Don't miss our weekly PhD newsletter | Sign up now Don't miss our weekly PhD newsletter | Sign up now

  Hybrid description methods for human faces


   School of Physics, Engineering and Technology

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

The group has pioneered the application of conditional probability density estimation to describing human faces. Our methods allow a system to estimate the age, sex, race and facial expression of people in a real-time video sequence. Accuracy is acceptable for some uses but not for demanding security applications where lighting may be poor and faces partly occluded. To tackle these difficult cases, we will combine our methods with new approaches in face landmark extraction, motion analysis and cascade classification. This project will explore these broad alternatives before focusing on promising avenues that will result in high-accuracy, high-speed robust face description.

Entry requirements:

Candidates should have (or expect to obtain) a minimum of a UK upper second class honours degree (2.1) or equivalent in Electronic and Electrical Engineering, Physics, Computer Science, Mathematics, Music Technology or a closely related subject.

How to apply:

Applicants should apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/. Please read the application guidance first so that you understand the various steps in the application process.

Computer Science (8) Engineering (12)

Funding Notes

This is a self-funded project and you will need to have sufficient funds in place (eg from scholarships, personal funds and/or other sources) to cover the tuition fees and living expenses for the duration of the research degree programme. Please check the School of Physics, Engineering and Technology website View Website for details about funding opportunities at York.

Register your interest for this project