Hello my name is Suhan Park from Korea University.
Our work is about reducing VR sickness by adding in
optical flow information that is reverse to the visual motion of the VR content
so that the perception of visual motion can be reduced
and so the sensory mismatch with the vestibular sense.
Simulator or VR sickness is a major problem in people adopting VR
and using it for an extended period of time.
It is caused by the sensory mismatch between the visual and vestibular sense.
That is, while the human visual system thinks the environment is apparently moving,
the user is actually stationary as detected by the vestimbular sense.
The conflicting signal between the two will cause various
sickness symptoms such as nausea, disorientation and headaches.
there have been some conventional methods to battle VR sickness.
these methods try to reduce the sensory mismatch
by limiting the visual motion or limiting the visual stimulation
For example, by reducing the FOV or blurring the peripheral visual field
It is also possible to try to modulate the vesibular sense
for example, by making partial limb motion,
or direclty stimulating the vestibular organ
We propose to add in motion information in the opposite direction of
the virtual navigation using the optical flow.
Since visual motion is percieved physiologically through
the direction of optical flow of elements in the scene,
We think that adding in artificial optical flow
in the reverse direction of the forward motion
can cancel out this perception at least physiologically
this will in turn ideally zero out the visual motion
as well as the sensory conflict with the vestibular
The figure shows in the left, the actuall flow seen in red
and the right, the reverse flow is added in explicity
So how do we visualize this reverse flow?
we propose that every short time intervals,
we extract visual features and over the next several frames
compute the reverse flow by switching the before and after time parameter
and add in the trail starting at the fixed locations of the extracted features
Note that the features are only extracted once at the
start of the time window and their locations fixed.
The result is illustrated below.
the feature extracted at the start of the window is the left most orange one
then as it moves, the reverse flow is computed
but added in starting at the fixed location of the feature
This is the overall system which operates on-line
the rendered image frame of the given content
is preprocessed to be down sampled and converted to grey level image
then the algorithm is applied
line segments drawn and overlayed on the image frame
Let's see the video even though this is small FOV desktop video,
perhaps one might be able to appreciate the sickness reduction effect
We ran valiation experiments to
see if the proposed method is effect at all, which
was the most important question in this work.
we also had the factor by the motion type to
see it relationship to the effect of the method
we also tried to re affirm our results for the usual VR navigation contents
so we conducted a similar expeiment for rolloercoastrer, ship ride and car race situations
dependent variables were of course
sickness level, user experience like presence/immersion
we also collected other data like self reported
level of sickenss and motion profile data
Here are the main results
in both experiments, you see the sickness was significantly reduced
in most sickness categories for all types of motion or content type
on the other hand presnece/immersion or UX was
lowered significantly in the first experiment
but not so in the second experiment
because the mixed-in reverse flow blended in better in the content
Note that in the first experiment with space exploration content
the white reverese flow line segments were much more distinct and eye catching
Here are some discussion points from our research
first Note that the Sickness is reduced but not entirely
Reverse flow visualization is only partial
that is it is not for all visual features
this is due to limitation that not all features are extracted or used
The proposed method was not so effective for the “Ship Ride” content
Reverse flow with respect to the ocean was not sufficient
because not enough visual features were extracted from ocean
Finally Mixing in reverse flow is still somewhat invasive to original content
this problem has to be addressed in the future
In conlcusion,
We propsoed to mix in reverse optical flow
to original navigational content with vection
and showed that it significantly reduced VR sickness
To further reduce or eliminate sickness,
We plan to consider using actual motion flow vs. predicted optical flow,
and combine our method with others
For practical application,
we also will consider pseudo reverse flow from camera motion,
adaptively apply the method consider different visualization methods
Thank you for your attention.