So, I'm going to talk about validation now the prototype hybrid tracker against the DPI and the to the spectrums.
So, this article was built to support augmented reality.
We're using for augmented reality, direct revenue projection, which means printing, with laser directly on to the retina, and the principle is shown here on the right.
It sense, the augmented reality presentation as a laser beam through a fast scanning mirror which operates like an old fashioned cathode ray monitor, sending a beam of light through this system oh that's just back to the retina and dust.
fashion. And this gives photorealistic color.
It can be used in bright sunlight, even Mediterranean Branson light. You can see black against the bright background which theoretically should not be possible but it happens.
It has a very high spatial and temporal resolution.
And it's verifocal continuously from 20 centimeters to infinity. And all this with a very low power consumption.
However, For this to work, we must
be able to change the beam, whenever the eye moves, so that we can keep projecting into the retina. To do this, we need a really good eye tracker.
We know that video-based P-CR trackers are not good enough.
Several studies have shown that they have issues. First of all, the amplitude of small saccades are mismeasured in P-CR trackers. Changes in pupil dilation have large effects on accuracy, which means that sunlight and ambient light
is a problem.
Participant features such as eye colour, direction of eyelashes, palpebral fissure have large effects on data quality. Variable light conditions including some light on the mind tracking all together.
movement of the headgear introduces noise and data loss. And importantly, database PCR drug is consumed up to 100 times more battery power than analog addresses, which is not good for an augmented reality system that may be used all day.
This is the system in its current state. It prints augmented reality content directly onto the retina.
And the laser beam is directed by a combined eye tracking signal: A mems-based CR-tracker running at 4000 hertz, which provides ultra high precision and very low energy consumption.
And a camera based limbus tracker running at between five and 10 hertz, which provides accuracy.
We tested the system against the Tobii Pro Spectrum, and the DPI, using 28 participants and several tasks.
This is the version of the system that we tested in September 2019.
On the right side you see the precision measurement, and please note that the horizontal scale is a log scale.
The EWET1 has a precision, a noise level, which is one order of magnitude better than the DPI, which is considered one of the most precise trackers, and around two orders of magnitude better precision than the Tobii Spectrum, which
is one of the most precise video based trackers, and the merged signal is slightly more precise than the DPI.
We also looked at microsaccade detection. Microsaccades were coded by hand.
This figure is a density plot of microsaccade amplitudes.
And it shows that both the DPI and the EyeWay tracker detects microsaccades with comparable amplitudes, while the Tobii Spectrum reports fewer microsaccades with larger amplitudes, most likely due to mismeasurement.
I would have liked to present new accuracy measurements, but I will have to come back on that, hopefully on the 25th of May.
We expect average accuracy to be below six minutes of arc.
It's very important for an augmented reality system to be resistant to changes in ambient luminance.
In order to test this, we had participants
look at a monitor, where we see the sinusoidally changed luminance as the gray plot shows.
This gives a change in pupil dilation which we can see as the black plot.
We then correlated luminance
and the resulting gaze.
It is well known that gaze changes when pupil dilation changes, in all P-CR eye trackers.
And we also noted that this happened in the DPI.
This is the correlation of gaze against luminance. The DPI, and the Tobii have large ranges of correlation values, which indicates that gaze is affected by changes in luminosity, whereas the EyeWay tracker have smaller ranges of correlations, which suggests
that it is resistant to changes in luminance. It is very good if you have an augmented reality system of this kind and you walk from a dark room out into sunlight.
We also checked the minimum step resolution of each of the eye trackers using the Stepperbox from one of our earliest studies.
It shows that the EyeWay tracker can easily resolve eye movements down to two minutes of arc, which the DPI also can do.
So in conclusion, the EyeWay tracker produces eye movement recordings of high quality that are resistant to variation in ambient light, and as such
it would work as a basis for augmented reality presentations of the kind that I sketched in the beginning of this talk.