Recognizing face identity from natural and morphed smiles

It is easier to identify a degraded familiar face when it is shown moving (smiling, talking; nonrigid motion), than when it is displayed as a static image (Knight & Johnston, 1997; Lander, Christie, & Bruce, 1999). Here we explore the theoretical underpinnings of the moving face recognition advantage. In Experiment 1 we show that the identification of personally familiar faces when shown naturally smiling is significantly better than when the person is shown artificially smiling (morphed motion), as a single static neutral image or as a single static smiling image. In Experiment 2 we demonstrate that speeding up the motion significantly impairs the recognition of identity from natural smiles, but has little effect on morphed smiles. We conclude that the recognition advantage for face motion does not reflect a general benefit for motion, but suggests that, for familiar faces, information about their characteristic motion is stored in memory.     

Recognizing face identity from natural and morphed smiles

It is easier to identify a degraded familiar face when it is shown moving (smiling, talking; nonrigid motion), than when it is displayed as a static image (Knight & Johnston, 1997; Lander, Christie, & Bruce, 1999). Here we explore the theoretical underpinnings of the moving face recognition advantage. In Experiment 1 we show that the identification of personally familiar faces when shown naturally smiling is significantly better than when the person is shown artificially smiling (morphed motion), as a single static neutral image or as a single static smiling image. In Experiment 2 we demonstrate that speeding up the motion significantly impairs the recognition of identity from natural smiles, but has little effect on morphed smiles. We conclude that the recognition advantage for face motion does not reflect a general benefit for motion, but suggests that, for familiar faces, information about their characteristic motion is stored in memory.     

Why are moving faces easier to recognize?

Previous work has suggested that seeing a famous face move aids the recognition of identity, especially when viewing conditions are degraded (Knight & Johnston, ; Lander, Christie, & Bruce, ). Experiment 1 investigated whether the beneficial effects of motion are related to a particular type of facial motion (expressing, talking, or rigid motion). Results showed a significant beneficial effect of both expressive and talking movements, but no advantage for rigid motion, compared with a single static image. Experiment 2 investigated whether the advantage for motion is uniform across identity. Participants rated moving famous faces for distinctiveness of motion. The famous faces (moving and static freeze frame) were then used as stimuli in a recognition task. The advantage for face motion was significant only when the motion displayed was distinctive. Results suggest that a reason why moving faces are easier to recognize is because some familiar faces have characteristic motion patterns, which act as an additional cue to identity.     

Repetition priming from moving faces

Recent experiments have suggested that seeing a familiar face move provides additional dynamic information to the viewer, useful in the recognition of identity. In four experiments, repetition priming was used to investigate whether dynamic information is intrinsic to the underlying face representations. The results suggest that a moving image primes more effectively than a static image, even when the same static image is shown in the prime and the test phases (Experiment 1). Furthermore, when moving images are presented in the test phase (Experiment 2), there is an advantage for moving prime images. The most priming advantage is found with naturally moving faces, rather than with those shown in slow motion (Experiment 3). Finally, showing the same moving sequence at prime and test produced more priming than that found when different moving sequences were shown (Experiment 4). The results suggest that dynamic information is intrinsic to the face representations and that there is an advantage to viewing the same moving sequence at prime and test.     

Getting to know you: How we learn new faces

Previous work has shown an advantage for matching the internal features of familiar faces in contrast to an advantage for the external features of unfamiliar faces. In the current experiment, we tracked this shift towards an internal feature advantage as subjects were familiarized with a set of initially unfamiliar faces. They were asked to learn a set of 24 faces from video images and complete a face matching task on 3 consecutive days. Half of the faces were learned from moving images while the others were learned from static images to determine whether movement was necessary to produce the internal advantage found when matching familiar faces. We found that by the end of the 3 days, performance on the internal features had improved and was equivalent to performance on the external features. In contrast, matching of the external features remained at a relatively constant level across the experiment. Faces were learned equally well from moving and static images suggesting that movement is not necessary to promote learning of the internal features.     

The role of motion in learning new faces

Four experiments are reported that investigate the usefulness of rigid (head nodding, shaking) and nonrigid (talking, expressions) motion for establishing new face representations of previously unfamiliar faces. Results show that viewing a face in motion leads to more accurate face learning, compared with viewing a single static image (Experiment 1). The advantage for viewing the face moving rigidly seems to be due to the different angles of view contained in these sequences (Experiment 2). However, the advantage for nonrigid motion is not simply due to multiple images (Experiment 3) and is not specifically linked to forwards motion but extends to reversed sequences (Experiment 4). Thus, although we have demonstrated beneficial effects of motion for face learning, they do not seem to be due to the specific dynamic properties of the sequences shown. Instead, the advantage for nonrigid motion may reflect increased attention to faces moving in a socially important manner.     

Do children utilize motion when recognizing faces?

Previous research indicates that unfamiliar faces may be recognized better if they are viewed in motion. This study utilized a three trial learning paradigm to investigate whether unfamiliar faces are learnt more quickly from moving clips than from static images. Children aged 6–7 years and 10–11 years were shown a series of faces as either static images or dynamic clips, followed by either by a static or a dynamic recognition test. Faces were recognized more accurately when presented in motion, but there was no advantage for testing in motion. Although older children were more accurate overall, younger females performed as well as older children for faces presented in motion, suggesting that females’ face processing skills develop more quickly than those of males. Results are discussed in terms of the motion advantage arising due to additional structural information enhancing the internal representation of the face.     

Demonstrating how unfamiliar faces become familiar using a face matching task

Two experiments examine a novel method of assessing face familiarity that does not require explicit identification of presented faces. Earlier research (Clutterbuck & Johnston, 2002; Young, Hay, McWeeny, Flude, & Ellis, 1985) has shown that different views of the same face can be matched more quickly for familiar than for unfamiliar faces. This study examines whether exposure to previously novel faces allows the speed with which they can be matched to be increased, thus allowing a means of assessing how faces become familiar. In Experiment 1, participants viewed two sets of unfamiliar faces presented for either many, short intervals or for few, long intervals. At test, previously familiar (famous) faces were matched more quickly than novel faces or learned faces. In addition, learned faces seen on many, brief occasions were matched more quickly than the novel faces or faces seen on fewer, longer occasions. However, this was only observed when participants performed “different” decision matches. In Experiment 2, the similarity between face pairs was controlled more strictly. Once again, matches were performed on familiar faces more quickly than on unfamiliar or learned items. However, matches made to learned faces were significantly faster than those made to completely novel faces. This was now observed for both same and different match decisions. The use of this matching task as a means of tracking how unfamiliar faces become familiar is discussed.     

Exploring the role of characteristic motion when learning new faces

Previous research has shown that it is easier to recognize familiar faces when shown moving, rather than static, especially when viewing conditions are difficult (Knight & Johnston, 1997 Knight, B. and Johnston, A. 1997. The role of movement in face recognition. Visual Cognition, 4: 265–273. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]; Lander, Christie, & Bruce, 1999 Bruce, V., Henderson, Z., Greenwood, K., Hancock, P. J. B., Burton, A. M. and Miller, P. 1999. Verification of face identities from images captured on video. Journal of Experimental Psychology: Applied, 5: 339–360. [Crossref], [Web of Science ®] , [Google Scholar]). One possible theoretical reason for the moving-face advantage is that we learn “characteristic motion signatures” for familiar faces, associated with the face representation in memory. To examine this idea we investigated the role of motion at test when learning faces from either static images or moving sequences (Experiment 1). Results suggest that there is only an advantage for motion at test when the face is learned moving. In Experiment 2 we map the importance of facial motion as a face becomes increasingly familiar, on a television drama. We demonstrate that the beneficial effect of motion is not dependent on the amount of time the face is viewed. Results from both experiments support the idea of rapidly learned characteristic motion patterns.     

The role of dynamic information in the recognition of unfamiliar faces

The effects of movement on unfamiliar face recognition were investigated. In an incidental learning task, faces were studied either as computer-animated (moving) displays or as a series of static images, with identical numbers of frames shown for each. The movements were either nonrigid transformations (changes in expression) or rigid rotations in depth (nodding or shaking). At test, participants saw either single, static images or moving sequences. Only one experiment showed a significant effect of study type, in favor of static instances. There was no additional advantage from studying faces in motion in these experiments, in which both study types showed the same amounts of information. Recognition memory was relatively unaffected by changes in expression between study and test. Effects of viewpoint change were large when expressive transformations had been studied but much smaller when rigid rotations in depth had been studied. The series of experiments did reveal a slight advantage for testing memory with moving compared with static faces, consistent with recent findings using familiar faces. Future work will need to examine whether such effects may also be due to the additional information provided by an animated sequence.     

The role of movement in the recognition of famous faces

The effects of movement on the recognition of famous faces shown in difficult conditions were investigated. Images were presented as negatives, upside down (inverted), and thresholded. Results indicate that, under all these conditions, moving faces were recognized significantly better than static ones. One possible explanation of this effect could be that a moving sequence contains more static information about the different views and expressions of the face than does a single static image. However, even when the amount of static information was equated (Experiments 3 and 4), there was still an advantage for moving sequences that contained their original dynamic properties. The results suggest that the dynamics of the motion provide additional information, helping to access an established familiar face representation. Both the theoretical and the practical implications for these findings are discussed.     

Walk this way: approaching bodies can influence the processing of faces

A highly familiar type of movement occurs whenever a person walks towards you. In the present study, we investigated whether this type of motion has an effect on face processing. We took a range of different 3D head models and placed them on a single, identical 3D body model. The resulting figures were animated to approach the observer. In a first series of experiments, we used a sequential matching task to investigate how the motion of an approaching person affects immediate responses to faces. We compared observers’ responses following approach sequences to their performance with figures walking backwards (receding motion) or remaining still. Observers were significantly faster in responding to a target face that followed an approach sequence, compared to both receding and static primes. In a second series of experiments, we investigated long-term effects of motion using a delayed visual search paradigm. After studying moving or static avatars, observers searched for target faces in static arrays of varying set sizes. Again, observers were faster at responding to faces that had been learned in the context of an approach sequence. Together these results suggest that the context of a moving body influences face processing, and support the hypothesis that our visual system has mechanisms that aid the encoding of behaviourally-relevant and familiar dynamic events.     

Evaluating the effectiveness of pixelation and blurring on masking the identity of familiar faces

Two experiments are reported that assess how well the identity of highly familiar (famous) faces can be masked from short naturalistic television clips. Recognition of identity was made more difficult by either pixelating (Experiment 1) or blurring (Experiment 2) the viewed face. Participants were asked to identify faces from both moving and static clips. Results indicated that participants were still able to recognize some of the viewed faces, despite these image degradations. In addition, moving images of faces were recognized better than static ones. The practical and theoretical implications of these findings are discussed. Copyright © 2001 John Wiley & Sons, Ltd.     

Learning influences the encoding of static and dynamic faces and their recognition across different spatial frequencies

Studies on face recognition have shown that observers are faster and more accurate at recognizing faces learned from dynamic sequences than those learned from static snapshots. Here, we investigated whether different learning procedures mediate the advantage for dynamic faces across different spatial frequencies. Observers learned two faces—one dynamic and one static—either in depth (Experiment 1) or using a more superficial learning procedure (Experiment 2). They had to search for the target faces in a subsequent visual search task. We used high-spatial frequency (HSF) and low-spatial frequency (LSF) filtered static faces during visual search to investigate whether the behavioural difference is based on encoding of different visual information for dynamically and statically learned faces. Such encoding differences may mediate the recognition of target faces in different spatial frequencies, as HSF may mediate featural face processing whereas LSF mediates configural processing. Our results show that the nature of the learning procedure alters how observers encode dynamic and static faces, and how they recognize those learned faces across different spatial frequencies. That is, these results point to a flexible usage of spatial frequencies tuned to the recognition task.     

Caricature generalization benefits for faces learned with enhanced idiosyncratic shape or texture

Recent findings show benefits for learning and subsequent recognition of faces caricatured in shape or texture, but there is little evidence on whether this caricature learning advantage generalizes to recognition of veridical counterparts at test. Moreover, it has been reported that there is a relatively higher contribution of texture information, at the expense of shape information, for familiar compared to unfamiliar face recognition. The aim of this study was to examine whether veridical faces are recognized better when they were learned as caricatures compared to when they were learned as veridicals—what we call a caricature generalization benefit. Photorealistic facial stimuli derived from a 3-D camera system were caricatured selectively in either shape or texture by 50 %. Faces were learned across different images either as veridicals, shape caricatures, or texture caricatures. At test, all learned and novel faces were presented as previously unseen frontal veridicals, and participants performed an old–new task. We assessed accuracies, reaction times, and face-sensitive event-related potentials (ERPs). Faces learned as caricatures were recognized more accurately than faces learned as veridicals. At learning, N250 and LPC were largest for shape caricatures, suggesting encoding advantages of distinctive facial shape. At test, LPC was largest for faces that had been learned as texture caricatures, indicating the importance of texture for familiar face recognition. Overall, our findings demonstrate that caricature learning advantages can generalize to and, importantly, improve recognition of veridical versions of faces.     

The State of Ecological Psychology

We report on two experiments that investigated the role of facial motion in the recognition of degraded famous face images. The results of these experiments suggest that seeing a face move is advantageous for the correct recognition of identity. This effect is not solely due to the extra static-based information contained in a moving sequence but is also due to additional dynamic information available from a moving face. Furthermore, famous faces were recognized more accurately when the original dynamic characteristics of the motion were maintained (Experiment 1), compared to when either the tempo or the direction of motion were altered (Experiment 2). It is suggested that there may be general benefit for viewing naturally moving faces, not specific benefit to any particular face identity. Alternatively, individual faces may have associated characteristic motion signatures.     

The effect of motion at encoding and retrieval for same- and other-race face recognition

In an experimental study, we assessed the role of motion when encoding and recognizing unfamiliar faces, using an old/new recognition memory paradigm. Our findings revealed a clear advantage for learning unfamiliar faces moving non-rigidly, compared with static faces. This advantage for motion was found with both same- and other-race faces. Furthermore, results indicate that it is more important that the face is learnt in motion than recognized from a moving clip. Interestingly, despite a reliable other-race effect being revealed, participants were able to utilize motion information exhibited by other-race faces in a manner akin to the motion advantage found for same-race faces. The implications of these findings are discussed in relation to the nature of the stored face representations, considering whether the facilitative role found here can be explained by factors other than motion per se.     

Learning the moves: the effect of familiarity and facial motion on person recognition across large changes in viewing format

Familiarity with a face or person can support recognition in tasks that require generalization to novel viewing contexts. Using naturalistic viewing conditions requiring recognition of people from face or whole body gait stimuli, we investigated the effects of familiarity, facial motion, and direction of learning/test transfer on person recognition. Participants were familiarized with previously unknown people from gait videos and were tested on faces (experiment 1a) or were familiarized with faces and were tested with gait videos (experiment 1b). Recognition was more accurate when learning from the face and testing with the gait videos, than when learning from the gait videos and testing with the face. The repetition of a single stimulus, either the face or gait, produced strong recognition gains across transfer conditions. Also, the presentation of moving faces resulted in better performance than that of static faces. In experiment 2, we investigated the role of facial motion further by testing recognition with static profile images. Motion provided no benefit for recognition, indicating that structure-from-motion is an unlikely source of the motion advantage found in the first set of experiments.     

中国学生的自我面孔识别

已有研究表明大脑右半球具有自我面孔再认的优势。为了进一步验证这个观点,该研究使用面孔识别任务,以13名右利手的中国大学生为被试,测量被试对morphing面孔的左右手反应差异。给被试呈现第一张面孔向第二张面孔的morphing过程,当被试看到morphing的面孔更像第二张面孔时报告停止。研究有两个morphing过程：一个为由自我面孔向名人面孔morphing,另一个为好朋友面孔（熟悉的）向名人面孔morphing。结果表明当用左手反应时,被试倾向于把morphing的面孔识别为自己,研究中自我面孔再认的左手优势与已有的发现一致。另外,研究还发现在一定trials条件下,熟悉面孔再认也具有左手优势,这一结果与西方被试的结果不一致,但东西方被试对熟悉面孔再认的差异与独立型自我和互倚型自我的观点一致。该文认为神经心理学有关自我的研究可能需要考虑文化和情境的复杂性。     

Perceptual learning and acquired face familiarity: Evidence from inversion,use of internal features,and generalization between viewpoints

Pairs of similar faces were created from photographs of different people using morphing software. The ability of participants to discriminate between novel pairs of faces and between those to which they had received brief, unsupervised, exposure (5×2 s each) was assessed. In all experiments exposure improved discrimination performance. Overall, discrimination was better when the faces were upright, but exposure produced improved discrimination for both upright and inverted faces (Experiment 1). The improvement produced by exposure was selective to internal face features (Experiment 2) and was evident when there was a change in orientation (three-quarter to full face or vice versa) between exposure and test (Experiment 3). These findings indicate that perceptual learning observed following brief exposure to faces exhibit well-established hallmarks of familiar face processing (i.e., internal feature advantage and insensitivity to a change of viewpoint). Considered in combination with previous studies using the same type of stimuli (Mundy, Honey, & Dwyer, 2007), the current results imply that general perceptual learning mechanisms contribute to the acquisition of face familiarity.