How does a newly encountered face become familiar? The effect of within-person variability on adults' and children's perception of identity

Prior familiarity enhances recognition memory of faces, not just images of faces, when accompanied by conceptual information

A recent paper reported that recognition discriminability was improved for faces that were familiarized prior to study, but only if that familiarization protocol included conceptual information, like a name (Akan & Benjamin, Journal of Memory and Language, 131, 104,433, 2023). In those experiments, familiarity with each facial identity was gained through exposures to the same facial image prior to study, and memory for each facial identity was tested using the same images across study and test. That design characteristic has a serious constraint on generality, since it is possible that prior conceptual information enhances memory for images (of faces), but not for the representation of the face itself. Here we evaluated whether this finding generalizes to a paradigm in which each exposure of a face is a novel image. In two experiments, faces were familiarized with orienting tasks that induced more perceptual or more conceptual processing prior to study and test phases. Results from recognition tests replicated the results from Akan and Benjamin (2023): (1) Discriminability was enhanced when prior familiarity involved conceptual processing but not when it involved perceptual processing, and (2) familiarity gained through either perceptual or conceptual processing led to an increase in both correct and false identifications. This successful replication in a design with exclusively novel images indicates that the discriminability advantage provided by conceptual familiarity goes beyond memory for facial images and applies to memory for faces. These findings have implications in practical contexts, such as eyewitness identification situations involving suspects who are previously known or familiar to the witness.

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.

Ensemble coding of facial identity is robust, but may not contribute to face learning

Ensemble coding - the rapid extraction of a perceptual average - has been proposed as a potential mechanism underlying face learning. We tested this proposal across five pre-registered experiments in which four ambient images of an identity were presented in the study phase. In Experiments 1 and 2a-c, participants were asked whether a test image was in the study array; these experiments examined the robustness of ensemble coding. Experiment 1 replicated ensemble coding in an online sample; participants recognize images from the study array and the average of those images. Experiments 2a-c provide evidence that ensemble coding meets several criteria of a possible learning mechanism: It is robust to changes in head orientation (± 60o), survives a short (30s) delay, and persists when images of two identities are interleaved during the study phase. Experiment 3 examined whether ensemble coding is sufficient for face learning (i.e., facilitates recognition of novel images of a target identity). Each study array comprised four ambient images (variability + average), a single image, or an average of four images (average only). Participants were asked whether a novel test image showed the identity from a study array. Performance was best in the four-image condition, with no difference between the single-image and average-only conditions. We conclude that ensemble coding of facial identity is robust but that the perceptual average per se is not sufficient for face learning.

The impact of stability in appearance on the development of facial representations

The way faces become familiar and what information is represented as familiarity develops has puzzled researchers in the field of human face recognition for decades. In this paper, we present three experiments serving as proof of concept for a cost-efficient mechanism of face learning describing how facial representations form over time and accounting for recognition errors. We propose that the encoding of facial information is dynamic and modulated by the intrinsic stability in individual faces' appearance. We drew on a robust and ecological method using a proxy of exposure to famous faces in the real world and manipulated test images to assess the prediction that recognition of famous faces is affected by their relative stability in appearance. We consistently show that stable facial appearances (like Tom Cruise's) facilitate recognition in early stages of familiarisation but that performance does not improve much over time. In contrast, variations in appearance (like Jared Leto's) hinder recognition at first but improve performance with further media exposure. This pattern of results is consistent with the proposed cost-efficient face learning mechanism whereby facial representations build on a foundation of large-scale diagnostic information and refine over time if needed. When coarse information loses its diagnostic value through the experience of variations in appearance across encounters, diagnostic facial details and/or their spatial relationships must receive more weights, leading to refined representations that are more discriminative and reliable than representations of stable faces.

Provoked overt recognition in acquired prosopagnosia using multiple different images of famous faces

Provoked overt recognition refers to the fact that patients with acquired prosopagnosia can sometimes recognize faces when presented in arrays of individuals from the same category (e.g., actors or politicians). We ask whether a prosopagnosic patient might experience recognition when presented with multiple different images of the same face simultaneously. Over two sessions, patient Herschel, a 66-year-old British man with acquired prosopagnosia, viewed face images individually or in arrays. On several occasions he failed to recognize single photos of an individual but successfully identified that person when the same photos were presented together. For example, Herschel failed to recognize any individual images of King Charles or Paul McCartney but recognised both in arrays of the same photos. Like reports based on category membership, overt recognition was transient and inconsistent. These findings are discussed in terms of models of covert recognition, alongside more recent research on within-person variability for face perception.

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.

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.

The importance of internal and external features in recognizing faces that vary in familiarity and race

Familiar and unfamiliar faces are recognized in fundamentally different ways. One way in which recognition differs is in terms of the features that facilitate recognition: previous studies have shown that familiar face recognition depends more on internal facial features (i.e., eyes, nose and mouth), whereas unfamiliar face recognition depends more on external facial features (i.e., hair, ears and contour). However, very few studies have examined the recognition of faces that vary in both familiarity and race, and the reliance on different facial features, whilst also using faces that incorporate natural within-person variability. In the current study, we used an online version of the card sorting task to assess adults' (n = 258) recognition of faces that varied in familiarity and race when presented with either the whole face, internal features only, or external features only. Adults better recognized familiar faces than unfamiliar faces in both the whole face and the internal features only conditions, but not in the external features only condition. Reasons why adults did not show an own-race advantage in recognition are discussed.

What happens to our representation of identity as familiar faces age? Evidence from priming and identity aftereffects

Matching identity in images of unfamiliar faces is error prone, but we can easily recognize highly variable images of familiar faces - even images taken decades apart. Recent theoretical development based on computational modelling can account for how we recognize extremely variable instances of the same identity. We provide complementary behavioural data by examining older adults' representation of older celebrities who were also famous when young. In Experiment 1, participants completed a long-lag repetition priming task in which primes and test stimuli were the same age or different ages. In Experiment 2, participants completed an identity after effects task in which the adapting stimulus was an older or young photograph of one celebrity and the test stimulus was a morph between the adapting identity and a different celebrity; the adapting stimulus was the same age as the test stimulus on some trials (e.g., both old) or a different age (e.g., adapter young, test stimulus old). The magnitude of priming and identity after effects were not influenced by whether the prime and adapting stimulus were the same age or different age as the test face. Collectively, our findings suggest that humans have one common mental representation for a familiar face (e.g., Paul McCartney) that incorporates visual changes across decades, rather than multiple age-specific representations. These findings make novel predictions for state-of-the-art algorithms (e.g., Deep Convolutional Neural Networks).

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.

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.

Naturalistic Face Learning in Infants and Adults

Everyday face recognition presents a difficult challenge because faces vary naturally in appearance as a result of changes in lighting, expression, viewing angle, and hairstyle. We know little about how humans develop the ability to learn faces despite natural facial variability. In the current study, we provide the first examination of attentional mechanisms underlying adults' and infants' learning of naturally varying faces. Adults (n = 48) and 6- to 12-month-old infants (n = 48) viewed videos of models reading a storybook; the facial appearance of these models was either high or low in variability. Participants then viewed the learned face paired with a novel face. Infants showed adultlike prioritization of face over nonface regions; both age groups fixated the face region more in the high- than low-variability condition. Overall, however, infants showed less ability to resist contextual distractions during learning, which potentially contributed to their lack of discrimination between the learned and novel faces. Mechanisms underlying face learning across natural variability are discussed.

Forgetting faces over a week: investigating self-reported face recognition ability and personality

Background

Although face recognition is now well studied, few researchers have considered the nature of forgetting over longer time periods. Here, I investigated how newly learned faces were recognised over the course of one week. In addition, I considered whether self-reported face recognition ability, as well as Big Five personality dimensions, were able to predict actual performance in a recognition task.

Methods

In this experiment (N = 570), faces were learned through short video interviews, and these identities were later presented in a recognition test (using previously unseen images) after no delay, six hours, twelve hours, one day, or seven days.

Results

The majority of forgetting took place within the first 24 hours, with no significant decrease after that timepoint. Further, self-reported face recognition abilities were moderately predictive of performance, while extraversion showed a small, negative association with performance. In both cases, these associations remained consistent across delay conditions.

Discussion

The current work begins to address important questions regarding face recognition using longitudinal, real-world time intervals, focussing on participant insight into their own abilities, and the process of forgetting more generally.

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

Previous research has shown that exposure to within-person variability facilitates face learning. A different body of work has examined potential benefits of providing multiple images in face matching tasks. Viewers are asked to judge whether a target face matches a single face image (as when checking photo-ID) or multiple face images of the same person. The evidence here is less clear, with some studies finding a small multiple-image benefit, and others finding no advantage. In four experiments, we address this discrepancy in the benefits of multiple images from learning and matching studies. We show that multiple-image arrays only facilitate face matching when arrays precede targets. Unlike simultaneous face matching tasks, sequential matching and learning tasks involve memory and require abstraction of a stable representation of the face from the array, for subsequent comparison with a target. Our results show that benefits from multiple-image arrays occur only when this abstraction is required, and not when array and target images are available at once. These studies reconcile apparent differences between face learning and face matching and provide a theoretical framework for the study of within-person variability in face perception.

Understanding face identification through within-person variability in appearance: Introduction to a virtual special issue

In the effort to determine the cognitive processes underlying the identification of faces, the dissimilarities between images of different people have long been studied. In contrast, the inherent variability between different images of the same face has either been treated as a nuisance variable that should be eliminated from psychological experiments or it has not been considered at all. Over the past decade, research efforts have increased substantially to demonstrate that this within-person variation is meaningful and can give insight into various processes of face identification, such as identity matching, face learning, and familiar face recognition. In this virtual special issue of the Quarterly Journal of Experimental Psychology, we explain the importance of within-person variability for face identification and bring together recent relevant articles published in the journal.

Adults' facial impressions of children's niceness, but not shyness, show modest accuracy

Lay wisdom warns against "judging a book by its cover." However, facial first impressions influence people's behaviour towards others, so it is critical that we understand whether these impressions are at all accurate. Understanding impressions of children's faces is particularly important because these impressions can have social consequences during a crucial time of development. Here, we examined the accuracy of two traits that capture the most variance in impressions of children's faces, niceness and shyness. We collected face images and parental reports of actual niceness/shyness for 86 children (4-11 years old). Different images of the same person can lead to different impressions, and so we employed a novel approach by obtaining impressions from five images of each child. These images were ambient, representing the natural variability in faces. Adult strangers rated the faces for niceness (Study 1) or shyness (Study 2). Niceness impressions were modestly accurate for different images of the same child, regardless of whether these images were presented individually or simultaneously as a group. Shyness impressions were not accurate, for images presented either individually or as a group. Together, these results demonstrate modest accuracy in adults' impressions of niceness, but not shyness, from children's faces. Furthermore, our results reveal that this accuracy can be captured by images which contain natural face variability, and holds across different images of the same child's face. These results invite future research into the cues and causal mechanisms underlying this link between facial impressions of niceness and nice behaviour in children.

Discrimination and recognition of faces with changed configuration

Subtle metric differences in facial configuration, such as between-person variation in the distances between the eyes, have been used widely in psychology to explain face recognition. However, these studies of configuration have typically utilized unfamiliar faces rather than the familiar faces that the process of recognition ultimately seeks to explain. This study investigates whether face recognition relies on the metric information presumed in configural theory, by manipulating the interocular distance in both unfamiliar and familiar faces. In Experiment 1, observers were asked to detect which face in a pair was presented with its configuration intact. In Experiment 2, this discrimination task was repeated with faces presented individually, and observers were also asked to make familiarity categorizations to the same stimuli. In both experiments, familiarity determined detection of faces in their original configuration, and also enhanced identity categorization in Experiment 2. However, discrimination of configuration was generally low. In turn, recognition accuracy was generally high irrespective of configuration condition. Moreover, observers most sensitive to configuration during discrimination did not appear to rely on this information for recognition of familiar faces. These results demonstrate that configuration theory provides limited explanatory power for the recognition of familiar faces.

Face search in CCTV surveillance

Background

We present a series of experiments on visual search in a highly complex environment, security closed-circuit television (CCTV). Using real surveillance footage from a large city transport hub, we ask viewers to search for target individuals. Search targets are presented in a number of ways, using naturally occurring images including their passports and photo ID, social media and custody images/videos. Our aim is to establish general principles for search efficiency within this realistic context.

Results

Across four studies we find that providing multiple photos of the search target consistently improves performance. Three different photos of the target, taken at different times, give substantial performance improvements by comparison to a single target. By contrast, providing targets in moving videos or with biographical context does not lead to improvements in search accuracy.

Conclusions

We discuss the multiple-image advantage in relation to a growing understanding of the importance of within-person variability in face recognition.

Electronic supplementary material

The online version of this article (10.1186/s41235-019-0193-0) contains supplementary material, which is available to authorized users.

Two Sides of Face Learning: Improving Between-Identity Discrimination While Tolerating More Within-Person Variability in Appearance

Two photos of an unfamiliar face are often perceived as belonging to different people—an error that disappears when a face is familiar. Face learning has been characterized as increased tolerance of within-person variability in appearance and is facilitated by exposure to such variability (e.g., differences in expression, lighting, and aesthetics). We hypothesized that increased tolerance of variability in appearance might lead to reduced discrimination and that misidentifications would be reduced if a face was learned in the context of a similar-looking identity. After validating our stimuli (Experiments 1a and 1b), we conducted three experiments investigating face learning. In two of these, participants learned three faces (Experiment 2: 15 images/identity and Experiment 3: 5 images/identity), two of which were similar. In a recognition task, misidentifications did not change as a function of similarity, although participants recognized more images of the target in Experiment 2 (i.e., after learning 15 images). In Experiment 4, participants learned one identity and the number of images studied varied across groups. Recognition of new images increased with the number of images studied, with no changes in false alarms; sensitivity (A′) marginally increased. The results suggest that recognition and discrimination reflect separable processes with minimal influence of between-person similarity on discrimination.

The effects of high variability training on voice identity learning

High variability training has been shown to benefit the learning of new face identities. In three experiments, we investigated whether this is also the case for voice identity learning. In Experiment 1a, we contrasted high variability training sets - which included stimuli extracted from a number of different recording sessions, speaking environments and speaking styles - with low variability stimulus sets that only included a single speaking style (read speech) extracted from one recording session (see Ritchie & Burton, 2017 for faces). Listeners were tested on an old/new recognition task using read sentences (i.e. test materials fully overlapped with the low variability training stimuli) and we found a high variability disadvantage. In Experiment 1b, listeners were trained in a similar way, however, now there was no overlap in speaking style or recording session between training sets and test stimuli. Here, we found a high variability advantage. In Experiment 2, variability was manipulated in terms of the number of unique items as opposed to number of unique speaking styles. Here, we contrasted the high variability training sets used in Experiment 1a with low variability training sets that included the same breadth of styles, but fewer unique items; instead, individual items were repeated (see Murphy, Ipser, Gaigg, & Cook, 2015 for faces). We found only weak evidence for a high variability advantage, which could be explained by stimulus-specific effects. We propose that high variability advantages may be particularly pronounced when listeners are required to generalise from trained stimuli to different-sounding, previously unheard stimuli. We discuss these findings in the context of mechanisms thought to underpin advantages for high variability training.

Social Evaluation of Faces Across Gender and Familiarity

Models of social evaluation aim to capture the information people use to form first impressions of unfamiliar others. However, little is currently known about the relationship between perceived traits across gender. In Study 1, we asked viewers to provide ratings of key social dimensions (dominance, trustworthiness, etc.) for multiple images of 40 unfamiliar identities. We observed clear sex differences in the perception of dominance—with negative evaluations of high dominance in unfamiliar females but not males. In Study 2, we used the social evaluation context to investigate the key predictions about the importance of pictorial information in familiar and unfamiliar face processing. We compared the consistency of ratings attributed to different images of the same identities and demonstrated that ratings of images depicting the same familiar identity are more tightly clustered than those of unfamiliar identities. Such results imply a shift from image rating to person rating with increased familiarity, a finding which generalises results previously observed in studies of identification.

Face perception: A brief journey through recent discoveries and current directions

Faces are a rich source of information about the people around us. Identity, state of mind, emotions, intentions, age, gender, ethnic background, attractiveness and a host of other attributes about an individual can be gleaned from a face. When face perception fails, dramatic psycho-social consequences can follow at the individual level, as in the case of prosopagnosic parents who are unable to recognize their children at school pick-up. At the species level, social interaction patterns are shaped by human face perception abilities. The computational feat of recognizing faces and facial attributes, and the challenges overcome by the human brain to achieve this feat, have fascinated generations of vision researchers. In this paper, we present a brief overview of some of the milestones of discovery as well as outline a selected set of current directions and open questions on this topic.

The Effects of Blur and Inversion on the Recognition of Ambient Face Images

When viewing unfamiliar faces that vary in expressions, angles, and image quality, observers make many recognition errors. Specifically, in unconstrained identity-sorting tasks, observers struggle to cope with variation across different images of the same person while succeeding at telling different people apart. The use of ambient face images in this simple card-sorting task reveals the magnitude of these face recognition errors and suggests a useful platform to reexamine the nature of face processing using naturalistic stimuli. In the present study, we chose to investigate the impact of two basic stimulus manipulations (image blur and face inversion) on identity sorting with ambient images. Although these manipulations are both known to affect face processing when well-controlled, frontally viewed face images are used, examining how they affect performance for ambient images is an important step toward linking the large body of research using controlled face images to more ecologically valid viewing conditions. Briefly, we observed a high cost of image blur regardless of blur magnitude, and a strong inversion effect that affected observers’ sensitivity to extrapersonal variability but did not affect the number of unique identities they estimated were present in the set of images presented to them.

Becoming Familiar With a Newly Encountered Face: Evidence of an Own-Race Advantage

Adults' ability to match identity in images of unfamiliar faces is impaired for other- compared with own-race faces; their ability to match identity in images of familiar faces is independent of face race. Exposure to within-person variability in appearance plays a key role in face learning. Past research suggests that children need exposure to higher levels of variability than adults to learn a new face-a difference that has been attributed to experience. We predicted that adults' limited experience with other-race faces would result in their needing exposure to higher levels of variability when learning other- compared with own-race faces. We introduced adults to four new identities (two own-race; two other-race) in one of the three conditions: a single image, a low-variability video (filmed on 1 day), or a high-variability video (filmed across 3 days). Adults' ability to recognize new instances of learned identities improved in the low-variability condition for own-race faces but only in the high-variability condition for other-race faces. We discuss learning mechanisms that might drive this difference-a difference we attribute to experience.

Tolerance to spatial-relational transformations in unfamiliar faces: A further challenge to a configural processing account of identity recognition

One of the most important questions in face perception research is to understand what information is extracted from a face in order to recognize its identity. Recognition of facial identity has been attributed to a special sensitivity to "configural" information. However, recent studies have challenged the configural account by showing that participants are poor in discriminating variations of metric distances among facial features, especially for familiar as opposed to unfamiliar faces, whereas a configural account predicts the opposite. We aimed to extend these previous results by examining classes of unfamiliar faces with which we have different levels of expertise. We hypothesized an inverse relation between sensitivity to configural information and expertise with a given class of faces, but only for neutral expressions. By first matching perceptual discriminability, we measured tolerance to subtle configural transformations with same-race (SR) versus other-race (OR) faces, and with upright versus upside-down faces. Consistently with our predictions, we found a lower sensitivity to at-threshold configural changes for SR compared to OR faces. We also found that, for our stimuli, the face inversion effect disappeared for neutral but not for emotional faces - a result that can also be attributed to a lower sensitivity to configural transformations for faces presented in a more familiar orientation. The present findings question a purely configural account of face processing and suggest that the role of spatial-relational information in face processing varies according to the functional demands of the task and to the characteristics of the stimuli.

Photo ID verification remains challenging despite years of practice

Background

Matching unfamiliar faces to photographic identification (ID) documents occurs across many domains, including financial transactions (e.g., mortgage documents), controlling the purchase of age-restricted goods (e.g., alcohol sales), and airport security. Laboratory research has repeatedly documented the fallibility of this process in novice observers, but little research has assessed individual differences based on occupational expertise (cf. White et al., PLoS One 9:e103510, 2014; White et al., Proceedings of the Royal Society B 282(1814):20151292, 2015). In the present study, over 800 professional notaries (who routinely verify identity prior to witnessing signatures on legal documents), 70 bank tellers, and 35 undergraduate students completed an online unfamiliar face-matching test. In this test, observers made match/nonmatch decisions to 30 face ID pairs (half of which were matches), with no time constraints and no trial-by-trial feedback.

Results

Results showed that all groups performed similarly, although age was negatively correlated with accuracy. Critically, weekly and yearly experience with unfamiliar face matching did not impact performance.

Conclusions

These results suggest that accumulated occupational experience has no bearing on unfamiliar face ID abilities and that cognitive declines associated with aging also manifest in unfamiliar face matching.

Getting to know you: The development of mechanisms underlying face learning

Nearly every study investigating the development of face recognition has focused on the ability to tell people apart using one or two tightly controlled images to represent each identity. Such research ignores the challenge of recognizing the same person despite variability in appearance. Whereas natural variation in appearance makes unfamiliar faces difficult to recognize, by 6 years of age people easily recognize multiple images of familiar faces. Two mechanisms are proposed to underlie the process by which adults become familiar with newly encountered faces. We provide the first examination of the development of these mechanisms during childhood (6-11 years). In Experiment 1, we examined children's (6- to 10-year-olds') and adults' ability to engage in ensemble coding-the ability to rapidly extract an average representation of an identity from several instances. In Experiment 2, we examined children's ability to use within-person variability in appearance to recognize novel instances of a newly encountered identity. We created a child-friendly perceptual matching task, and the number of images to which participants were exposed varied across targets. Although children were less accurate than adults overall in Experiment 2, we found no age-related improvement in either ensemble coding or the ability to benefit from exposure to within-person variability in appearance when learning a new face, suggesting that both abilities are developed by 6 years of age. We discuss the implications of these findings for understanding the nature of mechanisms underlying face learning and other developmental processes such as language and music.