Penix Research Paper

Running head: RECOGNITION FOLLOWING FACE MODIFICATIONS 1

Recognition of a Face following Superficial Modifications

Liselotte Penix

Cedar Crest College

RECOGNITION FOLLOWING SUPERFICIAL MODIFICATIONS

Abstract

This study examined the ability of 120 female Cedar Crest College students to recognize

faces after superficial modifications where made and whether or not time pressure influences

accuracy of face recognition. The two distinct superficial changes of the target face where

change of hairstyle (changed or not) and the change in facial appearance (enhanced face or not)

in relation to time pressure (timed or not). Participants had read a short vignette about a theft and

were presented with the target face. Later they made a forced choice decision from an eight-face

array. Results indicate that each participant did not choose the correct face by chance (1 in 8

people would choose the correct face). A significant main effect was found in the hair change

condition and the time condition for reaction time. A marginally significant interaction was

found in the face hair condition for reaction time. A significant main effect was found for the

hair change condition for confidence ratings.

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Recognition of a Face following Superficial Modifications

When passively observing the environment, our visual system has the tendency to pick out

what appears to be a face before it drifts to view other parts of the surroundings. Tsao and

Livingstone (2008) have written a review of theoretical works that explained how people are

capable of detecting and processing faces. Imaging studies in humans have concluded that face

recognition is processed at specific areas of the temporal lobe, but the degree of specialization

has yet to be discovered. Through extensive research, neurological evidence suggests that there

is a specific neural pathway in the brain that can differentiate between faces and object-

recognition (Tsao & Livingstone, 2008).

Face Perception

Face perception occurs in a part of the brain known as the Fusiform Face Area (FFA).

Within the brain, the FFA is located in the fusiform gyrus in the temporal lobe. This area

responds to faces holistically instead of individual parts that make up a whole (Kanwisher,

McDermott, & Chun, 1997).

Haxby, Ungerleider, Horwitze, Maisog, Rapoport, and Grady (1996) studied facial encoding,

and memory through the use of positron emission tomography (PET). Participants performed

face encoding, face recognition, face perception, and sensorimotor control tasks (Haxby,

Ungerleider, Horwitze, Maisog, & Gardy, 1996). The PET scan was used to map the brain

activity that occurred during each task participants were asked to perform in this study. The end

results showed there were no overlapping brain regions between the perception control task

(involved participants to pick which of the two choice stimuli matched the target stimuli

presented to them) and the recognition task (involved participants to choose which of the two

face stimuli was the same as the target face presented to them) during face encoding and memory

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recall (Haxby, Ungerleider, Horwitze, Maisog, & Gardy, 1996). They were able to locate a

generalized area of the brain devoted solely to face perception and recognition through the

course of this study. This eventually led to further studies in which psychologists and

neurologists look for a more specific area in the brain and then further delve into the question of

how that area may function (Haxby, Ungerleider, Horwitze, Maisog, & Gardy, 1996).

Through the use of the functional magnetic resonance imaging (fMRI), both neurologists and

psychologists have been able to locate an area of the brain in the fusiform gyrus that specifically

activates when a face is presented as stimuli over other objects (Kanwisher, McDermott, &

Chun, 1997). Kanwisher, McDermott, and Chun (1997) showed participants four types of

stimuli—the passive viewing of intact but scrambled two-tone faces, the passive viewing of full

front-view photos of faces and houses, the passive viewing of three-quarter-view of faces versus

photos of human hands, and the a matching task performed on three-quarter view faces versus

hands—while activation in the FFA was measured. Passive viewing of faces only and faces

versus objects was used to discriminate which parts of the brain activate for faces only. And

finally using different viewpoints of a face was a discriminating factor to see which part of the

brain activates at which angles. The researchers found that the FFA responded to a large array of

different facial stimuli and conclusively responds to faces in general, not to single features of a

face in 12 of the 15 participants (Kanwisher, McDermott, &Chun, 1997).

Goffaux and Rossion (2006) tested the whole-part advantage of face recognition and

composite face effects on face recognition. Experiment 1used 30 unfamiliar male and female

grayscale frontal view pictures of faces. The faces were unfamiliar in order to limit a recognition

confound during memory testing. All the faces were neutral in expression. Using Adobe

Photoshop, 20 faces swapped eyes, 5 swapped noses and 5 swapped mouths. These altered faces

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were paired with the original unaltered face was an unrelated face, or with the face that the

mouth, nose or eyes came from. Participants were asked to make a forced choice (they had to

give a definite response) when presented with the face pairs dictating if the faces were the same

or not and if they matched the target stimuli. The target stimuli were always an original face, but

the faces presented to the participants would be in full spectrum face (the face did not pass

through a filter), low-pass filtered face (the face was made to look blurred and shadowed), or

high-pass filtered face (the face was made to look like high and low contrasts) category. These

categories would be presented in a randomized order to participants. As a result, it was found

that faces of low-pass frequency had a whole part advantage, meaning that the face was

recognized as a whole. A similar result was found with the full-spectrum faces. This confirms

the hypothesis that coarse scales of face stimuli supports holistic processing.

In experiment 2, 20 egg-shaped full-front faces that were unfamiliar were split in half just

above the nostril upper limit. The face halves were then mixed to form 60 aligned (meaning the

top half of the face is the same face as the bottom half of the face) and 60 misaligned faces

(meaning that the top and bottom halves are a part of two different faces) of corresponding

gender. There is a small gap between the top half and bottom half of each face. Participants had

to complete a similar forced choice identification task as the first experiment. Goffaux and

Rossion (2006) have noticed that the participants tended to focus on the top half of each face, but

subconsciously allowed the bottom half of each face to influence matching face recognition.

Even though the face is split horizontally in half with a gap between the two parts of the face,

participants still had the tendency to see the face as a whole. This procedure allowed the

experimenters to test for feature recognition versus holistic face recognition.

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Experiment 3 went a bit further than the second experiment in this study. This experiment

was conducted in the same way as second experiment, however, all the face stimuli were shown

upside down. This was done in order to rule out a general masking effect and composite effects

that may have occurred in the previous two experiments. The researchers found that the

inversion of faces greatly reduced the composite effects in all conditions, both in accuracy and

reaction times (Goffaux & Rossion, 2006). The composite effects were thought to be a confound

in the previous part of this study.

The last experiment conducted in this study was directed towards replicating the second

experiment. The face stimuli were divided in half just above the nostrils. Then the faces were

put into pairs. The top half of each pair was the same, but the lower half may, or may not, have

been switched out. The participants were told to look at the top half of each face and indicate

whether or not the two faces presented were the same. The results for this last experiment not

only replicated the results from the second, but confirmed that the bottom half of the faces

influenced the responses to the top half of each face (Goffaux & Rossion, 2006).

This study used facial modifications that would fall under the category of reconstructive

surgery or plastic surgery. Having a face changed by using such methods is both time-

consuming and expensive. Now the question to ask is would these results be the same if the

changes made to each face was superficial and not reconstructive? If a makeup illusion was

made to make a nose look smaller and eyes larger, or if hair dye was used to change the coloring,

would participants still be able to recognize a face?

Memory

Along with possible face changes, memory tasks should also be considered. One

possible confound that could interfere with a recognition task is perceived familiarity. How does

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perceived familiarity influences face recognition? Monin (2003) studied how an increase in

perceived familiarity lead to faces being rated as familiar, even in the absence of prior exposure

to the perceived familiar face. Three experiments were conducted through the course of this

study to examine which faces were perceived as familiar (Monin, 2003). In the first experiment,

one group of participants rated the attractiveness of a set of faces, a second group of participants

rated the familiarity of the faces, while a third group of participants rated the unfamiliarity of the

face. In each of the three groups, participants were further divided into familiar and unfamiliar

face groups (Monin, 2003).

Participants were primed with a set of faces in the familiar face group while the

unfamiliar face group was not primed (Monin, 2003). In both familiar and unfamiliar face

groups, some participants were led to believe that half the faces were students and the other

participants were not. This was done in order to see if participants would rate faces as familiar if

they were to believe that the faces presented to fellow students and not complete strangers. The

second group of participants in this experiment where asked to rate either the maturity or

immaturity level of the faces presented to them. Finally, the third group of participants where to

rate the distinctiveness of each face. Each task was done with a rating scale that went from 0

(least) -10 (most) (Monin, 2003). They found that a strong correlation between the faces rated

most attractive and the faces rated most familiar, even when distinctiveness was partialed out

(Monin, 2003).

The second experiment used the same faces as the first experiment (Monin, 2003). The

total number of face images were divided in half so there were two sets of equally attractive

faces, half male and half female. One set of 40 images was given to a group of people in order

for them to indicate if the face presented was female or male. Then the participants were shown

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80 new images, then told to indicate if the faces presented were new or old (the face was shown

in part one of experiment 2) and then rate the confidence level of their answer on a 10-point scale

(Monin, 2003). Monin (2003) found that the more attractive the face was perceived, the more

often it was labeled as familiar.

Experiment 3 used the ratings collected from the first experiment in order to divide the

faces into three groups—attractive faces, unattractive faces, and neutral faces. Then, the neutral

faces were further divided into two equal sets (Monin, 2003). The procedure for this experiment

was the same as the first experiment. The results furthered the findings of the first two

experiments. The faces that were initially perceived as less attractive in the first experiment were

rated both more attractive and familiar in this experiment (Monin, 2003).

The second part of memory that needs to be defined is how a holistic face is remembered

when it is seen briefly. In order to further explore how people remember a briefly glimpsed face,

Martin, Cairns, Orme, DeBruine, Jones, and Macrae (2009) explored how repetition priming

affected facial memory of unfamiliar faces. Repetition priming occurs when a face is shown

prior to an identification task. In experiment 1, 24 faces were presented to participants, half

posed in ¾ view and half posed in frontal view, and participants chose if the faces shown were

female or male. The faces used were also morphed from an original face to a new face. The

morphed faces were either 100% the same, 75% the same, 50% the same, 25% the same or 0%

the same meaning a completely different face from the original. Participants were then shown 48

faces and asked to state if the faces were old or new, and female or male. The result showed that

repetition priming occurred when the face was shown in both the short and long lists due to

sensitivity in recognizing a face that was slightly morphed, meaning the face was still

recognizable if it was 75-50% similar (Martin, Cairns, Orme, DeBruine, Jones, & Macrae, 2009).

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A second experiment was conducted to distinguish between form-specific repetition

priming (e.g. when presented with a target face in a ¾ view, then participants will recognize the

face only if it is in the same ¾ view) and hyper specific stimulus response learning (all the small

details of a face is remembered no matter the view the face is presented in). Using the same

stimuli as the first experiment, participants identified the sex of the face in a set of 32 faces.

Then participants indicated whether or not a set of 48 faces were of high intelligence or low

intelligence, of which 16 faces were from the previous set of 32 faces (Martin, Cairns, Orme,

DeBruine, Jones, & Macrae, 2009). Repetition priming is form specific, meaning that if a face

were primed in a profile view, a participant would have great difficulty in recognizing the frontal

view of the same face (Martin, Cairns, Orme, DeBruine, Jones, & Macrae, 2009).

Experiment 3 was an expansion of experiment 1. The only change made was an increase

in the number of face stimuli used. Of a 160-face set, 80 faces were repeated and 80 faces were

new. Forty faces were unaltered and the rest were morphed (an original face was combined with

a second face) in equal parts to be 100%, 75%, 50%, 25%, and 0% similar to the original face.

Participants were asked to identify if two sequential faces were the same or not (Martin, Cairns,

Orme, DeBruine, Jones, & Macrae, 2009). Repetition priming of unfamiliar faces does not

continue after a certain perceptual change in identity. Meaning that once a face had been

morphed beyond a certain percentage, it became unrecognizable. This supports the finding that

repetition priming is form-specific to unfamiliar faces (Martin, Cairns, Orme, DeBruine, Jones,

& Macrae, 2009). This means that a face has to be in the same orientation and have similar

features in order for it to be recognizable. If a face is in a different orientation or is too different

in facial features, then a face will not be recognized as the original primed face.

Face Recognition Bias

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It is a commonly known fact that personal bias is capable of skewing our perceptions of

the world. This becomes especially true when pertaining to facial recognition exercises.

According to Baudouin and Tiberghien (2002), the impact of gender on categorization played a

large role in facial recognition. Composite androgynous faces were labeled with a female or

male name and then shown to the participants in a second task (Baudouin & Tiberghien, 2002).

The results implied that the name given to a face initially shown to the participants will indicate

which gender the participant is searching for. Therefore, participants tended to disregard the

faces of the supposed opposite gender. This was not a result of the actual gender of the face, but

the gender categorization of the name given to the face. The implication was the human face

was categorized in many ways, and having a gender helps limit the fields for recognition of a

specific face (Baudouin & Tiberghien, 2002).

As a follow up on gender as a base for face recognition, Loven, Herlitz, and Rehnman

(2011) conducted a study on own-gender bias in facial recognition to test the hypothesis that

women have own-gender bias. Participants were separated into full attention and divided

attention conditions for each experiment. In all three experiments, the female participants

consistently showed own-gender bias while the male participants did not show own-gender bias

(Loven, Herlitz, &Rehnman, 2011). Experiments 1 and 2 of this study were exactly the same.

The only difference was that a different set of faces that were used in the second experiment.

Participants were randomly divided into two groups, divided or full attention. In the divided

attention task, participants had to perform an unrelated memory task in-between the presentation

of a face set and the face recognition tasks. For both divided and full attention tasks, participants

were told to rate the distinctiveness of each face during the face recognition tasks. Both

experiments divided attention reduced memory performance in both male and female

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participants, but females place in the full attention condition displayed own-gender bias and the

males placed in the full attention condition did not show any bias during the face recognition

tasks.

The third experiment was conducted in order to find potential floor effects during the

divided attention condition. The methodology of this experiment was the same as experiments

one and two. The difference was in the group of participants placed in the divided attention

condition. Participants were asked to make a dash mark on paper every time they heard the

numbers one or five from a pre-recorded list without turning from the presented faces. The

female own-gender bias remained even with the added divided attention task.

It is important to confront recognition biases so that it does not become a confound in

new research. Many eyewitness studies have used all male faces as their target face and in line-

ups. The study conducted by Baudouin and Tiberghien (2002) gave me the idea of using

androgynous faces instead of all male faces. By using androgynous faces, superficial

modifications could be made to a greater extent to make a face look more male or female,

depending of facial enhancements or hairstyle changes. This also allows the use of female faces

with a lesser chance of own-gender bias occurring as it was found in the study conducted by

Loven, Herlitz, and Rehnman (2011).

Eyewitness Testimony

Eyewitness testimony has acquired an influential role in court throughout history. During

colonial days, if somebody were to accuse a person of a crime by stating that they have

witnessed the crime occur, then the accusers words were taken as truth and the accused was

sentenced accordingly. This was especially true during the Witch Hunts that spread across

Europe and the European colonies. If someone was accused as a witch, then they were killed

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with hardly any evidence to support these claims. This type of accusation/punishment

relationship continued for a long time before hard evidence was needed to back a claim. In

recent years, psychologists questioned the accuracy of eyewitness testimonies. It is difficult to

send a person to jail without hard evidence and only eyewitnesses.

Megreya and Burton (2008) conducted three experiments on eyewitness memory. They

have acknowledged that eyewitness accounts have poor accuracy at best with statistics stating

that performance level was around 70% for identification and around 68% for matching tasks

(Megreya & Burton, 2008). They suggest that poor performance could be due to difficulties in

the initial encoding of unfamiliar faces as well as event related memory problems (Megreya &

Burton, 2008).

The first experiment measured how accurately unfamiliar faces can be remembered. A

between-subjects design was used because one group was shown live faces while the second

group was shown video faces. There were also two sets of array slides in which one array had

the target face present and the second array did not have the target face. When the target was

present, the accuracy rate was about 60%, meaning that participants accurately chose the target

face 60% of the time, and when the target was absent, the accuracy rate was about 80%, meaning

the participants recognized that the target face was not present 80% of the time (Megreya &

Burton, 2008).

For the second experiment, the set up was very similar with having live and video faces

in a between-groups design. The difference in this experiment was that the target face was

shown along side the array of faces. The participant chose if the target face was in the array or

not, and if so which face was the target. Participants were about 70% accurate when picking out

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the correct face, but that statistic fell to about 35% for identifying a false face when the correct

face was not present in the array given (Megreya & Burton, 2008).

In the third experiment, participants followed the same procedure as experiment 2.

Participants were asked to match a face (live or image) to a single photograph instead of a line-

up. There was still the live condition group and the video condition group. Participants were

also told to take their time and be as accurate as possible when making their choice across trials.

This was to simulate the actions of bouncers and security guards when they ask to look at photo

identification. When given no time constraints, face encoding was a difficult task with an error

rate of 15% (Megreya & Burton, 2008).

Along with eyewitness memory, it is also important to understand the different types of

mug-shot presentations. The way face images are presented can influence the accuracy of a

participant’s memory recall. In the study by Stewart and McAllister (2001), mug-shots were

presented to participants one at a time or in groups of 12. To add another layer, half the books

were arranged randomly while the other half was arranged with a facial recognition algorithm

(Stewart & McAllister, 2001). The facial recognition algorithm was used to group similar faces

together on a page. It is believed that if participants were presented using a group of pictures or

a line-up of perpetrators, then the witness/participant will choose the person that is most similar

to the original, even if it is not the same person. This type of research is important due to the

new digital mug books being used by law enforcement (Stewart & McAllister, 2001). The

results of this study were surprising to the researchers. The one-at-a-time procedure produced a

significantly greater number of false positive identifications (Stewart & McAllister, 2001).

Megreya and Burton’s study brought up the issue of time in their study. The time given

to study a target face, the time interval between showing the target face and testing, and the time

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it took to respond to the forced choice in the testing phase were all manipulated at some point

during their study. As for a specific focus, consider looking at the time it took for participants to

respond and to what type of stimuli they were asked to respond too. By using the findings of the

Stewart and McAllister study, arranging an array of faces and giving a time limit to how long a

participant has to respond could simulate the urgency given to a low profile case when a larger

high profile case is being investigated at the same time.

Recognizing a superficially altered face

No previous research has focused on superficial changes in the appearance of a face. Can

a person recognize a face that has been superficially altered? The design of this study will be a

2x2x2 between groups factorial design. It was expected that the eyewitness aspect of this study

would be statistically low in accuracy, but this study specifically looked into the change of

hairstyle (change or no change) and the change in facial appearance (makeup or no makeup).

The target face will be shown for less than a second to imitate a face that is running past and the

time given for participants to respond will be recorded to see if participants are less accurate if

given a specific time frame to respond in rather than an unlimited amount of time.

For the change in superficial appearance, the greater the superficial change made to facial

appearance, the less likely a person will respond accurately. Response time will be slower and

participants will be less confident in their response. Participants will also be less accurate, faster

to respond, and less confident in their responses when placed under a time constraint. The need

for a time constraint was to consider the factor of being rushed to make an identification decision

in an investigation. Therefore, the expected outcome was that participants would be least

accurate while constrained for time than the participants who were not constrained for time.

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When both variables were combined, it was expected that time and both superficial changes of

the face were scored lowest for accuracy in the identification task.

Method

Participants

Participants were 120 female Cedar Crest College students with a mean age of 23.08 (SD

= 7.28). All participants were offered a single extra credit point for their willingness to

participate in this experiment. Participants were assigned to an experimental randomly. There

were 15 participants in each of the eight experimental conditions.

Materials

Participants were provided with a computer pre-set to show the slide slideshow

presentation of a vignette depicting a crime that the participants have supposedly witnessed. The

computer program used was called SuperLab. The first half of the vignette is written on the first

slide. The participant were to click the space bar to move onto the second slide, was timed for

750 milliseconds, depicting the offenders face. Then the participant where automatically

presented with the final slide that contained the second half of the vignette. The vignette was the

same in all conditions. This took approximately 5 minutes for participants to complete. After

the slideshow was completed, the participants were given a short quiz that consists of eight

yes/no questions about the vignette. This was presented using the SuperLab program as well.

Participants were asked to respond by typing y for yes and n for no. This served as a time-lapse

between viewing the offender’s face and viewing a line-up of possible suspects. Next,

participants were presented with an array of faces to choose from. There were eight faces shown

in the line-up. This task was either timed or not timed. A confidence question followed the 8-

face array. Finally, a demographics sheet was provided for participants asking to give their age,

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current year of schooling, and major. They were to also state whether they are a traditional

student or SAGE student, and full time or part time student. The participants were further asked

if they have ever witnessed a crime before, if they have ever served on a jury, and on a scale

from 1-7 (1 means not and 7 means very much) how important do you believe an eyewitness

testimony is in a courtroom?

There were two independent variables in this experiment: IV1 is the superficial change in

appearance of the target face (hairstyle and face enhancement) and IV2 was the time given for

the participants to make their choice (two minutes or as much time as needed).

Procedure

Participants would come in one at a time during the time-slot that they have

signed up for were welcomed upon arrival. The participants were guided to a chair in front of a

computer and given instructions and a consent form to read and sign before the experiment was

to begin. Then, participants were randomly assigned one of eight conditions before beginning

the Superlab simulation. If in one of the four timed conditions, participants were told before

typing an answer to the 8-face array that they would be given 15 seconds to respond. Following

the Superlab simulation, participants were given a demographics sheet to complete. Finally,

participants were thanked upon completion of the demographics and were asked not to talk about

this study with other students until an email was sent out stating that the data collection was

completed for this research. Participants were dismissed back to campus life.

Results

The current study employs a 2 x 2 x 2 between groups factorial design where hairstyle

change (hair of the target person stays the same or changes), appearance change (the appearance

of the target face is rough or polished), and time restraints (the time given to participants is

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constrained or not) were examined.

The results of the Chi-Square Test for Goodness of Fit involving accuracy of

participants across the four appearance change conditions were statistically significant, 2 (3) =

36.22, p < .0001, as shown in Figure 1. When this same test was conducted to compare the

accuracy of participants between the timed and not timed conditions. The results were not

statistically significant, 2 (1) = 0.074, p > .05, as shown in Figure 2.

A 2 (hair change) x 2 (face change) x 2 (time) Analysis of Variance (ANOVA) for

independent samples was computed to assess response time. There was a significant main effect

for hair change, F(1, 112) = 8.36, p < .005. In general, participants in the no change hair

condition (M = 9.48, SD = 8.19) had faster response times overall when compared to the hair

change condition (M = 13.45, SD = 9.76) as shown in Figure 3. There was a second significant

main effect for the time condition, F(1, 112) = 8.36, p < .005. The participants placed in the

timed condition (M = 6.76, SD = 3.37) had faster response times than the participants placed in

the non-timed condition (M = 16.14, SD = 10.70) as shown in Figure 4. A near significant

interaction was found between the hair change condition and face change condition, F(1, 112) =

3.86, p < .06, as charted in Figure 5.

A 2 (hair change) x 2 (face change) x 2 (time) Analysis of Variance (ANOVA) for

independent samples was computed to assess confidence ratings. There was a significant main

effect for hair change, F(1, 112) = 10.11, p < .002. In general, participants in the no change hair

condition (M = 5.50, SD = 1.37) had faster response times overall when compared to the hair

change condition (M = 4.55, SD = 1.83) as shown in Figure 6.

A Pearson’s correlation coefficient was computed to assess the relationship between

the accuracy and response time of participants. There was no correlation found between the two

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variables, r = 138, n = 120, p > .05.

Discussion

As shown in the results, face recognition was flawed especially when the hair was

changed. The hair was changed from dark to light and straight to curly. All hairstyles stayed

short so that the faces were similar and remained gender neutral in the line-up. This probably

occurred due to hair acting as a major focal point of a face shown for less than a second (as if a

person is running by).

This was shown when the chi-square test was conducted. The hair changes condition had

the least number of accurate responses, closely followed by the both change condition, where as

the no change condition and the face change condition had very high accuracy. The reason for

the both change condition having low accuracy was most likely due to the change in hair rather

than the combined change.

When it came to response time, both the hair change and time conditions had a main

effect that was as predicted. The response time was slower when the hair was changed and faster

when it was not changed. This implies that the participants in the changed hair condition had to

spend more time analyzing the images and going over their memory of the finer details in order

try and choose the correct face. When given a definitive time limit, participants responded faster

than when not giving a time limit. This implies that participants try to choose before the time

limit is up by focusing on the major futures of a face rather than wait till the last second to

respond. When no time limit is given, participants take longer to study the finer details of the

face rather than to rely solely on the major features of a face.

There was a near interaction between face change and hair change for response time.

What would be predicted that the no change condition would have the fastest response time

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while the both change condition would have the slowest. What my results have shown was that

the hair change condition had the slowest response time. This could be due to the fact that the

hair change was more dramatic than the face change, which was more subtle. This would imply

that participants were more focused on major features staying the same rather than a subtle

change in a face such as a mole being concealed.

Confidence ratings followed the predictions for the hair change condition as well. As the

results have shown, confidence ratings decreased when the hairstyle changed and increased when

the hairstyle did not change. This could be due to the fact that the change made was dramatic

enough to confuse participants. The implication behind this would be that in a trial, if there is

little other incriminating evidence, than a less confident response could lead to reasonable doubt

in eyewitness testimony. It could also lead to false convictions.

There were many limitations in this study. The most obvious one was that I modified the

faces using Photoshop. The faces were selected from a pre-existing database and were a

combination of male and female neutral faces. This could have been solved if I would have used

a live face and had the changes appear more natural rather than cropping and pasting other

features onto a photographed face. It would have been better for me to use all male faces as well

instead of mixing the genders. Using all male faces, rather than mixed-gendered faces, could

limit, or even further reduce the amount of own-gender bias of the female participants.. I

could have also used more modern faces with the current hair trends instead of the faces from the

database that were from the 1980’s.

The second limitation would be the varied times in which participants took to complete

my study. This could be fixed by standardizing the time interval between reading the vignette

and viewing the line-up. Instead of yes/no questions, I could have asked participants to write

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their answers on a separate sheet of paper and had each question timed for two minutes. This

would have lead to a more realistic time laps that could lead to implications in memory across

time. The time lapse was supposed to symbolize the time between seeing the perpetrator commit

a crime and then viewing a line-up of possible suspects a few hours later. To make this study

more realistic, I would suggest having participants read the vignette on one day, then come back

to the lab the next day to complete the questionnaire about the crime and view the line-up.

Further examination could be done in order to determine just exactly how much, and to

what extent can hair change and style be manipulated before it becomes completely

unrecognizable for face recognition. This would help further research in eyewitness testimony as

well as hopefully leading towards new standards for making composite sketches of a face.

Making a face have multiple different hairstyles and hair colors would probably aid police to

find a suspect faster.

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References

Baudouin, J. Y., & Tiberghien, G. (2002). Gender is a dimension of face recognition. Journal of

Experimental Psychology: Learning, Memory, and Cognition, 28, 362–365. doi:

10.1037//0278-7393.28.2.362

Goffaux, V., & Rossion, B. (2006). Faces are "spatial"-holistic face perception is supported by

low spatial frequencies. Journal of Experimental Psychology: Human Perception and

Performance, 32(4), 1023-1039. doi: 10.1037/0096-1523.32.4.1023

Haxby, J.V., Ungerleider, L.G., Horwitz, B., Maisog, J.M., Rapoport, S.I., & Grady, C.L. (1996).

Face encoding and recognition in the human brain. Proceedings of the National Academy

of Sciences of the United States of America, 93, 922-927.

Kanwisher, N., McDermott, J., & Chun, M.M. (1997). The fusiform face area: A module in

human extrastriate cortex specialized for face perception. The Journal of Neuroscience,

17(11), 4302-4311.

Kranz, F., & Ishai, A. (2006). Face perception is modulated by sexual preference. Current

Biology, 16, 63-68. doi: 10.1016/j.cub.2005.10.070

Loven, J., Herlitz, A., & Rehnman, J. (2011). Women’s own-gender bias in face recognition

memory. Experimental Psychology, 58(4), 333-340. doi: 10.1027/1618-3169/a000100

Martin, D., Caurns, S.A., Orme, E., DeBruine, L.M., Jones, B.C., & Macrae, C. (2010). Form-

specific repetition priming for unfamiliar faces. Experimental Psychology, 57(5), 338-

345. doi: 10.1027/1618-3169/a000040

Megreya, A.M., & Burton, A.M. (2008). Matching faces to photographs: Poor performance in

eyewitness memory (without the memory). Journal of Experimental Psychology, 14(4),

365-372. doi: 10.1037/a0013464

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Monin, B. (2003). The warm glow heuristic: When liking leads to familiarity. Journal of

Personality and Social Psychology, 85(6), 1035-1048. doi: 10.1037//0022-

3514.85.6.1035

Stwart, H.A., & McAllister, H.A. (2001). One-at-a-time versus grouped presentation of mug

book pictures: Some surprising results. Journal of Applied Psychology, 86(6), 1300-1305.

doi: 10.1037//0021-9010.86.6.13006.

SuperLab: Stimulus Presentation Software (Version 4.0) [Computer Software]. San Pendro, CA:

Cedrus.

The Psychological Image Collection at Stirling (http://pics.psych.stir.ac.uk) Emotions: Smile,

surprise, disgust Ilicitation: Posed Size: Aberdeen: 116 subjects Nottingham scans: 100

Not-faces-original: 100 Stirling Faces: 36 Kind: Contains seven face database of which

four largest are Aberdeen, Nottingham scans, Not-faces-original.

Tsao, D.Y., & Livingstone, M.S. (2008). Mechanisms of face perception. The Annual Review of

Neuroscience, 31, 411-437. doi: 10.1146/annurev.neuro.30.051606.094238ur

22

http://pics.psych.stir.ac.uk/


Figure 1: This graph depicts that accuracy was not left to chance. The accuracy of participants

was greater for the no change and face change conditions. The accuracy of participants was

much lower for the hair change and both change conditions.

No Change Face Change Hair Change Both Change0

5

10

15

20

25

30

Appearance Change

Nu

mb

er o

f Cor

rect

Res

pon

ses

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Timed Not Timed20

21

22

23

24

25

26

27

28

29

30

Time Condition

Nu

mb

er o

f Co

rrec

t R

esp

on

ses

Figure 2: This graph depicts that accuracy appeared to be left to chance when comparing the

timed and not timed conditions. There is no statistical significance between the two sub

conditions.

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No Change Change0

2

4

6

8

10

12

14

16

Hair Condition

Tim

e (s

ec.)

Figure 3: This graph depicts a significant main effect for the hair change condition. When no

change was made, response times were much faster than when the hair was changed.

25


Not Timed Timed0

2

4

6

8

10

12

14

16

18

Time Condition

Tim

e (s

ec.)

Figure 4: This graph depicts a significant main effect for the time condition. When not timed,

response times were much slower than when timed.

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Figure 5: This graph depicts a near significant interaction between the hair and face conditions.

What is unexpected was that the hair change condition had the slowest response time on average

rather than the both change condition.

Face ConditionH

air

Con

dit

ion

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No Change Change4.6

4.7

4.8

4.9

5

5.1

5.2

Hair Condition

Par

tici

pan

t R

atin

g

Figure 6: This graph depicts a significant main effect for the hair change condition. When no

change was made, confidence ratings were much higher than when the hair was changed.

28


Vignette

(Slide 1) A small, grey haired woman, laden with carriers, emerged from Smart Shop

Grocers and shuffled over to sit on the bench next to the bus stop. She appeared short and frail in

the evening glow, with a clutter of white plastic bags stored at her feet and a light brown purse

lying in her lap. She sat quietly hunched over among the other awaiting passengers, seemingly

ignored by them all. The exception to this was a young person seemingly engrossed in their

iPhone. This person has been following the elder lady since she has entered the Smart Shop

Grocers. The young person appeared to be completely disheveled and wore torn cloths. The

jeans were faded with holes in the knees and the jacket was black and speckled with light

threads. The young person had the look of a cat lying in wait for a mouse.

(Slide 2) A picture of the target face with no changes made to it will be presented for less

than a second.

(Slide 3) The bus arrived with a loud screech. Everyone gathered their belongings and

started to line up to get on. The old lady was collecting her bags, and the young person stuffed

their iPhone into the front jean pocket. It was mildly odd that the person was standing so close to

the elderly women since there was no familial resemblance and the younger was not even trying

to help the older. The young person was simply biding their time till the opportunity presented

itself. When the elderly woman turned her head to the side, the young person reach out to knock

the elderly woman aside. They snatched the purse and started running down the sidewalk and

took a turn into the closest alley. There was a stunned silence until sirens were heard and the

police arrived. It had taken a few days after interviewing witnesses and collecting evidence

before a suspect was brought in for questioning.

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Vignette Quiz

1. The color of the purse is black.

Yes No

2. The person who was mugged was an elderly lady.

Yes No

3. The thief was male.

Yes No

4. The thief wore a dark hoody.

Yes No

5. The thief was neat in appearance.

Yes No

6. The bus stop was located in front of a flower shop.

Yes No

7. The theft occurred before the bus arrived.

Yes No

8. The thief was listening to headphones.

Yes No

9. A slide presenting the 8-face array will be displayed. Each face will have a number and the

participant is to try and choose the correct face.

10. Please rate your confidence level on a scale from 1-7

(1=not confident, 4=neutral, and 7=confident).

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Demographics Questions

1. Age: _____________

2. Race:

a. Caucasian

b. African-American

c. Native-American

d. Hispanic

e. Asian

f. Other (please specify): _____________________

3. Which state are you from? ________________________________

4. School Year (please circle one): Freshman Sophomore Junior Senior

5. Major: ___________________________________

6. Type of student (please circle one of each):

a. Traditional SAGE

b. Part-time Full-time

7. Do you watch crime-based television shows? Yes No

8. If yes to question 6, please list them:

9. Have you ever witnessed a crime? Yes No

10. Do you believe eyewitness testimony is relevant for any/all convictions? Yes No

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Penix Research Paper

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