text:
- Original article
- Open Access
Applied screening tests for the detection of superior face recognition
- Sarah Bate1Email authorView ORCID ID profile,
- Charlie Frowd2,
- Rachel Bennetts3,
- Nabil Hasshim1,
- Ebony Murray1,
- Anna K. Bobak1,
- Harriet Wills1 and
- Sarah Richards1
© The Author(s) 2018
- Received: 25 January 2018
- Accepted: 20 April 2018
- Published: 27 June 2018
In recent years there has been growing interest in the identification of people with superior face recognition skills, for both theoretical and applied investigations. These individuals have mostly been identified via their performance on a single attempt at a tightly controlled test of face memory—the long form of the Cambridge Face Memory Test (CFMT+). The consistency of their skills over a range of tests, particularly those replicating more applied policing scenarios, has yet to be examined systematically. The current investigation screened 200 people who believed they have superior face recognition skills, using the CFMT+ and three new, more applied tests (measuring face memory, face matching and composite-face identification in a crowd). Of the sample, 59.5% showed at least some consistency in superior face recognition performance, although only five individuals outperformed controls on overall indices of target-present and target-absent trials. Only one participant outperformed controls on the Crowds test, suggesting that some applied face recognition tasks require very specific skills. In conclusion, future screening protocols need to be suitably thorough to test for consistency in performance, and to allow different types of superior performer to be detected from the outset. Screening for optimal performers may sometimes need to directly replicate the task in question, taking into account target-present and target-absent performance. Self-selection alone is not a reliable means of identifying those at the top end of the face recognition spectrum.
- Face recognition
- Individual differences
- Super recognisers
- Composite face-processing
In recent years there has been increasing real-world interest in the identification of people with naturally proficient face recognition skills. Because computerised face recognition systems are yet to replicate the capacity of human perceivers, individuals with superior skills may be particularly useful in policing scenarios. Such tasks may involve matching or identifying faces captured in CCTV footage, or "spotting" wanted perpetrators in a crowd. However, little work has considered the screening tests and protocols that should be used to identify top human performers, and existing real-world and laboratory procedures tend to rely on performance on a single attempt at a test of face memory. The findings of this paper highlight the need for objective screening of all available personnel, without influence of self-selection. Screening protocols should be suitably thorough to allow for detection of different types of superior performer, allowing independent detection of those who are adept at either face memory or face matching. Recruitment of top performers for some very specific face recognition tasks (e.g. those involving artificial facial stimuli) may require direct replication of the task in hand. In sum, these findings call for a review of "super recogniser" screening protocols in real-world settings.
Increasing work is examining individual differences in face recognition (e.g. Bate, Parris, Haslam, & Kay, 2010; Wilmer, 2017; Yovel, Wilmer, & Duchaine, 2014), with particular interest in people who lie at the two extremes. At the lower end of the spectrum are those with very poor face recognition skills who may have a condition known as "developmental prosopagnosia" (Bate & Cook, 2012; Bennetts, Butcher, Lander, Udale, & Bate, 2015; Burns et al., 2017; Dalrymple & Palermo, 2016; Duchaine & Nakayama, 2006), whereas those at the top end have an extraordinary ability to recognise faces (Bobak, Pampoulov, & Bate, 2016; Russell, Duchaine, & Nakayama, 2009). These so-called "super recognisers" (SRs) are of both theoretical and practical importance: while examination of the cognitive and neural underpinnings of this proficiency can inform our theoretical understanding of the typical and impaired face-processing system (Bate & Tree, 2017; Bennetts, Mole, & Bate, 2017; Bobak, Bennetts, Parris, Jansari, & Bate, 2016; Bobak, Parris, Gregory, Bennetts, & Bate, 2017; Ramon et al., 2016), SRs may also be useful in policing and security settings (Bobak, Dowsett, & Bate, 2016; Bobak, Hancock, & Bate, 2016; Davis, Lander, Evans, & Jansari, 2016; Robertson, Noyes, Dowsett, Jenkins, & Burton, 2016). However, most studies have relied on a single laboratory test of face recognition to identify SRs (for a review see Noyes, Phillips, & O'Toole, 2017) and the consistency of their skills across a larger variety of more applied face recognition tasks has yet to be examined systematically. This is an important issue as the police need to ensure that any officers (or police staff) deployed for specific face recognition tasks are indeed the best candidates for the job.
Clearly, then, a consistent diagnostic approach needs to be implemented by both researchers and their beneficiaries. Most investigations have "confirmed" super recognition in their experimental participants via the long form of the Cambridge Face Memory Test (CFMT+), a test that was initially described in the first published investigation into super recognition (Russell et al., 2009). The CFMT+ is an extended version of the standard Cambridge Face Memory Test (CFMT; Duchaine & Nakayama, 2006), in which participants are required to learn the faces of six individuals, and are tested on 72 triads of faces where they are asked to select one of the target faces. The standard version of the CFMT is a dominant test that is used worldwide to diagnose prosopagnosia (e.g. Bate, Adams, Bennetts, & Line, in press; Bowles et al., 2009; Dalrymple & Palermo, 2016; McKone et al., 2011), and has been shown to have high reliability (Bowles et al., 2009; Wilmer, Germine, Chabris, et al., 2010) and both convergent and divergent validity (Bowles et al., 2009; Dennett et al., 2012; Wilmer, Germine, Chabris, et al., 2010; Wilmer, Germine, Loken, et al., 2010). Alternative versions of the CFMT possess similar properties, indicating that the paradigm provides a reliable assessment of face memory (Bate et al., 2014; McKone et al., 2011; Wilmer, Germine, Loken, et al., 2010). To make the test suitable for the detection of SRs, the CFMT+ follows the identical format of the original CFMT but includes 30 additional, more difficult trials (Russell et al., 2009). Both group-based (Russell et al., 2009) and more conservative case-by-case (e.g. Bobak et al., 2016; Bobak, Dowsett, & Bate, 2016) statistics have been used to identify superior performance on the extended test, suggesting that it is appropriately calibrated for this task.
The latter statistical approach is important when considering the potential for heterogeneity in super recognition, as it allows researchers to examine the consistency of performance in each individual (as opposed to a group as a whole) across tests that tap into different processes. There is a theoretical basis for this assumption of heterogeneity when examining the patterns of presentation that have been observed in those with developmental prosopagnosia. Specifically, while some of these individuals appear to only have difficulties in their memory for faces (e.g. Bate, Haslam, Jansari, & Hodgson, 2009; Lee, Duchaine, Wilson, & Nakayama, 2010; McKone et al., 2011), others also have impairments in the perception of facial identity (i.e. when asked to make a judgement on the identity of an individual without placing any demands on memory; Bate et al., 2009; Chatterjee & Nakayama, 2012; Duchaine, Germine, & Nakayama, 2007). Given that this dissociation has also been observed in acquired cases of prosopagnosia (Barton, Press, Keenan, & O'Connor, 2002; De Haan, Young, & Newcombe, 1987, 1991; De Renzi, Faglioni, Grossi, & Nichelli, 1991), and hypotheses that developmental prosopagnosia simply resides at the bottom of a common face recognition spectrum where super recognition lies at the top (Barton & Corrow, 2016; Bate & Tree, 2017), a logical prediction is that some SRs may be proficient at both face memory and face perception, whereas others may have abilities that are restricted to one sub-process. In fact, some existing investigations into super recognition present evidence that supports this possibility, albeit with very small sample sizes (Bobak, Bennetts, et al., 2016; Bobak, Dowsett, & Bate, 2016; Bobak et al., 2016).
Such studies have assessed face perception skills in SRs using a variety of paradigms. For instance, the landmark SR paper of Russell et al. (2009) assessed face perception skills via the Cambridge Face Perception Test (CFPT; Duchaine et al., 2007). This test presents sets of six faces that have each been morphed to a different level of similarity from a target face. In each trial, participants are required to sort the faces in terms of their similarity to the identity of the target. While this test is frequently used to assess facial identity perception impairments in prosopagnosia (Bate & Tree, 2017; Bowles et al., 2009; Dalrymple & Palermo, 2016), it is not suitably calibrated for the detection of more able participants. Indeed, the large variability (and correspondingly large standard deviation) that has been observed in the performance of control participants prevents single-case comparisons at the top end from reaching significance (Bobak, Pampoulov, & Bate, 2016), and the reliability of the test has not yet been examined. Further, the very discrete artificially manipulated differences between images do not resemble a typical real-world face perception task, and the precise perceptual processes that are being assessed by the test remain unclear.
Other researchers have used face matching tasks to assess face perception, where participants are required to decide whether simultaneously presented pairs of faces display the same or different identities (e.g. Bobak, Dowsett, & Bate, 2016; Davis et al., 2016; Robertson et al., 2016). Another investigation assessed SRs on the well-used "One-in-Ten" test (Bruce et al., 1999), where participants are required to decide whether a target face is present within simultaneously presented line-ups containing 10 faces (Bobak et al., 2016). The studies reported by Bobak and Davis subsequently found that only some individuals outperformed controls on measures of face perception. Thus, because current protocols initially require superior performance on a test of face memory for experimental inclusion as a SR, the only available evidence suggests that superior face memory skills can present without superior face perception skills, and the converse has not yet been investigated. This clearly has both theoretical (e.g. in testing the assumptions of hierarchical accounts of face-processing) and practical (e.g. when seeking police officers who are proficient at particular face recognition tasks) importance; and further investigation into the patterns and prevalence of different subtypes of super recognition is sorely needed, using a wider variety of screening tests.
It is also pertinent that some inconsistencies have been observed in the performance of SRs across multiple measures of face memory or face perception (Bobak, Bennetts, et al., 2016; Bobak et al., 2016; Davis et al., 2016). This may indicate that some individuals achieve superior scores on a single attempt at a single test simply due to chance, and further testing reveals their true, more average abilities. Alternatively, differences in paradigm may bring about inconsistencies in performance, as has already been illustrated for face perception (i.e. in the use of the CFPT versus face matching tasks; see Bobak, Pampoulov, & Bate, 2016). That is, some individuals may have skills that are only suited to certain face-processing tasks, and this hypothesis may also extend to tests of face memory. For instance, all images of each individual identity in the CFMT+ were collected under tightly controlled conditions on the same day (Duchaine & Nakayama, 2006; Russell et al., 2009). Although some variability was incorporated into the greyscale images via changes in viewpoint, lighting, expression or the addition of noise, these manipulations do not capture the same variability that presents between images of the same person that have been collected on different days in a variety of naturalistic settings. Further, the CFMT+ only presents target-present trials, and does not assess the frequently encountered real-world scenario where a target face is actually absent. While another test used by Russell et al. (2009) may circumvent the former issue, it does not overcome the latter. Specifically, a "Before They Were Famous" test required participants to identify adult celebrities from childhood photographs, but no target-absent trials were included. Perhaps more fundamentally, the test is hampered by the difficulty of objective assessment across individuals due to potentially large differences in lifetime exposure to the target celebrities.
Finally, it could be argued that self-reported evidence of everyday face recognition may be used as a potential means to identify SRs. Such evidence could be collected anecdotally, or through more formal self-report questionnaires. Yet this issue of metacognition, particularly in relation to face recognition, has been much debated. While there is some evidence that self-report of everyday face recognition performance may be used as an approximate gauge of face recognition skills in the typical population (Bindemann, Attard, & Johnston, 2014; Bowles et al., 2009; Gray, Bird, & Cook, 2017; McGugin, Richler, Herzmann, Speegle, & Gauthier, 2012; Rotshtein, Geng, Driver, & Dolan, 2007) and those who may have prosopagnosia (e.g. Shah, Gaule, Sowden, Bird, & Cook, 2015), such investigations tend to only have mild-to-moderate effect sizes, and there is ample evidence and arguments to the contrary (e.g. Duchaine, 2008; Palermo et al., 2017; Tree, 2011). However, this issue has not yet been investigated at the top end of the face recognition spectrum, and it is possible that these individuals have a more accurate awareness of the level of their face recognition skills compared to those with typical or impaired abilities.
In sum, SRs need to be reliably identified for both theoretical and applied investigations, yet existing tests and protocols are open to criticism. As already stated, the main criterion for inclusion in a SR sample is superior performance on the CFMT+. While this procedure may overlook any candidate who is proficient only at face perception and not at face memory, it may also be overly simplistic by only taking one score on a single test at a single point in time as the critical measure. Indeed, some individuals may perform in the superior range on that occasion simply by chance, whereas others may fall short of the cut-off value due to extraneous variables such as fatigue, illness or simply "having a bad day". Examining the consistency of performance across a variety of more applied tests that tap the same and different components of face-processing will address this issue, and ensure that the correct individuals are allocated to specific tasks in real-world settings.
The current paper set out to address these issues in a large number of adult Caucasian participants who had self-referred to our laboratory in the belief that they have superior face recognition skills. Because of the large sample size and diverse geography of the participants, the study was carried out online. In order to examine the accuracy of self-selection for SR research, we initially calculated the proportion of our sample who objectively met at least one criterion for super recognition. We then investigated the heterogeneity of super recognition by looking for dissociations between measures of face memory and face perception (although note that the consistency of face perception skills was not assessed across tests in the current paper). However, because our testing battery contained both traditional and more applied tests, we were able to examine consistency of performance across different measures of assessment.
Following large-scale media coverage of our previous work, a large number of individuals self-referred to our laboratory (via our website: www.prosopagnosiaresearch.org) in the belief that they possess superior face recognition skills. All participants were invited to take part in the screening programme, and 424 subsequently completed all four of the tests that are described in this paper. However, 224 participants were excluded from the final dataset to leave a sample size of 200 (140 female; age range 18–50 years; M = 37.2, SD = 7.7). Exclusions were made on the basis of age (> 50 years), ethnicity (only Caucasian participants were retained—if non-Caucasian participants were included in the study, renowned own-race biases in face recognition suggest that independent, appropriately matched control groups would be needed; e.g. Meissner & Brigham, 2001), reported assistance with the tests, self-reported or computer-reported technical problems, and previous exposure to the CFMT+. All participants took part in the study online and on a voluntary basis, motivated by the desire to discover whether they fit the criteria for super recognition. This group of individuals as a whole is referred to as the "experimental group" for the remainder of this paper.
Forty control participants (20 male) also participated in this study. Their mean age was 33.4 years (range 18–50 years, SD = 10.2), and these participants were compensated for their time in order to ensure their motivation on the tasks. Because it is possible that differences in performance may be noted between online and laboratory-tested participants, we tested half of these participants (10 female) online and the remaining half under laboratory conditions.
Four objective tests were used in this investigation: the pre-existing CFMT+ and three new tests that were developed for the purposes of this study. The latter tests were designed to reflect more ecologically valid face recognition tasks, particularly those that may be encountered in policing scenarios. All tasks were designed to be carried out as accurately as possible, although, in an attempt to avoid particularly long response latencies, participants were informed that completion times would also be analysed. However, because the overall aim of this paper is to examine patterns of accuracy across tests, we only focus on this measure.
The CFMT+ (Russell et al., 2009)
This test is an extended version of the original CFMT (Duchaine & Nakayama, 2006), a dominant test of unfamiliar face recognition that uses tightly controlled greyscale facial images. In the standard test, participants initially encode the faces of six unfamiliar males. Three views of each target face are shown (frontal, and left and right profiles) for 3 s each, and participants are immediately required to select the identical images from three triads of faces. Eighteen points are available for this section, and most typical participants receive full marks (Bobak, Pampoulov, & Bate, 2016; Bowles et al., 2009)—an unremarkable feat given that the task simply requires pictorial recognition following a minimal delay. Participants then review all six target faces again for a duration of 20 s. They are subsequently required to select a target face from 30 triads of faces, now presented from novel viewpoints or lighting conditions. After another 20-s review of the target faces, 24 further triads are presented, with noise overlaid onto the images. The CFMT+ extends this section by including an additional 30 triads with more extreme changes in facial expression or viewpoint, providing a total score out of 102. All triads in the test contain a target face, and some distractors are repeated to enhance difficulty. Participants make responses using the 1–3 number keys on a keyboard, and triads remain on-screen until a response is made. Reaction time is not monitored.
Models memory test (MMT)
Our new test maintained a similar encoding procedure to that used in the CFMT+ (see Fig. 1): for each target face, three different images are each presented for 3 s, followed by three test triads where participants are required to select the repeated image. However, instead of each face being initially shown from three viewpoints, we displayed three frontal images of each face that were taken on different days in very different settings. To create the testing triads, each image of a target was matched to two distractor faces from the pool, according to their external facial features and viewpoint. These 18 encoding trials do not contribute to the overall score. We did maintain the first 20-s review of the six target faces from the CFMT+ (presented immediately after the encoding phase), but displayed a new frontal image of each target that was again taken on a different day and in a different environment.
Participants then received 90 test trials (45 target-present), in a random order for each participant, with a screen break after the first 45 trials. The inclusion of target-absent trials differs from the CFMT+. Because the latter is a direct development of a test that is designed to detect prosopagnosia, the inclusion of target-absent trials may result in low-ability participants eliciting this response on every trial. However, those who are truly at the higher end of the spectrum should be adept at both correct identifications and correct rejections—as is required in policing scenarios and in real-life interactions. Thus, by including both target-present and target-absent trials, our new test provides a more encompassing assessment of participants' face recognition abilities. As in the encoding phase, very different images of each target were included in the test triads. We collected a further five to seven images of each target face, and five distractor faces were selected from the pool that were considered to match each individual target image. Two were combined with the target image to form a target-present triad, and the remaining three were combined to form a matched target-absent triad. The resulting 90 triads were then divided into two equal groups, with the first containing images that were more similar to the encoding images of the target faces (i.e. those taken from similar viewpoints with minimal changes in facial appearance) and the second containing triads with more abrupt changes (i.e. the addition of facial hair or accessories that obscured part of the face, or a more dramatic change in viewpoint).
For each trial, participants were required to respond with the corresponding number key (1–3) to indicate the position of a target in the triad, or with the 0 key if they believed the triad to be target-absent. As in the CFMT+, each triad remains on-screen until a response is made. After completing the first 45 trials, participants view an instruction screen that invites them to have a brief rest before beginning the final, more challenging phase of the test. However, contrary to the CFMT+, this phase does not commence with an additional review of the target faces, in order to maintain the enhanced difficulty of the task.
Because of the inclusion of target-absent trials, five different categories of responses are possible in the task. In trials with a target face present, participants' responses can be categorised as either hits (correctly identifying the target face), misses (incorrectly saying that a target face was not present) or misidentifications (incorrectly identifying one of the distractor faces as a target). In trials without a target face, responses can be categorised as either correct rejections (correctly stating that no target face was present) or false positives (incorrectly identifying one of the faces as a target). Each of these measures was calculated separately for each participant, along with an overall accuracy score (the sum of hits and correct rejections).
Pairs matching test (PMT)
Crowds matching test
We made use of the EvoFIT holistic system, in current police use, as the resulting faces can be readily named by other people (e.g. M = 45% correct in Frowd et al., 2012). Constructors repeatedly select from arrays of alternatives, with choices combined, to allow a composite face to be "evolved"; the procedure involves focus on the internal features of the face, the area that is important for familiar-face recognition (e.g. Ellis, Shepherd, & Davies, 1979) and naming of the composite. We used a standard face-construction protocol (Frowd et al., 2012), as undertaken by real witnesses and victims of crime, and the composites were constructed by different participants after each person had seen an unfamiliar target face. As the procedure for set up of the stimuli (including composite face construction) is fairly involved, full details are provided in Additional file 1.
The experimental group initially filled in an online questionnaire that enquired about background demographical information and checked each participant's belief that they have superior face recognition skills. They were then sent online links to the four objective tests, which they completed in a counterbalanced order. After all tests were complete, participants were sent a "quality control" questionnaire that asked whether they had experienced any technical problems during completion of the tests, if they had received any assistance from other people and whether they have previously completed the CFMT+.
Control participants were recruited via Bournemouth University's established participant network, and were randomly allocated to either the online or laboratory condition. Those who completed the tests online were sent the links to the tests in the same manner as the experimental group. Laboratory participants completed all tests on the same online platform, but under monitored experimental conditions.
Statistical analyses
Initial analyses were carried out on the performance of the control participants to detect whether there was any differences in performance between online and laboratory participants. Akin to previous work (e.g. Germine et al., 2012), no differences were detected on any test (all ps > .55) and control data were subsequently collapsed across the two groups of participants for comparison to the experimental group. As there were no significant differences in age between the two control groups, or in comparison to the experimental group, we did not further sub-divide the participants according to age. Indeed, existing work indicates consistency in adult performance until the age of 50 (e.g. Bowles et al., 2009), the upper age limit for all of our participants.
Control norms (N = 40) for overall performance on each test
Maximum score
Control mean (SD)
Cut-off value
Proportion correct
Raw score
Proportion correct
Raw scorea
.68 (.10)
69.53 (10.02)
.54 (.14)
48.43 (12.44)
.69 (.07)
33.03 (3.49)
Crowds test
.63 (.12)
20.13 (3.76)
Performance on the CFMT+
Performance on the MMT
Breakdown of performance on the models memory test
Control mean (SD)
SR mean (SD)
Target-present trials: proportion of hits
.51 (.20)
.88 (.07)
Target-absent trials: proportion of correct rejections
.57 (.23)
.88 (.08)
Target-absent trials: proportion of misidentifications
.15 (.11)
.02 (.02)
Target-absent trials: proportion of misses
.34 (.21)
.10 (.07)
Overall proportion correct
.54 (.14)
.88 (.05)
d′ (sensitivity)
0.26 (0.84)
2.46 (0.59)
c (bias)
−0.12 (0.61)
−0.06 (0.33)
Proportion of positive responses in TP trials that were hits (vs misidentifications)
.77 (.15)
.98 (.02)
Second, we conducted signal detection-based analyses to compare performance between the group of 85 individuals who demonstrated superior performance on this test and the control group. To do this, we generated scores of sensitivity (d′) and bias (c) for each participant. The measure d′ incorporates information from hits and false positives to create a measure of sensitivity that is free from the influence of response bias (Macmillan & Creelman, 2005). A score of 0 indicates chance performance, and values for the current test can range from − 4.59 (consistently incorrect responding) to + 4.59 (perfect accuracy). The measure c is used as an indicator of response bias (i.e. whether the participant has a tendency to say that the target is present or absent; MacMillan & Creelman, 2005). A score of 0 indicates a neutral response criterion, whereas a positive score indicates conservative responding (a tendency to indicate that a target was not present) and a negative score indicates more liberal responding (a tendency to indicate that a target was present). For this analysis, we incorporated all instances when the participant indicated that a target was present, even when their identification of the target was incorrect (i.e. we included both hits and misidentifications for target-present trials, to calculate a measure of response bias that indexed a tendency to indicate that a target was present/absent overall). Scores for d′ and c were corrected using the loglinear approach proposed by Stanislaw and Todorov (1999).
There was a significant difference between the high-performing group and controls for d′, t(123) = 16.875, p = .001, d = 3.03, but not bias, t(123) = 0.722, p = .471. Follow-up analyses were carried out to analyse the pattern of responding in more detail. A two-way mixed ANOVA with group (SRs and controls) and correct response type (hits and correct rejections) confirmed that, averaged across the two types of responses, SRs outperformed controls, F(1,123) = 408.012, p = .001, ηρ2 = .768, but there was no main effect of response type nor a significant interaction between group and the type of correct response, F(1,123) = 1.320, p = .253 and F(1,123) = 2.563, p = .112, respectively (see Fig. 4c). In other words, the effects were not driven disproportionately by correct responses on target-present or target-absent trials. Furthermore, the SRs made proportionately fewer misidentification errors than the control group, t(1,123) = 9.925, p = .001, d = 1.54 (see Fig. 4d). This pattern held when analysing the raw number of misidentifications, and also when the number of misidentifications was controlled for by the number of overall positive identifications in target-present trials (by calculating the proportion of positive responses in target-present trials that were hits vs misidentifications), t(123) = 12.220, p = .001, d = 3.03.
Overall, this pattern of responses suggests that the participants who performed well on the MMT did so because they were capable of identifying the target faces more accurately when they were present, and correctly identifying when they were absent; this outcome is as opposed to either showing a general response bias or a tendency to indicate that a target face was present (regardless of whether they could subsequently identify the familiar face).
Performance on the PMT
Breakdown of performance on the pairs matching test
Control mean (SD)
SR mean (SD)
Proportion of hits
.68 (.17)
.88 (.08)
Proportion of correct rejections
.70 (.16)
.87 (.08)
Overall proportion correct
.69 (.07)
.87 (.03)
A (sensitivity)
.73 (.08)
.85 (.08)
b (bias)
1.09 (.45)
1.10 (.42)
Similarly to the MMT, the analysis of sensitivity (A) was significant, t(131) = 7.715, p = .001, d = 1.50, whereas the analysis of bias (b) was not, t(131) = 0.114, p = .909. SRs showed significantly better performance than controls, but there was no difference between the groups in response bias. Once again, we conducted follow-up analyses on the proportion of hits and correct rejections for each group using a two-way mixed ANOVA. While there was a significant main effect of group, F(1,131) = 392.472, p = .001, ηρ2 = .750, there was no main effect of response type nor significant interaction between the two, F(1,131) = 0.122, p = .727, and F(1,131) = 0.309, p = .579, respectively. This finding indicates that there was no significant difference in the proportion of hits versus correct rejections for these individuals compared to controls (see Fig. 5b).
Performance on the Crowds test
Control mean (SD) and SR (N = 1, only one individual outperformed controls on this task) scores on the Crowds test
Control mean (SD)
SR score
Proportion of hits
.61 (.16)
Proportion of correct rejections
.65 (.17)
Overall proportion correct
.63 (.12)
d′ (sensitivity)
0.68 (0.62)
c (bias)
0.06 (0.34)
These results suggest that it is difficult to surpass the control cut-off value on the Crowds task. Indeed, as argued in the Discussion, composites constructed from memory (as is the case here) are usually difficult to recognise or match to target. Given that 1.96 SDs from the control mean may be simply too conservative a cut-off value on this test, we also examined the performance of individuals who performed more than 1 SD above the control mean. Seventeen members (8.5%) of the experimental group exceeded this cut-off value, as did a somewhat larger proportion of the control group (20%). Seven of the 17 experimental group members (41.1%) displayed superior performance on the PMT, while three others (17.6%) achieved a superior score on the CFMT+. If we consider the other end of the spectrum on the Crowds task, specifically for the lowest 17 performers, a very similar pattern occurred: six individuals achieved a superior score on the PMT, and three others on the CFMT+.
Relationship between tests
Orthogonally rotated component loadings for factor analysis of the experimental group's performance on the four face recognition tests, including hits and correct rejections
MMT: hits
MMT: CRs
PMT: hits
PMT: CRs
Crowds: hits
Crowds: CRs
Correlation matrix for the experimental group's performance on the four face recognition tests, including hits and correct rejections
Crowds test
Factor loadings for combined performance of the control and experimental groups, based on principal components analysis with oblimin rotation
MMT: hits
MMT: CRs
PMT: hits
PMT: CRs
Crowds: hits
Crowds: CRs
Overall indices of performance
Norming data from control sample for target-present and target-absent indices
Standard deviation
Cut-off value
Dissociation between face matching and face memory performance in three "super matchers"
Test scores
Bayesian Standardized Difference Test: CFMT+ vs PMT
% population more extreme
This study aimed to examine the consistency of performance of 200 self-referred SRs (the experimental group) across four face-processing tests. First, participants completed the dominant test of face memory that is currently used to identify SRs (the CFMT+). They then participated in three new more applied tasks that were designed to mimic face recognition scenarios that are encountered by the police: a test of face memory (the MMT), a face matching task (PMT) and a test that requires participants to spot a composite target face in a crowd (Crowds test). When results from each test were examined independently, 37 people achieved consistently superior scores across three of these tests. However, dissociations were noted in a minority of individuals, with some only achieving superior scores on the two face memory tests, and some only on the PMT. Performance on the Crowds test was found to be unrelated to that on the other three tasks (and may even be tapping into different cognitive processes, as indicated by the significant negative correlation for hits between the PMT and Crowds tasks).
One of the main implications of these findings regards the protocols that are currently used to detect SRs. To date, most studies have relied on performance on the CFMT+ as the sole inclusion criterion. Based on the current findings, this criterion alone would have identified 89 individuals (44.5% of the entire sample) as SRs. Yet, when tested on two related face-processing tests, consistently superior performance was only noted in 37 participants—less than half of those who would have been identified by the CFMT+ alone. This finding highlights the need for a more rigorous screening procedure that involves repeated testing. Under such enhanced protocols, individuals who are consistently accurate at face recognition across a range of tasks may be more reliably detected.
Such an approach not only provides a more rigorous inclusion criterion, but may also provide a potential means of interpreting borderline cases. For instance, while a person may, for a variety of reasons, have just missed inclusion according to performance on the CFMT+, they may subsequently score extraordinarily well on a second test of face recognition that more convincingly identifies their superior face memory skills. In the current study, 34 individuals outperformed controls only on our new test of face memory, and these individuals would have been "missed" by the CFMT+. While a strong correlation was observed between the CFMT+ and hits on the MMT, it is also important to consider the important differences in paradigm, which may have implications for real-world face recognition performance. While the CFMT+ uses tightly controlled, cropped greyscale images of faces, the MMT was designed to embrace the natural variability that occurs between images of the same person in everyday face recognition scenarios. Further, we included target-absent trials in the MMT—a condition that is not present in the CFMT+. Including target-absent responses allowed a more fine-grained analysis of the skills underpinning excellent performance. On a group level, higher accuracy appears to be driven by increases in both hits (correct identifications when the target is present) and correct rejections (when the target is not present), and is not simply related to increased response bias (e.g. increased willingness to respond "no" when uncertain). This pattern was mirrored by high performers in the PMT and the single high-performer in the Crowds test, suggesting that it is not an artefact of the procedure used in the memory task. The design of the memory task also allowed us to discriminate between correct identifications (which likely reflect actual identification of the target face) and misidentifications (which could reflect uncertainty or guessing). This analysis revealed an important distinction between superior and control performers on the MMT: the former make relatively fewer misidentification errors than the latter. In combination, a real-world interpretation of this finding is that SRs may be less likely to make incorrect identifications—both in situations where the target is present (less misidentifications) and when they are not (more correct rejections). Thus, analysis of the type of error that is typically made in a memory task may be (and arguably should be) an important aspect of future real-world SR screening programmes.
Another way of looking at the consistency of overall performance is to create an index across related tests. Given that the PCA dissociated performance on target-present and target-absent trials across three of the four tests, we averaged scores across the tests to create two overall indices of performance. A dissociation between performance on target-present and target-absent trials has been reported in previous work (e.g. Megreya & Burton, 2007), and held here for both the control and experimental groups. Because we found no effect of response bias on any of the tasks, it is unlikely that this factor can explain the pattern of results. Instead, it seems that different individuals may be more accurate at target-present versus target-absent judgements. Indeed, only five individuals exceeded the cut-off values for superior performance on both indices—a figure that is substantially lower than the 37 individuals who outperformed controls on overall scores for each test. Further, while 103 of the 200 members of the experimental group surpassed the control cut-off value on target-present trials, only nine individuals exceeded control performance on the target-absent trials. In part, this pattern occurred because of the larger standard deviation in control performance on target-absent compared to target-present trials, resulting in a higher cut-off value for the former. It should also be noted that the target-present index was averaged from scores on three tests, whereas the target-absent index only resulted from two test scores (because the CFMT+ only contains target-present items). These issues aside, the data do indicate dissociations between target-present and target-absent performance, with very few individuals surpassing the cut-off value on both measures. Because target-absent judgements are of fundamental importance in a policing setting (i.e. accurately deciding that a suspect is not the person in CCTV footage prevents potential miscarriages of justice or waste of police time), future SR screening should take heed of both target-absent and target-present performance. Combining these scores into overall test performance, or even in overall indices, may obscure relative weaknesses on one measure as opposed to the other.
A second implication of the current work concerns the possibility that some individuals only excel at either face memory or face matching. This hypothesis has been raised in previous work using small case series or individual case studies (e.g. Bennetts, Mole, & Bate, 2017; Bobak, Bennetts, et al., 2016; Bobak, Hancock, & Bate, 2016). While it was clear that performance on the face matching task (the PMT) was at least mildly related to the two face memory measures, the current study nevertheless identified 18 individuals who only performed in the superior range on the PMT (although the consistency of this performance was not checked in a second related task) and 13 individuals who only performed in the superior range on the face memory tasks. In many of these individuals, performance on all three tasks was nevertheless in the range that encompasses the upper end of "normal" (i.e. that above 1 SD, or even 1.5 SDs, of the control mean on all three tasks), supporting the argument that the three tasks are inter-related at least to some degree. However, for three "super matchers", the difference between scores on the CFMT+ and the PMT were significantly larger than the mean difference between scores observed in controls. This finding provides more convincing support for a dissociation between super face matchers and super face memorisers; although it is of note that this pattern only emerged in a very small proportion of our sample, and that no evidence was observed for the reverse dissociation. That is, while superior face matching skills may be observed in the absence of superior face memory skills, people with excellent face memory skills also seem to have very good face matching skills. This finding supports hierarchical models of face-processing (e.g. Breen, Caine, & Coltheart, 2000; Bruce & Young, 1986; Ellis & Lewis, 2001), acknowledging the contribution of earlier perceptual processes in identity recognition. Such models make the assumption that perceptual analysis of a face occurs prior to identity recognition, and needs to be successfully completed in order for recognition to occur. This is backed up by the performance of those with prosopagnosia—while case studies have been reported where individuals have impairments to face memory alone, or to both facial identity perception and face memory (for a review see Bate & Bennetts, 2015), there are no reports of impaired facial identity perception in the context of intact face memory. The evidence reported here fits nicely with patterns of impairment in prosopagnosia, providing novel evidence from top performers that further bolsters the claims of theoretical models of face-processing. Importantly, then, SR screening procedures should include face matching measures from the outset, given that reliance on the CFMT+ (or any face memory measure) alone would overlook some individuals with superior face matching skills.
A similar argument may be directed towards the patterns of performance observed on the Crowds test. Using the original criterion of 1.96 SDs above the control mean, only one participant outperformed controls. Although the Crowds test had the greatest variability in performance of both controls and self-referred SRs, it was calibrated so that performance up to 3 SDs from the control mean could be detected (as confirmed in initial pilot-testing), and correct responses were recorded from at least some participants for every trial. It is possible that this test relies on a different set of sub-processes to the other three tests, and that successful performance relies less on the face recognition system itself. Indeed, the searching of crowds requires a range of perceptual and attentional skills that are likely not employed in face recognition tasks involving the simultaneous presentation of only two or three faces. Notably, a larger proportion of the control compared to the experimental sample performed above 1 SD from the control mean, and the top and bottom performers in the experimental group displayed varied performance on the other tests in the battery. However, given that we did not test for consistency in performance on this task, we cannot firmly reach this conclusion without further testing. Alternatively, it may be the use of composite faces that has brought about differences in performance levels.
There is good reason to suppose that this may be the case. It is inevitable that constructing a face from memory, even using a protocol designed to create identifiable images (e.g. Frowd et al., 2012), leads to inaccuracies in the resulting shape and appearance of individual features, and placement of features on the face (e.g. Frowd et al., 2005). Consequently, such composite faces are usually much harder to recognise, or even match to target, than photographs of the target identities themselves (e.g. Frowd et al., 2014; Frowd, Bruce, McIntyre, & Hancock, 2007). As mentioned earlier, EvoFIT involves a focus of construction on the internal features (e.g. Frowd et al., 2012), to coincide with the likely focus of attention for later naming using familiar face recognition (e.g. Ellis et al., 1979). However, completion of the Crowds task involves unfamiliar face perception, and so is likely to be dominated by external features, in particular hair (e.g. Bruce et al., 1999; Frowd, Skelton, Butt, Hassan, & Fields, 2011), face shape and age, so-called "cardinal" features (Ellis, 1986). Optimised in this way, it is not too surprising that the Crowds task was neither predicted by performance on the memory tasks (no reliable correlations, Table 7) nor on the PMT (reliable but negative correlation for both hits and CRs between the PMT and the Crowds test); indeed, low and high performance on the Crowds task led to a similar proportion of participants performing well on memory tasks and the PMT.
So, the Crowds task requires unique ability to match an error-prone stimulus (a composite) to a large number of unfamiliar face alternatives (a crowd of people). Indeed, the process involved with other holistic systems—EFIT-V or EFIT-6 (Gibson, Solomon, Maylin, & Clark, 2009) and ID (Tredoux, Nunez, Oxtoby, & Prag, 2006)—is somewhat similar to EvoFIT, resulting in an error-prone face, and so one would anticipate our results to generalise to other implementations. It is conceivable, however, that familiarity with composite stimuli in general may actually be beneficial. If this is the case, a randomly selected sample of police officers who are used to viewing facial-composite images would be expected to outperform our controls on this task. While further research is clearly needed to explore the precise underpinnings of successful performance, and indeed whether the test successfully mimics the intended real-world scenario, it may be tentatively inferred that some very specific real-world face-processing tasks require the recruitment of a different set of individuals. Regardless of whether the top performers will be those with natural facilitations in more general skills or those with experience with artificial facial images, screening for superior performers on some real-world tasks may require targeted tests that closely resemble the scenario in question.
Finally, it is of note that the sample of participants screened in this study all contacted us in the belief that they are SRs. While 18.5% of the participants outperformed controls on any three tests in the battery, a further 41% surpassed cut-off values on any two tests. It can therefore be seen that 59.5% of the sample displayed at least some consistency in superior performance (and 51% outperforming controls on the target-present index), indicating that there is utility of self-report measures in screening. However, 55 of the 200 participants (27.5%) failed to score within the superior range on any one test, and 13% only achieved the superior range on any one test. While these individuals may be genuinely mistaken about their face recognition ability, perhaps due to their point of comparison being the relatively weaker skills of a significant other, it is possible that the tests simply failed to detect their superior skills. This may be due to their reliability (although the identification of 59.5% of the experimental sample is respectable) or that they are not tapping every process which contributes to the self-perception of superior face recognition skills. For instance, our battery of tests used facial stimuli that were cropped above the neck, whereas in everyday life other aspects of the person may facilitate recognition, such as characteristics of the body and its movements. While future work should attempt to more extensively test person (and not just face) recognition skills, it can nevertheless be concluded that subjective self-report cannot reliably be used in place of objective testing. What is perhaps more striking is that only five individuals outperformed controls on both the target-present and target-absent indices, with many more surpassing cut-off values on the former but not the latter. This may indicate that self-report is based on target-present performance, given that everyday instances of recognition are likely given more weight than successful target-absent judgements. If "true" SRs are those who are top performers on both measures, they may be much less prevalent than previously thought, and more difficult to detect via self-report.
It also remains to be seen whether random sampling can identify any potential SRs who have no self-belief that they are adept at face recognition, in which case objective screening of all available personnel in applied settings should be encouraged. This question can somewhat be addressed by examination of the control data reported here, although the sample size is not representative of a wider screening procedure. When examining the data for the CFMT+, MMT and PMT, only two controls surpassed the cut-off values on any of the test: one individual achieved a score of 95/102 on the CFMT+, and another scored 43/48 on the PMT. Neither individual scored close to the cut-off values on the other tests, nor in their combined index scores. While the sample size is too small to draw any firm conclusions about the utility of random sampling irrespective of self-belief, it may be prudent to encourage all existing personnel to participate in SR screening programmes, regardless of self-perceived face recognition ability.
In sum, this paper has provided evidence to suggest that current screening protocols for super recognition need to be expanded. Both face memory and face matching skills should be assessed using both target-present and target-absent trials, but inclusion criteria should not require exceptional performance on both processes. Further, some very specified real-world face recognition tasks may require targeted screening using measures that specifically replicate the required scenario. Finally, our data indicate that the new screening measures developed in this test may be of benefit to the wider field, and the new MMT may be a particularly sensitive test for the detection of SRs. We are happy to share these resources with other researchers on request (please contact the corresponding author).
SB is supported by a British Academy Mid-Career Fellowship (MD170004).
Authors' contributions
All authors contributed to the design of this study, and collected and analysed data. SB, CF and RB wrote the manuscript. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Ethical approval for the study was granted by Bournemouth University's Ethics Committee. Informed consent to participate was provided by all participants.
Consent for publication
Consent to publish was obtained from all participants.
Competing interests
The authors declare that they have no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Authors' Affiliations
- Barton, J. J., Press, D. Z., Keenan, J. P., & O'Connor, M. (2002). Lesions of the fusiform face area impair perception of facial configuration in prosopagnosia. Neurology, 58, 71–78.View ArticlePubMedGoogle Scholar
- Barton, J. J. S., & Corrow, S. L. (2016). The problem of being bad at faces. Neuropsychologia, 89, 119–124.View ArticlePubMedPubMed CentralGoogle Scholar
- Bate, S., Adams, A., Bennetts, R., & Line, H. (in press). Developmental prosopagnosia with concurrent topographical disorientation: A case report and virtual reality training programme. Neuropsychological Rehabilitation. https://doi.org/10.1080/09602011.2017.1409640
- Bate, S., & Cook, S. (2012). Covert recognition relies on affective valence in developmental prosopagnosia: Evidence from the skin conductance response. Neuropsychology, 26, 670–674.View ArticlePubMedGoogle Scholar
- Bate, S., Cook, S. J., Duchaine, B., Tree, J. J., Burns, E. J., & Hodgson, T. L. (2014). Intranasal inhalation of oxytocin improves face processing in developmental prosopagnosia. Cortex, 50, 55–63.View ArticlePubMedGoogle Scholar
- Bate, S., Haslam, C., Jansari, A., & Hodgson, T. L. (2009). Covert face recognition relies on affective valence in congenital prosopagnosia. Cognitive Neuropsychology, 26, 391–411.View ArticlePubMedGoogle Scholar
- Bate, S., Parris, B. A., Haslam, C., & Kay, J. (2010). Socio-emotional functioning and face recognition ability in the normal population. Personality and Individual Differences, 48, 239–242.View ArticleGoogle Scholar
- Bate, S., & Bennetts, R. (2015). The independence of expression and identity in face-processing: Evidence from neuropsychological case studies. Frontiers in Psychology, 6, 770.View ArticlePubMedPubMed CentralGoogle Scholar
- Bate, S., & Tree, J. J. (2017). The definition and diagnosis of developmental prosopagnosia. Quarterly Journal of Experimental Psychology, 70, 193–200.View ArticleGoogle Scholar
- Bennetts, R., Butcher, N., Lander, K., Udale, R., & Bate, S. (2015). Movement cues aid face recognition in developmental prosopagnosia. Neuropsychology, 29, 855–860.View ArticlePubMedGoogle Scholar
- Bennetts, R. J., Mole, J. A., & Bate, S. (2017). Super recognition in development: A case study of an adolescent with extraordinary face recognition skills. Cognitive Neuropsychology, 34, 357–376.View ArticlePubMedGoogle Scholar
- Bindemann, M., Attard, J., & Johnston, R. A. (2014). Perceived ability and actual recognition accuracy for unfamiliar and famous faces. Cogent Psychology, 1, 986903.View ArticleGoogle Scholar
- Bobak, A., Pampoulov, P., & Bate, S. (2016). Detecting superior face recognition skills in a large sample of young British adults. Frontiers in Psychology, 7, 1378.View ArticlePubMedPubMed CentralGoogle Scholar
- Bobak, A. K., Bennetts, R. J., Parris, B. A., Jansari, A., & Bate, S. (2016). An in-depth cognitive examination of individuals with superior face recognition skills. Cortex, 82, 48–62.View ArticlePubMedGoogle Scholar
- Bobak, A. K., Dowsett, A., & Bate, S. (2016). Solving the border control problem: Evidence of enhanced face matching in individuals with extraordinary face recognition skills. PLoS One, 11, e0148148.View ArticlePubMedPubMed CentralGoogle Scholar
- Bobak, A. K., Hancock, P. J. B., & Bate, S. (2016). Super-recognizers in action: Evidence from face matching and face memory tasks. Applied Cognitive Psychology, 30, 81–91.View ArticleGoogle Scholar
- Bobak, A. K., Parris, B. A., Gregory, N. J., Bennetts, R. J., & Bate, S. (2017). Eye-movement strategies in developmental prosopagnosia and "super" face recognition. Quarterly Journal of Experimental Psychology, 70, 201–217.View ArticleGoogle Scholar
- Bowles, D. C., McKone, E., Dawel, A., Duchaine, B., Palermo, R., Schmalzl, L., … Yovel, G. (2009). Diagnosing prosopagnosia: Effects of aging, sex, and participant-stimulus ethnic match on the Cambridge face memory test and the Cambridge face perception test. Cognitive Neuropsychology, 26, 423–455.View ArticlePubMedGoogle Scholar
- Breen, N., Caine, D., & Coltheart, M. (2000). Models of face recognition and delusional misidentification: A critical review. Cognitive Neuropsychology, 17, 55–71.View ArticlePubMedGoogle Scholar
- Bruce, V., Henderson, Z., Greenwood, K., Hancock, P. J., Burton, A. M., & Miller, P. (1999). Verification of face identities from images captured on video. Journal of Experimental Psychology: Applied, 5, 339–360.Google Scholar
- Bruce, V., & Young, A. (1986). Understanding face recognition. British Journal of Psychology, 77, 305–327.View ArticlePubMedGoogle Scholar
- Burns, E. J., Bennetts, R. J., Bate, S., Wright, V. C., Weidemann, C. T., & Tree, J. J. (2017). Intact word processing in developmental prosopagnosia. Scientific Reports, 7, 1683.View ArticlePubMedPubMed CentralGoogle Scholar
- Burton, A. M., White, D., & McNeil, A. (2010). The Glasgow face matching test. Behavior Research Methods, 42, 286–291.View ArticlePubMedGoogle Scholar
- Chatterjee, G., & Nakayama, K. (2012). Normal facial age and gender perception in developmental prosopagnosia. Cognitive Neuropsychology, 29, 482–502.View ArticlePubMedGoogle Scholar
- Crawford, J. R., & Garthwaite, P. H. (2002). Investigation of the single case in neuropsychology: Confidence limits on the abnormality of test scores and test score differences. Neuropsychologia, 40, 1196–1208.View ArticlePubMedGoogle Scholar
- Dalrymple, K. A., & Palermo, R. (2016). Guidelines for studying developmental prosopagnosia in adults and children. Wiley Interdisciplinary Reviews: Cognitive Science, 7, 73–87.PubMedGoogle Scholar
- Davis, J. P., Lander, K., Evans, R., & Jansari, A. (2016). Investigating predictors of superior face recognition ability in police super-recognisers. Applied Cognitive Psychology, 30, 827–840.View ArticleGoogle Scholar
- De Haan, E. H., Young, A. W., & Newcombe, F. (1987). Face recognition without awareness. Cognitive Neuropsychology, 4, 385–415.View ArticleGoogle Scholar
- De Haan, E. H. F., Young, A. W., & Newcombe, F. (1991). Covert and overt recognition in prosopagnosia. Brain, 114, 2575–2591.View ArticlePubMedGoogle Scholar
- De Renzi, E., Faglioni, P., Grossi, D., & Nichelli, P. (1991). Apperceptive and associative forms of prosopagnosia. Cortex, 27, 213–221.View ArticlePubMedGoogle Scholar
- Dennett, H. W., McKone, E., Tavashmi, R., Hall, A., Pidcock, M., Edwards, M., & Duchaine, B. (2012). The Cambridge Car Memory Test: A task matched in format to the Cambridge Face Memory Test, with norms, reliability, sex differences, dissociations from face memory, and expertise effects. Behavior Research Methods, 44, 587–605.View ArticlePubMedGoogle Scholar
- Dowsett, A. J., & Burton, A. M. (2015). Unfamiliar face matching: Pairs out-perform individuals and provide a route to training. British Journal of Psychology, 106, 433–445.View ArticlePubMedGoogle Scholar
- Duchaine, B. (2008). Editorial comment on prevalence of hereditary prosopagnosia (HPA) in Hong Kong Chinese population. American Journal of Medical Genetics Part A, 146A, 2860–2862.View ArticlePubMedGoogle Scholar
- Duchaine, B., Germine, L., & Nakayama, K. (2007). Family resemblance: Ten family members with prosopagnosia and within-class object agnosia. Cognitive Neuropsychology, 24, 419–430.View ArticleGoogle Scholar
- Duchaine, B., & Nakayama, K. (2006). The Cambridge Face Memory Test: Results for neurologically intact individuals and an investigation of its validity using inverted face stimuli and prosopagnosic subjects. Neuropsychologia, 44, 576–585.View ArticlePubMedGoogle Scholar
- Ellis, H. D. (1986). Face recall: A psychological perspective. Human Learning, 5, 1–8.Google Scholar
- Ellis, H. D., & Lewis, M. B. (2001). Capgras delusion: A window on face recognition. Trends in Cognitive Sciences, 5, 149–156.View ArticlePubMedGoogle Scholar
- Ellis, H. D., Shepherd, J. W., & Davies, G. M. (1979). Identification of familiar and unfamiliar faces from internal and external features: Some implications for theories of face recognition. Perception, 8, 431–439.View ArticlePubMedGoogle Scholar
- Frowd, C. D., Bruce, V., McIntyre, A., & Hancock, P. J. B. (2007). The relative importance of external and internal features of facial composites. British Journal of Psychology, 98, 61–77.View ArticlePubMedGoogle Scholar
- Frowd, C. D., Carson, D., Ness, H., Richardson, J., Morrison, L., McLanaghan, S., & Hancock, P. J. B. (2005). A forensically valid comparison of facial composite systems. Psychology, Crime & Law, 11, 33–52.View ArticleGoogle Scholar
- Frowd, C. D., Skelton, F. C., Atherton, C., Pitchford, M., Hepton, G., Holden, L., … Hancock, P. J. B. (2012). Recovering faces from memory: The distracting influence of external facial features. Journal of Experimental Psychology: Applied, 18, 224–238.Google Scholar
- Frowd, C. D., Skelton, F. C., Butt, N., Hassan, A., & Fields, S. (2011). Familiarity effects in the construction of facial-composite images using modern software systems. Ergonomics, 54, 1147–1158.View ArticlePubMedGoogle Scholar
- Frowd, C. D., White, D., Kemp, R. I., Jenkins, R., Nawaz, K., & Herold, K. (2014). Constructing faces from memory: The impact of image likeness and prototypical representations. Journal of Forensic Practice, 16, 243–256.View ArticleGoogle Scholar
- Germine, L., Nakayama, K., Duchaine, B. C., Chabris, C. F., Chatterjee, G., & Wilmer, J. B. (2012). Is the web as good as the lab? Comparable performance from web and lab in cognitive/perceptual experiments. Psychonomic Bulletin & Review, 19, 847–857.View ArticleGoogle Scholar
- Gibson, S. J., Solomon, C. J., Maylin, M. I. S., & Clark, C. (2009). New methodology in facial composite construction: From theory to practice. International Journal of Electronic Security and Digital Forensics, 2, 156–168.View ArticleGoogle Scholar
- Gray, K. L. H., Bird, G., & Cook, R. (2017). Robust associations between the 20-item prosopagnosia index and the Cambridge Face Memory Test in the general population. Royal Society Open Science, 4, 160923.View ArticlePubMedPubMed CentralGoogle Scholar
- Herlitz, A., & Lovén, J. (2013). Sex differences and the own-gender bias in face recognition: A meta-analytic review. Visual Cognition, 21, 1306–1336.View ArticleGoogle Scholar
- Lee, Y., Duchaine, B., Wilson, H. R., & Nakayama, K. (2010). Three cases of developmental prosopagnosia from one family: Detailed neuropsychological and psychophysical investigation of face processing. Cortex, 46, 949–964.View ArticlePubMedGoogle Scholar
- Lovén, J., Herlitz, A., & Rehnman, J. (2011). Women's own-gender bias in face memory. Experimental Psychology, 58, 333–340.View ArticlePubMedGoogle Scholar
- Macmillan, N. A., & Creelman, C. D. (2005). Detection theory: a user's guide, (2nd ed., ). Mahwah: Lawrence Erlbaum Associates.Google Scholar
- McGugin, R. W., Richler, J. J., Herzmann, G., Speegle, M., & Gauthier, I. (2012). The Vanderbilt expertise test reveals domain-general and domain-specific sex effects in object recognition. Vision Research, 69, 10–22.View ArticlePubMedPubMed CentralGoogle Scholar
- McKone, E., Hall, A., Pidcock, M., Palermo, R., Wilkinson, R. B., Rivolta, D., … O'Connor, K. B. (2011). Face ethnicity and measurement reliability affect face recognition performance in developmental prosopagnosia: Evidence from the Cambridge Face Memory Test-Australian. Cognitive Neuropsychology, 28, 109–146.Google Scholar
- Megreya, A. M., & Burton, A. M. (2007). Hits and false positive in face matching: A familiarity-based dissociation. Attention, Perception and Psychophysics, 69, 1175–1184.View ArticleGoogle Scholar
- Meissner, C. A., & Brigham, J. C. (2001). Thirty years of investigating the own-race bias in memory for faces: A meta-analytic review. Psychology, Public Policy, and Law, 7, 3–35.View ArticleGoogle Scholar
- Noyes, E., Phillips, P. J., & O'Toole, A. J. (2017). What is a super-recogniser? In M. Bindemann, & A. M. Megreya (Eds.), Face processing: Systems, disorders, and cultural differences. New York: Nova.Google Scholar
- Palermo, R., Rossion, B., Rhodes, G., Laguesse, R., Tez, T., Hall, B., … McKone, E. (2017). Do people have insight into their face recognition abilities? Quarterly Journal of Experimental Psychology, 70, 218–233.View ArticleGoogle Scholar
- Ramon, M., Miellet, S., Dzieciol, A. M., Konrad, B. N., Dresler, M., & Caldara, R. (2016). Super-memorizers are not super-recognizers. PLoS One, 11, e0150972.View ArticlePubMedPubMed CentralGoogle Scholar
- Robertson, D. J., Noyes, E., Dowsett, A. J., Jenkins, R., & Burton, A. M. (2016). Face recognition by metropolitan police super-Recognisers. PLoS One, 11, e0150036.View ArticlePubMedPubMed CentralGoogle Scholar
- Rotshtein, P., Geng, J. J., Driver, J., & Dolan, R. J. (2007). Role of features and second-order spatial relations in face discrimination, face recognition, and individual face skills: Behavioral and functional magnetic resonance imaging data. Journal of Cognitive Neuroscience, 19, 1435–1452.View ArticlePubMedPubMed CentralGoogle Scholar
- Russell, R., Duchaine, B., & Nakayama, K. (2009). Super-recognizers: People with extraordinary face recognition ability. Psychonomic Bulletin & Review, 16, 252–257.View ArticleGoogle Scholar
- Shah, P., Gaule, A., Sowden, S., Bird, G., & Cook, R. (2015). The 20-item prosopagnosia index (PI20): A self-report instrument for identifying developmental prosopagnosia. Royal Society Open Science, 2(140343), 1–11.Google Scholar
- Stanislaw, H., & Todorov, N. (1999). Calculation of signal detection theory measures. Behavior Research Methods, Instruments, & Computers, 31, 137–149.View ArticleGoogle Scholar
- Tredoux, C. G., Nunez, D. T., Oxtoby, O., & Prag, B. (2006). An evaluation of ID: An eigenface based construction system. South African Computer Journal, 37, 1–9.Google Scholar
- Tree, J. (2011). Mental imagery in congenital prosopagnosia: A reply to Grüter et al. Cortex, 47, 514–518.View ArticlePubMedGoogle Scholar
- Wilmer, J. B. (2017). Individual differences in face recognition: A decade of discovery. Current Directions in Psychological Science, 26, 225–230.View ArticleGoogle Scholar
- Wilmer, J. B., Germine, L., Chabris, C. F., Chatterjee, G., Williams, M., Loken, E., … Duchaine, B. (2010). Human face recognition ability is specific and highly heritable. Proceedings of the National Academy of Sciences of the USA, 107, 5238e5241.View ArticleGoogle Scholar
- Wilmer, J. B., Germine, L., Loken, E., Guo, X. M., Chatterjee, G., Nakayama, K., … Duchaine, B. (2010). Response to Thomas: Is human face recognition ability entirely genetic? Proceedings of the National Academy of Sciences of the USA, 107, E101.View ArticlePubMed CentralGoogle Scholar
- Young, A. W., & Burton, A. M. (2017). Recognizing faces. Current Directions in Psychological Science, 26, 212–217.View ArticleGoogle Scholar
- Young, A. W., & Burton, A. M. (2018). Are we face experts? Trends in Cognitive Sciences, 22, 100-110.Google Scholar
- Yovel, G., Wilmer, J. B., & Duchaine, B. (2014). What can individual differences reveal about face processing? Frontiers in Human Neuroscience, 8, 562.View ArticlePubMedPubMed CentralGoogle Scholar
- Zhang, J., & Mueller, S. T. (2005). A note on ROC analysis and non-parametric estimate of sensitivity. Psychometrika, 70(1), 203–212.View ArticleGoogle Scholar


text:
Online reviews are an increasingly crucial part of any company's success. Whether selling products or providing a service, it's all about keeping your customers happy. Satisfied customers attract more customers and this encourages both customer loyalty and attracts more new customers. If you're not yet convinced that you need to encourage online reviews, here are some interesting statistics:
- 92% of customers read online reviews
- 40% of customers develop an opinion after reading 1 – 3 reviews
- 94% of customers will use companies with a 4-star rating
- Only 12% of customers read more than 10 reviews
- 23% of customers will visit a business immediately after reading positive reviews
- 68% of customers say that positive reviews encourage them to trust local businesses more
- 86% of customers hesitate to do business with a company that has negative reviews
- 2 of the most effective platforms for online reviews are Google and TripAdvisor
One important rule to remember when it comes to online reviews is to ask. Customers are far more likely to leave a review if you ask them. Of course, making contact with each and every one of your clients can be incredibly time-consuming. Rather than letting such an opportunity go to waste, you can put our expert services to good use.
We make use of email correspondence to breach the gap between customer and business. We follow up with each and every customer in order to provide them with the appropriate links to your business pages on top review websites. By doing so, we help keep all of your reviews in just a handful of places. This makes them that much easier to manage and with multiple reviews, your future customers will be that much more likely to choose you over your competition.

subset: commoncrawl


text:
Welsh Secretary says "Jones the Jag" row no big deal
Media monitoring is not usually the most onerous task at the Wales Office. With few executive responsibilities in the age of devolution, the department rarely makes headlines.
But today its boss has made the national newspapers not once, but twice. David Jones was one of only two cabinet ministers to vote against plans to legalise gay marriage, a story that made most of today's front pages.
Mr Jones has also hit the headlines for another reason. The Telegraph, The Times, The Sun, the Mirror and the Daily Mail (online) all feature his 100m journey in a chauffeur-driven Jaguar from the Wales Office in Whitehall to Downing Street. The media monitoring unit may need to buy another pair of scissors.
A phrase involving "PR" and "disaster" springs to mind. Last night, the Wales Office issued a terse statement explaining that Mr Jones wanted to read papers and briefing notes on his way to yesterday's cabinet meeting. The statement didn't explain why the chauffeur was needed to return Mr Jones to the Wales Office afterwards.
Mr Jones has turned down requests for broadcast interviews. He has spoken to his local paper, the Daily Post and is, by their account, unrepentant.
One of the benefits of being driven through the Downing Street gates is apparently that one can avoid the inconvenience of having to remove one's coat at the security checkpoint.
The Daily Post quotes Mr Jones as saying: "The fact is this is my ministerial car. I use it to go to Downing Street regularly because I'm always consulting papers right up to the last minute.
"It (travelling by car) enables me to do so without physically going through security at the gate, having to remove my coat or jacket.
"Plenty of secretaries of state go there by car - I'm not going to name colleagues - probably for exactly the same reasons I do and most secretary of state offices are within walking distance.
"I'm not in any sense troubled by this, it is all part of it. It's not a big deal."
It may not be a big deal but it is the only time during his five months as secretary of state that Mr Jones has made the national papers in his own right. And, as Lord Prescott may recall, things that are not a big deal can help define your ministerial career.
Labour have continued to exploit the story, highlighting Mr Jones's confession: "I've always liked cars, which may perhaps be a dangerous thing for any minister to admit to."
But as Mr Jones points out, he is not the only cabinet minister with an office nearby to use a ministerial car to travel to Downing Street. And he certainly isn't the first secretary of state for Wales to do so - Labour's Paul Murphy faced flak for taking a similar journey (albeit in a more humble Vauxhall Vectra) more than a decade ago.


text:
The concept behind the show was based around the stages of censorship. Taking Banksy and the controversial nature of graffiti as main inspiration, the exhibition is the conclusion of the journey taken by designers from 2014 Graphic Design Graduates.
Designers on the Work Based BA (Hons) Graphic Design Course at Weston College in partnership with Bath Spa University present this exhibition that is travelling from Bristol Paintworks to Weston College and then onto New Designers in London.
The concept behind our show is based around how our creativity as designers is constrained by the stages* of censorship. Self-initiated, real-life projects have been developed around a range of issues including; community, social and health and education all with the potential to be used in real life situations to make a positive change in society.
This is Censored For Show (CFS)
Uncover the future of limitless design
The client // Consider client's demands
The brief // Consider audience's needs
Society// Consider legal and moral issues


text:
Knitting This Week6:00 AM
Mom: I'll wash your blanket tonight.
Mittens: But I can't knead on him when he's wet.
Mom: i"ll be home soon.
Mittens: I can't wait.
Mom: You're awfully Kneady Mittens. LOL!
Mittens: You're a horrible person.
10 comments
LOVE your hitofude!!! simply gorgeous and I hope you meet your goal :)ReplyDelete
I am your cheerleader and have all the faith in the world that you will be wearing your cardigan for Rhinebeck. I just heard that today NY is having a heat wave, they are hotter than I am!ReplyDelete
I love children's books that make me laugh. My daughter Erin and Emerson were reading the Bad Kitty books and loved them; Erin said they made her laugh.
You can never plan for Rhinebeck. It could be freezing - it could be warm. You never know! I have a sweater in case it's cold and a vest in case it's nice. And I booked my bus ticket and am ready to go. I'll message you on Ravelry so we can make a plan to meet up!ReplyDelete
I hope you have a terrific time in Rhinebeck, and that you'll be enjoying your newly knitted sweater. :^)ReplyDelete
Your hitofude is knitting up beautifully!! I finished mine but I haven't had a chance to take a photo of it finished yet!ReplyDelete
Gorgeous Hitofude!! Wow! I love the color and can't wait until mine is at that point! I hope you get yours done in time, I would so love to go to Rhinebeck someday! Dream come true! The smoke was terrrrible here for days but is much better now. I am so sorry your husband is sick!ReplyDelete
Your Hitofude is gorgeous - hope you get it done in time. That book does look hilarious.ReplyDelete
Your Hitofude is gorgeous - hope you get it done in time. That book does look hilarious.ReplyDelete
Mmm, your hitofude is glorious, love the colour.ReplyDelete
great sweater! And that book...what a HOOT! I have a friend who is 2 cats shy of the crazy designation! I should get her this book, but I'll have to read it first!!ReplyDelete


text:
The Geo Air-Dome from Summergreen Systems, Ltd., can be installed over existing manure storage tanks without having to empty the tank. The high-density, woven polyethylene dome comes in different sizes.
Daniel Lambert, president of Summergreen Systems, explains the process by which the dome is installed. "A precast concrete column is placed in the center of the tank using a crane," Lambert says. "From this concrete column, straps (5,000-lb. tensile strength) radiate out and are attached to the outside of the tank wall at 12-ft. to 14-ft.-on-center intervals by way of a winch with a brake mechanism." After the center column and straps are adjusted and aligned, the fabric is lifted by crane and is spread out over the support straps. It is secured around the outside tank wall by an aluminum channel and anchor system. Next, an access pump-out door, air-inlet port and manure-inlet port are installed.
The Geo-Air Dome is inflated by a 11/46-hp turbine blower system that generates 1 in. of water column pressure and costs $80 to $90/year to operate.
When a producer gets ready to agitate or pump out the manure tank, the fan is shut off, and the fabric settles down on the support straps. The removable access door allows for agitating and pumping. The 4 ft. x 5 ft. access door and frame weigh about 40 lb. and are constructed of aluminum and PVC. "Once you have completed your pump out, simply reinstall the pump-out door and turn on the fan," Lambert says.
There is a 10-year warranty on the dome system.
Most installations of the Canadian-developed domes have been in Ontario. Lambert says several Geo Air-Domes are being installed in Iowa this summer.
Hoff asked about installation time and costs. Lambert says the dome is priced at $80-$90/diameter foot. Installation costs an additional $7-$8/diameter foot, and includes crane rental.
Craig Christensen was concerned about the ease of patching any rips or tears that might develop in the dome. Lambert said repairs can be made by sewing or welding the tear. He said it is important to keep the dome inflated to help prevent wind damage.
Possible repair difficulty was an area the panel felt producers should consider.
(Circle Reply Card No. 109)


text:
"Determine that the thing can and shall be done, and then we shall find the way" - Abraham Lincoln
Chiara has more than 10 years of experience in the HR field, with a focus on business development and recruitment.
She comes from Bolzano and is therefore bilingual in Italian and German. She moved to Bologna in 1998 to pursue an academic path at the University of Bologna, where she earned an M.A. in Educational Sciences, with a focus on training processes in the workplace.
She started her career in 2005 as an Account Manager for an employment company, and then founded her own search & selection agency, with the aim of launching an entrepreneurial venture.
After having collaborated extensively with In Job, she joined the team in 2014 as the Bologna Branch Manager.


text:
Be a Friend
"I hate this Facebook!" my friend said in a private message – although, of course, she was writing on Facebook. "Everything is so banal; all we do is rake over what's happened in the past month. It's just not enough."
"I know."
It wasn't exactly a sensitive answer, almost insulting, in fact. But I simply had nothing else to say. At some point you have to ask yourself whether a friendship is worth fighting for. The answer is not simple and depends on the character of your friend as well as on the relationship. In my case, the person was worth it, but the relationship was not.
The beginnings of most friendships are the same: the basis is in spending time together, going out, whispering in the corner of the courtyard about the boys from the senior class. This is a high school friendship. Later, our friendships become more sincere. In a good friendship, conversation is a melody you never tire of listening to, because each day the music is reborn with few added notes that repaint its hue.
This one was a teenage friendship just emerging into adulthood when I left to finish my schooling in the United Sates. It was still based on spending innocuous time together, and after a nine months' absence, I saw it gradually falling apart. I had known I was going to lose people, but with her, I believed, the situation would be different.
I tried. I talked. I cried. But she thought it was just a crisis, a phase, assuring me everything would be back to normal in a couple of months. But when I moved to Austria, it was gone forever.
I am 20 years old, and I have just learned what friendship is not. And so also what it has to be – an understanding, a pleasure in companionship that transcends time. Or even talk. It's often the silences that make the real conversations between friends. Not the saying but the never-needing-to-say is what counts.
The only way to have a friend, I realized, is to be one.
– Bojana Simeunovic


text:
You will receive reset instructions in your mailbox.
Add a touch of Colour and comfort to your room. beautiful Faux Linen cushions >
View More Laundry Products >
Product availability varies by location and the information shown may differ from the store's actual. It is recommended that you call the store to confirm it has sufficient quantity available for your needs, especially when low stock is indicated. While Daniadown is committed to accurate inventory data, this information is covered under our terms and condition of use and Daniadown cannot be held liable for any loss or damages you may incur by relying on this information.
Deodorizes Anything - smelly sports gear, garbage cans, stale vehicle interiors, smoke odours, pet odours and more. Shutout's unique SilverSync ingredient works in combination with pure essential oils like lemongrass, tea tree and peppermint to give a light natural scent that dissipates after just a few short minutes leaving your items smelling neutral and odour free.
Shutout's patented SilverSync+ Technology is designed to replace harsh chemicals in the products we use. SilverSync+ kills bacteria, molds, fungi and more while leaving the people who use it unharmed from allergic reactions or chemical sensitivities. With this technology in our hands early on, you can likely see why we decided to include it in so many products; it's used in deodorizing & sanitizing sprays, hard surface cleaners, laundry detergents, mopping solutions, skin-care products and more. The use of SilverSync+ also enables us to blend our products with 100% pure essential oils, where as chemical disinfectants would work against those natural ingredients if blended together.
Silver (Ag+) has powerful natural properties and Shutout® has become a world leader in utilizing this natural ingredient to make better products for the world we live in. We've taken Quality Control to another level; accurately controlling the shapes & sizes of the particles at a microscopic level to achieve deliberate results. All Shutout® products are designed to behave a certain way, with consistent results; some are longer lasting and some faster acting. This is just one example of what we focus on when creating new products in our design labs.
VIP Only offers, Advanced notice on sales and promotions, decorating tips, entry into our monthly VIP draws for free product.
You will be able to unsubscribe at any time. Please read our privacy policy.We will never send you spam, ever.
1(800) 663-9088


text:
I was knitting too tight. So a friend recommended that I use a larger needle to cast on then knit as usual and that should give me the room I need so I am not struggling so much to get the needle in the stitch. It seems to be working, but it is so loose and looks sloppy. Of course it could be that I need more practice. I am going to finish and see how it turns out.
I haven't gotten very far because knitting with an adorable 37 pound monkey on your chest isn't very easy.
|Kinda looks like he is falling off, but he didn't
How did I end up knitting with a monkey? When we got home I wanted to get a little knitting done. I am not sure what I am making, but I won't let that stop me. Rowan was really tired, but didn't want to go to bed so asked me to hold him. Since he is usually running like crazy and trying to hack stuff with his foam swords and then is disappointed when only the sword breaks, this was a nice change. I am sitting there when he drifted off to sleep and I was done looking at how cute he was, I wondered if I could knit with him there. I was successful, but I kept tickling his ear with my yarn and he would wiggle and knock stitches off the needle. Oh well, if that is the worst thing that happened in a day, then it was a good day.
Follow your craft


text:
This was not the homecoming Richmond forward Derrick Williams imagined.
Williams, a Harlem native, set in motion a bizarre finish featuring eight free throws and an ejection in the final five seconds of Charlotte's 68-63 win over Richmond yesterday in the first round of the Atlantic 10 Tournament at Barclays Center.
"Yeah, I would say that's the craziest end to a game I have ever seen," Charlotte coach Alan Major said. "You couldn't make that up if you wanted to make a movie out of that one."
Charlotte guard Pierria Henry was shooting free throws with 4.7 seconds left to play trailing by three points. After Henry, who led all scorers with 28 points, hit his first free throw, Williams aggressively threw Charlotte forward Willie Clayton to the floor and was called for a technical foul.
Henry converted the resulting free throws to give Charlotte (21-10) the lead and Richmond (18-14) came totally unraveled. Following a shooting foul by Henry, Richmond coach Chris Mooney was whistled for two technicals of his own and ejected.
"I was disappointed in how the game turned out," Mooney said. "I certainly wish the ending hadn't been the way it was. I apologize to the Richmond fans."
Henry once again took the shots from the charity stripe, hitting four of six free throws to give Charlotte the 68-63 win.
"I was trying to focus on my free throws," Henry said. "Coach Major called me to shoot them with all of the riff-raff going on and I knocked down the free throws. [It felt like I was on the line] for 30 minutes."
The ninth-seeded 49ers will play top-seeded St. Louis today.
Saint Joseph's 58, Xavier 57
Hawks guard Langston Galloway hit two free throws with 1.4 seconds remaining and Isaiah Philmore missed the would-be game winner as St. Joseph's (18-12) beat Xavier (17-14) to advance to play VCU in the second round.
A full-court pass hit off the backboard and into the hands of Philmore, who missed an open look that hit off the back rim just before time expired.
St. Joe's coach Phil Martelli called the miss "an act of God."
Butler 73, Dayton 67
Rotnei Clarke scored a game-high 21 points as Butler (25-7) eliminated the Flyers (17-14) and advanced to play La Salle in today's second round.
UMass 77, George Washington 72
Chaz Williams scored 16 points as UMass (20-10) topped George Washington (13-17) and advanced to face Temple.
"We came out a little passive at first," Clarke said. "We weren't aggressive enough, weren't playing hard enough, but then we got in the flow a little bit and shots started falling."
Clarke shot 7-of-14 from the field, including 6-of-12 from 3-point range.
"I give credit to my teammates and coach drew up good plays," Clarke said. "They set great screens for me, they look for me when I'm open. It's a really unselfish team."


text:
Pretty much anyone who knows me, knows that I was going to the playboy mansion this week. It really is kind of big news, at least for a midwest girl who lives in Colorado!
My sister Shelby is an actress in LA and got us on the guest list for the party.
Next came the hunt for a sexy, not too slutty costume but still had to show some skin. The playboy mansion diet began weeks before the event.
Lots of yogurt and fruit and not much else. Scary thought of being next to playboy bunny hot chicks.
We decided to be devil sisters and went down hollywood boulevard to all the sex/costume shops. Very fun shopping and so interesting, seedy yet energetic.
Decided on a red corset, undies, garter and fishnets. No, I would not wear this to trick or treat in denver.
anyway on to the good stuff about the party
you check in at a parking garage, get a picture taken and hop on a shuttle to the mansion. After pulling up into a long, long driveway, you see the almost Gothic looking house. The party is on the main floor. The instant you walk in you recognize so many celebrities. But really funny ones that you might not really hang out with, but some good ones.
first thing, a stop into the grotto. No action going on in there, but how cool to have a drink with your sister in the grotto? no one else was in there yet. the pool is also impressive.
there is never waiting at any of the many bars, everything is set up for complete ease of drinking and having a good time. All the staff was beyond amazing and friendly.
haunted house was so impressive. I decided that I needed to be behind the scenes and scare someone. So I hopped back with a Micheal myers masked guy, borrowed his mask and waited to scare someone.
who did i scare? let me tell you.... Paris and Nicky Hilton and the guys from entourage. so fun and funny
this is some of the randomness of the people I saw there
jim belushi, adrian and Kevin from entourage, pauly shore, scott baio, larry birkhead, jon lovitz, franke muniz, mario lopez, james woods, soo many others it is hard to remember. I got a bit tipsy by the end of the night.
did lots of dancing, there were lots of entertainer dancers everywhere. guys and girls.
I will have a separate blog about the women I saw there :)
at the end we sat back and watched all the frantic last ditch efforts to hook up before the shuttles carried us away. it carried me back to reality. still having a hard time adjusting.
came back to denver, made school lunches for my daughters and had nice playboy thoughts.


text:
Sacred Temple Over-the-Ear Passive Headphones
Journey to the Sacred Temple
- Highest levels of passive noise reduction available
- Clear, distinct, and finely balanced sound
- Designed by world-class audio engineer David DeVillez
Journey to the Sacred TempleThe Sacred Temple: it's the place in every video game RPG where you receive the ancient powerful weapon of the Gods/the Force/The Powers That Be, which will allow you to take down the Big Bad when the time comes. But it's also always this beautiful garden meadow place, with those rays of sunlight filtering in, and hauntingly beautiful epic background music. Do that game soundtrack justice, and listen to it through a pair of Sacred Temple headphones.
Designed by world-class audio engineer David DeVillez, these headphones feature an all-aluminum cone that provides clear, distinct, and finely-balanced sound at both the bottom and top end. Like an epic weapon, these are handcrafted using soft leather for the ear cushions and headband, and finely machined, forged aluminum. They'll fit easily in your inventory: they're lightweight, and fold up for easy transport on your many adventures. And with the highest levels of passive noise reduction available, nothing's going to distract you from your game (or movie, or music).
Product Specifications
- Sacred Temple over-the-ear passive headphones
- Designed by world-class audio engineer David DeVillez
- Highest levels of passive noise reduction available
- All-aluminum cone provides clear, distinct, finely-balanced sound
- Traveling audiophiles will drool over its superior sound, lightweight comfort, and portability
- Specs:
- Sensitivity: 10 dB/mW
- Impedance: 16 Ohm
- Drive Unit: 40mm
- Frequency Response: 20Hz – 20KHz
- Includes:
- Fully-adjustable and foldable Sacred Temple headset
- Leather Travel Pouch
- 36" coiled stereo cable 3.5mm (male) x 3.5mm (male) connector with gold plate
- 24" straight stereo cable 3.5mm (male) x 3.5mm (male)
- 24" straight stereo cable with Apple iOS and Android Talkbox features
- 1 1/4" RCA stereo adapter plug (threaded) with gold plate
- Dimensions: Headphone-sized