About the Project
This project investigates advanced 3D techniques for large-scale terrain reconstruction, which pose a problem for existing methods because of their irregular shape. Geomorphologists require coastal terrain reconstructions to identify risks of flooding and erosion. However, acquiring topographic data needed for such analysis is very costly and time-demanding, limiting the ability to analyse the evolution of coastal landscapes.
This research proposes to improve the state-of-the-art methods for 3D reconstruction of large terrains so that the urgent demand from the geomorphologists can be satisfied. With the development of new algorithms, immersive visualization for the constant monitoring of territory change in hazardous environment can be applied with low cost. The successful candidate will weigh the benefits of image-based and point-based methods and optimally combine their strengths in novel hybrid methods. On one hand, image data is captured from multiple static cameras for long-term observation and unmanned aerial vehicle (UAV) snapshots. On the other hand, point cloud data is provided from light detection and ranging (LiDAR) or terrestrial laser scanning (TLS). The successful candidate will implement and improve methods, e.g. structure-from-motion, multi-view stereo, and surface reconstruction augmented with cutting-edge Deep Learning methods, to process the data from multi-sources to reconstruct 3D terrains. Furthermore, the project will investigate 3D registration methods to align and combine the results so that the terrains can be visualised in the Computer Augmented Virtual Environment (CAVE) to inform geomorphologists about the environmental changes and communicate the effects of environmental policy to the public.
The ideal candidate is expected to have relevant experience such as:
- Programming in C/C++.
- Applied mathematics, mainly geometry and linear algebra (Preferable).
- Programming in Matlab (Preferable).
- Visual computing background (Preferable).
Informal enquiries may be addressed to Dr Hui Fang (Department of Computer Science) by email at [Email Address Removed]
Duties and Responsibilities:
Students will be expected to:
- Successfully undertake an initial programme of accredited research training.
- Undertake a PhD programme of research under the supervision of an appointed supervisory team.
- Enhance the research culture of the Department in which they are located, the Research Institute to which they are attached, and the University by participating in events, conferences and training.
- Successfully complete a programme of teacher training.
- Undertake up to six hours teaching a week or working with the Institute to which they are attached alongside University Departments or external agencies or organizations as directed by their Head of Department/Research Institute Director.
Eligibility:
- Candidates should have, or be expected to obtain, a good undergraduate honours degree level (2:1 or above) and/or a Masters level qualifications in a relevant subject area achieved within the last three to five years. If their most recent qualifications were obtained outside this period and/or they do not possess a Masters level qualification there needs to be convincing evidence that they will be able to make the transition to doctoral study.
- Although it is possible for candidates to apply for the GTA scheme more than once candidates who have applied unsuccessfully on two or more occasions are unlikely to be shortlisted for interview.
- International candidates who require a visa to study in the UK will need to demonstrate that they meet the requirements for a Tier 4 visa and possess appropriate English Language skills (IELTS Level C1/C2 or equivalent).
- Applications are not normally accepted from candidates who already possess a PhD, unless there are compelling reasons for doing so. If a PhD has been obtained in the UK as a Tier 4 (General) Student Visa holder, further sponsorship cannot be offered under the Tier 4 (General) Student Visa category, as this will not meet the academic progression requirements set by the UKVI.
How to apply
Applicants must complete the online application form, attaching one document containing:
- A ‘Research Proposal’ which should not exceed 2,000 words in length
- A full academic curriculum vitae
Selection Criteria:
Selection will be based on the following:
- Your curriculum vitae
- The synergy between your qualifications, research experience and declared research interest
- Performance at interview
- Supervisory capacity in the declared area of research
- Previous tutoring/teaching experience and related subject based qualifications
- The strategic and developmental needs of the Faculty
The Recruitment Process
Shortlisted candidates will be invited to interview and asked to give a presentation related to their research proposal. Successful candidates at interview will be put forward to a final selection panel which will make the decision on the award of the studentships. Candidates will not have to attend the final panel.
The closing date for all studentships is 5th May 2017
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