Supervisors

Dr Sareh Rowlands, University of Exeter

Location:

Department of Computer Science, Streatham Campus, Exeter

The University of Exeter’s Department of Computer Science is inviting applications for a PhD studentship fully-funded by the faculty of Environment, Science and Economy to commence on 23 September 2024 or as soon as possible thereafter.  For eligible students the studentship will cover Home or International  tuition fees plus an annual tax-free stipend of at least £19,237 for 3.5 years full-time, or pro rata for part-time study.  The student would be based in the Computer Science Department in the Faculty of Environment, Science and Economy at the Streatham Campus in Exeter.

Project Description:

Event recognition in videos has emerged as one of the most dynamic areas in computer vision. Researchers have extensively explored a wide range of topics, from recognising simple, short-term actions like running and walking, to complex, long-term multi-agent events such as surgical procedures or collaborative tasks. Typically, long videos consist of multiple actions, each composed of sub-actions with varying durations and sequences.
Inspired by the natural cognitive process of breaking down complex events into smaller sub-events, this project aims to advance the parsing of action videos, with a specific focus on first-person vision. In first-person vision (egocentric), a wearable camera is utilised to simulate the first-person perspective, capturing what the user sees and focusing on where the user looks. This unique viewpoint offers an exciting opportunity to develop intelligent wearable systems that can understand and interpret user activities and behaviours.
Such systems have the potential to significantly enhance quality of life by acting as caregivers or trainers in various settings, from healthcare to industrial environments. Building on the recent successes of deep neural networks and graph-based representations in video analysis, this project seeks to tackle the temporal segmentation challenge in egocentric vision. Additionally, we aim to explore action anticipation, where the system not only recognises ongoing actions but also predicts future actions based on the observed context and patterns.

To achieve these goals, we will develop various deep learning models and graph-based approaches to effectively represent and analyse temporal and spatial information in first-person video data. By leveraging these advanced techniques, our aim is to create a robust framework for understanding, interpreting, and anticipating complex events from a first-person perspective, ultimately contributing to the development of intelligent, user-centric applications.
This award provides annual funding to cover Home tuition fees and a tax-free stipend.  For students who pay Home tuition fees the award will cover the tuition fees in full, plus at least £19,237 per year tax-free stipend. The studentship will be awarded on the basis of merit for 3.5 years of full-time study to commence on 23 September 2024.

International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.
 

Entry requirements

Some of the necessary skills that are needed for the project are as follows:
Mathematics: Linear algebra, probabilities
Computer Science: Programming skills in Python, ideally already some experience with PyTorch or TensorFlow.
Other: Working knowledge of LaTeX

Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. 

If English is not your first language you will need to meet the required level as per our guidance at https://www.exeter.ac.uk/pg-research/apply/english/

How to apply

Apply now

In the application process you will be asked to upload several documents:

• CV
• Letter of application (outlining your academic interests, prior research experience and reasons for wishing to undertake the project).
• Research proposal
• Transcript(s) giving full details of subjects studied and grades/marks obtained (this should be an interim transcript if you are still studying)
• Two references from referees familiar with your academic work. If your referees prefer, they can email the reference direct to PGRApplicants@exeter.ac.uk quoting the studentship reference number.
• If you are not a national of a majority English-speaking country you will need to submit evidence of your proficiency in English.

The closing date for applications is midnight on August 16th 2024.  Interviews will be held virtually date TBC.

If you have any general enquiries about the application process please email PGRApplicants@exeter.ac.uk or phone 0300 555 60 60 (UK callers) +44 (0) 1392 723044 (EU/International callers)   Project-specific queries should be directed to the main supervisor.

Summary