Matching identities of familiar and unfamiliar faces caught on CCTV images.

Bruce, Vicki; Henderson, Zoë; Newman, Craig W.; Burton, A. Mike

doi:10.1037/1076-898x.7.3.207

Cited by 313 publications

(339 citation statements)

References 20 publications

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“…If face recognition can be understood as matching an image to a stored representation, then matching two images of an unfamiliar face will essentially be an image-matching (rather than a face-matching) task. Bruce et al, (1999Bruce et al, ( , 2001 and Hancock et al (2000) suggest that this is exactly the strategy used in unfamiliar face matching, in contrast to a more abstractive approach in which some canonical knowledge of face variation is recruited. In order to become an expert with a familiar face, and be able to recognise it over an increasing range of visual conditions, one simply needs to improve one's representation.…”

Section: Discussionmentioning

confidence: 99%

Robust representations for face recognition: The power of averages

Burton

Jenkins

Hancock

et al. 2005

Cognitive Psychology

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274

297

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We are able to recognise familiar faces easily across large variations in image quality, though our ability to match unfamiliar faces is strikingly poor. Here we ask how the representation of a face changes as we become familiar with it. We use a simple imageaveraging technique to derive abstract representations of known faces. Using Principal Components Analysis, we show that computational systems based on these averages consistently outperform systems based on collections of instances. Furthermore, the quality of the average improves as more images are used to derive it. These simulations are carried out with famous faces, over which we had no control of superficial image characteristics. We then present data from three experiments demonstrating that image averaging can also improve recognition by human observers. Finally, we describe how PCA on image averages appears to preserve identity-specific face information, while eliminating non-diagnostic pictorial information. We therefore suggest that this is a good candidate for a robust face representation.2 Robust representations for face recognition: the power of averages

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Section: Discussionmentioning

confidence: 99%

Robust representations for face recognition: The power of averages

Burton

Jenkins

Hancock

et al. 2005

Cognitive Psychology

Self Cite

274

297

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“…Bruce et al, 1999Bruce et al, , 2001Clutterbuck & Johnston, 2002;Megreya & Burton, 2006). However, when these studies are extended to include live matches, equivalently poor performance is seen.…”

Section: Introductionmentioning

confidence: 99%

Redesigning photo-ID to improve unfamiliar face matching performance.

White¹,

Burton²,

Jenkins³

et al. 2014

Journal of Experimental Psychology: Applied

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Viewers find it difficult to match photos of unfamiliar faces for identity. Despite this, the use of photographic ID is widespread. In this study we ask whether it is possible to improve face matching performance by replacing single photographs on ID documents with multiple photos or an average image of the bearer. In 3 experiments we compare photo-to-photo matching with photo-to-average matching (where the average is formed from multiple photos of the same person) and photo-to-array matching (where the array comprises separate photos of the same person). We consistently find an accuracy advantage for average images and photo arrays over single photos, and show that this improvement is driven by performance in match trials. In the final experiment, we find a benefit of 4-image arrays relative to average images for unfamiliar faces, but not for familiar faces. We propose that conventional photo-ID format can be improved, and discuss this finding in the context of face recognition more generally.

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“…It has been widely established that, while identification of familiar faces from CCTV footage is highly reliable and accurate (Burton, 2013; Burton, Wilson, Cowan & Bruce, 1999), the task of identifying or even matching unfamiliar faces is characterised by a high rate of error (Bruce et al, 1999; Bruce, Henderson, Newman & Burton, 2001; Burton et al, 1999). Indeed, Burton et al (1999) demonstrated that the recognition of familiar faces, even from poor‐quality CCTV, is fast and effortless.…”

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Super‐recognisers in Action: Evidence from Face‐matching and Face Memory Tasks

Bobak

Hancock

Bate

2015

Applied Cognitive Psychology

120

151

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SummaryIndividuals employed in forensic or security settings are often required to compare faces of ID holders to document photographs, or to recognise the faces of suspects in closed‐circuit television footage. It has long been established that both tasks produce a high error rate amongst typical perceivers. This study sought to determine the performance of individuals with exceptionally good face memory (‘super‐recognisers’) on applied facial identity matching and memory tasks. In experiment 1, super‐recognisers were significantly better than controls when matching target faces to simultaneously presented line‐ups. In experiment 2, super‐recognisers were also better at recognising faces from video footage. These findings suggest that super‐recognisers are more accurate at face matching and face memory tasks than typical perceivers, and they could be valuable expert employees in national security and forensic settings. © 2015 The Authors Applied Cognitive Psychology Published by John Wiley & Sons Ltd.

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Matching identities of familiar and unfamiliar faces caught on CCTV images.

Cited by 313 publications

References 20 publications

Robust representations for face recognition: The power of averages

Robust representations for face recognition: The power of averages

Redesigning photo-ID to improve unfamiliar face matching performance.

Super‐recognisers in Action: Evidence from Face‐matching and Face Memory Tasks

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