The paper I am presenting is titled effect of a constant
camera rotation on the visibility of Trans-,
Sacadic camera,
shifts gaze based interaction in VR,
has been advancing rapidly in the recent years and it's an important
and popular concept.
It's been used in many different fields such as commercial products
gaming,
and also educational Fields.
Eye movements in VR,
can reveal interesting information about a user. Fixations
can be indicative of areas and objects of interest when
we are exploring or interacting with an environment.
Also,
Saccades which are rapid conjugate.
Eye movements have been
used in VR,
Saccades direct the fovea to a new area of interest during
saccades eyes gather information,
but no Sharp Images are obtained.
And so,
the world image is smeared across the retina,
but we do not normally see these smreared images.
Therefore,
we have reduced visual Acuity and sensitivity to motion
during saccades which is known as saccadic suppression.
So cutting suppression has been applied and
in different studies and applications.
If the normally perceptible graphical changes
that are applied to the images of the display during a saccadic
eye movement,
then there is a good possibility,
they can be hidden from the user.
Another study has shown that Saccadic
suppression can be used to reduce sensitivity to
the latency of gaze contingent rendering in virtual
reality,
it has also been used in redirected walking in VR.
Redirected,
walking is a technique for Locomotion.
That allows users to move in a virtual environment that is much
larger than the physical space.
Second expression is a way of making orientation adjustments,
and also allows users to subliminally navigate and
reorient in a VR despite a limited physical space.
Also,
a lot of works that explore playing suppression in VR.
The motivation behind this work was to find out whether
an ongoing camera motion,
which simulates a head rotation in a scene,
has any effect on how the users perceive the transsaccadic
image Transformations.
The stimuli we used consisted of 3D we virtual virtual
environments,
and we use Unity 3D and C.
Sharp scripting to create them.
We used a Windows 7,
desktop with a 27 inch Samsung LCD,
the eye tracker that we used was an ilink 1000 in the
desktop mounted.
At a fixed viewing distance of 55 centimeters from the display
here in the top figures,
we can see the trial,
the trial stimulating at 12 degrees,
horizontal saccade,
the participants were requested to move their eyes to the lamp post,
on the right side of the scene,
when the left one was turned off.
And the right one was turned on this,
resulted them in producing a 12 degree,
horizontal saccade during these,
saccadic camera shift was applied to the whole scene,
participants would guess the direction of the camera shift after the
trial in a Two alternative forced Choice.
Task the figures at the bottom show,
trial stimulating at 12 degrees vertical saccade.
Ee conducted our experiment.
In three groups in group 1,
we had a continuous camera panning from left to right in all
our trials with a rotation speed of 0.04
degrees per frame.
We conducted in two sessions of horizontal and vertical saccades
with 12.
Participants in group 2,
we had a continuous camera tilt which was from
top to bottom with the same rotation speed as group.
One again,
with two sessions of horizontal and vertical,
saccades
12,
participants.
And in group 3,
we had static scenes where there was no continuous
Motion in the scenes and we had two sessions of horizontal
and vertical saccades with another group of 12.
Participants.
During participants saccade
we applied a camera transition to the whole scene.
The direction of Transsaccadic camera shifts were translations
in right or left up or down forward
or backward and rotations,
right or left and up or down after
each trial.
Participants guess the direction of the shifts that occurred
during their saccade at the two alternative for Choice,
task the options to them was right,
or left up or down and forward or backward.
We used a threshold estimation method and implemented an adaptive
Quest algorithm to measure the thresholds of scene Transformations
that we apply during teir saccade.
We use the quantile of the posterior probability
density function to recommend the next testing value
for next trial.
We also used
as a saccade detection algorithm since our eye tracker
provided 1,000 samples of gaze positions every second
we were able to Implement a velocity based algorithm saccade detection.
In Our experiment each participant took part in to
experimental sessions,
one with horizontal saccade and the other one with
the vertical saccade during all trials.
In both sessions.
There was a continuous camera pan throughout the trial.
We started each group with a short training session,
a 9 point calibration and then Session 1.
Then we had another calibration and ran session to with the vertical
Saccade. We follow the same procedure for.
groups Two.
And three of our study.
We analyzed our data,
in terms of two variables and their interactions.
We looked at Direction constant camera Motion in the scenes,
which had the states of pan tilt or no
motion and saccade Direction which was either horizontal
or vertical.
When we looked at the saccade Direction and found,
when there was a continuous camera pan in the scenes,
sensitivity to certain camera.
Transitions did not differ between vertical and horizontal saccades.
Similarly,
saccade direction did not affect discrimination of
a sudden camera shifts during a continuous
camera tilt.
The figures here,
show detected
thresholds for translations during horizontal saccades
on the left and vertical saccades on the right.
As it can be seen during both saccade directions.
Right
And left translations were less detectable with a camera pan
compared to a camera tilt.
And down translations were less detectable with a camera tilt
than a camera panning.
The scenes and here we can see figures
showing detected thresholds for rotations
during horizontal saccades The left and went to go see cats
on the right during both directions of horizontal and
vertical saccades up or down rotations,
were harder to detect with a tilt motion.
Then a panel static scenes,
also,
left or right Transit,
saccadic camera.
Rotations,
were harder to detect with a pan rotation,
compared to tilt,
or no motion.
We can see that direction of the continuous camera,
rotation affected,
the detectability of all,
four types are rotational trans-,
saccadic changes.
We were also interested in finding,
whether the angle between the direction
of the ongoing camera Motion in a scene and the saccade Direction,
influenced image displacement detect abilities.
Therefore,
we looked at two angles of 0 and 90 degrees.
The conditions we analyze where,
when the continuous camera Motion in the scene and the seek
a direction where parallel and when they were
orthogonal,
And what we found was that in most conditions
direction of camera motion was a more important factor
in determining the detectability of transsaccadic changes
than the saccade direction.
Our work showed that the ongoing camera motion
had a stronger effect.
than saccade direction on transsaccadic detect
abilities scene transitions that were
parallel to the direction of the simulated head movement.
Had a higher likelihood of being Mask during saccades.
For example,
having a right rotation for pan or down
rotation for tilt.
And we also found that in a virtual environment with a horizontal,
head rotation,
which is simulated as a camera pen.
There is a better tolerance of horizontal rotation,
rotational scene changes,
whether the saccade is horizontal or vertical,
likewise with vertical head movements,
which sits where simulated,
as a camera tilt vertical image,
displacement were better hidden during both horizontal and vertical.
See Cats,
the applications of this work include redirected
walking in VR for reorienting.
The Viewpoint of the user for Created rendering
for hiding.
Low-resolution rendered images and also in gaming or
rendering optimizations,
for future works with,
like,
to explore how well,
our current findings generalize to other combinations
of image.
Displacements head rotations and our movement directions,
and also validate our findings on an HMT
system with integrated eye.
Trackers to ensure our results translate to real application
and actively generated head motion.