Low‐quality images are problematic for face identification, for example, when the police identify faces from CCTV images. Here, we test whether face averages, comprising multiple poor‐quality images, can improve both human and computer recognition. We created averages from multiple pixelated or nonpixelated images and compared accuracy using these images and exemplars. To provide a broad assessment of the potential benefits of this method, we tested human observers (n = 88; Experiment 1), and also computer recognition, using a smartphone application (Experiment 2) and a commercial one‐to‐many face recognition system used in forensic settings (Experiment 3). The third experiment used large image databases of 900 ambient images and 7,980 passport images. In all three experiments, we found a substantial increase in performance by averaging multiple pixelated images of a person’s face. These results have implications for forensic settings in which faces are identified from poor‐quality images, such as CCTV.
Researchers have long been interested in how social evaluations are made based upon first impressions of faces. It is also important to consider the level of agreement we see in such evaluations across raters and what this may tell us. Typically, high levels of inter-rater agreement for facial judgements are reported, but the measures used may be misleading. At present, studies commonly report Cronbach’s α as a way to quantify agreement, although problematically, there are various issues with the use of this measure. Most importantly, because researchers treat raters as items, Cronbach’s α is inflated by larger sample sizes even when agreement between raters is fixed. Here, we considered several alternative measures and investigated whether these better discriminate between traits that were predicted to show low (parental resemblance), intermediate (attractiveness, dominance, trustworthiness), and high (age, gender) levels of agreement. Importantly, the level of inter-rater agreement has not previously been studied for many of these traits. In addition, we investigated whether familiar faces resulted in differing levels of agreement in comparison with unfamiliar faces. Our results suggest that alternative measures may prove more informative than Cronbach’s α when determining how well raters agree in their judgements. Further, we found no apparent influence of familiarity on levels of agreement. Finally, we show that, like attractiveness, both trustworthiness and dominance show significant levels of private taste (personal or idiosyncratic rater perceptions), although shared taste (perceptions shared with other raters) explains similar levels of variance in people’s perceptions. In conclusion, we recommend that researchers investigating social judgements of faces consider alternatives to Cronbach’s α but should also be prepared to examine both the potential value and origin of private taste as these might prove informative.
The amygdala is known to play an important role in the response to facial expressions that convey fear. However, it remains unclear whether the amygdala’s response to fear reflects its role in the interpretation of danger and threat, or whether it is to some extent activated by all facial expressions of emotion. Previous attempts to address this issue using neuroimaging have been confounded by differences in the use of control stimuli across studies. Here, we address this issue using a block design functional magnetic resonance imaging paradigm, in which we compared the response to face images posing expressions of fear, anger, happiness, disgust and sadness with a range of control conditions. The responses in the amygdala to different facial expressions were compared with the responses to a non-face condition (buildings), to mildly happy faces and to neutral faces. Results showed that only fear and anger elicited significantly greater responses compared with the control conditions involving faces. Overall, these findings are consistent with the role of the amygdala in processing threat, rather than in the processing of all facial expressions of emotion, and demonstrate the critical importance of the choice of comparison condition to the pattern of results.
The face-selective region of the right posterior superior temporal sulcus (pSTS) plays an important role in analysing facial expressions. However, it is less clear how facial expressions are represented in this region. In this study, we used the face composite effect to explore whether the pSTS contains a holistic or feature-based representation of facial expression. Aligned and misaligned composite images were created from the top and bottom halves of faces posing different expressions. In Experiment 1, participants performed a behavioural matching task in which they judged whether the top half of two images was the same or different. The ability to discriminate the top half of the face was affected by changes in the bottom half of the face when the images were aligned, but not when they were misaligned. This shows a holistic behavioural response to expression. In Experiment 2, we used fMR-adaptation to ask whether the pSTS has a corresponding holistic neural representation of expression. Aligned or misaligned images were presented in blocks that involved repeating the same image or in which the top or bottom half of the images changed. Increased neural responses were found in the right pSTS regardless of whether the change occurred in the top or bottom of the image, showing that changes in expression were detected across all parts of the face. However, in contrast to the behavioural data, the pattern did not differ between aligned and misaligned stimuli. This suggests that the pSTS does not encode facial expressions holistically. In contrast to the pSTS, a holistic pattern of response to facial expression was found in the right inferior frontal gyrus (IFG). Together, these results suggest that pSTS reflects an early stage in the processing of facial expression in which facial features are represented independently.
Models of face processing suggest that the neural response in different face regions is selective for higher-level attributes of the face, such as identity and expression. However, it remains unclear to what extent the response in these regions can also be explained by more basic organizing principles. Here, we used functional magnetic resonance imaging multivariate pattern analysis (fMRI-MVPA) to ask whether spatial patterns of response in the core face regions (occipital face area – OFA, fusiform face area – FFA, superior temporal sulcus – STS) can be predicted across different participants by lower level properties of the stimulus. First, we compared the neural response to face identity and viewpoint, by showing images of different identities from different viewpoints. The patterns of neural response in the core face regions were predicted by the viewpoint, but not the identity of the face. Next, we compared the neural response to viewpoint and expression, by showing images with different expressions from different viewpoints. Again, viewpoint, but not expression, predicted patterns of response in face regions. Finally, we show that the effect of viewpoint in both experiments could be explained by changes in low-level image properties. Our results suggest that a key determinant of the neural representation in these core face regions involves lower-level image properties rather than an explicit representation of higher-level attributes in the face. The advantage of a relatively image-based representation is that it can be used flexibly in the perception of faces.
Existing measures of breast size dissatisfaction have poor ecological validity or have not been fully evaluated in terms of psychometric properties. Here, we report on the development of the Breast Size Rating Scale (BSRS), a novel measure of breast size dissatisfaction consisting of 14 computer-generated images varying in breast size alone. Study 1 (N=107) supported the scale’s construct validity, insofar as participants were able to correctly order the images in terms of breast size. Study 2 (N=234) provided evidence of the test-retest reliability of BSRS-derived scores after 3 months. Studies 3 (N=730) and 4 (N=234) provided evidence of the convergent validity of BSRS-derived breast size dissatisfaction scores, which were significantly associated with a range of measures of body image. The BSRS provides a useful tool for researchers examining women’s breast size dissatisfaction.
Baron-Cohen’s extreme male brain theory proposes that autism results from elevated prenatal testosterone levels. In the present study, we assessed possible correlated effects of androgen exposure on adult morphology and, in particular, the development of facial features associated with masculinity. We created composite images capturing statistical regularities in facial appearance associated with high and low Autism-Spectrum Quotient (AQ) scores. In three experiments, we assessed correlations between perceived facial masculinity and AQ scores. In Experiment 1, observers selected the high-AQ males as more masculine. We replicated this result in Experiment 2, using different photographs, composite-image methods, and observers. There was no association of masculinity and AQ scores for female faces in either study. In Experiment 3, we created high- and low-AQ male composites from the five AQ subscales. High-AQ images were rated more masculine on each of the subscales. We discuss these findings with respect to the organizational-activational hypothesis of testosterone activity during development.
A central research question in natural vision is how to allocate fixation to extract informative cues for scene perception. With high quality images, psychological and computational studies have made significant progress to understand and predict human gaze allocation in scene exploration. However, it is unclear whether these findings can be generalised to degraded naturalistic visual inputs. In this eye-tracking and computational study, we methodically distorted both man-made and natural scenes with Gaussian low-pass filter, circular averaging filter and Additive Gaussian white noise, and monitored participants’ gaze behaviour in assessing perceived image qualities. Compared with original high quality images, distorted images attracted fewer numbers of fixations but longer fixation durations, shorter saccade distance and stronger central fixation bias. This impact of image noise manipulation on gaze distribution was mainly determined by noise intensity rather than noise type, and was more pronounced for natural scenes than for man-made scenes. We furthered compared four high performing visual attention models in predicting human gaze allocation in degraded scenes, and found that model performance lacked human-like sensitivity to noise type and intensity, and was considerably worse than human performance measured as inter-observer variance. Furthermore, the central fixation bias is a major predictor for human gaze allocation, which becomes more prominent with increased noise intensity. Our results indicate a crucial role of external noise intensity in determining scene-viewing gaze behaviour, which should be considered in the development of realistic human-vision-inspired attention models.
Why attention lapses during prolonged tasks is debated, specifically whether errors are a consequence of under-arousal or exerted effort. To explore this, we investigated whether increased impulsivity is associated with effortful processing by modifying the demand of a task by presenting it at a quiet intensity. Here, we consider whether attending at low but detectable levels affects impulsivity in a population with intact hearing. A modification of the Sustained Attention to Response Task was used with auditory stimuli at two levels: the participants’ personal “lowest detectable” level and a “normal speaking” level. At the quiet intensity, we found that more impulsive responses were made compared with listening at a normal speaking level. These errors were not due to a failure in discrimination. The findings suggest an increase in processing time for auditory stimuli at low levels that exceeds the time needed to interrupt a planned habitual motor response. This leads to a more impulsive and erroneous response style. These findings have important implications for understanding the nature of impulsivity in relation to effortful processing. They may explain why a high proportion of individuals with hearing loss are also diagnosed with Attention Deficit Hyperactivity Disorder.
Our recognition of familiar faces is excellent, and generalises across viewing conditions. However, unfamiliar face recognition is much poorer. For this reason, automatic face recognition systems might benefit from incorporating the advantages of familiarity. Here we put this to the test using the face verification system available on a popular smartphone (the Samsung Galaxy). In two experiments we tested the recognition performance of the smartphone when it was encoded with an individual’s ‘face-average’ – a representation derived from theories of human face perception. This technique significantly improved performance for both unconstrained celebrity images (Experiment 1) and for real faces (Experiment 2): users could unlock their phones more reliably when the device stored an average of the user’s face than when they stored a single image. This advantage was consistent across a wide variety of everyday viewing conditions. Furthermore, the benefit did not reduce the rejection of imposter faces. This benefit is brought about solely by consideration of suitable representations for automatic face recognition, and we argue that this is just as important as development of matching algorithms themselves. We propose that this representation could significantly improve recognition rates in everyday settings.