High scores are a signal that you could be a super-recogniser. However to be classified as a super-recogniser we typically look for consistently high scores across multiple tests. In our lab, we get super-recognisers to complete four tests: the UNSW Face Test, the Glasgow Face Matching Test (GFMT), the difficult version of the Glasgow Face Matching Test 2 (GFMT2-H), and the Extended Cambridge Face Memory Test (CFMT+). If an individual meets the cut off score on each test, then they are a super-recogniser.
To be considered a super-recogniser, you need to score at least as high as the following scores on each test:
UNSW Face Test: 69% or above
Glasgow Face Matching Test (GFMT): 100%
Glasgow Face Matching Test 2 (GFMT2-H): 90.2% or above
Cambridge Face Memory Test (CFMT+): 89.9% or above
Disclaimer: However, as face recognition research evolves… it is likely the cut off scores and our understanding of super-recognisers will as well – so don’t write yourself off as a super-recogniser just yet if you don’t meet this criterion!
Here are how particular scores on each test will rank you against others:
UNSW Face Test
If you scored 73% or above, you are in the top 1% of participants.
If you scored 69% or above, you are in the top 5% of participants.
If you scored 67% or above, you are in the top 10% of participants.
If you scored 63% or above, you are in the top 25% of participants.
If you scored 59% or above, you are in the top 50% of participants.
Glasgow Face Matching Test (GFMT)
If you scored 100%, you are in the top 3% of participants.
If you scored 98% or above, you are in the top 5% of participants.
If you scored 94% or above, you are in the top 10% of participants.
If you scored 88% or above, you are in the top 25% of participants.
If you scored 81% or above, you are in the top 50% of participants.
Glasgow Face Matching Test 2 (GFMT2-H)
If you scored 97% or above, you are in the top 1% of participants.
If you scored 90% or above, you are in the top 5% of participants.
If you scored 87% or above, you are in the top 10% of participants.
If you scored 81% or above, you are in the top 25% of participants.
If you scored 74% or above, you are in the top 50% of participants.
Cambridge Face Memory Test (CFMT+)
If you scored 98% or above, you are in the top 1% of participants.
If you scored 90% or above, you are in the top 5% of participants.
If you scored 85% or above, you are in the top 10% of participants.
If you scored 78% or above, you are in the top 25% of participants.
If you scored 69% or above, you are in the top 50% of participants.
You are welcome to retake the tests as many times as you’d like, however for scientific purposes we can only take the scores from a first attempt into consideration when determining if an individual is a super-recogniser. This is because redoing the test could result in a practice effect which elevates the test scores in a way that isn’t fair to individuals completing the test only once.
The UNSW Face Research Lab team does not provide employment opportunities. However, we do have paid research participation studies arise from time to time for people who are a part of our registry. Here is the link to join the UNSW Face Registry if you have not done so already: https://unswpsy.au1.qualtrics.com/jfe/form/SV_cO38pTXZNVr5yg5.
Currently, employment opportunities requiring this skill set are limited to specialist roles, and so far, these positions are not externally advertised. For example, super-recognisers in police forces were police officers first, and then identified as super-recognisers after (see: https://newsroom.unsw.edu.au/news/science-tech/how-unsw-psychologists-helped-nsw-police-find-super-recognisers-its-ranks). As research continues to better understand face recognition and the abilities of super-recognisers, there is increasing interest in areas such as law enforcement and border security, so there may be scope for more employment opportunities in the future.
The UNSW Face Lab also have some other tests available on our registry which you can com-plete at your leisure using the test links below. Please note, these tests are not used to deter-mine whether someone is a super-recogniser but do contribute to our research understanding how face recognition ability relates to other cognitive skills.
• Model Matching Test (approx. 20-30 minutes to complete)
• Fingerprint Matching Test (approx. 20-30 minutes to complete)
• Prosopagnosia Index (PI-20) (approx. 5-10 minutes to complete)
Our researchers have published numerous papers on topics like whether face recognition can be improved, whether some facial features are more useful than others in minimising face recognition errors and, more recently, which factors underly superior face recognition. Below is a link to a published research paper on our UNSW Face Test that was created by a research team in our lab. There are also some press links that you might find interesting to read/listen to.
UNSW Face Test article: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0241747
News article: https://theconversation.com/are-you-among-australias-best-facial-super-recognisers-take-our-test-to-find-out-150089
TV and radio appearances:
Facebook: We also have a Facebook page where we occasionally share our latest research (https://www.facebook.com/UNSWFaceTest).
The UNSW Face Registry involves a battery of tests which were designed to investigate human face-recognition ability. Some of the tests measure face-matching ability, face-memory ability, or both. This allows us to tease apart whether people are good at face memory only, face matching only, or good at both. They also help us investigate whether face recognition ability is linked to other cognitive abilities like fingerprint matching.
• UNSW Face Test: The UNSW Face Test is a general test of face-recognition ability. It consists of two tasks which measure your face-memory and face-matching ability. Including this test allows us to discriminate between participants who typically achieve very high performance on other face-recognition tests.
• Glasgow Face Matching Test: In the Glasgow Face Matching Test (GFMT) you are shown two face images side-by-side and are asked to decide whether they show the same person or two different people. By including the GFMT in our battery of tests we can get an objective measure of your unfamiliar face-matching ability.
• Glasgow Face Matching Test 2-H: The Glasgow Face Matching Test 2 (GFMT2-H) is similar to the GFMT in design however rather than black and white passport style images, participants are shown pictures which vary in head angle, expression, subject-to-camera distance and colour.
• Extended Cambridge Face Memory Test: The Extended Cambridge Face Memory Test (CFMT+) measures your face-memory ability, that is, your ability to learn and recognise unfamiliar faces. This means that instead of making an identification decision on simultaneously presented face images you are asked to learn a series of faces and then later tested on your memory of these faces.
• Model Matching Test: The Models Face Matching Test (Models) asks you to make ‘same person’ or ‘different people’ identity decisions for pairs of faces. Like the GFMT, it is an objective measure of unfamiliar face-matching ability.
• Prosopagnosia-Index: The Prosopagnosia-Index (PI20) is a self-report questionnaire containing 20 statements. It is frequently used in research to gauge individuals’ perception of their own face-recognition ability. Including the PI-20 allows us to look at whether your own insight into how well you interact with faces in an everyday context matches your face-recognition performance on the other tests. In our research we use the PI20 as a gauge of an individual’s perception of their own face-recognition ability. Low PI20 scores indicate that an individual believes they’re quite good at recognising faces whereas high scores indicate that individuals believe they are poorer at recognising faces.
• Fingerprint Matching Test: The Fingerprint Matching Test looks at object (non-face) recognition ability. You are asked to decide whether two fingerprints are from the same person or two different people. This test is included to understand which recognition abilities are the same across face and non-face objects.
Our research concerns the full spectrum of ability however we do not categorise congenital Prosopagnosia (CP) or non-CP. There is a research lab at the University of Western Australia focusing on Prosopagnosia. Prosopagnosia is an inability to recognise familiar faces. If you’re curious, below is a link to their website which may offer explanations behind lower to average face recognition ability. Link: https://www.uwa.edu.au/projects/prosopagnosia-research
As face recognition ability is believed to largely driven by genetics, it is most likely that super-recognisers were simply born that way. Beyond this, research has only recently started to focus on looking at what factors explain the wide range of face recognition ability we observe in the general public. For example, in our most recent work we measured eye movements of super-recognisers to examine how they look at faces when they initially encounter a new face and later recognise them.
We have found that the biggest differences between super-recognisers and the general population are found when they initially encounter a face. Super-recognisers may be reading the faces differently which causes them to paint a more vivid picture of the face in their minds eye.
There seems to be no gender ‘advantage’ for face recognition. Our findings indicate quite an equal distribution of male and females at all levels of face recognition ability. If there is an unequal distribution, it is because the sample is not an equal representation of genders. If you are curious, below is a paper about the UNSW Face Test and in the link, within S1 Appendix, there is a discussion about our findings on gender.
For more information see: UNSW Face Test: A screening tool for super-recognizers | PLOS ONE
Currently, there is some evidence to suggest a correlation in ability between those with superior face recognition and voice recognition. Below is a link to a podcast and an open access journal article which discusses this.
Voice and face recognition podcast: https://www.news-medical.net/news/20230103/Voice-and-face-recognition-are-more-closely-linked-than-previously-thought.aspx
Voice and face recognition article: https://onlinelibrary.wiley.com/doi/full/10.1002/acp.3813
There’s a lot of research into people’s face recognition abilities for different races. In the scien-tific literature, this is generally referred to as the ‘other-race effect’ (put forth by Malpass and Kravitz in 1969). It describes the finding that people recognise faces from their own race more accurately compared to other races.
Why the other race effect occurs is still under dispute and needs more research. One account is that the other race effect is affected by a person’s ‘experience’ or ‘contact’ with people from their own race, so that those with more contact with another race will have a small other-race effect than others who have less contact with that race.
If you want to read more about the other-race effect more generally, below is a link to a recent study looking into the other race effect for super-recognisers by Robertson and colleagues in 2019, and best of all this article is free to access. In summary, they found super-recognisers (those with superior facial recognition abilities) also had an other-race effect.
For more information see: https://onlinelibrary.wiley.com/doi/10.1002/acp.3608.
If you are having issues accessing the test, try opening the link up in a different browser. Alter-natively, you could try opening up a private browser. If you are unsure of how to do this, below are some instructions on how to achieve private browsing for some common browsers.
1. On your computer, open Chrome. At the top right, click More New Incognito Window. A new window appears. In the top corner, check for the Incognito icon or
2. You can also use a keyboard shortcut to open an Incognito window: Windows, Linux, or Chrome OS: Press Ctrl + Shift + n Mac: Press ⌘ + Shift + n
1. Open the Safari browser. Press Command + Shift + N keys at the same time or
2. Open the Safari browser. Click the File menu at the top of the browser window. In the file menu, select New Private Window
1. Select and hold (right-click) the Microsoft Edge logo in the taskbar and select New InPrivate window or
2. Select and hold (right-click) a link and select Open link in InPrivate window or
3. Select Settings and more > New InPrivate window
1. Click on Settings > Safety > InPrivate Browsing or
2. You can also use the keyboard shortcut Ctrl+Shift+P to launch it.
1. Click on Settings > New Private Window or
2. The keyboard shortcut Ctrl+Shift+P works here too
1. Click on the Opera settings button > New private window or
2. The keyboard shortcut is Ctrl+Shift+N
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