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Face identity recognition: Exploring the role of observer motion and motion of viewed person


Project Description

The ability to identify people around us is crucial to our everyday lives, determining the nature of our social interactions and relationships. Recent work has explored the role of motion in the recognition of identity. Here, the observer remains static whilst the viewed face or body moves. Recognition advantages have been shown for both rigid (head movement) and non-rigid (movement of face features) motion, across a range of different tasks. However, these experiments still overlook the most common situation in which people view faces – i.e. during self-movement of the observer’s head and/or eyes. Such movements cause complex but structured patterns of retinal motion (‘optic flow’) that interact with movement of external stimuli (e.g. the viewed individual’s face). In this PhD project we plan to use behavioural experiments and virtual reality (VR) to explore the interaction between movement of the viewed individual and movement of the observer, for identity recognition.

According to the flow parsing hypothesis (FPH), proposed by Rushton and (co-Supervisor) Warren, the brain is engaged in a continual process of identifying optic flow in the retinal motion field and attempting to filter it out so that remaining motion can be attributed to external sources. We propose that flow parsing plays a key role in the process of natural face recognition during observer movement.

Objectives
1. To understand the interaction between movement of the viewed face / body and movement of the observer and how this aids our theoretical understanding of face recognition
2. To explore the role of optic flow parsing in face processing
3. To investigate the practical implications of observer movement on face learning and establish new standards in ecologically valid tests of face processing ability

Training/techniques to be provided:
Training in appropriate experimental methods will be provided by the supervisory team. The PhD student will be using the recently established VR2 facility in the Division of Neuroscience and Experimental Psychology. Training on this equipment and facilities will be provided by the lead VR2 technician (Mr Graham Bell). Candidates without programming experience will also have the opportunity to learn these skills to generate experimental code/stimuli but this is not compulsory.

Entry Requirements:
Candidates are expected to hold, or about to obtain, a minimum upper second class undergraduate degree (or equivalent) in psychology, cognitive neuroscience, neuroscience, computer science or another related discipline (including some engineering). A Masters degree in a relevant subject would be an advantage.

This 3-year full-time PhD is open to candidates able to provide evidence of self-arranged funding/ sponsorship and could commence from January 2020 onwards.

Any enquiries relating to the project and/or suitability should be directed to Dr Lander (). Applications are invited on an on-going basis but early expression of interest is encouraged.

For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit http://www.internationalphd.manchester.ac.uk

Funding Notes

Applications are invited from self-funded students. This project has a Band 1 fee. Details of our different fee bands can be found on our website (View Website). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (View Website).

As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

References

Bulthoff, I., Mohler, B.J. & Thornton, I.M. (2019). Face recognition of full-bodied avatars by active
observers in a virtual environment. Vision Research, 157, 243-251.
Butcher, N., Lander, K., & Jagger, R. (2017). A search advantage for dynamic same-race and other-ace
faces. Visual Cognition, 25, 442-455.
Lander, K., & Chuang, L. (2005).Why are moving faces easier to recognize? Visual Cognition, 12, 429–
442.
Rushton, S.K. & Warren P.A. (2005). Moving observers, relative retinal motion and the detection of object
movement. Current Biology, 15, R542-R543.
Warren P. A. & Rushton, S.K. (2009). Optic Flow Processing for the assessment of Object Movement
during Ego Movement. Current Biology, 19, 1555-1560.

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