Beauty is Better Pursued: Effects of Attractiveness in 
Multiple-Face Tracking 

 
 

Journal: Quarterly Journal of Experimental Psychology 

Manuscript ID: QJE-STD 10-283.R3 

Manuscript Type: Standard Article 

Date Submitted by the 
Author: 

n/a 

Complete List of Authors: Liu, Chang; University of Hull, Department of Psychology 
Chen, Wenfeng; Institute of Psychology, Chinese Academy of 

Sciences 

Keywords: attractiveness, multiple-face tracking, attention 

  

 

 

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Dear Professor Tipper, 

 

Thank you for your thoughtful comments. We have now carefully revised our manuscript according 

to your new suggestions. 

 

1. Following your advice, we have performed separate analyses for male and female participants. 

This showed significant main effects of attractiveness and face gender for female participants. There 

was also an interaction between the two variables. However, no effects were found for male 

participants. The pattern of results is consistent with your prediction. The new analyses have been 

added to the result section. We have also discussed this gender effect further in General Discussion. 

We agree that if Schacht et al (2008) did use fewer females, it could have been a cause for discrepant 

findings. We have checked this and found that they used 13 female and 5 male participants. Perhaps 

as they suggest, "the effects of attractiveness are strongly task dependent." 

  

 

2. We have qualified our general conclusion that attractiveness is automatically computed and high 

level processes feedback into earlier tracking. We have cautioned that the attractive effects may only 

be true of female participants because of the findings in Experiment 3 (previously Experiment 2). We 

have also mentioned the similarity between the gender effect in our study and the effect in Bayliss et 

al. We have qualified the broad statements in the abstract as well. 

 

3. We agree that more data from male participants for all other experiments would have been ideal. 

However, due to our limited resources, we have found this to be quite difficult to accomplish. We 

have therefore followed your second solution to re-write and restructure the paper. We hope the 

potential sex difference will spark future research.  

 

Following your instruction, we have highlighted the changes we made in the manuscript by using the 

track changes mode in MS Word. 

 

 

Sincerely yours, 

Chang Hong Liu and Wenfeng Chen 

 

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Attractiveness Affects Multiple-face Tracking 1 

Running Head: ATTRACTIVENESS AFFECTS MULTIPLE-FACE TRACKING 

 

 

 

Beauty is Better Pursued: 

Effects of Attractiveness in Multiple-Face Tracking 

 

Chang Hong Liu 

University of Hull 

 

Wenfeng Chen  

Chinese Academy of Sciences 

 

 

 

Correspondences: 

Chang Hong Liu, PhD         Wenfeng Chen, PhD 

Department of Psychology        Institute of Psychology 

University of Hull          Chinese Academy of Sciences 

Cottingham Road          4A Datun Road 

Hull, HU6 7RX           Chaoyang District, Beijing 

United Kingdom           China 

 

Tel: +44 1482-465572         Tel: +86 10 6483-7040 

Fax: +44 1482-465599         Fax: +86 10 6487-2070 

Email: C.H.Liu@hull.ac.uk        Email: ChenWF@psych.ac.cn 

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mailto:ChenWF@psych.ac.cn


Attractiveness Affects Multiple-face Tracking 2 

Abstract 

Using the multiple-object tracking paradigm, this study examines how spontaneous appraisal for 

facial beauty affects distributed attention to multiple faces in dynamic displays. Observers 

tracked attractive faces more effectively relative to unattractive faces in this task. Tracking 

performance was only affected by target attractiveness, suggesting an absence of appraisal for 

distractor attractiveness. Attractive male faces also produced stronger binding of face identity 

and location for female participants. Together, the results suggest that facial attractiveness was 

appraised during tracking even though this was task irrelevant. Contrary to the theory that 

multiple-object tracking is driven by encapsulated low-level vision, our results show that the 

content of target representation is not only penetrable by social cognition but also modulates the 

course of tracking operations.

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Attractiveness Affects Multiple-face Tracking 3 

Beauty is Better Pursued: 

Effects of Attractiveness in Multiple-Face Tracking 

It is well known that human observers pay greater attention to faces than to non-face 

objects (e.g., Ro, Russell, & Lavie, 2001). Moreover, some face stimuli attract more attention 

than others. Apart from certain facial expressions such as fear and anger (Palermo & Rhodes, 

2007), attractive faces also trigger greater attention (Sui & Liu, 2009). Popular culture often 

suggests that a mere glance of a face elicits spontaneous appraisal of attractiveness. Humans 

may be predisposed to direct attention to attractive faces because of their biological and 

social significance. There is well-established evidence that even newborn babies look at 

attractive faces longer (e.g., Geldart, Maurer, & Carney, 1999; Langlois et al., 1987; Samuels 

et al., 1994; Slater et al., 1998). Adults also tend to spend more time looking at beautiful faces 

(Aharon et al., 2001; Kranz & Ishai, 2006), which are known to activate dopaminergic 

regions in the brain that are strongly linked to the reward system (Kampe, Frith, Dolan, & 

Frith, 2001).  

Appraisal of facial beauty appears to depend on how well a face resembles the average in 

a population (Langlois & Roggman, 1990). Although symmetry also plays a role in facial 

beauty (e.g., Grammer & Thornhill, 1994), there is evidence that it is less important than 

averageness (Rhodes, Sumich, & Byatt, 1999; also see Rhodes, 2006, for an extensive review). 

Hence attentional capture by attractive faces may rely on preattentive computation of 

averageness in face stimuli.  

However, little is known about how facial attractiveness affects attentional mechanisms. 

This issue may be addressed through the existing attention paradigms. For example, Maner, 

Gailliot, and DeWall (2007) employed a dot-probe paradigm to assess the effect of 

attractiveness on disengaging attention. Consistent with their hypothesis, their observers were 

slower at disengaging attention from attractive female faces relative to average-looking 

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Attractiveness Affects Multiple-face Tracking 4 

female or male faces. In another study, Maner, Gailliot, Rouby, and Miller (2007) used the 

same method and found that participants fixated on highly attractive faces within the first half 

second and took longer to stop looking at them when asked to shift their attention away. In a 

different approach, Sui and Liu (2009) investigated whether appraisal for attractiveness 

occurs when spatial attention has already been directed elsewhere. They employed a spatial 

cuing task, where participants were asked to judge the orientation of a cued target presented 

to the left or right visual field while ignoring a task-irrelevant face image flashed in the 

opposite field. They found that the presence of attractive faces significantly lengthened task 

performance. This suggests that facial beauty can automatically compete with an ongoing 

task for attention, although this does not necessarily mean that appraisal of facial beauty is a 

mandatory process (see Schacht, Werheid, & Sommer, 2008). The analysis of eye movements 

in Sui and Liu’s study revealed that the effect of facial attractiveness was not due to foveal 

fixation on the target or face stimuli, hence there is a strong possibility that facial 

attractiveness can be detected outside the fovea. This has been confirmed by a recent 

investigation, where discrimination of facial beauty was measured at several eccentricities 

(Guo, Liu, & Roebuck, 2011). 

Both dot-probe and cuing tasks require focused attention, where attention is directed to a 

single spatial location. However, attention in reality can be distributed to several different 

targets or spatial locations. For instance, a group activity requires attention to be paid to 

multiple individuals and locations. The main purpose of this research was to investigate the 

effect of facial attractiveness on distributed attention. Another motivation of this research 

comes from observation that spontaneous appraisal of attractiveness is rapid and transient 

(Schacht et al., 2008). It remains unclear whether such an appraisal only manifests in brief 

attentional shifts. Hence the second purpose of this study was to investigate whether a similar 

kind of automatic appraisal for facial attractiveness occurs continuously when sustained 

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Attractiveness Affects Multiple-face Tracking 5 

attention is distributed among faces in multiple locations.  

Pylyshyn and Storm (1988) designed a multiple-object tracking paradigm (MOT) to 

study how human observers maintain attention on multiple objects across space and time. In 

recent years, the issue of content addressability in object tracking is hotly debated. This issue 

was first raised by Pylyshyn (2004) who found that observers were remarkably poor at 

identifying the features or identity of correctly tracked objects. This phenomenon 

demonstrates a poor binding of object features and location. Pylyshyn’s explanation is that 

MOT is implemented by early or low-level vision, where the information about individual 

identity is encapsulated and inaccessible from higher level cognition. His theory assumes that 

early vision picks out a small number of objects while ignoring their visual properties. 

Because of this, object identity differentiated by visual properties is not coded or accessible 

from higher level cognitive processes even when the objects with those properties are 

attended. However, recent evidence has challenged this position by showing that tracking is 

content addressable (Horowitz et al., 2007).  

This debate has an important implication for the present study. If the information content 

of tracked faces is not processed, tracking performance should not be affected by facial 

attractiveness. It is known that information about face identity (i.e., individuation of face 

stimuli by features and configurations) is not completely lost in tracking tasks (Ren, Chen, 

Liu, & Fu, 2009). If representations of the tracked faces are to some extent content 

addressable, there is a chance that other high-level information such as facial attractiveness is 

also available for processing. If processing of such information is spontaneous, this could in 

turn affect multiple face tracking. The experiments in this study were designed to test this 

hypothesis. The outcome should reveal the extent to which a high-level social cognition can 

penetrate and influence the low-level visual perception. Appraisal for facial beauty requires 

high-level vision, because a main criterion for beauty—averageness—cannot be determined 

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Attractiveness Affects Multiple-face Tracking 6 

solely from low-level visual features such as luminance, contrast, and size. Computing 

averageness requires identifying the landmarks of higher level facial features such as the eyes, 

the mouth, and the face shape. The operations for image normalization, alignment, and 

comparison with the average in the hypothetical multi-dimensional face space also require 

high-level vision. To ensure that our results were controlled for the low-level contribution, we 

carefully scaled all our tracking stimuli to the same size, luminance, and contrast. 

Other high-level information accompanying appraisal of facial attractiveness could also 

contribute to multiple-face tracking performance. As Dion, Berscheid, and Walster (1972) 

showed in their seminal study, beautiful people are generally perceived to possess more 

positive attributes. They called this the “beauty-is-good” stereotype. Many studies have since 

produced evidence for this positive association between attractiveness and goodness (see 

Eagly, Ashmore, Makhijani, & Longo, 1991, and Langlois et al., 2000, for reviews). It is also 

referred to as the halo effect of attractiveness. This well established duality of beauty could 

predict a similar effect on tracking based on attractive and valence measures. Moreover, if the 

reward system is involved in perception of attractive faces (Kampe et al., 2001), arousal 

could also be responsible for any effect of attractiveness on tracking performance. To address 

these questions, we compared whether valence and arousal affect tracking performance in the 

same way as attractiveness.  

Experiment 1 

The main purpose of Experiment 1 was to investigate how target and distractor 

attractiveness may affect tracking performance differently. Given the prior finding that the 

target face identity is content addressable (Ren et al., 2009), we hypothesized that the target 

faces could be automatically appraised for their attractiveness. Attractive distractors, on the 

other hand, could impair tracking performance if they were also appraised for attractiveness.  

Method 

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Attractiveness Affects Multiple-face Tracking 7 

Participants. A total of 25 undergraduate students (19 females) from the University of 

Hull participated in this study. The age of the participants ranged from 18 to 28 years (Mdn = 

19). All participants had normal or corrected-to-normal vision. 

Stimuli. The face database was obtained from the University of St. Andrews. It contains 

702 frontal-view Caucasian faces with no external features (hair and clothing). The size of 

the faces was normalized according to the face width. The resulting image measured 3.0 × 3.8 

cm (2.8 × 3.6º) on screen. All images were scaled to the same mean luminance and 

root-mean-square contrast.  

All faces in the database were rated by 19 raters (aged between 18 and 29 years, 12 

females) for attractiveness on a 7-point scale. To contrast the effect of attractiveness, only the 

149 most attractive and the 132 least attractive faces were used in this experiment. The mean 

ratings for the two groups of faces were 3.91 (3.96 for females, 3.72 for males. SD = 0.39) 

and 2.39 (2.35 for females, 2.46 for males. SD = 0.38), respectively. These were significantly 

different from each other (p < .001). Slightly more than half (58.3%) of the faces were 

females. Each attractive or unattractive face was only used once for each participant: 80 were 

randomly chosen from the pool of attractive faces, and another 80 were randomly chosen 

form the pool of unattractive faces. 

We performed an additional norming study on the face stimuli to measure how 

attractiveness is related to valence and arousal. Twenty undergraduate students, aged between 

18 and 33 years (M = 21.1, SD = 4.4), rated a total of 452 faces for valence and arousal. The 

image set consisted of the attractive and unattractive faces in this experiment as well as the 

additional 171 average faces used in Experiment 3. The faces were rated one at a time. The 

presentation order was random. To avoid response bias, the raters were not informed until the 

end of the experiment that the rating data would be used to study facial attractiveness. The 

details of our procedure were identical to that for the International Affective Picture System 

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Attractiveness Affects Multiple-face Tracking 8 

(Lang, Bradley, & Cuthbert, 2008). A 9-point rating scale was used where 1 represented 

completely unhappy/calm, whereas 9 completely happy/excited respectively for the valence 

and arousal judgments. Table 1 shows the mean rating results for each face category. To 

determine whether valence and arousal ratings vary according to levels of attractiveness, we 

conducted separate analyses of variance (ANOVA) for the two variables. The main effect of 

valence was significant, F (1, 449) = 43.24, MSE = 19. 41, p < .001, partial η
2 

= .17, where 

the valence for attractive faces was higher than for average-looking and unattractive faces (p 

< .001), and the valence for average-looking faces was higher than for unattractive faces (p 

< .001). On the other hand, the main effect of arousal was not significant, F (1, 449) = 1.49, 

MSE = .41, p = .23, partial η
2 
= .01. 

The tracking stimuli were displayed on a 21" monitor (SONY Trinitron, GDM-F520). A 

central square area with 22.8 × 22.8º of visual angle was designated for stimulus presentation. 

The background color of the display was gray. E-Prime (Version 1.2) was used to generate 

the dynamic tracking and still displays and to control the flow of the experiment. 

Design. We employed a within-subject design. The independent variables were target 

attractiveness (attractive vs. unattractive) and distractor attractiveness (attractive vs. 

unattractive), and face gender (male vs. female). Following this design, the target faces, 

which were either all attractive or unattractive, were tracked among distractor faces, which 

were also either all attractive or unattractive. 

Procedure. Participants were tested individually. An adjustable headrest was used to fix 

the participant's viewing position, which was set 60 cm away from the computer monitor. The 

faces presented in each trial were of the same sex. They were randomly chosen for each trial 

from the pool of 281 faces. The chosen images were not repeated in the subsequent trials until 

all faces in the pool were used. The procedure for each trial of the experiments is illustrated 

in Figure 1A. Each trial was initiated by a key press. It began with 10 stationary black 

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Attractiveness Affects Multiple-face Tracking 9 

rectangles on the screen. The location of the rectangles was randomly assigned, with the 

constraint that none would occlude the others and the center-to-center distance was not less 

than twice of their size. Five of the rectangles would then start to blink twice for 2 s, 

signaling the target location. Following this, the rectangles changed abruptly into 10 faces, 

and started to move in random directions. The faces bounced off each other when the 

center-to-center distance was less than twice of their size. They avoided the edge of the 

display area when the center to edge distance was less than their size. Participants were asked 

to track the five moving targets. The velocity of the face images varied between 3.9 and 6.3 º 

/ s with a mean of 5.1º / s. All faces moving about the screen for 5 s. As soon as the motion 

stopped, all the faces were again occluded by black rectangles. The task was to pick out the 

five targets by clicking on the rectangles. Once being clicked, the rectangle was highlighted 

with a yellow border which could be switched on and off by clicking. Participants were 

forced to select 5 items and were allowed to guess. Once 5 items were selected, they clicked a 

“finish” button to start the next trial. The experiment lasted about 30 minutes. 

A total of 80 experimental trials were run after 4 practice trials. Each of the eight 

conditions (2 target attractiveness × 2 distractor attractiveness × 2 face gender) had 10 trials. 

All 80 trials were mixed in random order in one block. 

Results and Discussion 

An alpha level of .05 was used for all statistical analyses in this report. Results of 

tracking accuracy are shown in Figure 2. The data were analyzed using repeated-measures 

ANOVA. There was a significant main effect of target attractiveness, F (1, 24) = 8.50, MSE = 

18.52, p < .01, partial η
2 
= .26, where attractive faces were tracked better than unattractive 

faces. However, there was no difference between results for attractive and unattractive 

distractors, F (1, 24) = 1.77, MSE = 27.74, p = .20, partial η
2 

= .07. There was also a main 

effect of face gender, F (1, 24) = 7.47, MSE = 23.31, p < .01, partial η
2 
= .24, where male 

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faces were tracked better than female faces. However, face gender did not interact with other 

factors, ps > .57. None of the other two-way or three-way interactions was significant, ps 

> .15.  

The experiment shows that tracking performance was affected by appraisal of facial 

attractiveness. This effect was only present for the target faces, while the influence of 

attractive distractors was negligible. Although male faces were tracked better than female 

faces, the effect was not modulated by attractiveness.  

The effect of attractive faces on tracking performance could be due to varying levels of 

involuntary attention to task-irrelevant information. Some participants might be able to 

suppress or control attention to the task-irrelevant information better than others. If this is the 

case, it would be possible that those who were poor at the tracking task would show a 

stronger attractiveness effect, because they are poor at suppressing the attractiveness 

information. To test this prediction, we analyzed the correlation between the size of 

attractiveness effect and overall tracking performance. Consistent with this prediction, a 

negative correlation was found between the two, r = -0.59, p < .001. Figure 3A shows a 

scatter plot of this correlation.  

Because the attractive faces had greater valence rating than unattractive faces in our 

norming study, we evaluated how the difference of valence contributed to the attractiveness 

effect in this experiment. This was done by an item-based analysis of covariance (ANCOVA), 

where facial attractiveness was treated as a random factor, and the valence a covariate. 

ANCOVA measures whether attractiveness had an effect on tracking performance after 

removing the covariate valence. Because only the target attractiveness had an effect on 

tracking performance, we only used target attractiveness in our ANCOVA as an independent 

factor. Hence the target faces were used as random sample, and corresponding valence for 

these faces as covariate. Results showed a significant main effect of target attractiveness, F (1, 

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Attractiveness Affects Multiple-face Tracking 11 

278) = 3.57, MSE = .07, p < .03, partial η
2 

= .02, where attractive targets were tracked better 

than unattractive targets. However, the covariate was not significant, F (1, 278) =.59, MSE 

=.001, p = .44, partial η
2 
= .002, suggesting that the valence made no contribution to the 

attractiveness effect found in this experiment. 

Experiment 2 

In Experiment 1, the target faces were either attractive or unattractive. When the targets 

had a similar level of attractiveness, attention might be more or less evenly distributed among 

the targets. However, if attractiveness varies considerably among targets, attention and 

consequently tracking performance for a given target could be affected by its attractiveness 

relative to other targets. To test this hypothesis, we varied level of target attractiveness in this 

experiment such that the targets consisted of attractive, average, and unattractive faces. We 

then compared the performance for these different types of targets.  

Another issue concerning the use of all attractive or all unattractive targets was that 

attractive faces may be more visually similar to one another than unattractive faces. Yantis 

(1992) showed that similarity among targets improves tracking. Because of this, the tracking 

advantage for attractive targets may not reflect attractiveness directly, but rather through 

featural similarity. The design in the present experiment was able to eliminate this problem 

because an effect of attractiveness would no longer be due to greater similarity among the 

attractive targets. 

Method 

Participants. A different group of 61 undergraduate students (48 females and 13 males) 

from the University of Hull participated in this study. The age of the participants ranged from 

17 to 34 years (Mdn = 20). All participants had normal or corrected-to-normal vision. 

Stimuli. The attractive and unattractive face stimuli were the same as in Experiments 1 

and 2. In addition, we also added average-looking faces. The mean ratings for the 

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Attractiveness Affects Multiple-face Tracking 12 

average-looking faces was 2.99 (SD = 0.11, N = 171). As in the previous experiments, each 

face category consisted of 80 faces randomly selected from the respective pool of stimuli for 

each participant. Each trial contained one attractive, one unattractive, and three 

average-looking target faces. The distractors in this experiment consisted of average-looking 

faces. Because 8 average faces were used in each trial and 80 trials in total, this requires a 

total of 640 average faces (80 × 8). Since there were 171 average faces available, each face 

was repeated about 4 times (640 ÷ 171 = 3.7). 

Design. This was again a within-subject design. The independent variables were target 

attractiveness (attractive, average, and unattractive) and face gender. Because Experiment 1 

showed no effect of distractor attractiveness, this variable was not included in this and the 

next experiments. 

Procedure. This was identical to Experiment 1. 

Results and Discussion 

The tracking results are shown in Figure 4. The main effect of target attractiveness was 

significant, F (2, 120) = 4.96, MSE = 61.83, p < .01, partial η
2 

= .10. No significant effect 

was found for face gender, F (1, 60) = 0.01, MSE = 93.25, p = .98, or interaction between 

face gender and target attractiveness, F (2, 120) = 0.90, MSE = 70.68, p = .41. Post hoc 

comparisons of means with Bonferroni correction revealed better tracking performance for 

attractive targets relative to average or unattractive targets ts (60) > 2.66, ps < .02. There was 

no difference between results for average and unattractive targets, t (60) = 0.11, p = 1.00. The 

results suggest that attractive faces were attended more favourably whereas unattractive and 

average-looking faces were not treated differently during tracking. 

Consistent with Experiment 1, there was a significant negative correlation between 

participants’ overall tracking performance and the size of the attractiveness effect, r = -0.22, p 

< .04. A scatter plot of this correlation is shown in Figure 3B. 

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Results of ANCOVA for Experiment 2 show that there was a significant main effect of 

target attractiveness, F (1, 448) = 7.37, MSE = .07, p < .01, partial η
2 

= .03, where attractive 

faces were tracked better than average-looking and unattractive faces (ps < .01), and there 

was no difference between average-looking faces and unattractive faces (p = .51). The 

covariate, or valence of the faces, was also significantly related to the tracking performance, 

F (1, 448) = 9.90, MSE = .09, p < .01, partial η
2 
= .02. This indicates that the valence of faces 

also contributed to the attractiveness effect in this experiment. 

Experiment 3 

The tracking task in Experiments 1 and 2 did not explicitly require binding of a target 

identity with its location. If target attractiveness is appraised, it is possible that the location of 

an attractive target is monitored more accurately relative to an unattractive target. To test this 

hypothesis, we employed a variant of the MOT paradigm, where one of the faces was 

randomly chosen from the targets and probed at the end of each trial. The task here was to 

specify the location of the probe face.  

Method 

Participants. A different group of 50 undergraduate students (25 females and 25 males) 

from the University of Hull participated in this study. The age of the participants ranged from 

18 to 35 years (Mdn = 20). All participants had normal or corrected-to-normal vision. 

Stimuli. These were the same as Experiment 1. 

Design. This was again a within-subject design. The independent variables were 

attractiveness, face gender, and participant gender. Although not originally planned, potential 

participant gender difference was included in our analysis because the number of participants 

in each gender group was fully balanced. 

Procedure. The procedure of this experiment was identical to Experiment 1 except that at 

the end of each trial one of the faces was randomly chosen from the targets and probed (see 

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Figure 1B). The participant was required to specify the specific location of the probe face by 

clicking on one of the occluded faces with a mouse. The occluder of the chosen face was then 

removed to reveal the answer after the mouse click. This feedback was used to engage the 

participants. Because this task was harder than the standard task, the number of faces in each 

trial was reduced to 8, with the number of target faces reduced to 4. The task began with four 

practice trials followed by 40 experimental trials (10 trials × 4 conditions). 

Results and Discussion 

The locations of attractive targets were identified better than unattractive targets, F (1, 48) 

= 4.70, MSE = 241.50, p < .04, partial η
2 
= .11. Neither face gender nor participant gender 

produced a significant main effect, Fs (1, 48) = 1.08 and 0.001, ps = .30 and .98, respectively. 

However, this was qualified by a significant two-way interaction between participant gender 

and attractiveness, F (1, 48) = 9.97, MSE = 241.50, p < .01, partial η
2 

= .17, as well as a 

marginally significant interaction between participant gender and face gender, F (1, 48) = 

3.80, MSE = 204.27, p = .057, partial η
2 

= .07. The three-way interaction also approached the 

level of significance, F (1, 48) = 2.78, MSE = 168.51, p = .10, partial η
2 
= .06. The two-way 

interaction between face gender and attractiveness was not significant, (1, 48) = 1.63, p = .21, 

partial η
2 

= .03. The interaction effects are illustrated in Figure 4.  

To investigate the interaction effects, we conducted separate ANOVAs for the two 

participant genders. Results for the female participants showed a significant main effects of 

attractiveness, F (1, 24) = 14.73, MSE = 246.00, p < .001, partial η
2 
= .38, and face gender, F 

(1, 24) = 4.45, MSE = 478.39, p < .05, partial η
2 
= .16. There was also a significant 

interaction between attractiveness and face gender, F (1, 24) = 7.55, MSE = 96.54, p < .01, 

partial η
2 

= .24. Further analyses of the interaction via pairwise comparisons of means 

revealed that female participants identified the spatial locations for attractive male targets 

more accurately than for unattractive male targets, t (24) = 4.73, p < .001. In contrast, the 

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locations for these attractive and unattractive male targets were identified equally well by 

male participants, t (24) = -0.51, p = .61. In contrast to the results for female participants, 

ANOVA did not find any main effects of face gender and attractiveness, or the interaction 

between the two for the male participants, Fs (1, 24) < 0.42, ps > .53. 

Consistent with Experiments 1 and 2, the performance was again negatively correlated 

with the size of attractiveness effect, r = -0.29, p < .03. Figure 3C shows a scatter plot of this 

correlation. 

To determine whether valence has also contributed to tracking performance, we 

performed an ANCOVA on the data following the same statistical procedure as Experiment 1. 

Results showed a significant main effect of target attractiveness, F (1, 278) = 3.22, MSE =.78, 

p < .04, partial η
2 
= .02, where attractive faces were tracked better than unattractive faces. 

The valence, as a covariate, did not significantly affect the tracking performance, F (1, 278) 

=.39, MSE =.09, p = .53, partial η
2 

< .001. 

The data in this experiment suggest that an attractive target was more likely to create a 

stronger identity-location binding in female participants for attractive male targets. The 

difference between identity-location binding for attractive and unattractive female targets was 

not significant. Consistent with Experiment 1, valence did not contribute to the binding 

advantage of attractive targets. 

General Discussion 

Results in these experiments suggest a facilitative effect of facial attractiveness in 

multiple-face tracking. Experiment 1 showed a better tracking performance when attractive 

faces were assigned as targets. Experiment 2 showed that attractive targets were more likely 

to be tracked successfully when they were mixed with unattractive or average looking targets. 

Finally, Experiment 3 found that attractive targets could induce a stronger binding of face 

identity and location.  

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Given that attractive faces may be more visually similar to one another than unattractive 

faces and that Yantis (1992) showed that similarity among targets improves tracking, one may 

argue that the tracking advantage for attractive targets may not reflect attractiveness directly, 

but rather through featural similarity. The replicated attractiveness advantage of Experiment 2 

has eliminated this equivocal problem. Furthermore, attractive targets and attractive 

distractors were likely to be more similar than unattractive targets and unattractive distractors 

in Experiments 1 and 3. This may make tracking more difficult (Makovski & Jiang, 2009) 

and predict an opposite unattractiveness advantage. From this point, the tracking advantage 

for attractive targets is less likely to reflect featural similarity of attractive faces. 

Facial beauty would not produce an effect on these tracking tasks if facial features and 

their holistic information were not processed during the process of tracking. Therefore, given 

the pattern of our results, the representations of the target items must be content addressable. 

There is already evidence that face or object identities are processed in multiple target 

tracking (Horowitz et al., 2007; Oksama & Hyönä, 2008; Ren et al., 2009). The present study 

shows further that facial attractiveness is also processed during tracking. As the results in 

Experiment 1 indicate, attractiveness appeared to be assessed only for the target items, 

because distractors had negligible effects on tracking performance. This finding is consistent 

with the observation that only target identity is processed in multiple-object or multiple-face 

tracking (Pylyshyn, 2006; Ren et al., 2009). 

Contrary to the suggestion that multiple object tracking is purely driven by low-level 

vision, of which higher level cognitive processes are unable to penetrate, tracking 

performance appeared to be modulated by the information content of target items. Content 

addressability may depend on whether the information is important to the observer and 

whether the observer is predisposed to process the type of information. Like face identity, 

attractive faces may automatically engage the attention system. The appraisal for 

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attractiveness in our experiments was spontaneous because it was task irrelevant. Although 

the effects of such automatic appraisal in this and other studies (e.g., Sui & Liu, 2009) can be 

quite small, they are consistent and replicable. A small effect in these studies may suggest that 

task-irrelevant processing can be largely suppressed by the central control. The present study 

revealed that a participant’s tracking performance was negatively correlated with the size of 

attractiveness effect. This suggests that some individuals may have weaker central control 

than others: Those who were not as good at tracking showed a larger attractiveness effect 

because they might not have as much central control and were more easily distracted by the 

irrelevant information.
1
  

Perhaps due to the extent of the central control, not all evidence to date shows that 

appraisal of attractiveness is spontaneous or mandatory. Schacht, Werheid, and Sommer 

(2008) found that attractiveness appraisal depended on whether facial attractiveness was task 

relevant (e.g., beauty rating). This led them to conclude that attractiveness appraisal requires 

voluntary attention to the attractiveness dimension. The findings of our study show that facial 

attractiveness can be appraised even when it is not task relevant. Our analyses of the 

correlation between the effect of attractiveness and tracking performance in the three 

experiments provide preliminary evidence that participants with higher tracking performance 

tend to produce a smaller attractiveness effect. This may be due to these participants’ better 

central control to suppress task-irrelevant appraisal of facial attractiveness. Task irrelevant 

processing of facial beauty has been reported in brain research. Chatterjee, Thomas, Smith 

and Aguirre (2009) found that the ventral occipital region remained responsive to facial 

beauty when the task of their participants was to judge facial identity rather than to attend 

explicitly to attractiveness. They proposed that this region, which includes the fusiform gyrus, 

the lateral occipital cortex and medially adjacent regions, is activated automatically by beauty 

and may serve as a neural trigger for pervasive effects of attractiveness in social interactions 

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(see also Kampe et al., 2001). Undoubtedly, the exact level of control that the central 

executive can have over automatic processing of certain task-irrelevant stimuli will require 

systematic future research.  

The present study also provides preliminary evidence that target tracking is 

spontaneously affected by gender detection. Experiment 1 showed that male faces were 

tracked better than female faces. This could be due to a gender bias as participants in this 

experiment were mainly comprised of females. When we tested equal number of male and 

female participants in Experiment 3, results showed that female participants tracked the 

location of an attractive male face more accurately relative to an unattractive male face. 

However, it is unclear why the same effect was not found for female faces. The gender effect 

found in Experiment 3 may be similar to Bayliss et al (2005), who found that averted eyes of 

a face or nonpredictive arrows produce a stronger reflexive shift of attention in females than 

in males. Given that the participants in our Experiments 1 and 2 were predominantly females, 

the results in these experiments could be largely driven by certain aspects of gender 

difference. The role of gender difference in attentive tracking is therefore an important area 

for future investigation.  

Consistent with prior research, attractive face stimuli in this study were also rated more 

positively on the valence dimension. Although valence did not contribute to the tracking 

advantage of attractive faces when the tracked faces had similar attractiveness (Experiments 1 

and 3), it did contribute to the tracking performance when the target faces consisted of a full 

range of attractiveness (Experiment 2). Thus, the lack of valence effect in Experiments 1 and 

3 may be due to the much smaller range of this variable associated with the attractive targets. 

Positive valence is a central trait of facial beauty. It is therefore not surprising that it produced 

a similar effect to attractiveness on distributed attention. It should be noted, however, that the 

differences in valence ratings of attractive and non-attractive faces were quite small. No 

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significant difference was found in arousal ratings of attractive and non-attractive faces. 

These rating data may suggest a moderate link between facial attractiveness and valence, 

whereas the link between facial attractiveness and arousal is negligible.  

Although it is difficult to separate attractiveness from positive valence due to the very 

nature of beauty, it is possible to study whether valence in other types of stimuli produces a 

similar effect on multiple object tracking. A similar conclusion can be made about the 

relationship between attractiveness and averageness. It would not be possible to separate 

attractiveness from averageness because averageness is a defining feature of attractiveness. 

However, it is possible to study whether averageness in non-face stimuli also produces a 

similar advantage in a multiple object tracking task. There is little evidence that averageness 

in other kinds of stimuli also attracts attention although it is highly likely that beautiful things 

in general attract more attention. Unlike faces, the relationship between averageness and 

other types of beautiful things remains to be seen. In face research, this relationship is 

established through image morphing techniques. However, it is often difficult to use the same 

method that requires well-defined corresponding features to build an average for other 

categories of things such as beautiful sunsets, because obvious correspondence in such 

images is often absent. 

The attentional bias for attractive faces found in this study suggests that multiple object 

tracking is modulated by underlying biological significance of the tracked targets. It may 

reflect biological interests of the observer. The preference for attractive faces may be deeply 

rooted in evolution (Langlois et al., 2000; Rhodes, 2006). Prior research has demonstrated an 

automatic reaction to facial beauty in focalized attention. The present study shows a similar 

response to beauty in distributed attention. Because multiple object tracking depends on 

attentional resources in the working memory (Oksama & Hyona, 2004), our results may 

suggest higher working memory capacity and greater attentional resources for attractive 

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faces. 

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Author Notes 

 This research was supported by grants from The Royal Society, KC Wong Foundation, 

and 973 Program (2011CB302201). We thank Professor David Perrett for offering the face 

stimuli, and Emma Medford for her thoughtful comments on an earlier version of this 

manuscript. We especially thank the reviewers for their constructive comments and 

suggestions. 

 

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Footnote 

 
1
We thank Dr. Trafton Drew for suggesting this idea. 

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Pylyshyn, Z. W. (2004). Some puzzling findings in multiple object tracking: I. Tracking 

without keeping track of object identities. Visual Cognition, 11, 801-822. 

Pylyshyn, Z. W. (2006). Some puzzling findings in multiple object tracking (MOT): II. 

Inhibition of moving nontargets. Visual Cognition, 14, 175 - 198. 

Pylyshyn, Z. W., & Storm, R. W. (1988). Tracking multiple independent targets: Evidence 

for a parallel tracking mechanism. Spatial Vision, 3, 1-19. 

Ren, D., Chen, W., Liu, C. H., & Fu, X. (2009). Identity processing in multiple-face tracking. 

Journal of Vision, 9(5):18, 1-15. 

Rhodes, G. (2006). The evolutionary psychology of facial beauty. Annual Review Psychology, 

57, 119-226. 

Rhodes, G., Sumich, A., & Byatt, G. (1999). Are average facial configurations attractive only 

because of their symmetry? Psychological Science, 10, 52–58. 

Samuels, C. A., Butterworth, G., Roberts, T., Graupner, L., & Hole, G. (1994). Facial 

aesthetics: Babies prefer attractiveness to symmetry. Perception, 23, 823-831. 

Schacht, A., Werheid, K., & Sommer, W. (2008). The appraisal of facial beauty is rapid but 

not mandatory. Cognitive, Affective, and Behavioral Neuroscience, 8, 132-142. 

Slater, A., von der Schulenberg, C., Brown, E., Bademoch, M., Butterworth, G., Parsons, S., 

& Samuels, C. (1998). Newborn infants prefer attractive faces. Infant Behavior & 

Development, 21, 345-354. 

Sui, J., & Liu, C. H. (2009). Can beauty be ignored? Effects of facial attractiveness on covert 

attention. Psychonomic Bulletin & Review, 16, 276-281. 

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Yantis, (1992). Multielement visual tracking: Attention and perceptual organization. 

Cognitive Psychology, 24, 295-340.

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Attractiveness Affects Multiple-face Tracking 27 

 

Table 1 

Mean ratings of valence and arousal. Values in parentheses represent standard deviation. 

____________________________________________ 

Attractiveness Valence       Arousal 

____________________________________________ 

 Attractive 5.08 (0.65) 4.03 (0.48) 

 Average 4.68 (0.62) 3.94 (0.52) 

 Unattractive 4.33 (0.74) 3.99 (0.56) 

____________________________________________ 

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Attractiveness Affects Multiple-face Tracking 28 

 

Figure Captions 

Figure 1. Illustration of the procedure used in the study. A. Procedure used in Experiments 1 

and 2. B. Procedure used in Experiment 3. 

Figure 2. Tracking accuracy in Experiment 1 as a function of target and distractor attractiveness. 

A. Results of male faces. B. Results of female faces. Error bars represent standard errors.  

Figure 3. Scatter plots for the correlation between the size of attractiveness effect and tracking 

performance. 

Figure 4. Tracking accuracy in Experiment 2 as a function of target attractiveness and face 

gender. Error bars represent standard errors.  

Figure 5. Tracking accuracy in Experiment 3 as a function of target attractiveness and face 

gender. A. Results of male faces. B. Results of female faces. Error bars represent standard errors. 

 

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Figure 1. Illustration of the procedure used in the study. A. Procedure used in Experiments 1 and 2. 
B. Procedure used in Experiment 3.  

160x82mm (300 x 300 DPI)  

 
 

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Figure 2. Tracking accuracy in Experiment 1 as a function of target and distractor attractiveness. A. 
Results of male faces. B. Results of female faces. Error bars represent standard errors.  

152x243mm (300 x 300 DPI)  

 
 

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Figure 3. Scatter plots for the correlation between the size of attractiveness effect and tracking 
performance.  

463x193mm (300 x 300 DPI)  

 
 

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Figure 4. Tracking accuracy in Experiment 2 as a function of target attractiveness and face gender. 
Error bars represent standard errors.  

231x146mm (300 x 300 DPI)  

 
 

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Figure 5. Tracking accuracy in Experiment 3 as a function of target attractiveness and face gender. 
A. Results of male faces. B. Results of female faces. Error bars represent standard errors.  

152x243mm (300 x 300 DPI)  

 
 

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Attractiveness Affects Multiple-face Tracking 1 

Running Head: ATTRACTIVENESS AFFECTS MULTIPLE-FACE TRACKING 

 

 

 

Beauty is Better Pursued: 

Effects of Attractiveness in Multiple-Face Tracking 

 

Chang Hong Liu 

University of Hull 

 

Wenfeng Chen  

Chinese Academy of Sciences 

 

 

 

Correspondences: 

Chang Hong Liu, PhD         Wenfeng Chen, PhD 

Department of Psychology        Institute of Psychology 

University of Hull          Chinese Academy of Sciences 

Cottingham Road          4A Datun Road 

Hull, HU6 7RX           Chaoyang District, Beijing 

United Kingdom           China 

 

Tel: +44 1482-465572         Tel: +86 10 6483-7040 

Fax: +44 1482-465599         Fax: +86 10 6487-2070 

Email: C.H.Liu@hull.ac.uk        Email: ChenWF@psych.ac.cn 

Abstract 

Using the multiple-object tracking paradigm, this study examines how spontaneous appraisal 

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mailto:ChenWF@psych.ac.cn


Attractiveness Affects Multiple-face Tracking 2 

for facial beauty affects distributed attention to multiple faces in dynamic displays. Observers 

tracked attractive faces more effectively relative to unattractive faces in this task. Tracking 

performance was only affected by target attractiveness, suggesting an absence of appraisal for 

distractor attractiveness. Attractive male faces also produced stronger binding of face identity 

and location for female participants. Together, the results suggest that facial attractiveness 

was appraised during tracking even though this was task irrelevant. Contrary to the theory 

that multiple-object tracking is driven by encapsulated low-level vision, our results show that 

the content of target representation is not only penetrable by social cognition but also 

modulates the course of tracking operations.

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Attractiveness Affects Multiple-face Tracking 3 

Beauty is Better Pursued: 

Effects of Attractiveness in Multiple-Face Tracking 

It is well known that human observers pay greater attention to faces than to non-face objects 

(e.g., Ro, Russell, & Lavie, 2001). Moreover, some face stimuli attract more attention than others. 

Apart from certain facial expressions such as fear and anger (Palermo & Rhodes, 2007), 

attractive faces also trigger greater attention (Sui & Liu, 2009). Popular culture often suggests 

that a mere glance of a face elicits spontaneous appraisal of attractiveness. Humans may be 

predisposed to direct attention to attractive faces because of their biological and social 

significance. There is well-established evidence that even newborn babies look at attractive faces 

longer (e.g., Geldart, Maurer, & Carney, 1999; Langlois et al., 1987; Samuels et al., 1994; Slater 

et al., 1998). Adults also tend to spend more time looking at beautiful faces (Aharon et al., 2001; 

Kranz & Ishai, 2006), which are known to activate dopaminergic regions in the brain that are 

strongly linked to the reward system (Kampe, Frith, Dolan, & Frith, 2001).  

Appraisal of facial beauty appears to depend on how well a face resembles the average in a 

population (Langlois & Roggman, 1990). Although symmetry also plays a role in facial beauty 

(e.g., Grammer & Thornhill, 1994), there is evidence that it is less important than averageness 

(Rhodes, Sumich, & Byatt, 1999; also see Rhodes, 2006, for an extensive review). Hence 

attentional capture by attractive faces may rely on preattentive computation of averageness in 

face stimuli.  

However, little is known about how facial attractiveness affects attentional mechanisms. 

This issue may be addressed through the existing attention paradigms. For example, Maner, 

Gailliot, and DeWall (2007) employed a dot-probe paradigm to assess the effect of attractiveness 

on disengaging attention. Consistent with their hypothesis, their observers were slower at 

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Attractiveness Affects Multiple-face Tracking 4 

disengaging attention from attractive female faces relative to average-looking female or male 

faces. In another study, Maner, Gailliot, Rouby, and Miller (2007) used the same method and 

found that participants fixated on highly attractive faces within the first half second and took 

longer to stop looking at them when asked to shift their attention away. In a different approach, 

Sui and Liu (2009) investigated whether appraisal for attractiveness occurs when spatial attention 

has already been directed elsewhere. They employed a spatial cuing task, where participants 

were asked to judge the orientation of a cued target presented to the left or right visual field 

while ignoring a task-irrelevant face image flashed in the opposite field. They found that the 

presence of attractive faces significantly lengthened task performance. This suggests that facial 

beauty can automatically compete with an ongoing task for attention, although this does not 

necessarily mean that appraisal of facial beauty is a mandatory process (see Schacht, Werheid, & 

Sommer, 2008). The analysis of eye movements in Sui and Liu’s study revealed that the effect of 

facial attractiveness was not due to foveal fixation on the target or face stimuli, hence there is a 

strong possibility that facial attractiveness can be detected outside the fovea. This has been 

confirmed by a recent investigation, where discrimination of facial beauty was measured at 

several eccentricities (Guo, Liu, & Roebuck, 2011). 

Both dot-probe and cuing tasks require focused attention, where attention is directed to a 

single spatial location. However, attention in reality can be distributed to several different targets 

or spatial locations. For instance, a group activity requires attention to be paid to multiple 

individuals and locations. The main purpose of this research was to investigate the effect of facial 

attractiveness on distributed attention. Another motivation of this research comes from 

observation that spontaneous appraisal of attractiveness is rapid and transient (Schacht et al., 

2008). It remains unclear whether such an appraisal only manifests in brief attentional shifts. 

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Attractiveness Affects Multiple-face Tracking 5 

Hence the second purpose of this study was to investigate whether a similar kind of automatic 

appraisal for facial attractiveness occurs continuously when sustained attention is distributed 

among faces in multiple locations.  

Pylyshyn and Storm (1988) designed a multiple-object tracking paradigm (MOT) to study 

how human observers maintain attention on multiple objects across space and time. In recent 

years, the issue of content addressability in object tracking is hotly debated. This issue was first 

raised by Pylyshyn (2004) who found that observers were remarkably poor at identifying the 

features or identity of correctly tracked objects. This phenomenon demonstrates a poor binding 

of object features and location. Pylyshyn’s explanation is that MOT is implemented by early or 

low-level vision, where the information about individual identity is encapsulated and 

inaccessible from higher level cognition. His theory assumes that early vision picks out a small 

number of objects while ignoring their visual properties. Because of this, object identity 

differentiated by visual properties is not coded or accessible from higher level cognitive 

processes even when the objects with those properties are attended. However, recent evidence 

has challenged this position by showing that tracking is content addressable (Horowitz et al., 

2007).  

This debate has an important implication for the present study. If the information content of 

tracked faces is not processed, tracking performance should not be affected by facial 

attractiveness. It is known that information about face identity (i.e., individuation of face stimuli 

by features and configurations) is not completely lost in tracking tasks (Ren, Chen, Liu, & Fu, 

2009). If representations of the tracked faces are to some extent content addressable, there is a 

chance that other high-level information such as facial attractiveness is also available for 

processing. If processing of such information is spontaneous, this could in turn affect multiple 

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face tracking. The experiments in this study were designed to test this hypothesis. The outcome 

should reveal the extent to which a high-level social cognition can penetrate and influence the 

low-level visual perception. Appraisal for facial beauty requires high-level vision, because a 

main criterion for beauty—averageness—cannot be determined solely from low-level visual 

features such as luminance, contrast, and size. Computing averageness requires identifying the 

landmarks of higher level facial features such as the eyes, the mouth, and the face shape. The 

operations for image normalization, alignment, and comparison with the average in the 

hypothetical multi-dimensional face space also require high-level vision. To ensure that our 

results were controlled for the low-level contribution, we carefully scaled all our tracking stimuli 

to the same size, luminance, and contrast. 

Other high-level information accompanying appraisal of facial attractiveness could also 

contribute to multiple-face tracking performance. As Dion, Berscheid, and Walster (1972) 

showed in their seminal study, beautiful people are generally perceived to possess more positive 

attributes. They called this the “beauty-is-good” stereotype. Many studies have since produced 

evidence for this positive association between attractiveness and goodness (see Eagly, Ashmore, 

Makhijani, & Longo, 1991, and Langlois et al., 2000, for reviews). It is also referred to as the 

halo effect of attractiveness. This well established duality of beauty could predict a similar effect 

on tracking based on attractive and valence measures. Moreover, if the reward system is involved 

in perception of attractive faces (Kampe et al., 2001), arousal could also be responsible for any 

effect of attractiveness on tracking performance. To address these questions, we compared 

whether valence and arousal affect tracking performance in the same way as attractiveness.  

Experiment 1 

The main purpose of Experiment 1 was to investigate how target and distractor 

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attractiveness may affect tracking performance differently. Given the prior finding that the target 

face identity is content addressable (Ren et al., 2009), we hypothesized that the target faces could 

be automatically appraised for their attractiveness. Attractive distractors, on the other hand, could 

impair tracking performance if they were also appraised for attractiveness.  

Method 

Participants. A total of 25 undergraduate students (19 females) from the University of Hull 

participated in this study. The age of the participants ranged from 18 to 28 years (Mdn = 19). All 

participants had normal or corrected-to-normal vision. 

Stimuli. The face database was obtained from the University of St. Andrews. It contains 702 

frontal-view Caucasian faces with no external features (hair and clothing). The size of the faces 

was normalized according to the face width. The resulting image measured 3.0 × 3.8 cm (2.8 × 

3.6º) on screen. All images were scaled to the same mean luminance and root-mean-square 

contrast.  

All faces in the database were rated by 19 raters (aged between 18 and 29 years, 12 females) 

for attractiveness on a 7-point scale. To contrast the effect of attractiveness, only the 149 most 

attractive and the 132 least attractive faces were used in this experiment. The mean ratings for 

the two groups of faces were 3.91 (3.96 for females, 3.72 for males. SD = 0.39) and 2.39 (2.35 

for females, 2.46 for males. SD = 0.38), respectively. These were significantly different from 

each other (p < .001). Slightly more than half (58.3%) of the faces were females. Each attractive 

or unattractive face was only used once for each participant: 80 were randomly chosen from the 

pool of attractive faces, and another 80 were randomly chosen form the pool of unattractive 

faces. 

We performed an additional norming study on the face stimuli to measure how attractiveness 

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is related to valence and arousal. Twenty undergraduate students, aged between 18 and 33 years 

(M = 21.1, SD = 4.4), rated a total of 452 faces for valence and arousal. The image set consisted 

of the attractive and unattractive faces in this experiment as well as the additional 171 average 

faces used in Experiment 3. The faces were rated one at a time. The presentation order was 

random. To avoid response bias, the raters were not informed until the end of the experiment that 

the rating data would be used to study facial attractiveness. The details of our procedure were 

identical to that for the International Affective Picture System (Lang, Bradley, & Cuthbert, 2008). 

A 9-point rating scale was used where 1 represented completely unhappy/calm, whereas 9 

completely happy/excited respectively for the valence and arousal judgments. Table 1 shows the 

mean rating results for each face category. To determine whether valence and arousal ratings 

vary according to levels of attractiveness, we conducted separate analyses of variance (ANOVA) 

for the two variables. The main effect of valence was significant, F (1, 449) = 43.24, MSE = 19. 

41, p < .001, partial η
2 
= .17, where the valence for attractive faces was higher than for 

average-looking and unattractive faces (p < .001), and the valence for average-looking faces was 

higher than for unattractive faces (p < .001). On the other hand, the main effect of arousal was 

not significant, F (1, 449) = 1.49, MSE = .41, p = .23, partial η
2 

= .01. 

The tracking stimuli were displayed on a 21" monitor (SONY Trinitron, GDM-F520). A 

central square area with 22.8 × 22.8º of visual angle was designated for stimulus presentation. 

The background color of the display was gray. E-Prime (Version 1.2) was used to generate the 

dynamic tracking and still displays and to control the flow of the experiment. 

Design. We employed a within-subject design. The independent variables were target 

attractiveness (attractive vs. unattractive) and distractor attractiveness (attractive vs. unattractive), 

and face gender (male vs. female). Following this design, the target faces, which were either all 

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attractive or unattractive, were tracked among distractor faces, which were also either all 

attractive or unattractive. 

Procedure. Participants were tested individually. An adjustable headrest was used to fix the 

participant's viewing position, which was set 60 cm away from the computer monitor. The faces 

presented in each trial were of the same sex. They were randomly chosen for each trial from the 

pool of 281 faces. The chosen images were not repeated in the subsequent trials until all faces in 

the pool were used. The procedure for each trial of the experiments is illustrated in Figure 1A. 

Each trial was initiated by a key press. It began with 10 stationary black rectangles on the screen. 

The location of the rectangles was randomly assigned, with the constraint that none would 

occlude the others and the center-to-center distance was not less than twice of their size. Five of 

the rectangles would then start to blink twice for 2 s, signaling the target location. Following this, 

the rectangles changed abruptly into 10 faces, and started to move in random directions. The 

faces bounced off each other when the center-to-center distance was less than twice of their size. 

They avoided the edge of the display area when the center to edge distance was less than their 

size. Participants were asked to track the five moving targets. The velocity of the face images 

varied between 3.9 and 6.3 º / s with a mean of 5.1º / s. All faces moving about the screen for 5 s. 

As soon as the motion stopped, all the faces were again occluded by black rectangles. The task 

was to pick out the five targets by clicking on the rectangles. Once being clicked, the rectangle 

was highlighted with a yellow border which could be switched on and off by clicking. 

Participants were forced to select 5 items and were allowed to guess. Once 5 items were selected, 

they clicked a “finish” button to start the next trial. The experiment lasted about 30 minutes. 

A total of 80 experimental trials were run after 4 practice trials. Each of the eight conditions 

(2 target attractiveness × 2 distractor attractiveness × 2 face gender) had 10 trials. All 80 trials 

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were mixed in random order in one block. 

Results and Discussion 

An alpha level of .05 was used for all statistical analyses in this report. Results of tracking 

accuracy are shown in Figure 2. The data were analyzed using repeated-measures ANOVA. 

There was a significant main effect of target attractiveness, F (1, 24) = 8.50, MSE = 18.52, p 

< .01, partial η
2 
= .26, where attractive faces were tracked better than unattractive faces. 

However, there was no difference between results for attractive and unattractive distractors, F (1, 

24) = 1.77, MSE = 27.74, p = .20, partial η
2 

= .07. There was also a main effect of face gender, F 

(1, 24) = 7.47, MSE = 23.31, p < .01, partial η
2 
= .24, where male faces were tracked better than 

female faces. However, face gender did not interact with other factors, ps > .57. None of the 

other two-way or three-way interactions was significant, ps > .15.  

The experiment shows that tracking performance was affected by appraisal of facial 

attractiveness. This effect was only present for the target faces, while the influence of attractive 

distractors was negligible. Although male faces were tracked better than female faces, the effect 

was not modulated by attractiveness.  

The effect of attractive faces on tracking performance could be due to varying levels of 

involuntary attention to task-irrelevant information. Some participants might be able to suppress 

or control attention to the task-irrelevant information better than others. If this is the case, it 

would be possible that those who were poor at the tracking task would show a stronger 

attractiveness effect, because they are poor at suppressing the attractiveness information. To test 

this prediction, we analyzed the correlation between the size of attractiveness effect and overall 

tracking performance. Consistent with this prediction, a negative correlation was found between 

the two, r = -0.59, p < .001. Figure 3A shows a scatter plot of this correlation.  

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Because the attractive faces had greater valence rating than unattractive faces in our norming 

study, we evaluated how the difference of valence contributed to the attractiveness effect in this 

experiment. This was done by an item-based analysis of covariance (ANCOVA), where facial 

attractiveness was treated as a random factor, and the valence a covariate. ANCOVA measures 

whether attractiveness had an effect on tracking performance after removing the covariate 

valence. Because only the target attractiveness had an effect on tracking performance, we only 

used target attractiveness in our ANCOVA as an independent factor. Hence the target faces were 

used as random sample, and corresponding valence for these faces as covariate. Results showed a 

significant main effect of target attractiveness, F (1, 278) = 3.57, MSE = .07, p < .03, partial η
2 

= .02, where attractive targets were tracked better than unattractive targets. However, the 

covariate was not significant, F (1, 278) =.59, MSE =.001, p = .44, partial η
2 

= .002, suggesting 

that the valence made no contribution to the attractiveness effect found in this experiment. 

Experiment 2 

In Experiment 1, the target faces were either attractive or unattractive. When the targets had 

a similar level of attractiveness, attention might be more or less evenly distributed among the 

targets. However, if attractiveness varies considerably among targets, attention and consequently 

tracking performance for a given target could be affected by its attractiveness relative to other 

targets. To test this hypothesis, we varied level of target attractiveness in this experiment such 

that the targets consisted of attractive, average, and unattractive faces. We then compared the 

performance for these different types of targets.  

Another issue concerning the use of all attractive or all unattractive targets was that 

attractive faces may be more visually similar to one another than unattractive faces. Yantis (1992) 

showed that similarity among targets improves tracking. Because of this, the tracking advantage 

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for attractive targets may not reflect attractiveness directly, but rather through featural similarity. 

The design in the present experiment was able to eliminate this problem because an effect of 

attractiveness would no longer be due to greater similarity among the attractive targets. 

Method 

Participants. A different group of 61 undergraduate students (48 females and 13 males) from 

the University of Hull participated in this study. The age of the participants ranged from 17 to 34 

years (Mdn = 20). All participants had normal or corrected-to-normal vision. 

Stimuli. The attractive and unattractive face stimuli were the same as in Experiments 1 and 2. 

In addition, we also added average-looking faces. The mean ratings for the average-looking faces 

was 2.99 (SD = 0.11, N = 171). As in the previous experiments, each face category consisted of 

80 faces randomly selected from the respective pool of stimuli for each participant. Each trial 

contained one attractive, one unattractive, and three average-looking target faces. The distractors 

in this experiment consisted of average-looking faces. Because 8 average faces were used in each 

trial and 80 trials in total, this requires a total of 640 average faces (80 × 8). Since there were 171 

average faces available, each face was repeated about 4 times (640 ÷ 171 = 3.7). 

Design. This was again a within-subject design. The independent variables were target 

attractiveness (attractive, average, and unattractive) and face gender. Because Experiment 1 

showed no effect of distractor attractiveness, this variable was not included in this and the next 

experiments. 

Procedure. This was identical to Experiment 1. 

Results and Discussion 

The tracking results are shown in Figure 4. The main effect of target attractiveness was 

significant, F (2, 120) = 4.96, MSE = 61.83, p < .01, partial η
2 

= .10. No significant effect was 

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found for face gender, F (1, 60) = 0.01, MSE = 93.25, p = .98, or interaction between face gender 

and target attractiveness, F (2, 120) = 0.90, MSE = 70.68, p = .41. Post hoc comparisons of 

means with Bonferroni correction revealed better tracking performance for attractive targets 

relative to average or unattractive targets ts (60) > 2.66, ps < .02. There was no difference 

between results for average and unattractive targets, t (60) = 0.11, p = 1.00. The results suggest 

that attractive faces were attended more favourably whereas unattractive and average-looking 

faces were not treated differently during tracking. 

Consistent with Experiment 1, there was a significant negative correlation between 

participants’ overall tracking performance and the size of the attractiveness effect, r = -0.22, p 

< .04. A scatter plot of this correlation is shown in Figure 3B. 

Results of ANCOVA for Experiment 2 show that there was a significant main effect of target 

attractiveness, F (1, 448) = 7.37, MSE = .07, p < .01, partial η
2 
= .03, where attractive faces were 

tracked better than average-looking and unattractive faces (ps < .01), and there was no difference 

between average-looking faces and unattractive faces (p = .51). The covariate, or valence of the 

faces, was also significantly related to the tracking performance, F (1, 448) = 9.90, MSE = .09, p 

< .01, partial η
2 
= .02. This indicates that the valence of faces also contributed to the 

attractiveness effect in this experiment. 

Experiment 3 

The tracking task in Experiments 1 and 2 did not explicitly require binding of a target 

identity with its location. If target attractiveness is appraised, it is possible that the location of an 

attractive target is monitored more accurately relative to an unattractive target. To test this 

hypothesis, we employed a variant of the MOT paradigm, where one of the faces was randomly 

chosen from the targets and probed at the end of each trial. The task here was to specify the 

Deleted: Experiment

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location of the probe face.  

Method 

Participants. A different group of 50 undergraduate students (25 females and 25 males) from 

the University of Hull participated in this study. The age of the participants ranged from 18 to 35 

years (Mdn = 20). All participants had normal or corrected-to-normal vision. 

Stimuli. These were the same as Experiment 1. 

Design. This was again a within-subject design. The independent variables were 

attractiveness, face gender, and participant gender. Although not originally planned, potential 

participant gender difference was included in our analysis because the number of participants in 

each gender group was fully balanced. 

Procedure. The procedure of this experiment was identical to Experiment 1 except that at the 

end of each trial one of the faces was randomly chosen from the targets and probed (see Figure 

1B). The participant was required to specify the specific location of the probe face by clicking on 

one of the occluded faces with a mouse. The occluder of the chosen face was then removed to 

reveal the answer after the mouse click. This feedback was used to engage the participants. 

Because this task was harder than the standard task, the number of faces in each trial was 

reduced to 8, with the number of target faces reduced to 4. The task began with four practice 

trials followed by 40 experimental trials (10 trials × 4 conditions). 

Results and Discussion 

The locations of attractive targets were identified better than unattractive targets, F (1, 48) = 

4.70, MSE = 241.50, p < .04, partial η
2 

= .11. Neither face gender nor participant gender 

produced a significant main effect, Fs (1, 48) = 1.08 and 0.001, ps = .30 and .98, respectively. 

However, this was qualified by a significant two-way interaction between participant gender and 

Deleted: more balanced than 
Experiment 1. However, it should be 
stressed that because gender difference 

was not originally planned as an aim of 

this study, the number of participants in 

each gender group was far from balanced. 

Also, because Experiment 1 showed no 

effect of distractor attractiveness, this 

variable was not included in this and the 

next experiments. The distractors were 

selected in the same way as in 
Experiment 1

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Attractiveness Affects Multiple-face Tracking 15 

attractiveness, F (1, 48) = 9.97, MSE = 241.50, p < .01, partial η
2 

= .17, as well as a marginally 

significant interaction between participant gender and face gender, F (1, 48) = 3.80, MSE = 

204.27, p = .057, partial η
2 

= .07. The three-way interaction also approached the level of 

significance, F (1, 48) = 2.78, MSE = 168.51, p = .10, partial η
2 

= .06. The two-way interaction 

between face gender and attractiveness was not significant, (1, 48) = 1.63, p = .21, partial η
2 

= .03. The interaction effects are illustrated in Figure 4.  

To investigate the interaction effects, we conducted separate ANOVAs for the two 

participant genders. Results for the female participants showed a significant main effects of 

attractiveness, F (1, 24) = 14.73, MSE = 246.00, p < .001, partial η
2 

= .38, and face gender, F (1, 

24) = 4.45, MSE = 478.39, p < .05, partial η
2 

= .16. There was also a significant interaction 

between attractiveness and face gender, F (1, 24) = 7.55, MSE = 96.54, p < .01, partial η
2 

= .24. 

Further analyses of the interaction via pairwise comparisons of means revealed that female 

participants identified the spatial locations for attractive male targets more accurately than for 

unattractive male targets, t (24) = 4.73, p < .001. In contrast, the locations for these attractive and 

unattractive male targets were identified equally well by male participants, t (24) = -0.51, p = .61. 

In contrast to the results for female participants, ANOVA did not find any main effects of face 

gender and attractiveness, or the interaction between the two for the male participants, Fs (1, 24) 

< 0.42, ps > .53. 

Consistent with Experiments 1 and 2, the performance was again negatively correlated with 

the size of attractiveness effect, r = -0.29, p < .03. Figure 3C shows a scatter plot of this 

correlation. 

To determine whether valence has also contributed to tracking performance, we performed 

an ANCOVA on the data following the same statistical procedure as Experiment 1. Results 

Deleted: face

Deleted: male faces

Deleted: effect

Deleted: 48) = 5.74

Deleted: 240.90

Deleted: 02

Deleted: 11, and

Deleted: participant

Deleted: 48) = 10.38

Deleted: 240.90

Deleted: 18. The main effect of 
participant gender was not significant, F 

(1, 48) = 0.85, MSE = 478.39, p = .36, 

partial η
2 
= .02

Deleted: male faces

Deleted: participant

Deleted: female faces

Deleted: 48) < 2.23

Deleted: 13

Deleted: Experiment

Deleted: 3B

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showed a significant main effect of target attractiveness, F (1, 278) = 3.22, MSE =.78, p < .04, 

partial η
2 
= .02, where attractive faces were tracked better than unattractive faces. The valence, 

as a covariate, did not significantly affect the tracking performance, F (1, 278) =.39, MSE =.09, p 

= .53, partial η
2 
< .001. 

The data in this experiment suggest that an attractive target was more likely to create a 

stronger identity-location binding in female participants for attractive male targets. The 

difference between identity-location binding for attractive and unattractive female targets was 

not significant. Consistent with Experiment 1, valence did not contribute to the binding 

advantage of attractive targets. 

General Discussion 

Results in these experiments suggest a facilitative effect of facial attractiveness in 

multiple-face tracking. Experiment 1 showed a better tracking performance when attractive faces 

were assigned as targets. Experiment 2 showed that attractive targets were more likely to be 

tracked successfully when they were mixed with unattractive or average looking targets. Finally, 

Experiment 3 found that attractive targets could induce a stronger binding of face identity and 

location.  

Given that attractive faces may be more visually similar to one another than unattractive 

faces and that Yantis (1992) showed that similarity among targets improves tracking, one may 

argue that the tracking advantage for attractive targets may not reflect attractiveness directly, but 

rather through featural similarity. The replicated attractiveness advantage of Experiment 2 has 

eliminated this equivocal problem. Furthermore, attractive targets and attractive distractors were 

likely to be more similar than unattractive targets and unattractive distractors in Experiments 1 

and 3. This may make tracking more difficult (Makovski & Jiang, 2009) and predict an opposite 

Deleted: Experiment 3¶
In both Experiments 1 and 2, the target 

faces were either attractive or unattractive. 
When the targets had a similar level of 

attractiveness, attention might be more or 

less evenly distributed among the targets. 

However, if attractiveness varies 

considerably among targets, attention and 

consequently tracking performance for a 
given target could be affected by its 

attractiveness relative to other targets. To 

test this hypothesis, we varied level of 

target attractiveness in this experiment 

such that the targets consisted of 

attractive, average, and unattractive faces. 
We then compared the performance for 

these different types of targets. ¶

Another issue concerning the use of all 

attractive or all unattractive targets was 

that attractive faces may be more visually 

similar to one another than unattractive 

faces. Yantis (1992) showed that 

similarity among targets improves 

tracking. Because of this, the tracking 
advantage for attractive targets may not 

reflect attractiveness directly, but rather 

through featural similarity. The design in 

the present experiment was able to 

eliminate this problem because an effect 

of attractiveness would no longer be due 
to greater similarity among the attractive 

targets.¶

Method¶

Participants. A different group of 61 

undergraduate students (48 females and 

13 males) from the University of Hull 
participated in this study. The age of the 

participants ranged from 17 to 34 years 

(Mdn = 20). All participants had normal 

or corrected-to-normal vision.¶

Stimuli. The attractive and unattractive 

face stimuli were the same as in 

Experiments 1 and 2. In addition, we also 

added average-looking faces. The mean 

ratings for the average-looking faces was 

2.99 (SD = 0.11, N = 171). As in the 

previous experiments, each face category 
consisted of 80 faces randomly selected 

from the respective pool of stimuli for 

each participant. Each trial contained one 

attractive, one unattractive, and three 

average-looking target faces. The 

distractors in this experiment consisted of 
average-looking faces. Because 8 average 

faces were used in each trial and 80 trials 

in total, this requires a total of 640 

average faces (80 × 8). Since there were 

171 average faces available, each face 

was repeated about 4 times (640 ÷ 171 = 
3.7).¶

Deleted: Experiment 2 confirmed that 
attractive targets could induce a stronger 

binding of face identity and location. 

Finally, Experiment 3

Deleted: 3

Deleted: Experiment

Deleted: 2

... [1]

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unattractiveness advantage. From this point, the tracking advantage for attractive targets is less 

likely to reflect featural similarity of attractive faces. 

Facial beauty would not produce an effect on these tracking tasks if facial features and their 

holistic information were not processed during the process of tracking. Therefore, given the 

pattern of our results, the representations of the target items must be content addressable. There 

is already evidence that face or object identities are processed in multiple target tracking 

(Horowitz et al., 2007; Oksama & Hyönä, 2008; Ren et al., 2009). The present study shows 

further that facial attractiveness is also processed during tracking. As the results in Experiment 1 

indicate, attractiveness appeared to be assessed only for the target items, because distractors had 

negligible effects on tracking performance. This finding is consistent with the observation that 

only target identity is processed in multiple-object or multiple-face tracking (Pylyshyn, 2006; 

Ren et al., 2009). 

Contrary to the suggestion that multiple object tracking is purely driven by low-level vision, 

of which higher level cognitive processes are unable to penetrate, tracking performance appeared 

to be modulated by the information content of target items. Content addressability may depend 

on whether the information is important to the observer and whether the observer is predisposed 

to process the type of information. Like face identity, attractive faces may automatically engage 

the attention system. The appraisal for attractiveness in our experiments was spontaneous 

because it was task irrelevant. Although the effects of such automatic appraisal in this and other 

studies (e.g., Sui & Liu, 2009) can be quite small, they are consistent and replicable. A small 

effect in these studies may suggest that task-irrelevant processing can be largely suppressed by 

the central control. The present study revealed that a participant’s tracking performance was 

negatively correlated with the size of attractiveness effect. This suggests that some individuals 

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may have weaker central control than others: Those who were not as good at tracking showed a 

larger attractiveness effect because they might not have as much central control and were more 

easily distracted by the irrelevant information.
1
  

Perhaps due to the extent of the central control, not all evidence to date shows that appraisal 

of attractiveness is spontaneous or mandatory. Schacht, Werheid, and Sommer (2008) found that 

attractiveness appraisal depended on whether facial attractiveness was task relevant (e.g., beauty 

rating). This led them to conclude that attractiveness appraisal requires voluntary attention to the 

attractiveness dimension. The findings of our study show that facial attractiveness can be 

appraised even when it is not task relevant. Our analyses of the correlation between the effect of 

attractiveness and tracking performance in the three experiments provide preliminary evidence 

that participants with higher tracking performance tend to produce a smaller attractiveness effect. 

This may be due to these participants’ better central control to suppress task-irrelevant appraisal 

of facial attractiveness. Task irrelevant processing of facial beauty has been reported in brain 

research. Chatterjee, Thomas, Smith and Aguirre (2009) found that the ventral occipital region 

remained responsive to facial beauty when the task of their participants was to judge facial 

identity rather than to attend explicitly to attractiveness. They proposed that this region, which 

includes the fusiform gyrus, the lateral occipital cortex and medially adjacent regions, is 

activated automatically by beauty and may serve as a neural trigger for pervasive effects of 

attractiveness in social interactions (see also Kampe et al., 2001). Undoubtedly, the exact level of 

control that the central executive can have over automatic processing of certain task-irrelevant 

stimuli will require systematic future research.  

The present study also provides preliminary evidence that target tracking is spontaneously 

affected by gender detection. Experiment 1 showed that male faces were tracked better than 

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female faces. This could be due to a gender bias as participants in this experiment were mainly 

comprised of females. When we tested equal number of male and female participants in 

Experiment 3, results showed that female participants tracked the location of an attractive male 

face more accurately relative to an unattractive male face. However, it is unclear why the same 

effect was not found for female faces. The gender effect found in Experiment 3 may be similar to 

Bayliss et al (2005), who found that averted eyes of a face or nonpredictive arrows produce a 

stronger reflexive shift of attention in females than in males. Given that the participants in our 

Experiments 1 and 2 were predominantly females, the results in these experiments could be 

largely driven by certain aspects of gender difference. The role of gender difference in attentive 

tracking is therefore an important area for future investigation.  

Consistent with prior research, attractive face stimuli in this study were also rated more 

positively on the valence dimension. Although valence did not contribute to the tracking 

advantage of attractive faces when the tracked faces had similar attractiveness (Experiments 1 

and 3), it did contribute to the tracking performance when the target faces consisted of a full 

range of attractiveness (Experiment 2). Thus, the lack of valence effect in Experiments 1 and 3 

may be due to the much smaller range of this variable associated with the attractive targets. 

Positive valence is a central trait of facial beauty. It is therefore not surprising that it produced a 

similar effect to attractiveness on distributed attention. It should be noted, however, that the 

differences in valence ratings of attractive and non-attractive faces were quite small. No 

significant difference was found in arousal ratings of attractive and non-attractive faces. These 

rating data may suggest a moderate link between facial attractiveness and valence, whereas the 

link between facial attractiveness and arousal is negligible.  

Although it is difficult to separate attractiveness from positive valence due to the very 

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nature of beauty, it is possible to study whether valence in other types of stimuli produces a 

similar effect on multiple object tracking. A similar conclusion can be made about the 

relationship between attractiveness and averageness. It would not be possible to separate 

attractiveness from averageness because averageness is a defining feature of attractiveness. 

However, it is possible to study whether averageness in non-face stimuli also produces a similar 

advantage in a multiple object tracking task. There is little evidence that averageness in other 

kinds of stimuli also attracts attention although it is highly likely that beautiful things in general 

attract more attention. Unlike faces, the relationship between averageness and other types of 

beautiful things remains to be seen. In face research, this relationship is established through 

image morphing techniques. However, it is often difficult to use the same method that requires 

well-defined corresponding features to build an average for other categories of things such as 

beautiful sunsets, because obvious correspondence in such images is often absent. 

The attentional bias for attractive faces found in this study suggests that multiple object 

tracking is modulated by underlying biological significance of the tracked targets. It may reflect 

biological interests of the observer. The preference for attractive faces may be deeply rooted in 

evolution (Langlois et al., 2000; Rhodes, 2006). Prior research has demonstrated an automatic 

reaction to facial beauty in focalized attention. The present study shows a similar response to 

beauty in distributed attention. Because multiple object tracking depends on attentional resources 

in the working memory (Oksama & Hyona, 2004), our results may suggest higher working 

memory capacity and greater attentional resources for attractive faces. 

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Attractiveness Affects Multiple-face Tracking 21 

Author Notes 

 This research was supported by grants from The Royal Society, KC Wong Foundation, 

and 973 Program (2011CB302201). We thank Professor David Perrett for offering the face 

stimuli, and Emma Medford for her thoughtful comments on an earlier version of this manuscript. 

We especially thank the reviewers for their constructive comments and suggestions on. 

 

Deleted:  the earlier versions

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Attractiveness Affects Multiple-face Tracking 22 

Footnote 

 
1
We thank Dr. Trafton Drew for suggesting this idea. 

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Table 1 

Mean ratings of valence and arousal. Values in parentheses represent standard deviation. 

____________________________________________ 

Attractiveness Valence       Arousal 

____________________________________________ 

 Attractive 5.08 (0.65) 4.03 (0.48) 

 Average 4.68 (0.62) 3.94 (0.52) 

 Unattractive 4.33 (0.74) 3.99 (0.56) 

____________________________________________ 

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Attractiveness Affects Multiple-face Tracking 28 

 

Figure Captions 

Figure 1. Illustration of the procedure used in the study. A. Procedure used in Experiments 1 

and 2. B. Procedure used in Experiment 3. 

Figure 2. Tracking accuracy in Experiment 1 as a function of target and distractor attractiveness. 

A. Results of male faces. B. Results of female faces. Error bars represent standard errors.  

Figure 3. Scatter plots for the correlation between the size of attractiveness effect and tracking 

performance. 

Figure 4. Tracking accuracy in Experiment 2 as a function of target attractiveness and face 

gender. Error bars represent standard errors.  

Figure 5. Tracking accuracy in Experiment 3 as a function of target attractiveness and face 

gender. A. Results of male faces. B. Results of female faces. Error bars represent standard errors. 

 

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Deleted: A. Results of male faces. B. 
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Experiment 3 

In both Experiments 1 and 2, the target faces were either attractive or unattractive. 

When the targets had a similar level of attractiveness, attention might be more or less 

evenly distributed among the targets. However, if attractiveness varies considerably 

among targets, attention and consequently tracking performance for a given target could 

be affected by its attractiveness relative to other targets. To test this hypothesis, we varied 

level of target attractiveness in this experiment such that the targets consisted of 

attractive, average, and unattractive faces. We then compared the performance for these 

different types of targets.  

Another issue concerning the use of all attractive or all unattractive targets was that 

attractive faces may be more visually similar to one another than unattractive faces. 

Yantis (1992) showed that similarity among targets improves tracking. Because of this, 

the tracking advantage for attractive targets may not reflect attractiveness directly, but 

rather through featural similarity. The design in the present experiment was able to 

eliminate this problem because an effect of attractiveness would no longer be due to 

greater similarity among the attractive targets. 

Method 

Participants. A different group of 61 undergraduate students (48 females and 13 

males) from the University of Hull participated in this study. The age of the participants 

ranged from 17 to 34 years (Mdn = 20). All participants had normal or corrected-to-

normal vision. 

Stimuli. The attractive and unattractive face stimuli were the same as in Experiments 

1 and 2. In addition, we also added average-looking faces. The mean ratings for the 

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average-looking faces was 2.99 (SD = 0.11, N = 171). As in the previous experiments, 

each face category consisted of 80 faces randomly selected from the respective pool of 

stimuli for each participant. Each trial contained one attractive, one unattractive, and 

three average-looking target faces. The distractors in this experiment consisted of 

average-looking faces. Because 8 average faces were used in each trial and 80 trials in 

total, this requires a total of 640 average faces (80 × 8). Since there were 171 average 

faces available, each face was repeated about 4 times (640 ÷ 171 = 3.7). 

Design. This was again a within-subject design. The independent variables were 

target attractiveness (attractive, average, and unattractive) and face gender.  

Procedure. This was identical to Experiment 1. 

Results and Discussion 

The tracking results are shown in Figure 5. The main effect of target attractiveness 

was significant, F (2, 120) = 4.96, MSE = 61.83, p < .01, partial η
2 
= .10. No significant 

effect was found for face gender, F (1, 60) = 0.01, MSE = 93.25, p = .98, or interaction 

between face gender and target attractiveness, F (2, 120) = 0.90, MSE = 70.68, p = .41. 

Post hoc comparisons of means with Bonferroni correction revealed better tracking 

performance for attractive targets relative to average or unattractive targets ts (60) > 2.66, 

ps < .02. There was no difference between results for average and unattractive targets, t 

(60) = 0.11, p = 1.00. The results suggest that attractive faces were attended more 

favourably whereas unattractive and average-looking faces were not treated differently 

during tracking. 

Consistent with Experiments 1 and 2, there was a significant negative correlation 

between participants’ overall tracking performance and the size of the attractiveness 

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effect, r = -0.22, p < .04. A scatter plot of this correlation is shown in Figure 3C. 

Results of ANCOVA for Experiment 3 show that there was a significant main effect 

of target attractiveness, F (1, 448) = 7.37, MSE = .07, p < .01, partial η
2 
= .03, where 

attractive faces were tracked better than average-looking and unattractive faces (ps < .01), 

and there was no difference between average-looking faces and unattractive faces (p = 

.51). The covariate, or valence of the faces, was also significantly related to the tracking 

performance, F (1, 448) = 9.90, MSE = .09, p < .01, partial η
2 
= .02. This indicates that 

the valence of faces also contributed to the attractiveness effect in this experiment. 

 

 

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