Displays, input, touch

MobileHCI'18, September 3-6, Barcelona, Spain

PinchMove: Improved Accuracy of User Mobility for
Near-Field Navigation in Virtual Environments
Yun Suen Pai
Keio University Graduate
School of Media Design
Yokohama, Japanyspai1412@gmail.com

Zikun Chen
Keio University Graduate
School of Media Design
Yokohama, Japanzkzk.chen@gmail.com

Liwei ChanNational Chiao Tung
University
Hsinchu, Taiwan
liweichan@cs.nctu.edu.tw

Megumi Isogai
NTT Media Intelligence
Laboratories
Tokyo, Japan
isogai.megumi@lab.ntt.co.jp

Hideaki Kimata
NTT Media Intelligence
Laboratories
Tokyo, Japankimata.hideaki@lab.ntt.co.jp

Kai Kunze
Keio University Graduate
School of Media Design
Yokohama, Japan
kai.kunze@gmail.com

ABSTRACT

Navigation and mobility mechanics for virtual environments
aim to be realistic or fun, but rarely prioritize the accuracy of
movement. We propose PinchMove, a highly accurate navigation mechanic utilizing pinch gestures and manipulationof the viewport for confined environments that prefers accurate movement. We ran a pilot study to first determine thedegree of simulator sickness caused by this mechanic, and acomprehensive user study to evaluate its accuracy in a virtualenvironment. We found that utilizing an 80°tunneling effect at
a maximum speed of 15.18°per second was deemed suitablefor PinchMove in reducing motion sickness. We also found
our system to be at average, more accurate in enclosed virtualenvironments when compared to conventional methods. This
paper makes the following three contributions: 1) We proposea navigation solution in near-field virtual environments for accurate movement, 2)we determined the appropriate tunneling
effect for our method to minimize motion sickness, and 3) We
validated our proposed solution by comparing it with conventional navigation solutions in terms of accuracy of movement.
We also propose several use- case scenarios where accuracy
in movement is desirable and further discuss the effectivenessof PinchMove.

Figure 1. PinchMove being used bimanually, where the user’s translation and axis of rotation are about the hands to achieve accurate navigation virtually.

Author Keywords

Virtual environment; accurate navigation; pinch gesture;
simulator sickness; near-field
INTRODUCTION

In today’s virtual (VR) and augmented reality (AR) systems,
it is nearly impossible to create a perfect navigation mechanic
suited for all types of applications and scenarios. Large virtual environments may benefit from more instantaneous andquick navigation, whereas small confined spaces may preferto just use actual physical walking, depending on the hardware support. However, for spaces that are larger than that,yet still confined and requires accuracy, a suitable navigation
mechanic is still unknown. The currently preferred method for
VR, teleportation, works well in mitigating simulator sickness
and navigating the user in large virtual environments. However, it is not possible to perform accurate movements; whichis acceptable since it was never designed to achieve that in thefirst place. On the other hand, physically walking is arguably
still the best method, but requires a physical area as big as its
virtual counterpart, equipped with precise trackers. Therefore,
what is the best form of navigation for a room-spaced environ-

ACM Classification Keywords

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MobileHCI ’18, September 3-6, 2018, Barcelona, Spain.
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https://doi.org/10.1145/3229434.3229470

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ment, like an office, workshop, or lab, where the user requires
accurate control of his or her position for professional use or
simulation?

Navigation in Virtual Environments

Mobility in virtual environments is one of the most important
input, and arguably the most popular navigation mechanic for
VR today is teleportation, which causes an instant change inposition using a fade and blink animation [2]. A variation tothis is Dash, where instead of teleporting, the user moves athigh speed to the designated target location to provide a better
sense of movement. This variation in speed and transition
for teleportation could mean that a proper tweak in speed andtransition can improve the experience [16]. However, thesemethods of navigation do not allow fine-tuning of position.
For that, the user needs to walk to the desired position after
teleporting, adding to additional navigation time.

PinchMove aims to address this by using a pinch gesture to
grab a position in space and drag the user based on the change
in position of the user’s hand. This form of manipulation of
the viewpoint is accurate and allows the user to move in four
directions freely, as well as rotate depending on the angle of apinch. It is based on a discrete style of navigation as opposed
to controlling the rate of movement (joystick controls). Furthermore, it is also suitable for users who are in a confined
physical space, yet still, require accurate control of his or her
location in the virtual world since only arm movements are
required.

Other more immersive forms of navigation also exist, such as
those that require movements of legs and arms, akin to real
walking [30, 21]. However, the main issue with such methods
is that even though they take less physical space than actually
walking, they require the user to stand and perform gesturesthat can both be tiring and imprecise. Accuracy is further
sacrificed due to under and overshooting of position when theuser stops since the system needs to detect stopping.

However, the primary concern for any form of navigation isthe degree of simulator sickness it may cause. In our pilot
study, we performed a comparative study between three tunneling speeds; slow, medium and fast, which are based on thesmoothing time of the visual effect. We found that a medium
tunneling speed with a maximum of 15.18 degrees per second
was suitable for PinchMove, since it causes the least amountof nausea, oculomotor and disorientation. In our main user
study, we aim to determine the degree of accuracy our system
can achieve compared to more conventional methods. We
compared between conventional gamepad input, unimanual
pinch navigation, and bimanual pinch navigation based on
three levels of preset accuracy, 6 positions, and 3 orientations.
We found that on average, bimanual navigation performed thefastest for all three levels of accuracy.

One of the currently available solutions most related to our
proposed method is the grabbing locomotion, where the user
grabs the space in front of them to traverse. This can often
be seen in climbing VR games like Climbey[15] and The
Climb[5]. However, these games were made specifically forvertical navigation only and do not provide other means ofnavigation such as rotation.
Based on the related work, the factors to consider in an implemented navigation mechanic usually boils down to simulator
sickness, quickness, and sense of realism or immersion. However, one other factor less mentioned is the consideration for
accuracy, or how much degree of control a user can be given
to reposition himself or herself as accurately as possible.

We further discussed other contributing factors that may influence the proposed solution, such as optimal velocity, different
forms of gestures, as well as utilizing different hardware toachieve a similar result.
The following are the contributions of this work:
1. We developed a highly accurate navigation mechanic for
virtual environments that are suited for near-field navigation.

Simulator Sickness

Simulator sickness, cybersickness or motion sickness, areterms used particularly in VR environments to mean nausea
or dizziness, often caused by the ’sensory conflict theory’that refers to how our vision is augmented to receive motion
signals, yet our non-vestibular proprioceptive senses don’t,
resulting in a variance that causes said sickness [24, 10]. To
help curb this issue, there has been an established guideline for
VR development, such as how movement acceleration should
be linear and not too long, avoid rotation on the forward-axis,
avoid yaw-axis rotation, and avoid direct control of the main
camera view [17]. Among the current solutions are adding
a motion platform, performing direct vestibular stimulation,and implementing rest or static frames, of which only the last
option can be considered to avoid any third party peripherals
or custom sensors [14].

2. We ran a user study to determine the best tunneling parameters in reducing simulator sickness with the proposed
method.
3. We evaluated its accuracy compared to conventional navigation solutions in virtual environments and found thatbimanual input achieved the highest speed in achieving thedesired accuracy (6.849, p = 0.004<0.005).
RELATED WORK

Among the numerous available options for navigating in a
virtual environment, most of them cater to either avoiding
simulator sickness, being fast, being realistic, or all three atonce. These are important factors to consider, yet at the end of
the day, the best navigation method is highly dependent on theapplication itself. Furthermore, an additional dimension that
we wish to consider in this work is the accuracy of navigationor the ability given to the user to navigate to the desired point,
given moderately limited space.

Furthermore, over the years, VR researchers have begun implementing several visual tricks, one of them being ’grounding’,
where part of the foreground remains static [1]. Essentially,
it reduces the immersion level of the user through methods
like reducing the field-of-view (FOV) [9], or adding a static
visual frame for the user. This can greatly reduce the effects

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MobileHCI'18, September 3-6, Barcelona, Spainof visual update delays and simulator sickness compared to awider FOV [6]. Finding an optimum FOV can be tricky because reducing it can greatly effect the immersion and requires
the user to perform a bigger head and eye movement to viewcontent at the periphery [31].

Unlike the other previously mentioned related works, PinchMove is a software-based approach that uses the fine positioning of the user’s hand for the user’s self positioning. It
relies on intermittent hand translational movements and subtle orbital movement for rotation that takes into account the
space and the environment itself. It also uses very minimal
to no pinch-gesture memorization (depending on unimanualor bimanual). Even though the pinch gesture itself can besubstituted with other forms of gesture or even a button input,
we were motivated based on the mentioned related work thatpinching is the simplest input gesture for inducing self haptic feedback on the hand, making it possible to be used forgesture-only solutions.

However, it was also mentioned that a smaller FOV is more
acceptable for the smaller virtual environment compared tolarger ones. Fernandes et al. found that a FOV of 80°was
the limit of an acceptable FOV before it started to detract theexperience [9]. Among some of the other methods exploredby researchers are using an independent visual background(IVB) which is similar to Google Daydream’s implementationof a virtual meta world, though it was only proven to work indriving simulations at this point of time [8].

IMPLEMENTATION

Our system was implemented using the Oculus Rift CV1 with
the Touch controllers. The Touch controllers are 6-DOF input
controllers for each hands, with each buttons equipped witha capacitive sensor. However, any device with 6-DOF hand
tracking can be used, such as future peripherals for ARCore
and ARKit on mobile devices. For our implementation, theuser simply needs to rest the thumb on any of the face buttons
or the analog stick (since the capacitive sensors can sense thiswithout actually pressing any button), while pressing the index
trigger. This creates a pinch animation on the virtual hands aswell. We divided the implementation based on two methods;
unimanual and bimanual, depending on the user’s preference.

Pinch Gesture Devices and Inputs

Glove-based devices like the Z-Glove and DataGlove [33] thatuses ultrasonic positioning and magnetic positioning respectively were developed in the past to allow finger-based gesturerecognition. Even though these devices allow whole handinteraction [26], pinching between 2 fingers is the most minimal form of performing a gesture that provides proper haptic
feedback, when compared to other gestures like grasping or
grabbing, or bimanual gestures like clapping.
A two-handed navigation system was developed using the
PinchGlove where the relative vectors between the hands allows the user to determine the direction and pinching allows
navigation, whereas a different pinch gesture allows velocity
control [3]. Even though the technique was deemed flexible,
no proper studies were conducted, and since it controls the rateof movement as opposed to discrete positioning, it sufferedfrom accuracy. Furthermore, relying on various pinch gesturesusing multiple fingers may provide additional functions, yetat the same time make it less intuitive if the user needs tomemorize each function. FingARtips focuses on the pinch
between index and thumb for grabbing, pointing, and pressing
in an AR environment [4]. However, this work was meant for
urban design, and not physical movement of the user avatar
which presents new set of challenges like movement accuracy
and simulator sickness.

The pinch gesture works by "pinching" the viewport or any
point in space and dragging it towards yourself, creating an
inverted movement that causes the user to navigate to the direction the controller was previously. This inverted movement
is metaphorically referred to as Camera-in-hand or eyeball in
hand, which was deemed as a superior navigation mechanic[28, 32]. A similar example would be grabbing a rope andpulling it while sitting on a wheeled-office chair. Though not
the most popular navigation method for VR, a variation of thismethod can be seen in VR games like Climbey [15] and The
Climb [5], because it emulates the arm movements of actual
wall climbing. Grabbing a point and lifting up moves the user
upwards, akin to PinchMove. However, the games above differentiate in two factors; they allow only vertical movement,
and rotation is not possible.

Another previous work used pinch gestures to manipulate
computer-aided design (CAD) models using bimanual pinch
gestures [25]. GaFinC combined gaze with pinch gestures forselection and manipulation, with different pinch movements
resulting in translation and rotation of the 3D model. However,merely adopting object manipulation mechanics like GaFinC
into navigation presents an issue; object manipulation onlychanges the position and orientation of an object with reference to its center point as pivot, whereas for navigation, we
need to consider both the user’s position and orientation, as
well as the environmental cues for it to be natural and accurate.
If GaFinC was directly used for navigation, the desired final
position with respect to the environment cannot be achieved,
which is properly explained in the Unimanual Navigation subsection with reference to Figure 2 that shows the difference
between PinchMove and conventional methods (more similar
to GaFinC).

This particular form of navigation can potentially feel morenatural than using a gamepad because the distance traveled
and velocity of the arm gestures are directly reflected on theuser for accurate positioning. This is also relatable to how
we can move forward when grabbing and pulling an object ofhigher mass than us, or movements like crawling or climbing.
For example, to be really accurate, we won’t just say "I want tostand in front of a table", we say "I want to stand 10cm in frontof a table". Therefore, PinchMove leverages this by allowing
the user to place their hands on these environment references
and navigate based on them. For our implementation, wechoose to disable vertical movement or movement about they-axis since we are focusing on ground-based navigation forthis study, though it can easily be added depending on theapplication. Another feature that we chose to exclude forthe current implementation is speed control, thus catering

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PinchMove for near-field environments. This is because wewish to analyze it as its most basic form (one-to-one translation
and rotation) before adding additional features that may impact
its accuracy.
To allow the user to move forward by pinching the space, wefirst find the initial position of the controller the frame thetrigger is pressed and final position after the controller moves
to a new position. This difference in Euclidean space is added
to the user’s current position, allowing them to move front,
back, left and right depending on the controller’s movement
vector. Once the user has decided on the final position andreleased the trigger, movement is halted and their final position
becomes the new current position. Therefore, if a user places
their hand on a virtual object and pinches themselves towards
it, they will be standing directly in front of the object basedon the desired distance. Essentially, it is an implementation ofrotate, scale, and translate (RST) manipulation without scaling
for the user in fully immersive virtual space [13]. However,mirroring RST mechanics for rotation by rotating the user
about their upward axis will result in a position that is undesirable if the user wishes to move and face to a specific virtual
object. Therefore, the key innovation is in how the rotationis handled, which will be detailed further in the subsections
below.

Figure 2. An example of 90°rotation behavior where (A1) shows beforeand (A2) shows after for conventional rotation with pivot point about
the user, whereas (B1) shows before and (B2) shows after PinchMove
rotation with pivot point about the hand.

Unimanual Navigation

Unimanual navigation ensures that the user can fully control
his or her position in virtual space using a single Touch controller. This leaves the second hand to be free for other tasks.
However, care needs to be taken when mapping functions
for translation and rotation to avoid unintended navigation.
To emulate pinching, the index finger trigger allows the user
to perform pinch translation, whereas the middle finger trigger allows the user to rotate about the y-axis. Initially, we
experimented with using a single trigger button for both translation and rotation, but this resulted in an inaccurate movement
where the user keeps performing minor rotations during translation that was rather nauseous. The use of separate buttons forthe different function was to avoid any accidental activation.
We argue that users who use unimanual navigation are most
likely engaged in other activities at the same time, thus may
require navigation controls that are simpler and with minimal
memorization. The center of rotation is assigned to the controller held in hand instead of the user, where the user orbits
around the controller during rotation. This is the key difference compared to other works like RST [13] with central pivot
rotation; it is mathematically impossible to our knowledge toachieve this result using other pivotal points. We illustrate thisin Figure 2. In this figure, the user desires to stand directlyin front of the table, with the table being within arms reach(Figure 2(A1) and (B1)). The user then rests his/her handon the table’s edge as a reference and performs the rotation
gestures. The two main differences between Figure 2(A2) and2(B2) is the pivot point location and direction of rotation of
the hand (not the user).

the right to turn right. The resulting final orientation would
be the same with PinchMove, but the position of the user
would be undesirable. This is because the user simply rotates
about his/her center point, causing him/her to turn right (thearm positions in space changes since it is always in frontof the user) but not reposition correctly at the same time.
This method of rotation is adopted in RST, which is perfectly
suitable for object manipulation.
However, in navigation where the user wishes to reach thedesired position, he/she needs to orbit around the point of rotation using the opposite gesture direction (inverted direction aspreviously mentioned, since the viewport is being manipulated
instead) that is outside of the user. PinchMove leverages theuser’s hand position or controller to achieve this as shown in
Figure 2(B2), making the hand position in space static but
the user’s body position changes with reference to the hand’srotation. The resulting orbital movement means that rotation
has combined with translation, similar to Hovercam [12] andShocam [19] which were intended for desktop use. The user
can actually choose to only translate, or orbit (translate androtate), to a desired position. Orbital-like movements in VR
has been explored before and has been used as a primary navigation mechanic [20], though this work relies on head rotationand eye tracking. Furthermore, our applied orbital movement
mechanic is more subtle since the controller is never too far
away from the user. This subtleness provides the illusion thatthe user is rotating conventionally, i.e. about themselves, butwith a higher degree of accuracy of self-placement in the virtual space. A large orbital movement resulting from further
pivot points will be disorienting unless made for a specificpurpose like AnyOrbit [20]. The angle of rotation is basedon the hand controller orientation about the y-axis. When

Figure 2(A2) shows the conventional method adapted directlyfrom the RST method with the pivot point being the centerof the user and the rotation gesture being rotating the wrist to

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MobileHCI'18, September 3-6, Barcelona, Spainthe controller is rotated, it is as though the viewport rotatesalong with it, though in actuality the user has successfully rotated about the controller. Therefore, if the user performs thismovement when placing the controller on a virtual object asshown in Figure 2 facing another direction, they will be able toreposition themselves in front of it at any desired orientation.
The resulting implementation makes translation and rotation
feel extremely natural.

Figure 3. Environment for the pilot study. The left image is the top view
with all waypoints position shown, whereas the right image shows theparticipant’s view during the study.

Bimanual Navigation
USER STUDY

Bimanual navigation allows the user to navigate either withthe left controller, right controller, or both at the same time.
Either left or right translation would behave no different fromunimanual navigation. However, for bimanual, we take theaverage position of both controllers as a reference for movement. If one controller travels further than the other, thenrotation is triggered, where the user rotates about the reference
object. Therefore, if the user performs this movement whenplacing both controllers on a virtual object, they will be able
to reposition themselves accurately based on the movementsof both of their hands.

The user study is divided into a pilot study that focuses ondetermining the right parameter for tunneling to minimize
motion sickness and the main study that focuses on evaluating
the accuracy of positioning and orientation. We chose to
use the Oculus Rift CV1 with the Oculus Touch controllers
due to its more ergonomic and natural controller shape forpinching, though our implementation has been tested with the
HTC Vive as well. The reason we employed the pilot study
was to reduce the possibility of motion sickness as much as
possible before conducting the main study, so that it does not
significantly effect the accuracy of PinchMove. Furthermore,
we also believe that understanding motion sickness is always
important for studies on navigation in virtual environments.

The implemented bimanual controls are for users to use both
hands as reference positions during navigation. We argue thatusers of bimanual navigation wish to focus purely on accurate
navigation. Therefore we choose to mirror the controls forboth hands and use the same button input for both translation
and rotation to minimize memorization of functions. Furthermore, assigning rotation to another trigger button is excessive,
since the user already has access to a set of index trigger buttons on both hands anyway. Naturally, enabling PinchMove
for both hands removes the ability of the user to use a free
hand for another task. However, we wish to evaluate the performance comparison of these two methods and determine theusers’ preference with regards to accuracy.

Pilot Study

For this study, the goal is to determine if the proposed navigation method causes a significant amount of simulator sickness
depending on the speed of the tunneling effect. Although there
exist several methods to mitigate sickness in VR, we chosethe conventional tunneling effect of limiting the FOV of theuser as it has been proven time and again to be effective [9].
Fernandes et, al. found that in a pilot study, a FOV of 90°is
deemed to be the preferred minimum FOV whereas 80°is thelargest FOV to detract from the experience.
Therefore, we choose to use a FOV of 80°so that it would
not further detract the experience. Furthermore, a subtle andslow decrease in the FOV restrictor even causes some of theparticipants to not notice the change in FOV. However, a majordifference between that study and ours is that the study was
designed for the participants to navigate a huge virtual space,
whereas PinchMove was designed for a more confined area.
Secondly, pinching the viewport results in a more discrete
style of navigation as opposed to regular navigation that iscontinuous and works by controlling the movement rate. The
tunneling effect only appears when the user is moving in theenvironment and slowly dissipates when the user is static.
Therefore, the tunneling effect would appear at a slower rate
as opposed to the conventional method, since releasing thepinch gesture dissipates the tunneling.

Tunneling

To ensure that simulator sickness is minimized, we employ
the tunneling method for PinchMove. Tunneling is enabledthrough the vignetting and chromatic aberration visual effectattached to the main camera in the scene. A vignetting intensity of 0 creates a maximum FOV for the user, in this case,
110°which is the FOV of the Oculus CV1 headset. When thevignetting intensity is increased to 1, the screen is completely
blacked out, equaling to a FOV of 0°. The two importanttunneling parameters are therefore the intensity as well as therate of which the tunneling effect appears, as discussed by
Fernandes et, al[9].
In this work, it was determined that an 80°FOV was the minimum allowable FOV before it starts to detract from the experience. Even though the rate of tunneling was also determined, movement in PinchMove is largely different than regular gamepad input where the rate of movement is controlled,
whereas PinchMove is more discrete. Therefore, a pilot study
was designed to determine the appropriate maximum speed
for tunneling and will be further explained in the following
section.

We recruited a total of 8 participants for the pilot study. To
determine the appropriate tunneling rate and sickness, we designed an office-like environment where the user is required
to navigate using PinchMove for two minutes. We also predefined three levels of tunneling speed, slow (maximum of
10.15 degree per second), medium (maximum 15.18 degree
per second) and fast (maximum of 30.08 degrees per second)

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Figure 5. Parameters in defining the accuracy of translation and rotation. α is the angle between the user cube and target cube, d is the
distance between the center points of the user cube and target cube,
whereas s is the distance between the center point of the target cubewith its corner

Figure 4. Flow Chart for the designed user study

by altering the tunneling smoothing time from 110°to 80°. To
reduce ordering effect, we employed a Latin Square order forcounterbalancing (though since we have 8 participants with 3
conditions, the last order was eliminated, but we neverthelessdeem it acceptable for a preliminary study).At the beginningand end of each session, each participant is required to answer
the Simulator Sickness Questionnaire (SSQ) to estimate current nausea, oculomotor, disorientation, total sickness score,
and total rise in sickness that is being felt [11].

with an orange face to depict the front of the cube), illustrated
in Figure 6.
To determine the possible predefined locations, we consider
the FOV (3 angles) and distance from the user (2 distances) todetermine 6 possible positions. We use FOV to ensure that thetarget cube is always visible to the participant at the beginningof each trial, and we select distances according to the standard
arm length for near-field interactions. There is a possibilityof 3 orientations per position (-45°, 0°, and 45°). We also fix
three accuracy levels for the user for each trial (98%, 96%
and 94%) for the position and orientation, which can be seen
on Figure 5. For the position accuracy, an accuracy of 100%means that the center point of the user object is exactly at thecenter point of the target object, or when d = 0. 0% accuracy
is the furthest possible distance between the two center points
when they are in in contact, which is also equivalent to the
distance between the center point and the middle point of theedge of the target cube ( when d > s). The predefined valuesof 98%, 96% and 94% were determined from initial testing;our test participants found that an accuracy level of 100% was
nearly impossible, whereas it becomes relatively easy at 92%.
Therefore, to keep even spacing between the accuracy levels,
we decided to chose the aforementioned values.

During the study, the participant is required to navigate
through white capsule waypoints that appear one at a timein a confined office space which is placed in a way that forcesthem to translate and rotate the viewpoint, similar to the experiment by Fernandes et, al. as shown in Figure 3. At theend of each session, each participant is also required to answer another set of questionnaires designed by Suma et, al.
to determine if the change in FOV was noticeable or not [27].
Participants were asked to rate the following questions from ascale of 1 to 7, where 1 means "I did not notice anything" and7 means "I obviously noticed it."
1. I saw the virtual environment get smaller or larger.
2. I saw the virtual environment flicker.
3. I saw the virtual environment get brighter or dimmer.
4. I saw that something in the virtual environment had changedsize.

For the orientation accuracy, an accuracy of 100% means thatthe angle between the user object and target object, α, is 0°.
0% accuracy is the largest possible angle deviation between
the two objects. Since we measure the acute angle as thedifference in orientation, 90°is deemed 0% for orientation
accuracy (when α > 90). Finally, each trial is repeated threetimes. The three input methods are described below:

5. I felt like my field of view was changing in size.
6. I felt like I was getting bigger or smaller.
7. I saw that something in the virtual environment had changedsize.

• GamePad: A conventional navigation mechanic utilizing
the thumbsticks on the gamepad to move and rotate. This
input method serves as the standard baseline of comparison.

Experiment Design

To determine the accuracy of navigation, we designed a virtualenvironment for the participant to navigate using PinchMovethat is inspired by the RST user study [13]. The flow of thestudy is illustrated in Figure 4. To determine the accuracyof movement, each participant is required to complete a task
where the time required to complete each trial is recorded.
The task requires the user to align a user object with a target
object. The user object is a cube placed in front of the userthat follows the user’s translation and rotation (blue cube).
The target cube is a cube placed in the virtual environment at
a predefined position and orientation (semi-transparent cube

• Unimanual: In addition to navigation with the index trigger,
the middle finger trigger is used to enable rotation. The
participant will be seated on a leg chair for this scenario.
• Bimanual: Both controllers are required to rotate the participant by the relative angle between them, without any
additional button. The participant will be seated on a leg
chair for this scenario.

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Figure 7. The participant’s view of the study and a top-down view of theenvironment. The target cube can be seen at Position 0

Figure 6. The positions of the target cube (only 1 can be seen at a giventime) for the user study with 3 possible orientations.

Only one target cube will appear at a given time, and the next
cube will only appear once the participant successfully completes that trial. Correct alignment of the cubes are detected
automatically by the system. Once the participant completes
the trial, there will be a one second delay before the next cube
appears for them to know what the next difficult level andinput method is for the upcoming trial. The total amount of
trials per participant is 6(positions) x 3(orientation) x 3(inputs)
x 3(accuracy) = 162 trials per participant. In this study, theindependent variables are the input methods, accuracy, position and orientation of the cube. The dependent variable is thetime required to complete the trial. Figure 7 shows the viewof the participant during the user study.

Figure 8. SSQ results by comparing between three tunneling speeds

tunneling speed scores overall causes less sickness as well.
The data were analyzed using repeated-measures ANOVA.
The repeated measures ANOVA reveals that there is no difference found on increase score between the treatments (F2,14 =
1.57; p = 0.243). Interestingly, a faster tunneling speed scoredlower than slow tunneling speed in all these categories except
for the average increase of total sickness. For the noticibility
questionnaire, the only relevant questions were the third andfifth questions which are related to the change in FOV. According to Figure 9, participants were much quicker to realize thatthe environment seemed darker at the fastest tunneling speed
whereas the slow and medium speed were about equally slow
to realize. However, most participants realize the change in
FOV at the medium speed, followed by fast, and finally slow.

Prior to the study, the participants are allowed to familiarize themselves with the navigation mechanic for 5 minutes.
During this period, we also perform a quick calibration foreach user to collect the speed of movement during PinchMove.
We then modify the gamepad input speed to be equal to theaverage speed of PinchMove for each participant. This is because the speed of navigation for PinchMove purely depends
on the speed of arm movement for each participant, whereas
the speed of movement for the gamepad needs to be predetermined. Therefore, to ensure fair comparison, the gamepad
movement speed is calibrated to be on average, equal to thepinchMove speed for each participant. We recruited a totalof 19 participants (10 male, 9 female) aged between 22 to 34
years (mean: 25.63, SD: 2.81). At the end of the study, eachparticipant finally answers a Likert-scale questionnaire from arating of 1 to 5 for perceived accuracy, efficiency, reliability,
learnability and likability for each navigation method [29].

For the main user study, the results were analyzed using
ANOVA repeated measures where we evaluated the accuracyof each input method based on completion time of the predefined accuracy. Figure 10 shows the estimated marginal means
for the gamepad, unimanual, and bimanual interfaces for theaccuracy of 94%, 96% and 98%. All post-hoc comparisons
used Bonferroni corrected confidence intervals. There was asignificant main effect of accuracy (F2,36 = 7.250; p = 0.002< 0.005) and pairwise tests show that users were significantly
faster with an accuracy of 94% compared to 98% (6.326 vs.
8.329, p = 0.002 < 0.005). There was also a significant main
effect of interface (F2,36 = 3.41; p = 0.002 < 0.005). Pairwise
test found that bimanual input was faster than unimanual input(6.849 vs. 8.183, p = 0.004 < 0.005). However, there was no

RESULTSFor the pilot study, Figure 8 show that a medium tunnelingspeed overall caused the least rise in motion sickness with ascore of 10.285 compared to a higher tunneling speed witha rising score of 17.3 and a slower tunneling speed with arising score of 24.78. Looking at the average score for nausea,
oculomotor, disorientation and overall total score, the medium

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Figure 9. Noticibility Score for the three tunneling speeds

Figure 11. Qualitative results of three input methods

is a significant difference between gamepad and bimanual (p <0.05), and between unimanual and bimanual (p < 0.05). Thereis no significant difference for reliability (F2,36 = 2.520; p =0.095).
DISCUSSION

Based on the quantitative results from the main study, it was
found that at 98% accuracy, gamepad still performed slightly,
though not significantly better, than both unimanual and bimanual, with unimanual being overall the least accurate methodof navigation. as the accuracy requirement drops slowly to
96% and finally 94%, bimanual scores the fastest time forthe completion of the task. In average for all three levels of
accuracy, bimanual ends up as the best performer, followed
by gamepad and finally unimanual. Furthermore, for ourqualitative questionnaire, it can be seen that bimanual was
significantly preferred in terms of efficiency and likability,
and scoring almost the same for accuracy and reliability with
gamepad. It only score significantly lesser for learnability due
to it being a newly developed method.
For the main study, we asked the participants their general experience in VR, informally rank their preferred input methods
from best to worst, overall comment on the user study, as wellas suggestions for scenarios that can benefit PinchMove. Outof the 19 participants, 14 preferred PinchMove over conventional gamepad, and 12 from them preferred bimanual input
over unimanual. The 5 participants who preferred gamepad
mainly said that it was simply due to it being more conventional and common, leading to lesser time to master since theoperation does not need to be understood. PinchMove also
lead to fatigue of the arm since each user was required to keep
up with the pinch and pull motion. Finally, another common
feedback is that since PinchMove relies on pulling as opposed
to gamepad which is more akin to pushing, the inverted controls presented some difficulties for these participants, similar
to scrolling on a touchscreen where scrolling upwards withthe finger causes the screen to scroll downwards instead.

Figure 10. Estimated Marginal Mean of three input methods according
to accuracy.

significant difference between gamepad and bimanual, as well
as gamepad with unimanual.
For the final qualitative questionnaire, Figure 11 shows thatbimanual was at average, generally perceived to be the mostaccurate, efficient, and likable. Gamepad input was slightly,
but not significantly, higher than bimanual in terms of reliability, but is noticeably higher in terms of learnability. For
perceived accuracy, bimanual was slightly, though not significantly higher than gamepad, with the unimanual method
being the least accurate. Significant differences were foundin accuracy, efficiency, likability, and learnablity, but not in
reliability. For accuracy (F2,36 = 5.16; p < 0.05), significanceexist between gamepad and unimanual (p < 0.05) as well as
unimanual and bimanual (p < 0.05). For efficiency (F2,36 =
9.38; p < 0.001), significance can be seen between gamepad
and bimanual (p < 0.05), and between unimanual and bimanual (p < 0.05). For likability (F2,36 = 4.0; p < 0.05), there is asignificant difference between unimanual and bimanual (p <0.05). Finally, for learnability (F2,36 = 7.317; p < 0.005), there

The users who prefer PinchMove navigation presented someinteresting related scenarios. One participant mentioned that,a gamepad was similar to sitting in a car and moving forwards,
whereas PinchMove is more like grabbing the road and pullingit to move forward. Furthermore, PinchMove allows finecontrol of movement speed, where the user moves as fast as

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MobileHCI'18, September 3-6, Barcelona, Spaintheir hand, as opposed to gamepad with a predefined maximum
speed. Compared to the conventional gamepad, PinchMove
was overall more enjoyable to use.

it is overall less tiring to use as mentioned by the participants,
which is why for this point of time, we specifically state that
PinchMove is limited to near-field navigation so users do notneed to navigate too far or for a long period of time.

Bimanual was overall preferred because it provided a better
spatial sense during movement, and using both hands for positioning overall feels easier and more intuitive. A common
negative feedback for bimanual navigation is that since only
the index trigger was used, participants who moved too fastcaused accidental rotation, since they press the second controller trigger before releasing the first one for a split second.
However, some participants also mentioned that since only asingle trigger button was used for both controllers, no memorization was needed and it was easier to master. One of theparticipants who was experienced in VR, even used strategies
for bimanual navigation for maximum speed, such as using acircular, pedaling motion between hands for quick movement,
and orbiting one controller around another for quick rotation.

SUGGESTED SCENARIOSAs previously mentioned, PinchMove was designed for specific scenarios that are near-field and prioritizes accuracy. Thissection will discuss some of the possible application scenarios
where PinchMove may prove beneficial, given the context, as
well as some of the scenarios suggested by the participants.
For a more general use, we look at PinchMove as a possible direction for a definitive form of navigation for AR/VR.
Seeing as motion controllers have become the definitive input mechanic for AR/VR. Teleportation has also become amethod for far navigation that is an easy and motion-sickness
free method of navigation. However, for fine tuning position, we need to physically walk towards where we desire. If
the user lacks the necessary space or is seated, they would
need to stand, or reposition themselves with the teleportation
mechanic. PinchMove can possibly be the solution for thisfine-tuning of position.

The 2 participants who preferred unimanual navigation agreed
that it was overall more intuitive after the learning phase. However, it heavily depends on the scenario as well, since the onehand option was provided so that the user is free to use another
hand for other use anyway. They also mentioned that sincetranslation and rotation was mapped to different buttons, nounintended movement can occur. For PinchMove, participants
overall prefer bimanual over unimanual because they claimthat unimanual rotation felt inverted, even though rotation forboth methods actually rotate at the same direction.

For accuracy-based applications, we looked into professional
scenarios where AR/VR is used for simulation, training, ora tool. A possible application is in architecture and productdesign. In these fields, careful dimensioning of buildings
and objects is vital. Since PinchMove navigates based on
movement distance of the arms, this allows users to take advantage of proprioceptive sensing for precise near-field locomotion. Therefore, we believe PinchMove provides a accurate
measurement-based locomotion that can be coupled with thework in architecture, computer-aided design modeling, andsculpting.

In terms of motion sickness, more participants claim to havefelt more motion sick using gamepad, followed by one-hand,and finally bimanual. A participant claimed that pulling navigation overall presented less motion sickness compared topushing navigation. It is a common design rule in VR to avoid
mapping rotation externally as this can cause heavy sickness,more so than translation [7, 18, 23]. Even though all input
methods implement this, sickness was less for PinchMove
since the rotation provided the participants with a sensationthat they were rotating the world around them instead. Becauseof this, a participant even claimed that mastering PinchMove
in return caused him or her to be more motion sick when using
conventional gamepad.

The previously suggested applications are catered towards 3Dmodeling, though we also see PinchMove as a useful toolfor 2D interface design in VR as well. For example, userinterface (UI) designers for mobile application or web pages
can now possibly utilize VR to produce accurate design andnavigate between several screens, as well as understand thespaces between each of their designs through navigation.

Overall, we showed the feasibility of PinchMove as an accurate navigation mechanic for virtual environments, with its performance being overall slightly better than a regular gamepad.
We find these results to be acceptable for our first implementation of PinchMove, since gamepad is an input method that has
been available for a long time for use of navigation in virtualenvironments. However, we would argue for its superiority
over a gamepad for several reasons. Firstly, PinchMove is a
gesture-based input which is arguably more natural for interactions in AR/VR space as opposed to gamepad (based on theparticipants feedback on it feeling easier and intuitive with abetter spatial sense). Secondly, we believe that with further
fine tuning with feedback gathered from the participants inthis study, it is highly possible for PinchMove’s performanceto perform much better than a gamepad (such as increasing
learning time). It is worth mentioning though, that with theuse of a gamepad versus a gesture based input like PinchMove,

Another very relatable scenario is using PinchMove as a accurate navigating for simulation of space astronauts. Althoughseveral space exploration VR games utilize grab-and-pull mechanics to simulate zero gravity navigation [22], they don’tallow the player to pivot around a grabbed object like PinchMove, nor provide the option for unimanual or bimanual navigation. Therefore, we believe PinchMove is a more accurate
use for this scenario, not just in games, but for real simulationsof astronaut navigation.
CONCLUSION AND FUTURE WORKS

We presented a novel navigation mechanic for virtual environments that allows manipulation of the viewport for near-field,
accurate movement. Even though this paper presented a study
on PinchMove using a VR environment, it can also easily
be adopted into an AR environment for navigation, as longas proper 6DOF tracking is provided. This means that this

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work is also supported by recent mixed reality hardware withinside-out tracking like Windows Mixed Reality and Hololens.
We will also investigate different methods of interaction tocompare with pinching, such as grasping and grabbing to determine the difference in perceived comfort and intuitiveness.
Furthermore, we would like to investigate why some participants claim unimanual navigation to be more intuitive or feels
inverted.

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