Multiple-image arrays in face matching tasks with and without memory

Multiple images captured from a single encounter do not promote face learning

Viewing multiple images of a newly encountered face improves recognition of that identity in new instances. Studies examining face learning have presented high-variability (HV) images that incorporate changes that occur from moment-to-moment (e.g., head orientation and expression) and over time (e.g., lighting, hairstyle, and health). We examined whether low-variability (LV) images (i.e., images that incorporate only moment-to-moment changes) also promote generalisation of learning such that novel instances are recognised. Participants viewed a single image, six LV images, or six HV images of a target identity before being asked to recognise novel images of that identity in a face matching task (training stimuli remained visible) or a memory task (training stimuli were removed). In Experiment 1 (n = 71), participants indicated which image(s) in 8-image arrays belonged to the target identity. In Experiment 2 (n = 73), participants indicated whether sequentially presented images belonged to the target identity. Relative to the single-image condition, sensitivity to identity improved and response biases were less conservative in the HV condition; we found no evidence of generalisation of learning in the LV condition regardless of testing protocol. Our findings suggest that day-to-day variability in appearance plays an essential role in acquiring expertise with a novel face.

Face masks and fake masks: the effect of real and superimposed masks on face matching with super-recognisers, typical observers, and algorithms

Mask wearing has been required in various settings since the outbreak of COVID-19, and research has shown that identity judgements are difficult for faces wearing masks. To date, however, the majority of experiments on face identification with masked faces tested humans and computer algorithms using images with superimposed masks rather than images of people wearing real face coverings. In three experiments we test humans (control participants and super-recognisers) and algorithms with images showing different types of face coverings. In all experiments we tested matching concealed or unconcealed faces to an unconcealed reference image, and we found a consistent decrease in face matching accuracy with masked compared to unconcealed faces. In Experiment 1, typical human observers were most accurate at face matching with unconcealed images, and poorer for three different types of superimposed mask conditions. In Experiment 2, we tested both typical observers and super-recognisers with superimposed and real face masks, and found that performance was poorer for real compared to superimposed masks. The same pattern was observed in Experiment 3 with algorithms. Our results highlight the importance of testing both humans and algorithms with real face masks, as using only superimposed masks may underestimate their detrimental effect on face identification.

Unfamiliar face matching ability predicts the slope of face learning

We provide the first examination of individual differences in the efficiency of face learning. Investigating individual differences in face learning can illuminate potential mechanisms and provide greater understanding of why certain individuals might be more efficient face learners. Participants completed two unfamiliar face matching tasks and a learning task in which learning was assessed after viewing 1, 3, 6, and 9 images of to-be-learned identities. Individual differences in the slope of face learning (i.e., increases in sensitivity to identity) were predicted by the ability to discriminate between matched (same-identity) vs. mismatched (different-identity) pairs of wholly unfamiliar faces. A Dual Process Signal Detection model showed that three parameters increased with learning: Familiarity (an unconscious type of memory that varies in strength), recollection-old (conscious recognition of a learned identity), and recollection-new (conscious/confident rejection of novel identities). Good (vs. poor) matchers had higher Recollection-Old scores throughout learning and showed a steeper increase in Recollection-New. We conclude that good matchers are better able to capitalize on exposure to within-person variability in appearance, an effect that is attributable to their conscious memory for both learned and novel faces. These results have applied implications and will inform contemporary and traditional models of face identification.

Stable individual differences in unfamiliar face identification: Evidence from simultaneous and sequential matching tasks

Matching identity in images of unfamiliar faces is difficult: Images of the same person can look different and images of different people can look similar. Recent studies have capitalized on individual differences in the ability to distinguish match (same ID) vs. mismatch (different IDs) face pairs to inform models of face recognition. We addressed two significant gaps in the literature by examining the stability of individual differences in both sensitivity to identity and response bias. In Study 1, 210 participants completed a battery of four tasks in each of two sessions separated by one week. Tasks varied in protocol (same/different, lineup, sorting) and stimulus characteristics (low vs. high within-person variability in appearance). In Study 2, 148 participants completed a battery of three tasks in a single session. Stimuli were presented simultaneously on some trials and sequentially on others, introducing short-term memory demands. Principal components analysis revealed two components that were stable across time and tasks: sensitivity to identity and bias. Analyses of response times suggest that individual differences in bias reflect decision-making processes. We discuss the implications of our findings in applied settings and for models of face recognition.

Two face masks are better than one: congruency effects in face matching

Although the positive effects of congruency between stimuli are well replicated in face memory paradigms, mixed findings have been found in face matching. Due to the current COVID-19 pandemic, face masks are now very common during daily life outdoor activities. Thus, the present study aims to further explore congruency effects in matching faces partially occluded by surgical masks. Observers performed a face matching task consisting of pairs of faces presented in full view (i.e., full-view condition), pairs of faces in which only one of the faces had a mask (i.e., one-mask condition), and pairs of faces in which both faces had a mask (i.e., two-mask condition). Although face masks disrupted performance in identity match and identity mismatch trials, in match trials, we found better performance in the two-mask condition compared to the one-mask condition. This finding highlights the importance of congruency between stimuli on face matching when telling faces together.

Perceptual similarity modulates effects of learning from variability on face recognition

Face recognition is a challenging classification task that humans perform effortlessly for familiar faces. Recent studies have emphasized the importance of exposure to high variability appearances of the same identity to perform this task. However, these studies did not explicitly measure the perceptual similarity between the learned images and the images presented at test, which may account for the advantage of learning from high variability. Particularly, randomly selected test images are more likely to be perceptually similar to learned high variability images, and dissimilar to learned low variability images. Here we dissociated effects of learning from variability and study-test perceptual similarity, by collecting human similarity ratings for the study and test images. Using these measures, we independently manipulated the variability between the learning images and their perceptual similarity to the test images. Different groups of participants learned face identities from a low or high variability set of images. The learning phase was followed by a face matching test (Experiment 1) or a face recognition task (Experiment 2) that presented novel images of the learned identities that were perceptually dissimilar or similar to the learned images. Results of both experiments show that perceptual similarity between study and test, rather than image variability at learning per se, predicts face recognition. We conclude that learning from high variability improves face recognition for perceptually similar but not for perceptually dissimilar images. These findings may not be specific to faces and should be similarly evaluated for other domains.

Image variability and face matching

This study investigates whether variability in perceived trait judgements disrupts our ability to match unfamiliar faces. In this preregistered study, 174 participants completed a face matching task where they were asked to indicate whether two ambient face images belonged to the same person or different people (17,748 total data points). Participants completed 51 match trials consisting of images of the same person that differed substantially on one trait (either trustworthiness, dominance or attractiveness) with minimal differences in the alternate traits. Participants also completed 51 mismatch trials which contained two photos of similar-looking individuals. We hypothesised that participants would make more errors on match trials when images differed in terms of attractiveness ratings than when they differed on trustworthiness or dominance. Contrary to expectations, images that differed in terms of attractiveness were matched most accurately, and there was no relationship between the extent of differences in attractiveness ratings and accuracy. There was some evidence that differences in perceived dominance and, to a lesser extent, trustworthiness were associated with lower face matching performance. However, these relationships were not significant when alternate traits were accounted for. The findings of our study suggest that face matching performance is largely robust against variation in trait judgements.

Children's ability to recognize their parent's face improves with age

Adults are experts at recognizing familiar faces across images that incorporate natural within-person variability in appearance (i.e., ambient images). Little is known about children's ability to do so. In the current study, we investigated whether 4- to 7-year-olds (n = 56) could recognize images of their own parent-a person with whom children have had abundant exposure in a variety of different contexts. Children were asked to identify images of their parent that were intermixed with images of other people. We included images of each parent taken both before and after their child was born to manipulate how close the images were to the child's own experience. When viewing before-birth images, 4- and 5-year-olds were less sensitive to identity than were older children; sensitivity did not differ when viewing images taken after the child was born. These findings suggest that with even the most familiar face, 4- and 5-year-olds have difficulty recognizing instances that go beyond their direct experience. We discuss two factors that may contribute to the prolonged development of familiar face recognition.

Multi-cultural cities reduce disadvantages in recognizing naturalistic images of other-race faces: evidence from a novel face learning task

People often find it more difficult to recognize other- than own-race faces. This other-race effect is robust across numerous ethnic groups. Yet, it remains unclear how this effect changes in people who live in a multiracial environment, and in immigrants whose lifetime perceptual experience changes over time. In the present study, we developed a novel face recognition test that approximates face recognition in the real world. We tested five groups of White and East Asian adults (n = 120) living in racially homogeneous versus heterogeneous cities and East Asians who immigrated to a multiracial city between infancy and adulthood. Multiracial cities reduce the other-race effect. The magnitude of the other-race effect changes as a function of experience, mirroring the racial diversity in perceivers' living environment. Our study highlights the challenge of forming reliable face representations across naturalistic facial variability and suggests a facilitative role of multiracial environments in eliminating the other-race effect.

The pairs training effect in unfamiliar face matching

A wealth of studies have shown that humans are remarkably poor at determining whether two face images show the same person or not (face matching). Given the prevalence of photo-ID, and the fact that people employed to check photo-ID are typically unfamiliar with the person pictured, there is a need to improve unfamiliar face matching accuracy. One method of improvement is to have participants complete the task in a pair, which results in subsequent improvements in the low performer (“the pairs training effect”). Here, we sought to replicate the original finding, to test the longevity of the pairs training effect, and to shed light on the potential underlying mechanisms. In two experiments, we replicated the pairs training effect and showed it is maintained after a delay (Experiment 1). We found no differences between high and low performers in confidence (Experiment 1) or response times (Experiment 2), and the content of the pairs’ discussions (Experiment 2) did not explain the results. The pairs training effect in unfamiliar face matching is robust, but the mechanisms underlying the effects remain as yet unexplained.

Face learning via brief real-world social interactions includes changes in face-selective brain areas and hippocampus

Making new acquaintances requires learning to recognise previously unfamiliar faces. In the current study, we investigated this process by staging real-world social interactions between actors and the participants. Participants completed a face-matching behavioural task in which they matched photographs of the actors (whom they had yet to meet), or faces similar to the actors (henceforth called foils). Participants were then scanned using functional magnetic resonance imaging (fMRI) while viewing photographs of actors and foils. Immediately after exiting the scanner, participants met the actors for the first time and interacted with them for 10 min. On subsequent days, participants completed a second behavioural experiment and then a second fMRI scan. Prior to each session, actors again interacted with the participants for 10 min. Behavioural results showed that social interactions improved performance accuracy when matching actor photographs, but not foil photographs. The fMRI analysis revealed a difference in the neural response to actor photographs and foil photographs across all regions of interest (ROIs) only after social interactions had occurred. Our results demonstrate that short social interactions were sufficient to learn and discriminate previously unfamiliar individuals. Moreover, these learning effects were present in brain areas involved in face processing and memory.

Learning faces from variability: Four- and five-year-olds differ from older children and adults

Children under 6 years of age have difficulty recognizing a familiar face across changes in appearance and telling the face apart from similar-looking people. Understanding the process by which newly encountered faces become familiar can provide insights into these difficulties. Exposure to the ways in which a person varies in appearance is one mechanism by which adults and older children (≥6 years) learn new faces. We provide the first investigation of whether this mechanism for face learning functions in younger children. Children aged 4 and 5 years were read two storybooks featuring an unfamiliar character. Participants viewed six images of the character in one story and one image of the character in the other story. After each story, children were asked to identify novel images of the character that were intermixed with images of a similar-looking distractor. Like older children, 4- and 5-year-olds were more sensitive to identity in the 6-image condition, but they also adapted a less conservative criterion. Young children identified more images of the character after viewing six images versus one image. However, many also incorrectly identified more images of the distractor after viewing six images versus one image, an effect not previously found for older children and adults. These results suggest that this mechanism for face learning is not fully refined before 6 years of age.

Visual search performance in 'CCTV' and mobile phone-like video footage

Finding an unfamiliar person in a crowd of others is an integral task for police officers, CCTV-operators, and security staff who may be looking for a suspect or missing person; however, research suggests that it is difficult and accuracy in such tasks is low. In two real-world visual-search experiments, we examined whether being provided with four images versus one image of an unfamiliar target person would help improve accuracy when searching for that person through video footage. In Experiment 1, videos were taken from above and at a distance to simulate CCTV, and images of the target showed their face and torso. In Experiment 2, videos were taken from approximately shoulder height, such as one would expect from body-camera or mobile phone recordings, and target images included only the face. Our findings suggest that having four images as exemplars leads to higher accuracy in the visual search tasks, but this only reached significance in Experiment 2. There also appears to be a conservative bias whereby participants are more likely to respond that the target is not in the video when presented with only one image as opposed to 4. These results point to there being an advantage for providing multiple images of targets for use in video visual-search.