- [Sam] So hi my name is Sam Tregillus,
and I'm at the University of Nevada Reno
I work with Professor Eelke Folmer,
and I'm presenting our work called
"VR-step: Walking-in-Place using Inertial Sensing
for Hands Free Navigation in Mobile VR Environments"
And that is me walking up there kinda awkwardly,
so you can kinda see as we go.
So really quick, if you're not familiar
with Google Cardboard, or mobile VR in general,
it's basically a box that turns your phone
into virtual reality, it lets you
use your phone for virtual reality.
And with close to like 2 billion smartphones in the world,
mobile VR solutions like Google Cardboard
have the potential to bring VR to the masses.
And with well over 5 million Google Cardboard units shipped,
people are already experiencing a ton
of really immersive VR experiences.
But a major challenge for VR developers right now
is that input options are pretty limited.
You basically, since the phone
is inside the adapter here, you can see
that you can't actually touch the touchscreen at all,
so touchscreen input is out of the window,
and input is kinda limited to
head-tracking and single-button input.
So kind of as a result, most of the mobile VR applications
are just basically simple roller coasters,
or kinda "look-and-see" applications.
You basically aren't free to like
explore these kind of exciting virtual worlds.
You're just sorta being guided through them.
And so, to that end,
some people have been trying to find
some different ways of solving this problem.
And so, given the limited input options,
there's a few techniques that people have tried
to enable basic navigation.
So traditional input like a joystick does work,
but typically with the Google Cardboard,
you are holding the cardboard and a joystick
at the same time, and it's kinda difficult to do that.
And kinda joystick input is
not really similar to real movement.
It's not very immersive.
So there's also some people have
tried an autowalk technique.
This is kind of in the Tuscany Demo.
And essentially you move by looking down at your feet
to start an autowalk technique.
You'll move forward in the direction of your gaze,
and then you look down again to stop.
And this works pretty well.
Also another technique that people have tried
are kind of a beacon-based movement,
where you basically focus your gaze
on a beacon for a number of seconds,
and then you'll move to that beacon.
So these are all obviously they work,
but they're kinda far from immersive.
When you have to look down to activate a button,
you are pulling yourself out of the current environment,
and you're forcing yourself to look somewhere else.
And the beacon-based approach
kinda severely limits where you can actually go.
You don't have the freedom to move around
in your environment at all, it's all, you just have to go
wherever the beacons have been generated.
So we kinda asked the question:
What type of input is kinda the most natural
and immersive for virtual navigation,
specifically in mobile VR?
And kind of a cool video that
I really like to kinda show this.
This is a video where a bunch of kids
are given a Google Cardboard.
And you'll kinda see what they do.
(video plays)
You can see them. They're trying to jump,
they're trying to walk around,
they're trying to, they want to move in VR
and that's kinda their first idea.
So we kinda thought walking and running
is probably the most natural form of input.
But right now this input just didn't exist on mobile VR.
There's no way of actually doing this.
So we kinda thought,
there are existing systems that let you walk,
like in HTC Vives, the positional tracking.
And other walking-in-place implementations have been done.
But current solutions all kind of
require external instrumentation.
So we kinda thought:
why not just use the smartphone's inertial sensors?
Because that way you don't have to have
any external implementation.
So we created basically using some previous work
where we kind of evaluated different
step detection methods on Google Glass.
We also developed
a realtime step detection algorithm for mobile VR.
And you can see kinda here me walking,
I'm walking to move around in the virtual environment.
And our implementation is called VR-step.
So essentially we detect steps in realtime
using a very low overhead algorithm.
Kinda the low overhead is pretty important to us
because you're already on a smartphone
trying to render two 3D images at 60 frames a second,
you already have very little time to do each step.
So even the smallest computational overhead
can be a problem.
So after we've detected steps,
we basically translate those steps
into virtual locomotion.
And to determine the user's velocity,
we kinda measure the time between steps -
a larger time between steps
would kinda indicate that they're walking slowly,
so you would move more slowly.
And if you walk more quickly,
like smaller time between steps,
you get a faster movement.
So you kinda have a dynamic control of your velocity.
We conducted a user study to evaluate our approach.
And because other studies have kind of already evaluated
walking in place compared to joystick input,
we kinda were focused on other hands-free input techniques.
So we used the Autowalk technique that we mentioned earlier,
and kinda did a comparison with these two methods.
We had 18 subjects, and we recorded
their performance in our task,
and we asked for their qualitative feedback.
So this is the task that we asked them to do.
On the left VR-step is shown,
and the other one is Autowalk.
And you can kinda see that their goal
is to get in that blue column.
And in about half of the cases,
they had to run around an obstacle,
kind of for a different trajectory.
And so essentially we were hoping that
our technique was just as effective
in terms of performance as the Autowalk technique,
and we thought that we would probably
see more immersion with our technique.
So we didn't really find any significant differences between
task navigation methods for distance and time.
So essentially we found what we wanted to.
Our method was just as good as this other method.
And I do want to mention that
we did see a small difference in time -
it took a little bit longer with our VR-step thing
when there are obstacles present.
OK and then here's a quick qualitative response.
We asked users to rate each method.
And you can kinda see for efficiency or reliability,
they actually preferred the Autowalk technique,
but in reality their results kind of
there were no differences in
their actual efficiency in the task.
But most people preferred VR-step
for learnability and immersion
because they felt that it was more immersive.
So for our future work, we kinda want to
investigate different types of motion gestures,
maybe jumping and stomps and nods,
and kind of different ways of
augmenting the experience with that.
Maybe we want to try and evaluate
some VR exercise games.
I think it would be really fun to
run around in a virtual environment for exercise.
Right now, all of the movement
is kind of in the direction of your gaze.
So wherever you're looking you'll move.
But we also kind of have been thinking about
basically using your head kind of like a joystick,
so you can maybe tilt your head in a direction,
actually change the direction that you're moving,
kind of just like you would
be able to do with a normal joystick.
Also things like Roomscale in the HTC Vive,
have positional tracking.
But that also is very limited
to a small area - you can only move around
in your small area.
So we kinda wanted to investigate
kind of a combination approach,
where you use the positional tracking
to do small adjustments, and our VR-step thing
for doing larger movements in the world.
And also there have been indications,
and as the Roberts have mentioned,
the simulation sickness is definitely a problem.
And we think that our technique would
reduce simulation sickness because of the fact
that you're actually generating proprioceptive feedback
by bouncing your head as you walk.
So we're hoping to kind of evaluate that a little bit more.
Other studies have kind of suggested
that that's what we'll find.
So overall, this will allow you
to build more immersive experiences,
it doesn't require any extra instrumentation,
it's a little bit more immersive
and it's definitely intuitive and easy to learn.
And if you don't believe me, you can actually try our app.
And also, we'll be presenting this in the morning
for the student game competition.
But this is available for free online.
If you have a Google Cardboard, you can try it out.
And also we're offering it as a Unity plugin
on the Unity Asset Store.
Does anyone have any questions?
(applause)