3D Interaction Techniques for Virtual Shopping: Design and Preliminary

Study

Eulalie Verhulst

1,2

, Paul Richard

, Emmanuelle Richard

, Philippe Allain

and Pierre Nolin

Laboratoire Angevin de Recherche en Ing

enierie des Syst

emes (LARIS - EA 7315), Universit

e d’Angers, Angers, France

Laboratoire de Psychologie des Pays de la Loire (LPPL EA 4838), Universit

e d’Angers, Angers, France

Laboratoire de Recherche Interdisciplinaire en R

ealit

e Virtuelle (LARI-RV),

Keywords:

Virtual Reality, Interaction Techniques, Virtual Supermarket, User Study.

Abstract:

Virtual Reality is now recognized as a powerful tool for the assessment and rehabilitation of both motor and

cognitive impairments. In this context, effective Virtual Environments (VEs) that simulate everyday tasks

must be proposed. We have developed a virtual supermarket (VS) in which the user can explore and collect

various items using a shopping cart. Four interaction techniques have been designed and compared in terms

of usability, performance and workload with healthy volunteer participants. These techniques go beyond

the desktop paradigm by offering a more immersive and intuitive way of interaction. Results showed that

participants were more efﬁcient in terms of performance (completion time and travelled distance) using the

game-pad rather than using full body gestures. However, they had more fun performing the task under these

conditions.

1 INTRODUCTION

Virtual Reality (VR) is now recognized as a powerful

tool for the assessment and rehabilitation of both mo-

tor and cognitive impairments (Merians et al., 2002;

Broeren et al., 2002; Flynn et al., 2003; Katz et al.,

2005). Indeed, VR provides a unique medium for

the achievement of several requirements of effective

rehabilitation intervention: repetitive practice, feed-

back about performance, and motivation to endure

practice (Riva, 2003; Gaggioli et al., 2009; Raspelli

et al., 2012; Cipresso et al., 2012; Villani et al., 2013;

Pallavicini et al., 2013). In addition, VR techniques

lead to constantly monitor patient’s performance and

to quantify his improvements. Another important ad-

vantage of VR is related to the beneﬁts of the immer-

sive experience or presence in the virtual environment

(VE) (Cipresso et al., 2013; Repetto et al., 2013; Riva

et al., 2011).

The most common navigation techniques used for

the virtual supermarket (VS) is based on desktop

hardware such as a computer mouse, keyboard, or a

joystick. However, even if most people usually work

or play with a computer mouse or a keyboard, they

usually don’t use them in an optimal way for navi-

gation tasks (McClymont et al., 2011) and the use of

a joystick appears to be more convenient than a key-

board (Vera et al., 2007). Some systems use more

complex interaction techniques or expensive devices,

and are therefore somehow difﬁcult to set-up outside

the lab or in clinical environments (von Kapri et al.,

2011; Cruz-Neira et al., 1992; Williams et al., 2007).

To be effective in the context of virtual rehabil-

itation, VEs and 3D interaction techniques have to

be easy-to-use or easy-to-learn. However, although

many research has been carried out to make it easier,

interacting with VEs is still not straightforward, es-

pecially for people with special needs, disabilities or

deﬁciencies. Therefore, more research is needed in

this context.

The goal of this research is to provide differ-

ent navigation and selection techniques ranging from

desktop interaction techniques based on the use of

joystick or game-pad to interaction techniques based

on body gestures. In this context, we have designed

and compared different 3D interaction technique in

terms of usability performance and workload. The re-

sults provide information about different interaction

techniques and which aspects of the techniques could

bring beneﬁts to users with special needs, disabilities

or deﬁciencies in a context of rehabilitation and train-

ing in a VS.

Verhulst, E., Richard, P., Richard, E., Allain, P. and Nolin, P.

3D Interaction Techniques for Virtual Shopping: Design and Preliminary Study.

DOI: 10.5220/0005725402690277

In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 1: GRAPP, pages 271-279

ISBN: 978-989-758-175-5

271

The paper is organized as following: the next sec-

tion provides a survey of the related work concern-

ing the use of virtual supermarkets in the context

of virtual rehabilitation and the techniques proposed

for navigation and selection. Section 3 presents an

overview of the developed system, including the de-

scription of the virtual supermarket and the proposed

interaction techniques. In Section 4, we describe our

user study aimed at comparing the proposed inter-

action techniques. Section 5 provides a discussion

concerning the participants’ performance (completion

time, distance travelled, and errors) and the subjective

data collected using questionnaires. Section 6 con-

cludes the paper and discusses directions for future

work.

2 RELATED WORKS

2.1 Virtual Supermarkets

During the last decade, researchers have investigated

the potentials of virtual supermarkets (VS) to evalu-

ate executive functions in several populations (Elbaz

et al., 2009; Josman et al., 2014). In this context,

different VS have been developed such as the Vir-

tual Interactive Shopper (VIS) (Hadad, 2012) or the

V-Mall (Rand et al., 2009).

Although they have similar conﬁgurations, the

proposed VS differ in terms of interaction techniques

and experimental set-up. For example, Rand et

al. (Rand et al., 2005) developed a virtual mall to treat

post-stroke patients. They used a relatively expensive

system which requires video studio conditions (i.e. a

green backdrop, lighting and large space).

Castelnuovo et al. (Castelnuovo et al., 2003) de-

scribed the V-Store as a rehabilitation tool where pa-

tients with neurological damaged could be involved

in several tasks with higher degree of complexity de-

signed to stimulate the executive function, program-

ming, categorical abstraction, short-term memory and

attention. The authors provide no results of evaluation

with patients. Lee et al. (Lee et al., 2003) designed a

VS for the assessment and rehabilitation of daily-life

activities. They mainly focused on the usability of

the VE and tested it on patients with traumatic brain

injury and stroke. A Eye tred

T M

FMD-250Z head-

mounted display, a Intertrax2

T M

position sensor and

a Airstik

T M

2000 joystick were used for observation,

navigation and interaction.

Other studies were carried out using VS. For ex-

ample, Carelli et al. (Carelli et al., 2008; Carelli et al.,

2009) conducted a feasibility study of a shopping task

developed using VR techniques. The task was to

choose and buy products from a shopping list. The

objective of the study was to investigate the usability

of the system. Twenty healthy adults had to navigate

in the VS using a handle (pushing right/left buttons)

and select the items by pressing a button. Cardoso et

al. have developed a VS to assess cognitive disabil-

ity of patients with a left hemisphere stroke (Cardoso

et al., 2006). The patients had to navigate within the

VS and collect items using a mouse. Task was to com-

plete a shopping list. Each time the patient selected

a given item, a window appeared, asking him/her to

choose the price which corresponded to the product.

Klinger (Klinger et al., 2003; Klinger et al., 2006)

and Mari

e et al. (Mari

e et al., 2003) designed the vir-

tual action planning supermarket (VAP-S). The par-

ticipants, seated in front of a 2D monitor, were in-

structed to explore the supermarket using a keyboard

for navigation and a mouse for items collection (Jos-

man et al., 2006; Josman et al., 2008).

2.2 3D Interaction Techniques

3D interaction techniques are the main components

of VR systems. They have been classiﬁed as fol-

lows (Mine, 1995; Bowman, 1998; Bowman and

Hodges, 1999): selection, manipulation, navigation

and application control. During the two last decades

several navigation techniques have been proposed and

evaluated (Ruddle et al., 1997; Bowman et al., 1999;

Usoh et al., 1999; Sutcliffe and Kaur, 1999; Vila et al.,

2003; Suma et al., 2007; von Kapri et al., 2011; Bolte

et al., 2011; Cirio et al., 2012).

Bowman et al. (Bowman et al., 1997) pro-

posed a framework for the design and evaluation

of navigation techniques for speciﬁc tasks in VEs.

Later, Arns proposed extended Bowman’s taxonomy

and distinguished real translation/rotation and virtual

ones (Arns, 2002). Results from experiments indi-

cated that pointing techniques are advantageous rela-

tive to gaze-directed steering techniques. It was how-

ever observed that navigation techniques which in-

stantly teleport users to new locations are correlated

with increased user disorientation. Some generic

hand directed motion techniques have also been pro-

posed for navigation. The position and orientation of

the hand determine the direction of motion through

the VEs. These techniques appear efﬁcient but tiring

since the user has to constantly move his/her arms in

space.

To be efﬁcient, navigation techniques must allow

the user to move easily within VEs while looking

around. Therefore, researchers tried to develop in-

tuitive interaction techniques for navigation and item

selection. For exemple Renner et al. (Renner et al.,

GRAPP 2016 - International Conference on Computer Graphics Theory and Applications

272

2010) proposed a VS in which the user is able to nav-

igate and look around at the same time using well-

known interaction techniques based of body gestures.

The authors used several methods like path draw-

ing where subject use the Wii Remote

T M

to navigate

through the VE by drawing a path, the walking in

place where they make step-in-place on a Wii Bal-

ance Board

T M

to navigate in the VE. The authors also

use non immersive interaction technique like world

in miniature where users could see the VE like a

map, and move from one point to another. More

recent gaming input devices like the Nintendo Wii

Remote

T M

and the Nintendo Wii Balance Board

T M

have been used for navigation and interaction with

VEs (Fischer et al., 2011).

The most effective navigation techniques are

based on real or real-like walking. Real-like walking

techniques such as step-in-place have been developed

and evaluated in a general context (Templeman et al.,

1999; Bouguila et al., 2004; Richard et al., 2007).

Beckhaus, Blom and Haringer (Beckhaus et al., 2005)

present a navigation method based on the dance-pad,

a physical device that has directional arrows acti-

vated by stepping. Real walking techniques have also

been developed (Slater et al., 1995; Choi and Ricci,

1997) and proved to be very efﬁcient (Suma et al.,

2009). However, this approach either limits the users

navigation space (Williams et al., 2007), or require

some complex set-up such as cyberspheres (Fernan-

des et al., 2003), omnidirectional treadmills (Darken

et al., 1997; Iwata, 1999; Suryajaya et al., 2010) or

complex robotics system (Iwata et al., 2005).

3 EXPERIMENT

Our motivation to conduct this experiment relies on

the need to get both objective and subjective data al-

lowing to analyse user performance and preference

for different interaction techniques in the context of

shopping activities. The main objective is to identify

the advantages, drawbacks and limits of the proposed

interaction techniques.

3.1 Apparatus

The experiment was carried out using the VR plat-

form illustrated in Figure 1. The platform is made

of a back-projected screen (2m large x 2m high).

The projector used for the experiment is an Optoma

HD141X Full HD 3D 1080p Projector. The platform

provides low-cost interaction devices such as the Mi-

crosoft Xbox

T M

360 ones : the game-pad controller

and the Kinect

T M

sensor. For real-time head tracking,

we used a TrackIR

T M

device.

Figure 1: Set-up used for the experiment.

3.2 Virtual Environment

The supermarket is of relatively limited size so that it

can be explored in a relatively limited time. It consists

of two shelves, a frozen food area, a bakery area, a

magazine space, a cool space and two areas dedicated

to fruits and vegetables (Figure 2). The 3D models

were developed using 3DS Max. Then, they were ex-

ported in .fbx format and imported into the Unity3D

game engine. The user can freely navigate inside the

store and collect items. Once selected, the items are

automatically put in the shopping cart that is placed

in front of the user (Figure 3). Different disruptors

(audible or visual) may be embedded in the simula-

tion. Similarly, avatars can wander around the store

and behave differently vis-

a-vis the environment or

the participants. The system records all movements

and actions performed by the participants within the

VE.

Figure 2: First-person view of the virtual shop.

3D Interaction Techniques for Virtual Shopping: Design and Preliminary Study

273

3.3 Design and Procedure

Eighty volunteer students from our school of Engi-

neers were recruited to participate in the study. They

were split in four groups of twenty students each.

Each group performed the task in a different condition

, C

, and C

). Each subject was installed in

front the visual display which was set in monoscopic

viewing mode.

In condition C

(mean age : 19.0 ; SD : 1.41),

illustrated in Figure 4 (a), the participants used the

Xbox

T M

360 controller for travelling in the VE (left

joystick), looking around (right joystick) and select

items (green button).

In condition C

(mean age : 19.04 ; SD : 1.78),

illustrated in Figure 4 (b), the subjects used the left

joystick of the Xbox

T M

360 controller for travelling,

and a low-cost head tracking device (TrackIR

T M

) for

looking around.

In the condition C

(mean age : 22.05 ; SD : 2.25),

illustrated in Figure 4 (c), the participants navigated

in the VS using dynamic body gestures, similar to the

ones used for operating a real shopping cart. Thus,

to move the cart forwards, the users have to put both

hands forwards. To move the cart backwards, they

have to put both hands backwards. The navigation in

the VS is based on hand movements, so to turn right

or left, participants have to move up their hand in the

chosen way. So to turn right, subjects have to place

their right arm perpendicularly to their body.

Figure 3: Shopping cart containing some collected items.

As in the previous condition, the TrackIR

T M

sys-

tem was used for looking around. To collect the items,

participants have to point on them and clap their

hands. The Kinect

T M

was used to capture participants

arm movements. Motion data were processed using

FAAST

T M

(Flexible Action and Articulated Skeleton

Toolkit).

In condition C

(mean age : 19.94 ; SD : 1.77), il-

lustrated in Figure 4 (d), the users navigated in the VS

using a step-in-place technique. To move forwards

the subjects have to step-in-place in front of the vi-

sual display. Turning right or left was made using

upper body’s (shoulders) orientation.To collect items,

participants had to point on them and clap their hands.

As in the previous condition, the Kinect

T M

sensor and

FAAST

T M

were used. The four conditions were cho-

sen to be easy to use and based on low-cost devices.

(a) (b)

Figure 4: Interaction techniques : (a) using the game-pad

only, (b) using the game-pad and the TrackIR

T M

, (c) and

(d) using the Kinect

T M

and the TrackIR

T M

3.3.1 Task

The task asked to the participants was to navigate in-

side the supermarket and collect the seven items from

a list using one of the interaction techniques previ-

ously described. The list is positioned on the shop-

ping card and is available to the subject during the

completed task (Figure 3). User scan see the list in

its integrity by changing his point of view. The pur-

chased items are not delete when they are selected .

Once the subject considered that all the items from

the list were collected, they had to reach the cash reg-

ister as quickly as possible. As the subject reached

this area, the task was considered to be completed and

the simulation ended. Each participant completed the

task twice. At the end of the experiment, participants

were asked to ﬁll in the NASA TLX and the subjec-

tive questionnaires.

3.3.2 Collected Data

In order to compare the different interaction tech-

niques, we collected performance data such as the

task completion time and the travelled distance. We

didn’t observe any error. Users would made errors if

they didn’t respect the items of the list.

In addition, we used the NASA Task Load Index

(NASA TLX) to assess the task’s mental, physical and

GRAPP 2016 - International Conference on Computer Graphics Theory and Applications

274

temporal demand, the user’s perceived performance,

effort and frustration. A non standardized usability

questionnaire was used to assess participants’ habits

in playing video games and to evaluate on a seven

Likert scale their enjoyment during the task and over-

all system usability. We also observed the subjects

while performing the task and noted their comments,

strategies and behaviour.

3.4 Results

The R statistical software was used to analyse the

data, at a signiﬁcance level of 0.05. Kruskall-Wallis

test was used to compare the four conditions C

, C

and C

using performance data (time, errors and

distance travelled) and using the data collected via

the questionnaires. Post-hoc analyses, conducted with

a Mann-Withney test for independent samples, were

used to compare the different conditions and a Cliff

Delta was conducted to measure size effect. A mod-

iﬁed T-test (Crawford and Howell, 1998) was con-

ducted to compare an individual score against the

norm. It was used in the context of comparing in-

dividuals with no experiences in video games to the

the rest of participants of her/his group with habits in

video games.

The results are presented in the following order.

First, we look at the task completion time associated

with each condition. Then, we report about the dis-

tance travelled by the subjects while performing the

task. Finally, the data collected using the question-

naires (NASA TLX and usability) are presented.

The results revealed that no subject has made mis-

takes during the task and have collected all the items

of the list. Comparisons between trials 1 and 2 was

made with a U Mann-Whitney test. For all conditions,

trial 2 was better than trial 1 in terms of completion

time, numbers of errors and distance travelled. In this

section, we present the data for the second trial only.

3.4.1 Completion Time

Results are illustrated in Figure 5. To complete the

task, users needed signiﬁcantly less time in C

condi-

tion (game-pad + head tracking) than in C

condition

(game-pad only) (U = 124 ; p = 0.04*)(∆ = -0.38),

(arms movement + head tracking) (U = 46.5 ; p =

0.00005***) (∆ = -0.75) and C

(step in place + head

tracking) (U = 16.5 ; p = 0.000001***)(∆= -0.91).

There is no signiﬁcant different between C

and C

conditions (U = 137 ; p = 0.21).

Figure 5: Time to complete the task (second trial) in the

four conditions.

3.4.2 Distance Travelled

Results are illustrated in Figure 6. They showed that

in C

condition (game-pad + head tracking) partici-

pants travelled signiﬁcant shorter distances than those

in C

(U = 128.5 ; p = 0.05*)(∆ = -0.35), C

(U = 622

; p = 0.0003***) (∆ = -0.67) and C

conditions (U =

58 ; p = 0.0002***)(∆ = -0.69).

3.4.3 Effect of Skill

A modiﬁed T-test was realized to analyse the per-

formance of players with bad skills in video games.

Some of them needed signiﬁcantly more time to com-

plete the task. Indeed, the analysis shows that sev-

eral subjects with bad skills in video games had

poor time’s performance. In C

(game-pad + head

tracking), one participant presents bad skills in video

games and took signiﬁcantly more time to complete

the task (t = 2.14). In C

(arms movement + head

tracking), seven participants were unfamiliar with

video games and only one took signiﬁcantly more

time to complete the task (t = 1.9). In the ﬁrst con-

dition with game-pad, over seven participants, one

took signiﬁcantly more time to complete the task (t

= 2.1), and another made a signiﬁcantly longer path (t

= 2.09).

In the two conditions C

and C

, there were seven

users with bad skills in video games, so these condi-

tions were divided in two groups: one with users who

have good skills in video games and the other with

participants who have a strong experience of video

games.

In the game-pad conditions, the group with bad

skills in video games made signiﬁcantly longer paths

(U = 17 ; p= 0.02*)(∆ = -0.62) and needed signiﬁ-

3D Interaction Techniques for Virtual Shopping: Design and Preliminary Study

275

Figure 6: Distance travelled (second trial) in the four con-

ditions.

cantly more time to complete the task (U = 5.5 ; p =

0.01*) (∆ = -0.88). However, in the Kinect

T M

condi-

tions, there was no signiﬁcant difference between the

group with good skills and the group with bad skills,

in term of travelled distance (U =53; p =0.53) and

completion time (U = 34 ; p= 0.39).

3.4.4 Subjective Data

We observed that two scales of the NASA TLX were

signiﬁcantly different : effort and frustration. Partici-

pants from the C

condition (game-pad + head track-

ing) produced less effort than those from the C

con-

dition (arms movement + head tracking) (U= 101 ;

p= 0.01*)(∆ = -0.46) , and less effort than those from

the C

condition (step-in-place + head tracking)(U=

89 ; p= 0.004**)(∆ = -0.53). Results of the frustra-

tion scale indicated that the participants from the C

condition felt less frustration than those from the C

condition (U= 11.6 ; p= 0.04*) (∆ = -0.38) and those

from the C

condition (U= 66.5 ; p= 0.0005***) (∆

= -0.65). Participants from the C

condition also felt

more frustration than those from the C

condition (U

= 261 ; p = 0.02) (∆ = 0.44).

Participants were asked to complete a question-

naire about easiness of the interaction technique and

the task’s enjoyment. The Kruskal-Wallis test indi-

cated no difference between the four navigation tech-

niques (p=0.08). Participants from the C

condition

found the task less funny than those from the C

con-

dition (U = 286.5, p=0.02*) (∆ = 0.36) and those from

the C

condition (U=250 ; p = 0.04* )(∆= 0.31). Sim-

ilarly, participants from the C

condition found the

task less funny than those from the C

condition (U =

128.5 ; p = 0.02*) (∆ = -0.38) and from the C

condi-

tion (U= 121.5 ; p = 0.03*) (∆ = -0.36).

4 DISCUSSION

We developed a virtual supermarket for the assess-

ment and rehabilitation of patients with cognitive im-

pairments. In order to get both performance and sub-

jective control data, we carried out a user study with

volunteer students. The goal was to compare navi-

gation and selection techniques ranging from desk-

top interaction techniques using a game-pad to full

body gestures. Navigating and collecting items us-

ing full body gestures seem a-priori more intuitive

and natural, especially for the step-in-place technique

condition). However, desk-top devices such as

the game-pad are easy-to-use (Vera et al., 2007) and

most people who play video games know how to use

it very well. We observed, that no matter the inter-

action techniques, in all conditions, participants were

signiﬁcantly more efﬁcient in performing the task af-

ter one trial. They all travelled shorter distances in

the supermarket and spent less time to complete the

task. Thus, the proposed interaction techniques and

the task are easy-to-learn.

Interaction techniques based on the Kinect

T M

was

proposed for people unfamiliar with video games be-

cause of their easiness (Roup

e et al., 2014). Indeed,

full body gestures are more suited for people with

no skills in video games. According to a previous

study (Roup

e et al., 2014), results show that the par-

ticipants with no skills in video games could perform

the shopping task as well as participants with good

skills in video games. However for the game-pad con-

ditions, participants with no skills in video games got

lower performance, and needed more time to perform

the task.

Previous studies present various results. Consis-

tent with our results, Teixeira et al. (Teixeira et al.,

2012) showed that the game-pad was more effective

than a step-in-place navigation technique (Teixeira

et al., 2012; Figueiredo et al., 2014). However in Ren-

ner et al. (Renner et al., 2010), the step-in-place con-

dition was the most effective for navigating in a vir-

tual shop. In another VE, the walking-in-place condi-

tion was better than a joystick condition (Riecke et al.,

2010). In this study, users worn an HMD and had

to ﬁnd some hidden items in a VS. The poor perfor-

mance with the joystick may be due to the lack of

visual exploration of the VE (Riecke et al., 2010).

Results of the NASA TLX indicated that partic-

ipants produced more effort in the Kinect

T M

condi-

tions than in the game-pad conditions. This is not sur-

prising since the participants have to move their arms

(condition C

) or their whole body (condition C

) to

control the shopping cart and collect items. Results

also revealed that in these conditions, the participants

GRAPP 2016 - International Conference on Computer Graphics Theory and Applications

276

felt some frustration because of the difﬁculty to con-

trol the cart (DSouza, 2011). Thus, such interac-

tion techniques do not appear to be the most effec-

tive ones, especially for the elderly people or people

with motor impairments, however participants found

them more enjoyable than those with game-pad. In

addition, producing efforts to navigate and interact

with VEs may increase user’s sensation of immer-

sion (Herrewijn et al., 2013).

Time and distance travelled in a VE appear to be

the good data to assess users performance and the us-

ability of interaction techniques. Indeed, interaction

techniques are considered effective when the user can

build up a cognitive map with the acquisition of spa-

tial knowledge (Bowman and Wingrave, 2001). In

this context game-pad devices are the most effective

but need several trials to be used with optimum abili-

ties, whereas full body gestures interaction techniques

based on motion capture devices such as the Kinect

T M

are more easy to use for people unfamiliar in video

games. In addition, navigating using body gestures

made the task more enjoyable for the users.

Change the interaction techniques may be inter-

esting according the task or the difﬁculties encoun-

tered by the patient. For example, according the

mood of the patient, we may simplify the interac-

tion technique. Indeed, rehabilitation training could

be long and repetitive, so the interaction technique

with Kinect

T M

may permit to raise the patients moti-

vation when he/she is fed up with doing the same task

again. On another side, if the patient wants to see his

progress, an interaction technique based on game-pad

may be effective.

5 CONCLUSION AND

PERSPECTIVE

In the paper, we have presented a VE that simulates

an everyday task to assess cognitive impairments: go-

ing shopping at the supermarket. A user study has

been carried out to collect baseline control data us-

ing volunteer students from our school of engineers.

The task was to collect various items within the super-

market using a shopping cart. Four different interac-

tion techniques have been compared ranging from the

desktop paradigm to natural interaction techniques

based on full-body gestures. We observed that sub-

jects were more efﬁcient in terms of completion time

using a game-pad but enjoyed more the interaction

techniques based on full-body gestures. However, the

NASA TLX questionnaire revealed that these inter-

action techniques led to more fatigue and frustration.

As future work, we plan to evaluate users sensation

of presence associated with the different proposed in-

teraction techniques using questionnaires and physio-

logical responses.

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