Automatic Face Recognition based on Human Perception
University of Glasgow - Departments of Psychology and Electronics & Electrical Engineering
Applications are invited for a studentship on an interdisciplinary project in face recognition. The student will work on automated face processing systems incorporating recent developments in psychology and engineering. The project will lead to hardware implementation of the system on a chip. A project summary is given below.
Candidates should have at least a 2:1 honours degree in electrical engineering, computing science or related discipline. Excellent programming skills in C and C++ are essential and a good understanding of Linux and embedded systems is desirable. Because the final version will be a system on a chip or an embedded device, experience in hardware development is required.
The duration of the studentship is three years, and the successful candidate will receive an annual stipend of £13,290 per annum. PhD fees will be paid.
This studentship is funded by the University of Glasgow Kelvin-Smith scheme. See http://www.gla.ac.uk/research/kelvinsmithfellowshipsscholarships for details. Informal enquiries may be made to Professor Mike Burton (firstname.lastname@example.org), Dr Bernd Porr (email@example.com), or Dr Rob Jenkins (firstname.lastname@example.org).
Applicants should send a CV, a letter detailing their suitability for the studentship, and details of two academic referees to Lynda Young, Department of Psychology, University of Glasgow, Glasgow G12 8QQ, or by email to email@example.com
CLOSING DATE: 30 NOVEMBER 2009
Project Summary: Automatic face recognition based on human perception
Automatic face recognition is not currently good enough to work in practical settings, such as airport security. In contrast, humans seem to be good at recognising faces. In fact, we are only experts in face recognition when we know someone - our ability to match unfamiliar people to their photos (e.g. ID-cards or passports) is rather poor. Our recent research has revealed differences between familiar and unfamiliar face recognition, which account for human perception. However, this analysis - based on an understanding of how faces become familiar - is completely absent from automated systems. Here we propose a project in which knowledge of human familiar face recognition can be built-in to an automated system, and implemented on a chip. The resulting system has considerable potential both commercially, and as a technique for theory development. The project is highly inter-disciplinary, relying on the most recent research methods in psychology and engineering.
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