Real time camera view transformation and visualisation in mixed reality PhD
- Mechanical, Electrical and Manufacturing Engineering
- Entry requirements:
- 4 years
- not available
- Reference number:
- Start date:
- 01 October 2018
- Is funding available?
- UK/EU fees:
- International fees:
- Application deadline:
- 01 April 2018
in the UK for research quality
in the UK for Mechanical Engineering
The Complete University Guide 2018
of 2 Queen's Anniversary Prizes
Loughborough University is a top-ten rated university in England for research intensity (REF2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.
In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.
We are seeking excellent candidates with interests in computer vision, image processing, Artificial Intelligence (AI), and deep learning who want to study at a top 10 UK research-led University whilst working with industrial partners.
This project is part of the EPSRC Centre for Doctoral Training in Embedded Intelligence. In choosing this project you’ll work alongside academics that are leaders in their field and benefit from a four-year studentship award that includes an enhanced EPSRC tax-free annual stipend of at least £17,553 per annum and UK/EU tuition fees. Furthermore, you will have access to a personal training budget of £10,000, which is in addition to a research budget and support from academic members of staff and industrial partners.
Loughborough University aims to ensure equality for men and women. We follow the principles of the Athena SWAN Charter by wishing to attract, support, and reward women in STEMM at all career stages.
The studentship is co-sponsored by Suke Intel and you will join a growing research group within the Department of Computer Science. This project is an exciting opportunity to develop computer vision algorithms and software to conduct automatic and robust camera calibration, 3D reconstruction, and real time online view transformation for applications such as mixed reality, surveillance, entertainment, virtual shopping and human-computer interaction. Any knowledge in image processing, AI and deep learning algorithms will be helpful. Any experience in robust vanishing point detection would be desirable. The successful candidate will understand the real challenges from real applications on computer vision algorithms and their implementation on embedded systems.
Primary supervisor: Dr Qinggang Meng
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in related engineering or computer science degree with strong programming skills. A relevant Master’s degree and/or experience in computer vision is desirable.
Applicants must meet the minimum English Language requirements, details available on the website.
Fees and funding
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Special arrangements are made for payments by part-time students.
The studentship is for four years and provides a tax free stipend of £17,553 per annum for the duration, plus tuition fees at the UK/EU rate. Due to funding restrictions, this is only available to those who are eligible to pay UK/EU fees. In order to qualify for a full award, all applicants must meet the EPSRC eligibility criteria including the minimum UK residency requirement.
How to apply
All applications should be made online. Under programme name, select CDT Embedded Intelligence Wolfson School
Please quote reference number: CDTEI_Meng
|Application deadline:||01 April 2018|
|Start date:||01 October 2018|