Investigation of temporal changes ofgaze locations during characteristic evaluation
when viewing whole-body photos
Fuyuko IWASAKI1 ,Masashi NISHIYAMA1[0000−0002−5964−3209] , and Yoshio IWAI1
Graduate School of Engineering, Tottori University
101 Minami 4-chome, Koyama-cho, Tottori, 680-8550, Japannishiyama@tottori-u.ac.jp

Abstract. We investigated how the observer’s gaze locations temporally
shift over the body parts of a subject in an image when the observer istasked to evaluate the subject’s characteristics. We also investigated how
the temporal changes of the gaze locations vary when different characteristic words are contained in the tasks. Previous analytical studies did notconsider time-series gaze locations, although they did determine that theinitial location that the observer’s gaze fixates on is the subject’s face. In
our analysis, we assigned characteristic evaluation tasks to observers andmeasured their gaze locations temporally while they viewed human images. We computed the distance from the observer’s gaze location to thesubject’s body part at each time point and evaluated the temporal difference of the distances between the tasks. We found that the observer’s
gaze fixated on the face initially and shifted to the upper and lower bodyparts. We determined a common pattern of time-series signals of gazelocations among many participants and individual patterns among a few
participants. Furthermore, we found that the temporal changes of thegaze locations became similar or dissimilar according to the characteristic words contained in the tasks.
Keywords: Gaze · Temporal change · Subject’s characteristic.

1

Introduction

Interactions through displays, such as online presentations and parties, are becoming increasingly popular. In the future, it may be common to interact withothers using large displays that show whole bodies (Fig. 1). These potential
future online interactions will offer opportunities to gauge other people’s characteristics through display images. In formal, real-world scenarios, it is essential
to make a favorable impression on others, and this is likely to remain importantin the online space. In this paper, we consider how observers alter their behavior
when perceiving unfamiliar subjects’ characteristics through display images informal scenarios.

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Online presentation

Online party

Fig. 1. Future interactions on large displays, in which people use their whole bodies.
We consider that people hold online presentations and parties when far away from eachother. Observers have more opportunities to perceive subjects’ characteristics throughimages on large displays. In these opportunities, conveying the characteristic that theobservers feel favorable is essential, as well as the interaction in real space.

In real-space interactions, observers obtain a large amount of information
through vision when they evaluate the characteristics of other people [11, 2, 10,13]. These visual functions play an important role when evaluating subjects’characteristics on display images. In this study, we consider gaze behavior as avisual function. Specifically, we consider the case in which observers direct theirgaze to a subject’s face, upper body, lower body, and other body parts.
In analytical studies [7, 14] in cognitive science, researchers investigated theinitial gaze locations of observers performing characteristic evaluation tasks.
These researchers reported that the gaze first fixates on subjects’ faces in images. Based on this observation, we can assume that the face is an important cue
in evaluating subjects’ characteristics. However, in these analytical studies, theresearchers did not investigate how gaze locations temporally shift over otherbody parts after the observer first looks at a face.
In this study, we investigated how the gaze locations of observers, who aretasked to evaluate characteristics, temporally shift over body parts after theobserver first looks at a face. We also investigated whether the temporal changesof the gaze locations varied when the characteristic word included in the taskchanged. To achieve this, we displayed a stimulus image containing a subject on
the display screen. We measured the time series of gaze locations of an observer
looking at the stimulus image. We assigned observers the task of evaluating acharacteristic word and asked them whether they considered the word to matchthe stimulus image. We calculated the distance from the body part of the subject
in the image to the gaze location measured from the observer and evaluated thetime-series signals of the distances. The experimental results demonstrated thatthe observer’s gaze fixated on the face initially, and moved away from the faceand variously to the upper and lower body parts as time passed. We found acommon pattern of time-series signals of gaze locations among many participants
and individual patterns among a small number of participants. We also foundInvestigation of temporal changes of gaze locations

I feelcharacteristic 𝑊! .

I feelcharacteristic 𝑊" .

𝑡!

𝑡!

𝑡"

𝑡"

𝑡#

Observer

3

Time

(a)

Observer

𝑡#

Time
(b)

Fig. 2. We assumed that the gaze location of the observer shifted over the body partsof the subject in the image as time passed when the observer was tasked to evaluatecharacteristic words WA and WB .

that some of the characteristic words included in the tasks had similar timeseries signals to the gaze locations, whereas others did not have those of thegaze locations.

2

Analysis of temporal changes of the gaze locations

2.1

Hypotheses

We formulated hypotheses to analyze the time-series signals of the gaze locations
measured in the task of evaluating characteristics of human images as follows:
H1 : When the participants are tasked to evaluate the characteristics of subjects,
the participants’ gaze locations temporally shift from the faces of the subjects
to other body parts.
H2 : When the characteristic words included in the task change, the time-series
signals of the gaze locations described in Hypothesis H1 change.
In this study, we define the gaze location as the point where the gaze direction
vector intersects the stimulus image on the display screen at a certain time.
First, we present a specific example (Fig. 2(a)) of what is expected for H1.
We consider the case in which a task containing characteristic word WA , suchas gentle or intellectual, is assigned to a participant. We consider that the gazefirst fixates on the subject’s face, as described in [7, 14, 9, 1, 8, 15, 12]. Then thegaze location shifts from the face to other body parts, such as the chest, as time
passes. When we assign a task with another characteristic word WB , we consider
the gaze locations to shift differently over time, as shown in Fig. 2(b). Second,
we present a specific example of what is expected for H2. When we compare thetime-series signals of the gaze locations between Figs. 2(a) and (b), we consider

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F. IWASAKI et al.

that the gaze location at each time point differs because of the difference in thecharacteristic words included in the tasks. To confirm these two hypotheses, we
design an experimental method for measuring and analyzing gaze locations. We
describe the details below.
2.2

Task

We explain the characteristic words contained in the task. We use characteristic
words that often apply to formal scenarios in which many people share social
conventions. Specifically, we target characteristic words used in formal scenarios,
such as presentations and parties. Note that formal scenarios make people likely
to hope to make a positive impression on another person; hence, we exclude
words that express negative characteristics.
We had a free discussion to select the characteristic words that fit formal
scenarios. As a result, we chose the following six characteristic words used in our
analysis:– Gentle– Ambitious– Unique– Rich– Intellectual– Stylish
In our analysis, we assign observers the task of evaluating the characteristic
words used in the formal scenario to measure the observers’ gaze locations. The
tasks are as follows:
T1 : Do you feel the subject is gentle?
T2 : Do you feel the subject is ambitious?
T3 : Do you feel the subject is unique?
T4 : Do you feel the subject is rich?
T5 : Do you feel the subject is intellectual?
T6 : Do you feel the subject is stylish?
We asked the participants to complete each task by answering yes or no in our
analysis.
2.3

Stimulus images

We describe the details of the stimulus images observed by the participants.
For each participant, we used 100 stimulus images containing subjects. Figure 3
shows a sample of the stimulus images used in our analysis. We only used images
containing standing subjects, which are often encountered in formal scenarios,
such as poster presentation areas and standing party receptions. The hands andfeet were not aligned between the subjects. We assumed that the subject’s bodyarea was visible from head to toe and that the subject’s face was close to theInvestigation of temporal changes of gaze locations

5

Fig. 3. Sample of stimulus images used in our analysis.

front. We excluded sitting and supine postures. We used only one subject per
stimulus image. We set the ratio of female to male subjects to 1:1, with 50 males
and 50 females. We chose the subject’s clothing to be appropriate for formal
scenarios such as presentations and parties. We set the subject’s facial expression
to either smiling or neutral. We assumed that there was no background object inthe stimulus image that was more prominent than the subject. We also assumed
that there were no other objects in front of the subject. We resized the image
to 972 pixels in height. We maintained the aspect ratio of the original image.
The average size of the image width was 447.2±82.5 pixels. We collected images
from the photo website1 .
1https://www.photo-ac.com/

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F. IWASAKI et al.

65 cm
Display screen
114 cm

Table
70 cm

Observer’s eyes
110 - 120 cm

Gazemeasurement
deviceChair 44 cm

Female participant

Male participant

Fig. 4. Experimental settings for gaze measurement.

2.4

Settings

Twenty-four participants (12 males and 12 females, with an average age of
22.0±1.2 years old, Japanese students) participated in the study. We fully explained the disadvantages of gaze measurement to the participants and obtained
their consent on a form. The participants and the subjects in the stimulus images were not directly acquainted with each other. During gaze measurement,
we required the participants to complete all tasks (T1 , . . . , T6 ). The procedure
followed by the participants performing tasks is described in Section 2.5.
In this section, we describe the settings for our analysis. The participant wasseated on a chair at a distance of 65 cm horizontally from the display screen. The
height of the chair was 44 cm from the floor. The eye height of the participant was
between 110 and 120 cm from the floor. We used the settings shown in Fig. 4 tomeasure the gaze locations of the participants. We displayed the stimulus image
on the 24-inch display screen (AOC G2460PF, resolution 1920 × 1080 pixels,
refresh rate 59.94 Hz) to measure the gaze locations. Figure 5 shows examplesof the stimulus images on the display screen. We displayed the stimulus images
at random locations on the screen to avoid center bias [3, 4]. We used Gazepoint
GP3 HD as the gaze measurement device. The sampling rate of this device was
150 Hz. In practice, the interval of the measurement time of the gaze location

Investigation of temporal changes of gaze locations

7

Fig. 5. Examples of stimulus images displayed on the screen.

varied. Thus, we resampled at 60 Hz to make the interval equal using bilinear
interpolation.
As a preliminary experiment, we evaluated the gaze measurement error using these settings. We showed reference images containing six reference points
with known locations to seven people on the screen. The average error from thereference points to the gaze locations was 71.4 ± 32.0 pixels.
2.5

Gaze measurement procedure

We used the following procedure to measure the gaze locations of the participantsin our analysis.
P1 : We randomly selected one participant for gaze measurement.
P2 : We randomly set the order of tasks (T1 , . . . , T6 ) to be assigned to theparticipant.
P3 : We explained the task given to the participant, and the measurement procedure.
P4 : We displayed a gray image on the screen for one second.
P5 : We randomly selected one stimulus image from all the stimulus images,
without overlap.
P6 : We displayed the selected stimulus image on the screen for six seconds andrecorded the time-series gaze locations of the participant.
P7 : We displayed a black image on the screen for three seconds.
P8 : We asked the participant to provide an answer for completing the task
explained in P3 .
P9 : We repeated the procedure from P4 to P8 until we used all the stimulus
images.
P10 : We repeated the procedure from P3 to P9 until all tasks were completed
according to the task order set in P2 .
P11 : We repeated the procedure from P1 to P10 until all participants had completed the tasks.
2.6

Body parts used in our analysis

The subjects in the stimulus images used in our analysis were in standing postures, as described in Section 2.3. The subjects’ hands and feet were freely posi-

8

F. IWASAKI et al.
𝑏! : Nose𝑏" : Right shoulder

𝑏% : Left shoulder𝑏# : Right elbow

𝑏& : Left elbow

𝑏$ : Right wrist𝑏' : Left wrist𝑏( : Waist𝑏) : Right knee𝑏!! : Right toes

ｃ

ｃ

(a)

𝑏!* : Left knee𝑏!" : Left toes(b)

Fig. 6. (a) Body parts used for our analysis. (b) Examples of the body parts detectedfrom the stimulus images.

tioned. When the subjects in the images were in various standing postures, thepositions of the body parts differed between the stimulus images. Thus, we cannot directly compare the measured gaze locations between the stimulus images.
We considered detecting body parts from the stimulus images and calculated therelative distances between the body parts and the gaze locations. We explain how
we calculated the distance in Section 2.7.
In this section, we explain body parts b ∈ {b1 , · · · , b12 } in Figure 6(a) used in
our analysis. We used 12 body parts: the nose in the center of the head region,
the right and left shoulders in the torso region, the waist, two right and two left
joints in the arms, and two right and two left joints in the feet. To detect the
body parts of the subjects in the stimulus images, we used OpenPose [5]. Notethat we excluded body parts with close distances between joints, such as palm
joints and toe joints, and used only body parts with far distances between joints.
Figure 6(b) shows examples of body parts detected in the stimulus images.
2.7

Calculation of the temporal changes of the gaze locations

In our analysis, we used the distance from the measured gaze location to the bodypart. We describe the method used to calculate the distance below. Suppose gazelocation x(t, i, T, X ) measured at time t when participant i observes stimulus

Investigation of temporal changes of gaze locations
Distance 𝑑 of 𝑡1

Task 𝑇: I feel
impression 𝑊𝐴 .
Distance 𝑑 of 𝑡2

Observer 𝑖

9𝒑
Left shoulder 𝑏3

Distance 𝑑 of 𝑡3

Gaze 𝒙Fig. 7. Calculating distance d(t, b3 , i, T, X ) of time t between gaze location x(t, i, T, X )and left shoulder location p(b3 , X ).

image X when task T ∈ {T1 , · · · , T6 } is given. Distance d(t, b, i, T, X ) from gazelocation x(t, i, T, X ) to location p(b, X ) of body part b of the subject in thestimulus image is expressed asd(t, b, i, T, X ) =ĎX∥x(t, i, T, X ) − p(b, X )∥2 .
DX(1)

We use the L2 norm as the distance metric. Let DX be the distance from the
midpoint of the left and right shoulders to the waist point on each stimulus image,and let ĎX be the average value of DX computed from all the stimulus images.
In our analysis, ĎX was 250.0 pixels. As an example, the case of measuring
distance d(t, b3 , i, T, X ) for left shoulder b3 is shown in Fig. 7.
Next, using the set S containing all the stimulus images, we calculate theaverage distance for body part b at time t as
1 X
d(t, b, i, T, X ),(2)d(t, b, i, T ) =X
X ∈S

where X is the number of stimulus images. In our analysis, we measured the gazelocation at 60 Hz for 6 sec; hence, the total number of gaze locations sampled in
the procedure P6 of Section 2.5 was 360. We had to pay attention to eye blinking,which often resulted in times when the gaze location was not measured. In thiscase, we did not include times that corresponded to blinking when we calculated
the distance.
Finally, we refer to the time-series signal for which the values of distanced(t, b, i, T ) at each time point t were aligned in the time direction as the temporalchange of the gaze locations.

3

Experimental results

3.1

Analysis of the average temporal changes of the gaze locations

We investigated hypothesis H1 described in Section 2.1 by computing the average
temporal changes of the gaze location using distance d(t, b) of time t between

10

F. IWASAKI et al.
𝑏! (Nose)𝑏",$ (Shoulder)𝑏%,& (Elbow)

𝑏+ (Waist)𝑏),!* (Knee)𝑏!!,!" (Toes)𝑏',( (Wrist)

Distance 𝑑 𝑡, 𝑏 [pixel]

900

600

300

0
0

1

2

3

4

5

6

Time 𝑡 [s]Fig. 8. Average temporal changes of the gaze location for each body part b. Average
distance d(t, b) at each time point t was computed from the results for all tasks andparticipants.

the measured gaze and each body part b as follows:
1 XX
d(t, b, i, T ),d(t, b) =6I(3)

T ∈T i∈I

where d(t, b, i, T ) is the distance in Eq. (2), T is the set of tasks {T1 , · · · , T6 }, I
is the number of participants, and I is the set containing all participants.
Before evaluating distance d(t, b), we checked distance d(t, b, i, T ) calculated
from the symmetrical body parts. Differences in the distance were minimal between the right and left shoulders, between the right and left elbows, between
the right and left wrists, between the right and left knees, and between the rightand left toes. Thus, we averaged the distances between the left and right bodyparts for symmetrical cases. In our analysis, to calculate the distance, we used
the following body parts: shoulder B2,3 , elbow B4,5 , wrist B6,7 , knee B9,10 , andtoes B11,12 .
Figure 8 shows the average temporal changes of the gaze location using distance d(t, b) for each body part b. The vertical axis represents the magnitude of
the value of d(t, b). If this magnitude is small, the gaze location is close to thebody part location on average. The horizontal axis represents time t when thegaze location was measured.
Between t = 0 sec and 0.3 sec, there was a period when the average distance
was almost unchanged. We consider that the participants’ brains worked to respond in some way to the stimulus image in this period. After t = 0.3 sec, theaverage distance for the nose b1 continually became smaller, reaching a minimum
distance at 0.6 sec. We consider that the participants shifted their gaze to thesubject shown at a random position on the display screen and started to observe

Investigation of temporal changes of gaze locations

11

the subject’s face. This result shows the same tendency as the results in previous
analytical studies [7, 14]. After t = 0.6 sec, the average distance for the nose b1
tended to increase toward 3.1 sec, and this increase gradually became smaller.
By contrast, the average distance for the toes b11,12 tended to decrease, and thisdecrease gradually became smaller. We did not determine any particular bodypart for which the average distance was extremely small in this period. Betweent = 3.1 sec and 6 sec, the average distance for the nose b1 gradually decreased,
and conversely, the average distance for the toes b11,12 gradually increased.
We summarize the results of our analysis of hypothesis H1. The participants
not only looked at the face at all times but also observed other body partsin addition to the face after first looking at it. However, we cannot say thatthe body part where the gaze fixated was common among the participants or
stimulus images. We confirmed that the gaze locations variously shifted to upperand lower body parts over time.
3.2

Temporal changes of the gaze locations of each participant

We evaluated the temporal changes of the gaze locations of each participant. We
computed distance d(t, b, i) of participant i asd(t, b, i) =1 X
d(t, b, i, T ),
6

(4)

T ∈T

where d(t, b, i, T ) is the distance in Eq. (2) for each task T and T is the setof tasks {T1 , · · · , T6 }. We used seven body parts b as follows: nose, shoulders,elbows, wrists, waist, knees, and toes.
We applied hierarchical clustering to visualize the temporal change patternsof the gaze location. First, we computed distance d(t, b, i) using Eq.(4) at bodypart b for time t for each participant i by averaging the distances for all stimulus
images and all tasks. Next, we generated a matrix with d(t, b, i) elements foreach participant. The size of the matrix was 360 × 7. Each matrix corresponded
to a specific participant. We used the Frobenius norm as the distance metricbetween matrices. We set the number of clusters to four.
We applied hierarchical clustering to the temporal changes of the gaze locations of 24 participants and found that 17 belonged to cluster 1, 3 to cluster 2,
2 to cluster 3, and 2 to cluster 4. Figure 9 shows the representative temporalchange of the gaze location for one participant in each cluster. The vertical axis
represents the magnitude of d(t, b, i). A small value indicates that the gaze location was close to the location of body part b. In the figure, we show the temporalchanges of gaze location for one of the participants of the pair with the smallest
norm in each cluster. Figure 9(a) shows the temporal change of the gaze locationin cluster 1, which included most participants. In this cluster, participants not
only looked at the face at all times but also observed other body parts after
first looking at the face. The remaining clusters are shown in Figs. 9(b)–(d). Although the number of participants that belonged to the cluster was small, eachcluster demonstrated an individual pattern of temporal change of gaze location.

F. IWASAKI et al.
𝑏1 (Nose)

𝑏2,3 (Shoulder)𝑏4,5 (Elbow)

𝑏8 (Waist)𝑏9,10 (Knee)𝑏11,12 (Toes)

900

Distance 𝑑 𝑡, 𝑏, 𝑖 [pixel]

Distance 𝑑 𝑡, 𝑏, 𝑖 [pixel]

12

600

300

0

0

1

2

3

4

5

6

900

600

300

0

0

900

600

300

0

1

2

3

4

5

1

2

3

4

5

6

Time 𝑡 [s](b) Cluster 2 (3 participants)

Distance 𝑑 𝑡, 𝑏, 𝑖 [pixel]

Distance 𝑑 𝑡, 𝑏, 𝑖 [pixel]

Time 𝑡 [s](a) Cluster 1 (17 participants)

0𝑏6,7 (Wrist)

6

Time 𝑡 [s](c) Cluster 3 (2 participants)

900

600

300

0

0

1

2

3

4

5

6

Time 𝑡 [s](d) Cluster 4 (2 participants)

Fig. 9. Temporal changes of gaze locations d(t, b, i) for representative participant i. We
performed hierarchical clustering using all participants.

In cluster 2, the participants’ gaze first gathered at the nose and continued tostay near the face. In clusters 3 and 4, the participants shifted their gaze more to
the lower part of the body, such as the feet, compared with the results in cluster
1. From these results, we believe that there was a common pattern of temporalchange of gaze location among many participants and individual patterns amonga small number of participants.
3.3

Comparison of the temporal changes of the gaze locations
between characteristic words

We investigated hypothesis H2 described in Section 2.1 by visualizing the differences in the temporal change of the gaze locations between tasks containing
different characteristic words. In this analysis, we focused on the body part of
the nose b1 . We computed distance d(t, b1 , T ) for each task T ∈ {T1 , . . . , T6 } asd(t, b1 , T ) =1X
d(t, b1 , i, T ),
I
i∈I

(5)

Investigation of temporal changes of gaze locations
𝑇! (Gentle)
𝑇$ (Rich)𝑇" (Ambitious)
𝑇& (Intellectual)

13

𝑇# (Unique)
𝑇% (Stylish)

Distance 𝑑 𝑡, 𝑏, 𝑇 [pixel]

300

200

100

0
0

1

2

3

4

5

6

Time 𝑡 [s]Fig. 10. Visualization of the temporal changes of the gaze locations d(t, b1 , T ) for eachtask T ∈ {T1 , . . . , T6 } of each characteristic word. We computed these temporal changes
for the body part of the nose b1 .

Table 1. We computed the distance matrix between the task vectors using the temporalchanges of the gaze locations d(t, b1 , T ). T1 : Gentle, T2 : Ambitious, T3 : Unique, T4 : Rich,
T5 : Intellectual, T6 : Stylish.

T1

T1

T2

0

254.5 1040.2 1548.1 512.9 1562.6

T2 254.5

0

T3 1040.2 823.2

T3

T4

T5

T6

823.2 1325.5 302.6 1348.8
0

T4 1548.1 1325.5 536.5

536.5 547.7 537.3
0

T5 512.9 302.6 547.7 1049.8

1049.8 218.8
0

T6 1562.6 1348.8 537.3 218.8 1070.4

1070.40

where d(t, b1 , i, T ) is the distance in Eq. (2), I is the number of participants, andI is the set containing all participants. Figure 10 shows the time-series signalsof distance d(t, b1 , T ). Between t = 0 sec and 0.6 sec, the distances were almost
common among all tasks. Between 0.6 sec and 6 sec, the distances increased
and decreased over time for all tasks. Additionally, there were differences inthe timing of the increase and decrease among the tasks. The experimental
results demonstrated that the tendency was similar in all tasks; that is, the gazelocations approached the nose first and then left. We found that the timing of
the gaze shift after the participant looked at the nose differed between tasks.
We further investigated the differences in the temporal changes of the gazelocations. We generated a task vector for each task’s d(t, b1 , T ) values, arranged
in ascending order at time t. We calculated the distance matrix between thetask vectors using the L2 norm. Table 1 shows the distance matrix between

14

F. IWASAKI et al.
900
𝑇! (Gentle)

600

𝑇" (Ambitious)

300

𝑇# (Unique)0

𝑇$ (Rich)-300

𝑇% (Intellectual)

-600
-900
-900 -600 -300

𝑇& (Stylish)
0300 600 900

Fig. 11. Results of placing each temporal change of the gaze location for each characteristic word on a two-dimensional plane. We calculated metric MDS using the distancematrix of the task vector.

the task vectors. We applied the metric multidimensional scaling (MDS) [6] tothe distance matrix and placed the task vectors on a two-dimensional plane, as
shown in Fig. 11. The distance between gentle T1 and ambitious T2 was small,which indicates that the temporal changes of the gaze locations were similar toeach other. Similarly, the distance between rich T4 and stylish T6 was small,which indicates that the temporal changes of the gaze locations were similar toeach other. T1 and T2 were placed further away from T4 and T6 , which indicatesthat the temporal changes of the gaze locations were not similar. In particular,
the distance between T1 and T6 was the largest. For the unique T3 , there wasnothing placed particularly close to it. The intellectual T5 was placed close toT2 . From the results of our analysis into hypothesis H2, we found that there
were words with similar and dissimilar temporal changes of the gaze locations
among the characteristic words included in the tasks. This suggests that changes
in characteristic words probably cause differences in the temporal changes of thegaze locations.

4

Conclusions

We investigated how observers temporally view the body parts of subjects inimages when they are assigned a task to evaluate characteristics. We also investigated whether the temporal changes of the gaze locations differed when thecharacteristic words in the task changed. We calculated the distance from thebody part of the subject in the image to the measured gaze location. We compared the time-series signals of the calculated distance. From the experimental
results, we confirmed that the observer’s gaze initially fixated on the face, thenmoved away from the face and variously shifted to the upper and lower bodyparts as time passed. We also confirmed a common pattern of temporal change ofInvestigation of temporal changes of gaze locations

15

gaze locations among many participants and individual patterns among a small
number of participants. Furthermore, we determined characteristic words withsimilar and dissimilar temporal changes of the gaze locations.
In future work, we will analyze the temporal changes of the gaze locations
measured using various characteristic words. We will also expand our analysis tovarious subjects’ appearances, such as age, body shape, and race, in the stimulus
images.

Acknowledgment
This work was partially supported by JSPS KAKENHI Grant No. JP20K11864.
We would like to thank Ms. Nonoka Kawaguchi for her cooperation in our evaluation and data collection.

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