden(at)