Development of deep learning algorithms for accurate gaze estimation

Gaze estimation aims to obtain the direction where you are looking at. It has been actively studied in the past three decades due to its importance in various fields, e.g. human-machine interfaces, human behavior analysis, marketing research, driver safety analysis, cognitive science, and psychology. The recent ten years have seen great performance improvements in gaze estimation methods, however, there is still a huge gap in applying these methods directly into daily webcam-based environments due to the challenges caused by low resolutions, large head movements, eye appearance variations.

This project will focus on developing accurate deep learning-based gaze estimation methods to bridge this gap. Different deep learning models like Convolutional Neural Networks, Generative Adversarial Networks will be explored to improve the accuracy of gaze estimation in common human interaction scenarios. This project is meaningful in that not only does it offer you an opportunity to learn state-of-the-art deep learning methods, but it also enables you to develop practical gaze related applications.

Entry requirements
Students are required to meet the following English Language requirements

You should have, or expect to achieve, at least a 2:1 honours degree (or equivalent international qualification) in a relevant subject.

Start date: 1st October 2020

Full-time (3 years)

How to apply
All applications should be made online

Under school/department name, select 'Computer Science'. Please quote reference CO/HC-Un1/2020.

The deadline for applications is 31 May 2020.