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Pro eye unsuitable for research - data SUPER heavily filtered during fixation.


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  • 2 weeks later...
On 11/11/2019 at 10:57 PM, wenjieshen said:

Hi Marcellotham,

SetEyeParameter() is still supported in Eyedata_v2 but filtering always only works on gaze rays. 

So the versions of data doesn't effect filtering.

Thanks,

WenJie

Thank WenJie,

So if I'm interested in the verbose data from eyedata_v2, I shouldn't be worrying about filtering? Is it safe to just disable it nonetheless.

Thank you

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On 11/14/2019 at 3:36 AM, marcellotham said:

Thank WenJie,

So if I'm interested in the verbose data from eyedata_v2, I shouldn't be worrying about filtering? Is it safe to just disable it nonetheless.

Thank you

Hi Marcellotham,

Yes, filtering works as previous version.

Thanks,

WenJie

Edited by wenjiec_shen
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  • 2 months later...
On 8/14/2019 at 4:45 AM, gazeBehavior said:

 

Here are the latency measurements taken by one of our students.  Images reflect the azimuthal component of the head and eye during vestibulo-ocular reflex (while fixating a stable object and rotating one's head about the vertical axis).  The first figure shows the original signals - deg/s over time.  The second shows the results of the cross correlation, and the third shows a zoomed in look at the signals before/after adjustment for the measured latency.  

The two signals were maximally correlated with 83 ms of shift, meaning that there was 83 ms of latency in the eye tracker relative to the head tracker. Vive head tracking is typically 22-33 ms absolute latency, so that puts the ET above 100 ms of absolute latency.  
 
We have only measured this once.  Really, we should measure a few more times, with different people.  We could also learn more by testing for possible effects of rotational velocity, and GPU load on the amount of latency.  
 
An effect of the former (head velocity) would indicate that this latency results form a dynamic filter.  This seems unlikely, because if it were, they would just have us turn it off.  
 
It's more likely attributed to the core functions of the eye tracking pipeline, such as pupil segmentation in the 2D imagery, or gaze mapping (which converts from 2D pupil centroids to 3D gaze vectors). If so, I would expect the latency to increase with GPU load.
 
Something to test, anyhow. Or, HTC could jump in and say a bit more...
 

image (1).png

image (2).png

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Hello!

Thanks for sharing this. Can I ask how you actually measured these?

 

Thanks

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  • 6 months later...

Hi folks ,

I am relatively new to VR, but I have just written my master research piece on spider fear for the pro Eye. The software is ready to go and studies fear of objects presented in the periphery.

3 things:

1. I am looking for participants who have the pro eye to take part. Takes about 12 minutes runtime and max 25 minutes in all. Details if you are interested. (sorry to shamelessly plug my research, but corona is making things difficult which is why I had to abandon lab-based research).

2. I am wondering if there is a good platform that I can upload my reserach software to for easy download. Really basic stuff I know.  I am totally new to all this.

3. Accuracy. This discussion is interesting. I am not using head movement. The visual field is fixed. So my question is whether you believe the eye tracking as a stand alone is accurate enough for research purposes: specifically -

  -- latency - I am noticing a lot of empty data that appears around 40ms after "eyeopenness" goes to 0 (i.e. closed). So the recording of blinks appears to be out of sync.

  -- calibration: if the tracker stops recording (which sometimes happens for up to 1 second, do we need to recalibrate? I don't think so as long as the device is not moved. It would disturb the flow of any experiment if that was the case.

Thanks for any info you can give.

 

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