Gaze distribution of an observer while imagining
wearing clothing portrayed in an advertisement
and predicting the impression on others
Fuyuko IWASAKI, Michiko INOUE, andMasashi NISHIYAMA[0000−0002−5964−3209]
Graduate School of Engineering, Tottori University
101 Minami 4-chome, Koyama-cho, Tottori, 680-8550, Japannishiyama@tottori-u.ac.jp

Abstract. Observers using image-sharing social networking services often imagine wearing the clothing portrayed in advertising images andpredict the impression on others. It is likely that an observer’s gaze isdrawn to specific body parts of the person shown wearing the clothes,and as such, the specific body parts that are focused on by the observer
could provide cues regarding impression prediction. Although previous
analytical studies have investigated the role of gaze distribution in evaluating the subject attractiveness, no studies have examined the gaze ofobservers while they imagined wearing clothes and predicted the impression on others. In this paper, we measured the gaze distribution whileobservers imagined wearing a portrayed subject’s clothing and predicted
the impression on others. We further investigated the degree to which anobserver’s gaze was focused on each subject’s body part according to thecharacteristics of the gaze distribution. The experimental results showed
that, in the case of an image taken from head to toe, the observer’s gazetended to be focused most on the subject’s chest, followed by the head.
In the case of images taken with the head occluded, the observer’s gazetended to focus most on the subject’s chest, followed by the stomach.
Keywords: Gaze distribution · Impression prediction · Imagining wearing clothing · Advertising images.

1

Introduction

In recent years, image-sharing social networking services (SNSs) have become acommon platform for advertising and purchasing clothing [13, 12]. As a result,
SNS feeds often show many images of people wearing fashionably coordinatedclothing. Here, we refer to the people in the images as subjects. The subjects in
SNS images are often photographed from head to toe, or their heads are hidden.
Here, a ‘whole-body image’ refers to an image in which a subject is visible fromhead to toe, while a ‘head-occluded image’ shows a subject with their head
hidden.

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 Imagine wearing a subject’s clothing Predict the impression on others
Maybe I can make a good
impression on others
by wearing this clothing!?

Measurement
andanalysis GazeObserver

Subjects in SNS images

Fig. 1. We investigated gaze distribution by measuring and analyzing the female observer’s gaze. The observer looks at the subject in the image, imagines wearing the
subject’s clothing, and predicts whether she would make a good impression on others.

People using image-sharing SNSs subjectively predict whether they would
make a good impression on others in a certain outfit by imagining themselves
wearing the portrayed subject’s clothing [3, 5, 9]. This is the case for both wholebody and head-occluded images. In the following, we refer to people who use
image-sharing SNSs as observers. When observers who are using SNSs make a
prediction about the impression on others that a certain outfit would produce,
they look directly at the subject’s body, as shown in Fig. 1. While imagining
wearing the subject’s clothing, it is likely that the observer’s gaze is drawn to thesubject’s body parts, which could provide cues about the impression on others.
If we could identify the body parts that are the focus of the observer’s gaze, wemight be able to determine which body parts provide helpful information when
making decisions about purchasing clothing. This information could be applied
to the field of clothing marketing.
In this study, we investigated the gaze of female observers who were asked
to imagine wearing a subject’s clothing and to predict the impression on others.
Although the analysis conditions differed from those in our present research,several previous studies investigated the subject body parts that were most frequently gazed at by observers who were asked to predict the degree to which
others would find the subject attractive. For example, Gervais et al. [6] analyzed
gaze characteristics for subjects with different body shapes in a whole-body image. Furthermore, Cornelissen et al. [4] examined gaze characteristics for naked
subjects in a head-occluded image. However, these studies [6, 4] did not consider
the gaze of observers asked to imagine wearing a subject’s clothing and to predict
the impression on others.
In this paper, we attempted to determine which body parts in a whole-body
image or a head-occluded image were the focus of a female observer who wasGaze distribution of an observer while imagining wearing clothing3

asked to imagine wearing the portrayed subject’s clothing and to predict the
impression on others. First, we measured the gaze distribution while observers
imagined wearing a portrayed subject’s clothing and predicted the impression
on others. Second, we investigated the degree to which an observer’s gaze was
focused on each subject’s body part. We confirmed the following results in subjective assessments involving 24 female observers. The female observer’s gazetended to be focused most on the subject’s chest, followed by the head, in thecase of an image taken from head to toe. In contrast, the female observer’s gazetended to focus most on the subject’s chest, followed by the stomach, in the caseof images taken with the head occluded.

2

Hypothesis

In our subjective assessments, to investigate the degree to which the observer’s
gaze was focused on each subject’s body part, we asked the female observer toimagine wearing the portrayed subject’s clothing and to predict the impression
on others. No existing analytical studies have conducted subjective assessments
for this purpose, as described in Section 1. In our subjective assessments, we
generated the following hypotheses based on the previous studies [6, 4].
H1 : When a female observer imagines wearing a subject’s clothing in a wholebody image and predicts the impression on others, the observer’s gaze will
be most focused on the subject’s head.
H2 : When a female observer imagines wearing a subject’s clothing in a headoccluded image and predicts the impression on others, the observer’s gaze
will be most focused on the subject’s stomach.
We explain the detail of the previous study [6] that we referred to whengenerating hypothesis H1. This previous study analyzed the observer’s gaze when
predicting the appearance attractiveness of the subject’s body shape in a wholebody image. They used whole-body images of women wearing the same whitetank top and blue jeans and conducted subjective assessments with male andfemale observers in this previous study. They reported that the observer’s gaze
was more focused on the chest and waist than the face when the observers
were asked an appearance-focused question (compared to a personality-focusedquestion). However, through the experimental results in [6], they also reported
that the dwell time on the face is longer than that on the chest and waist. Fromthese results, we generated hypothesis H1, that the gaze is drawn to the head.
Next, we explain the detail of the previous study [4] that we referred to whengenerating hypothesis H2. This previous study analyzed the observer’s gaze when
predicting the physical attractiveness of a naked subject in a head-occluded
image. They used head-occluded images of naked women with mosaicing faces
and conducted subjective assessments with male and female observers in thisprevious study. They reported that the observer’s gaze was more focused on
the upper abdomen and chest than the pelvic and hip when the observers wereasked an attractiveness question. Furthermore, the experimental results in [4]4F. IWASAKI et al.

demonstrated that female observers did not focus their gaze on the chest as
much as male observers. From these results, we generated hypothesis H2, thatthe gaze focuses on the stomach.

3

Gaze measurement from observers

3.1

Stimulus image

Figure 2 shows a part of the stimulus images used in our experiment. In the following, we denote a set of whole-body images as Sw and a set of head-occluded
images as Sh . The number of subjects in each stimulus image was set to 1. The
total number of stimulus images per observer was 104, with 52 whole-body images and 52 head-occluded images. All subjects in stimulus images were female.
To generate a head-occluded image, an area above the tip line of a chin was
cropped from a whole-body image. We used only the subject’s standing posture,
where her clothes and face were visible. No restrictions were placed on the position and orientation of the limbs of subjects to ensure that the postures ofsubjects were aligned. We selected the subject’s facial expressions that did notgive a negative impression but gave a positive or neutral impression. The sizeof whole body images was resized to 900 pixels in height and 382±82 pixels inwidth while maintaining the aspect ratio. The size of head-occluded images was
757±9 pixels in height and 382±82 pixels in width. These stimulus images were
downloaded from the photo material site1 .
Next, we describe how to select stimulus images for our experiments. We
assumed a formal setting, such as a wedding or a concert, and a casual setting,such as an outdoor festival or a theme park, as scenes in which observers predict
impressions on others. To consider these scenes, we prepared the same numberof stimulus images for both formal and casual clothing. We also prepared thesame number of stimulus images with backgrounds taken outdoors and indoors.
3.2

Observers

We recruited 24 observers (21.5±1.3 years old, university students, Japanese
ethnicity). All observers were female. In the following, the female observer isdenoted as o, and a set of the observers is denoted as O.
We asked a female observer o ∈ O the following question when she viewed
the subject in the stimulus image.
Q : When you imagine yourself wearing the subject’s clothes, do you feel thatthe people around you will have a good impression of you?
Each observer responded on a 4-point scale (4: yes, 3: likely yes, 2: likely no,
1: no). Before performing our subjective assessments, we asked an observer toimagine a situation in which they would use image-sharing SNSs to purchase
clothing that would make a good impression on others. We thoroughly explained
the disadvantages of gaze measurement to the participants and obtained theirconsent on a form.
1

https://www.photo-ac.com/

Gaze distribution of an observer while imagining wearing clothing

5(a) Whole-body images(b) Head-occluded images

Fig. 2. A part of the stimulus images of Sw , Sh used in our experiment.

3.3

Setting

Figure 3 shows our experimental setting. A 24-inch display (AOC G2460PF, 1920
× 1080 pixel resolution) was used to show the stimulus images. A gazepoint GP3HD, a stationary eye-tracker, was used to measure the gaze of female observers.
This eye-tracker was placed in front of the display. An observer was seated withher face facing the display screen. The distance from her face to the display screen
was kept at 65 cm. The height of the observer’s eyes varied among individuals,
ranging from 110 cm to 120 cm from the floor. Observers were instructed to keep
their faces as still as possible when measuring gaze. The sampling rate of the eyetracker was set to 150 Hz. We performed resampling using linear interpolation
at 50 Hz to ensure that the time intervals were equally aligned because the6

F. IWASAKI et al.

Eye tracker
Observer’s eyes

Display110-120 cm

65 cm

123 cmCase of viewing
a whole-body image

Table

70 cm

Case of viewing
a head-occluded image

Fig. 3. Setting for gaze measurement.

time interval of the measured gaze was not constant due to the eye-tracker’s
specifications.
3.4

Procedure

We describe the procedure for measuring the female observer’s gaze.
P1 : One observer o was randomly selected from a set of observers O.
P2 : The question content and measurement procedure were explained to an
observer o.
P3 : The start image was shown on the display for two seconds.
P4 : One stimulus image was randomly selected from a set of whole-body images
Sw or a set of head-occluded images Sh and then shown on the display forthree seconds without overlap. The observer’s gaze was measured during thisperiod.
P5 : The end image was shown on the display for two seconds. An observer
answered the question Q described in Section 3.2.
P6 : The procedure from P3 to P5 was repeated until all stimulus images in Sw
and Sh were selected.
P7 : The procedure from P1 to P6 was repeated until all observers in O wereselected.
Examples of images shown on the display in procedures from P3 to P5 are shownin Fig. 4(a) for a whole-body image and Fig. 4(b) for a head-occluded image.
When showing a stimulus image on the display, we need to be aware of center
bias [1], which fixes the observer’s gaze at the center of the display at the initialtime. We asked an observer to look at the center of a randomly placed whitecross in the start image of procedure P3 to avoid center bias. In procedure P4 ,a stimulus image was randomly placed to avoid overlapping the position of awhite cross in the start image with the position of a subject in an image.

Gaze distribution of an observer while imagining wearing clothing

7

𝑃𝑃3
Start image

Start image

Stimulus image

Stimulus image

End imageEnd image(a) Case of
a whole-body image(b) Case ofa head-occluded image

𝑃𝑃4

𝑃𝑃5

Fig. 4. Examples of the images shown on the display when measuring gaze.

4Gaze analysis

4.1

overview

When analyzing the observer’s gaze, we need to notice that the pixels representing the body parts differ among the stimulus images. The subject’s body parts
are not aligned in the stimulus images, as described in Section 3.1. For example,
a subject placed body parts with both hands downward, one hand on the waist,
both feet shoulder-width apart, or both knees crossed. When using a heatmap
representation on stimulus images for gaze analysis, such as [11, 10, 7], it is noteasy to compare the measured gaze pixels among stimulus images directly.
For gaze analysis, we used the body-part attention probability analysis [8],which indicates how likely it was that the observer’s gaze was focused on eachsubject body part. This probability was calculated based on the distance between a pixel representing each subject body part and a pixel where the observer’s gaze was measured. We describe the body parts used in gaze analysis in
Section 4.2, and the method for calculating the body-part attention probability
in Section 4.3.

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F. IWASAKI et al.
𝑏𝑏1 : Head𝑏𝑏2 : Chest

𝑏𝑏4 : Right shoulder

𝑏𝑏5 : Left shoulder

𝑏𝑏6 : Right elbow

𝑏𝑏7 : Left elbow

𝑏𝑏8 : Right wrist

𝑏𝑏9 : Left wrist
𝑏𝑏10 : Waist

𝑏𝑏3 : Stomach

𝑏𝑏11 : Right knee𝑏𝑏13 : Right toes(a)𝑏𝑏12 : Left knee

𝑏𝑏14 : Left toes(b)

Fig. 5. Body parts for gaze analysis.

4.2

Body parts for gaze analysis

Figure 5 shows the body parts used in gaze analysis. The body parts are definedas head b1 , chest b2 , stomach b3 , right shoulder b4 , left shoulder b5 , right elbow
b6 , left elbow b7 , right wrist b8 , left wrist b9 , waist b10 , right knee b11 , left knee
b12 , right toes b13 , and left toes b14 . When selecting the body parts for gaze
analysis, we did not use those close to other body parts, such as fingers. Instead,
we used the body parts that were distant from each other among the bodyparts. In the case of a whole-body image, we denote a body part bw , and a set
Bw = {b1 , b2 , · · · , b14 } consisting of 14 body parts. In the case of a head-occluded
image, we denote a body part bh , and a set Bh = {b2 , · · · , b14 } consisting of 13
body parts excluding the head b1 .
When perfoming gaze analysis, we detected the head position (b1 ) and the 12
body part positions (b4 , · · · , b14 ) using OpenPose [2]. The head b1 is indicatedby the nose position of OpenPose. Note that this detector do not define bodyparts for chest b2 and stomach b3 . Let b2 be the 1:4 endpoint of the line segment
connecting the midpoint of the line segment connecting the right shoulder b4 andthe left shoulder b5 to the waist b10 . Let b3 be the midpoint of the line segment
connecting the chest b2 and the waist b10 . In the following, we denote a pixel
ibw representing a body part bw detected in a whole-body image, and a pixel ibh
representing a body part bh detected in a head-occluded image.
4.3

Body-part attention probability

In the case of a whole-body image, we calculate the body-part attention probability using [8] for body part bw of Section 4.2. In the following, one whole-body
image is denoted as Iw that is an element of a set of whole-body images Sw .
Suppose a pixel iw is an element of Iw . When a female observer o ∈ O views
a whole-body image Iw , the body-part attention probability p(bw |o, Iw ) represents that her gaze is focused on a body part bw in the image. This probability

Gaze distribution of an observer while imagining wearing clothing

9

is calculated as follows:p(bw |o, Iw ) =X

N (iw |ibw , Σ)p(iw |o, Iw ).

(1)

iw ∈Iw

Note that this equation satisfies as follows:Xp(bw |o, Iw ) = 1.

(2)

bw ∈Bw

The first term N (iw |ibw , Σ) of Equation (1) is a bivariate normal distribution,
where a mean is ibw and a covariance matrix is Σ = diag(σ 2 , σ 2 ). The closer the
distance from a pixel iw to a pixel ibw of a body part bw , the higher the valueof N (iw |ibw , Σ) is recorded. The second term p(iw |o, Iw ) of Equation (1) refers
to the probability that the gaze of an observer o is focused at a pixel iw thatconsists of a whole body image Iw . The probability p(iw |o, Iw ) is calculated asfollows:
1 X
p(iw |o, Iw ) =N (iw |ig (t), Σ),
(3)
n(T )
t∈T

where ig (t) is a pixel representing the gaze measured from an observer o at timet, T is a set of times when the gaze was measured, and n( ) is a function that
returns the number of elements in a set.
Next, in the case of a head-occluded image, we calculate the body-part attention probability using [8] for body part bh of Section 4.2. In the following,
one head-occluded image is denoted as Ih that is an element of a set of headoccluded images Sw . Suppose a pixel ih is an element of Ih . The body-partattention probability for a head-occluded image is calculated as follows:Xp(bh |o, Ih ) =N (ih |ibh , Σ)p(ih |o, Ih ),(4)
ih ∈Ihwhere the first and second terms of this equation are calculated in the same way
as for a whole-body image.

5

Experiments

5.1

Subjective assessments on hypothesis H1 and hypothesis H2

Protocol We explain the case of a whole-body image for the experiment on
hypothesis H1 described in Section 2. Using a set of observers O and a setof whole-body images Sw , we marginalized the body-part attention probabilityp(bw |o, Iw ) defined in Equation (1), and calculated the marginalized probabilityp(bw ) for whole-body images as follows:p(bw ) =X X
1p(bw |o, Iw ),n(O)n(Sw )o∈O Iw ∈Sw

(5)

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F. IWASAKI et al.

0.5
Body-part attention
probability 𝑝𝑝 𝑏𝑏𝑤𝑤

0.4
0.3
0.2

0

Head
Chest
StomachRight shoulder
Left shoulder
Right elbow
Left elbow
Right wrist
Left wrist
Waist
Right knee
Left knee
Right toes
Left toes

0.1

Fig. 6. Body-part attention probability p(bw ) for a set of whole-body images Sw .

where we set n(O) = 24, n(Sw ) = 52.
Next, we explain the case of a head-occluded image for the experiment on
hypothesis H2. Using a set of head-occluded images Sh , we marginalized the
body-part attention probability p(bh |o, Ih ) defined in Equation (4), and calculated the marginalized probability p(bh ) for head-occluded images as follows:
X X
1p(bh ) =p(bh |o, Ih ),(6)n(O)n(Sh )o∈O Ih ∈Sh

where we set n(O) = 24, n(Sh ) = 52.
Results for hypothesis H1 Figure 6 shows a bar graph representation of thebody-part attention probability p(bw ) of Equation (5) for the case of a wholebody image. The horizontal axis shows the body part indicated in Fig. 5, andthe vertical axis indicates the value of p(bw ). The higher the probability of acertain body part, the more the gaze tended to be focused on that body part.
The experimental results showed that the chest was the body part with thehighest p(bw ), and the head was the body part with the next highest p(bw ).
The difference between these probabilities was 0.01, indicating that the gazeprobability was similar between the head and the chest. Hypothesis H1 statedthat the female observer’s gaze would be most focused on the subject’s head, but
this did not hold. Instead, in the case of full-body images, the female observer’s
gaze tended to focus most on the chest, followed by the head.
Results for hypothesis H2 Figure 7 shows a bar graph representation of thebody-part attention probability p(bh ) of Equation (6) for the case of a headoccluded image. The experimental results showed that the chest was the bodyGaze distribution of an observer while imagining wearing clothing

11

0.5
Body-part attention
probability 𝑝𝑝 𝑏𝑏ℎ

0.4
0.3
0.2

0

Chest
StomachRight shoulder
Left shoulder
Right elbow
Left elbow
Right wrist
Left wrist
Waist
Right knee
Left knee
Right toes
Left toes

0.1

Fig. 7. Body-part attention probability p(bh ) for a set of head-occluded images Sh .

part with the highest p(bh ), and the stomach was the body part with the next
highest p(bh ). The difference between these probabilities was 0.05, indicating aslightly different trend between the chest and stomach. Hypothesis H2 statedthat the female observer’s gaze would be most focused on the subject’s stomach,but this did not hold. Instead, in the case of head-occluded images, the female
observer’s gaze tended to be focused most on the chest, followed by the stomach.

5.2

Visualization of gaze distribution for each stimulus image

Protocol We visualized how the gaze was focused on body parts for each stimulus image. In the case of a whole-body image, we used the second term p(iw |o, Iw )of Equation (1). This term refers to the probability that the gaze of a female
observer o is focused on a pixel iw consisting of a whole-body image Iw , as described in Section 4.3. Using a set of observers O, we marginalized p(iw |o, Iw ),and calculated the marginalized probability p(iw |Iw ) for each whole-body image
as follows:
1 X
p(iw |Iw ) =p(iw |o, Iw ).
(7)
n(O)
o∈O

In the case of a head-occluded image, we used the second term p(ih |o, Ih ) of
Equation (4). Using a set of observers O, we marginalized p(ih |o, Ih ), and calculated the marginalized probability p(ih |Ih ) for each head-occluded image asfollows:
1 X
p(ih |o, Ih ).
(8)p(ih |Ih ) =
n(O)
o∈O

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F. IWASAKI et al.

(a)

(b)

Fig. 8. Visualization of gaze distribution for each stimulus image. In (a), p(iw |Iw ) isfor a whole-body image. In (b), p(ih |Ih ) is for a head-occluded image.

Results Figure 8(a) shows the visualization of p(iw |Iw ) of Equation (7) for
each whole-body image. In this figure, the black area indicates that the observer’s
gaze is focused. In contrast, a white area indicates that the observer’s gaze is not
focused. In the subject on the left in Fig. 8(a), the observer’s gaze was focused
mainly on the chest, followed by the head. For the subject on the right, theobserver’s gaze was focused mainly on the chest, followed by the head. We believethat p(iw |Iw ) for each whole-body image indicates that the female observer’s
gaze tends to focus on the chest, followed by the head.
Next, Fig. 8(b) shows the visualization of p(ih |Ih ) of Equation (8) for eachhead-occluded image. In the subject on the left in Fig. 8(b), the observer’s gaze
was focused on the chest, followed by the stomach. For the subject on the right,
the observer’s gaze was focused mainly on the chest, followed by the stomach.
We believe that p(ih |Ih ) for each head-occluded image indicates that the female
observer’s gaze tends to focus on the chest, followed by the stomach.

6

Conclusions

In this paper, we investigated which body parts in a whole-body image or ahead-occluded image were the focus of a female observer who was asked toGaze distribution of an observer while imagining wearing clothing

13

imagine wearing a subject’s clothing and to predict the impression on others.
We confirmed that the female observer’s gaze tended to be focused most on thesubject’s chest, followed by the head, in the case of whole-body images. We also
confirmed that the female observer’s gaze tended to focus most on the subject’s
chest, followed by the stomach, in the case of head-occluded images.
In future work, we will investigate the observer’s gaze distribution by increasing the number of observers and measuring gaze diversity concerning thegender, age, and ethnicity of observers. We will also expand our analysis tovarious subjects’ postures in stimulus images, such as sitting and side-facing
standing postures.

Acknowledgment
This work was partially supported by JSPS KAKENHI Grant No. JP23K11145.
We appreciate Professor Yoshio Iwai for his valuable advice and suggestions
during this research.

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