Recognition of the Ageing Face, 2021-2023

DOI

People can recognise the faces of friends and family across a huge range of conditions, including across changes in age. Changes over time are, however, a problem for unfamiliar face processing. For example, our passports can be up to ten years old, and yet a viewer checking our identity must nevertheless make the match. Some people are particularly good at unfamiliar face processing - people known as super-recognisers are employed in some police and security settings. In addition, trained practitioners, known as forensic examiners, have been found to have an advantage at face matching. However, we do not know whether these people are especially good at generalising photos across age ranges and at matching/recognising age separated images. This project investigated the ability to recognise familiar and unfamiliar faces across age-separated images using a series of behavioural experiments and computational modelling. The data provided here examined the ability to generalise across age in untrained control participants, super-recognisers and forensic examiners.We can recognise the faces of our friends and family across a huge range of conditions. However, despite decades of research, we still do not know how this is achieved. One clue - so far unstudied - arises from our perception of faces as they age. For those around us, we typically only notice face changes when shown an old picture. For famous people, some have spent a lifetime in the public eye (The Queen, Paul McCartney); whereas others are famous for more limited times periods (Angela Merkel, Meghan Markle). How do we represent these people in order to recognise them? In this project, I will study the psychological mechanisms that allow us to recognise the same face across substantial changes. For example, do we need multiple representations of The Queen or Paul McCartney, or have we somehow developed representations of them that are sufficiently general to work across the huge range of their photos? For people known over a more limited time, how well do our representations generalise? Could we recognise Mrs Merkel at 20? In these ways I will study the fundamental processes of face recognition - how do we recognise one another? However, I will be taking advantage of natural changes that occur around us throughout life - changes that are typically ignored in face recognition research, but which I believe could provide critical evidence. Changes over time are also a problem for unfamiliar face processing. For example, our passports can be up to ten years old, and yet a viewer checking our identity must nevertheless make the match. It has been known for many years that unfamiliar face matching is difficult, and it becomes more difficult with larger time intervals between photos. In this project, I will study this problem, and establish the circumstances under which unfamiliar face recognition is prone to age changes, and how this is mitigated by the method of presentation (for example, should a younger image be presented before an older image?). We know that some people are particularly good at unfamiliar face matching - people known as super-recognisers are employed in some police and security settings. However, we do not know whether these people are especially good at generalising photos across age ranges. I will test this, and use the results to establish recommendations for selection and training of personnel in these key roles. In summary, the project examines face recognition across changes in age, using this natural process as an opportunity to gain understanding of a fundamental human ability - our ability to recognise one another.

Behavioural experiments were conducted online. Participants were presented with images of faces at different ages and were asked to make identification responses. Participants were volunteers from the general population and forensic examiners. All participants provided informed consent to take part.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-856788
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=d65c8429db6fcd11e1fc00404f893aee47433d0ebe69e9c6b2803926fa38db3b
Provenance
Creator Laurence, S, The Open University
Publisher UK Data Service
Publication Year 2024
Funding Reference ESRC
Rights Sarah Laurence, The Open University; The UK Data Archive has granted a dissemination embargo. The embargo will end on 24 January 2025 and the data will then be available in accordance with the access level selected.
OpenAccess true
Representation
Resource Type Numeric
Discipline Psychology; Social and Behavioural Sciences
Spatial Coverage United Kingdom