Learning faces from variability

Research on face learning has tended to use sets of images that vary systematically on dimensions such as pose and illumination. In contrast, we have proposed that exposure to naturally varying images of a person may be a critical part of the familiarization process. Here, we present two experiments investigating face learning with “ambient images”—relatively unconstrained photos taken from internet searches. Participants learned name and face associations for unfamiliar identities presented in high or low within-person variability—that is, images of the same person returned by internet search on their name (high variability) versus different images of the same person taken from the same event (low variability). In Experiment 1 we show more accurate performance on a speeded name verification task for identities learned in high than in low variability, when the test images are completely novel photos. In Experiment 2 we show more accurate performance on a face matching task for identities previously learned in high than in low variability. The results show that exposure to a large range of within-person variability leads to enhanced learning of new identities

Checking ID-cards for the sale of restricted goods : age decisions bias face decisions

Matching unfamiliar faces is highly error-prone, and most studies highlight the implications for real-world ID-checking. Here we study a particular instance of ID-checking: proof of age for buying restricted goods such as alcohol. In this case, checkers must establish that an identity document is carried by its legitimate owner (i.e., that the ID photo matches the face of the bearer) and that the ID proves the bearer to be old enough to make the purchase. Across three experiments, using two common forms of photo-ID (i.e., driving licenses, PASS+ cards) we show that observers produce very high error rates when age requirements are met, but faces mismatch. This bias away from detecting a face mismatch remained evident in experienced cashiers—though to a somewhat attenuated level. We discuss interactions between face matching and other tasks, and the practical consequences of a bias which favours those using photo-ID with fraudulent intent

Matching face images taken on the same day or months apart : The limitations of photo ID

Summary: It is well-established that matching images of unfamiliar faces is rather error prone. However, there is an important mismatch between face matching in laboratory and realistic settings. All of the currently available face-matching databases were designed to establish the baseline level of unfamiliar face perception. Therefore, target and test images for each face identity have been taken on the same day, minimizing within-face variations. In realistic settings, on the other hand, faces do vary, even day to day. This study examined the proficiency of matching images of unfamiliar faces, which were taken on the same day or months apart. In two experiments, same-day images were matched substantially more accurately and faster than different-date photographs using the standard 1-in-10 and pairwise face-matching tasks. This suggests that experimental studies on face matching underestimate its difficulty in real-world situations. Photographs of unfamiliar faces seem to be unreliable proofs of identity, especially if the ID documents do not use very recent images of the holders

Matching face images taken on the same day or months apart : the limitations of photo ID

Peer reviewedPostprin

From pixels to people: a model of familiar face recognition

Research in face recognition has largely been divided between those projects concerned with front-end image processing and those projects concerned with memory for familiar people. These perceptual and cognitive programmes of research have proceeded in parallel, with only limited mutual influence. In this paper we present a model of human face recognition which combines both a perceptual and a cognitive component. The perceptual front-end is based on principal components analysis of images, and the cognitive back-end is based on a simple interactive activation and competition architecture. We demonstrate that this model has a much wider predictive range than either perceptual or cognitive models alone, and we show that this type of combination is necessary in order to analyse some important effects in human face recognition. In sum, the model takes varying images of "known" faces and delivers information about these people

Face matching impairment in developmental prosopagnosia

Developmental prosopagnosia (DP) is commonly referred to as ‘face blindness’, a term that implies a perceptual basis to the condition. However, DP presents as a deficit in face recognition and is diagnosed using memory-based tasks. Here, we test face identification ability in six people with DP, who are severely impaired on face memory tasks, using tasks that do not rely on memory. First, we compared DP to control participants on a standardised test of unfamiliar face matching using facial images taken on the same day and under standardised studio conditions (Glasgow Face Matching Test; GFMT). DP participants did not differ from normative accuracy scores on the GFMT. Second, we tested face matching performance on a test created using images that were sourced from the Internet and so vary substantially due to changes in viewing conditions and in a person’s appearance (Local Heroes Test; LHT). DP participants show significantly poorer matching accuracy on the LHT relative to control participants, for both unfamiliar and familiar face matching. Interestingly, this deficit is specific to ‘match’ trials, suggesting that people with DP may have particular difficulty in matching images of the same person that contain natural day-to-day variations in appearance. We discuss these results in the broader context of individual differences in face matching ability

Causal evidence of the involvement of the right occipital face area in face-identity acquisition

There is growing evidence that the occipital face area (OFA), originally thought to be involved in the construction of a low-level representation of the physical features of a face, is also taking part in higher-level face processing. To test whether the OFA is causally involved in the learning of novel face identities, we have used transcranial magnetic stimulation (TMS) together with a sequential sorting – face matching paradigm (Andrews et al. 2015). First, participants sorted images of two unknown persons during the initial learning phase while either their right OFA or the Vertex was stimulated using TMS. In the subsequent test phase, we measured the participants’ face matching performance for novel images of the previously trained identities and for two novel identities. We found that face-matching performance accuracy was higher for the trained as compared to the novel identities in the vertex control group, suggesting that the sorting task led to incidental learning of the identities involved. However, no such difference was observed between trained and novel identities in the rOFA stimulation group. Our results support the hypothesis that the role of the rOFA is not limited to the processing of low-level physical features, but it has a significant causal role in face identity encoding and in the formation of identity-specific memory-traces

Viewers extract the mean from images of the same person: a route to face learning

Research on ensemble encoding has found that viewers extract summary information from sets of similar items. When shown a set of four faces of different people, viewers merge identity information from the exemplars into a representation of the set average. Here, we presented sets containing unconstrained images of the same identity. In response to a subsequent probe, viewers recognized the exemplars accurately. However, they also reported having seen a merged average of these images. Importantly, viewers reported seeing the matching average of the set (the average of the four presented images) more often than a nonmatching average (an average of four other images of the same identity). These results were consistent for both simultaneous and sequential presentation of the sets. Our findings support previous research suggesting that viewers form representations of both the exemplars and the set average. Given the unconstrained nature of the photographs, we also provide further evidence that the average representation is invariant to several high-level characteristics

Viewers base estimates of face matching accuracy on their own familiarity: Explaining the photo-ID paradox

Matching two different images of a face is a very easy task for familiar viewers, but much harder for unfamiliar viewers. Despite this, use of photo-ID is widespread, and people appear not to know how unreliable it is. We present a series of experiments investigating bias both when performing a matching task and when predicting other people’s performance. Participants saw pairs of faces and were asked to make a same/different judgement, after which they were asked to predict how well other people, unfamiliar with these faces, would perform. In four experiments we show different groups of participants familiar and unfamiliar faces, manipulating this in different ways: celebrities in experiments 1 to 3 and personally familiar faces in experiment 4. The results consistently show that people match images of familiar faces more accurately than unfamiliar faces. However, people also reliably predict that the faces they themselves know will be more accurately matched by different viewers. This bias is discussed in the context of current theoretical debates about face recognition, and we suggest that it may underlie the continued use of photo-ID, despite the availability of evidence about its unreliability