Thank but the issue is that it is not sold in Japan officially. There are many vendors available importing it to sell in Japan

As far as I understand, there is no penalty to sell it but there is to use it. I really hope you can solve this to use Invisible properly in Japan….

Hi all 🙂 I have set the glasses up to record normal video but is there any in depth documentation on setting up heat mapping? We are testing this with a user sitting in front of 6 monitors (static images, mainly excel spreadsheets) and want to track what screens/sheets they look at the most during a 30 minute window. TIA

Hi all, I have a problem with getting my last measurements with Pupil Invisible to play in Pupil Player. This is the notification I've got. Do you know how to solve this?

Ah yes I see, this resolved the problem. Thank you!

Placing it out of the One Drive folder, the offline_data is still in it

Thanks, this would be good to know. The use case I have in mind is three people viewing a large display, each wearing pupil invisible. The aim is to plot gaze position on the display for each person in real time. Would this require the wifi approach?

Using a wifi you can expect something like 10-100 ms of transmission delay depending on your setup. I.e. if a subject changes their gaze point on the screen, it would take 10-100 ms for the gaze point visualization on the screen to update. For most applications, including things like gaze interaction, this should be sufficient. If it suffices for your use case depends on what exactly you are trying to achieve.

I see! I'd recommend piloting it just to be safe, but yes, that sounds feasible to me!

hey How can I buy this device in UAE?

hello, I am using ubuntu 18.04 and I wanted to use pupil-labs-realtime-api in my code but I'm getting this error when I tried to install it. what should I do?

hi I'm not able to find any devices using pupil-labs-realtime-api the companion and laptop are on same network . I also checked that the RTSP streaming is working but when I search of devices using the python lib, there are no devices found

can anyone help with this please?

I have a question : what is the best completable EEG to Integrate with invisible for neuromarketing ?

yes I need a device for record EEG signals Please introduce a device that should be integrated with you. Are epoc flex or Enobio 8 devices suitable?

by going to the address in browser

the ip address

What happens if you enter the dns name instead?

it works, I've tried on multiple networks also but the api can still not find devices.

This is unusual. What is the exact API call that you use for discovery?

Have you tried passing a longer timeout?

it results in AttributeError: 'Device' object has no attribute '_event_manager'

yes, I'm using Anaconda Powershell on the same computer. No VM etc

hello everyone; for the data analysis of pupil data i tried running the code from 'https://pyplr.github.io/cvd_pupillometry/04d_analysis.html' but i am not able to run it.. i am getting an error in plr processing.. i dont know what to do.. i want to do the preprocessing of pupil diameter but i am not able to do it..' does anyone have any solution regarding this?

Hi @user-e91538! Unfortunately, Pupil Invisible does not provide pupillometry data. The eye cameras are located so far off to the side that a lot of the time the pupil is not visible at all in the image, so the available data streams are limited to gaze, fixations and blinks. To measure the pupil diameter you'd have to use Pupil Core.

Hi, I used a pupil invisible for a car drive to check if the person has observed the traffic signs while driving. In here, I got the video and the person's gaze data which I want to map with each other but found out that the frequency of the both the data are different. The video frequency is 30 frames per second and gaze frequency is 50 frames per second. I would like to know how the pupil software deals with this problem and maps both the data. So that I could do the same.

I see! I'll forward your message to the 👁 core channel then, so my colleagues can help you there!

Hi @user-d119ac! Both the video frames and the gaze samples are timestamped, which allows you to correlate them with one another. Given the differences in framerate you will end up with multiple gaze samples per video frame.

Today we coincidentally published a guide on how to manually sync data streams using timestamps in Python: https://docs.pupil-labs.com/invisible/how-tos/advanced-analysis/syncing-sensors/

Does this guide help you with your question, or were you looking for something else?

FYI If you download a Pupil Invisible recording from Pupil Cloud the gaze sampling frequency will be even higher at 200 Hz.

@user-4a6a05 Could you reply to this message from 💻 software-dev channel please: https://discord.com/channels/285728493612957698/446977689690177536/1006566797006360576

Hi! Could you please release an updated client (https://github.com/pupil-labs/pupil-cloud-client-python) for api version2 (https://api.cloud.pupil-labs.com/v2) Or is it possible that I can generate the python client code myself with the swagger.json? And is there any possibility to export videos via api? If not. Could you please implement this?

Two questions. Firstly after applying the marker mapper enrichment if in the video the markets are intermittently identified will fixations still be identified within the area of interest identified when setting up the enrichment or it only those fixations when the markers are identified? Also is it possible to download video of the fixations overlays together with the gaze overlays?

Hi @user-057596! There is the "raw" fixations signal, containing fixations in the scene camera, which would be included in the recording download. This data stream will always contain fixations throughout the recording.

And there is "mapped" fixations, which are the same fixations mapped onto the surface tracked by the marker mapper. Those would be included in the marker mapper download. In order to map a fixation to a surface, the surface needs to be detected. So if the detection failed for a couple seconds, the fixations within those seconds would not be mapped.

It is currently not possible to download the fixation scanpath as video. The only thing I can point you to is this Python example script of how to render the scanpath yourself: https://gist.github.com/marc-tonsen/d8e4cd7d1a322a8edcc7f1666961b2b9

Thanks Marc

hi Pupil friends. we were wondering what this feature does (companion app) "Eye Video Transcoding"

Hi, does someone know how the pupil invisible recordings are upscaled to 200 Hz in cloud since the recorded data on device is around 120Hz. Is there a software upscale implemented on the recorded data when it is uploaded to cloud or is there some meta data used to generate higher resolution

The eye video is recorded at 200 Hz on the phone. The only reason why the real-time gaze signal is lower is because the phone's processing power does not suffice. In cloud the gaze signal is calculated again from scratch using the full video framerate . So the 200 Hz are not just interpolated or upscaled, but are based on actual video frames at that frequency.

Hello community! I have a problem with the Invisible calibration, I can't find the red circle, it doesn't make me see it while I try to do the setup of the device. But if I record a sequence, it appears and also the bindings, but of course they are not aligned to real look. What can happen? I did all the Oneplus 8 upgrades

@user-4a6a05 Thank you for your reply, Android is 12. Invisible Companion Version is 1.4.25-prod.

Thanks! In theory this combination of versions should work.

In the screenshots you shared it looks like the gaze circle is visible in the live preview in the top left corner. Is the gaze circle stuck in this position?

Also, can you confirm that no error messages are shown by the app?

Would you be able to share an example recording of ~1 min length which is affected by the issue? If this recording is uploaded to Cloud, it would suffice for you to let me know the recording ID and to give us explicit permission to access it to investigate.

Hi! My setup is as follows: I have a camera fixed on the dashboard of the car and the driver is wearing a Pupil Invisible device. I have the gaze with respect to the world camera of the Invisible device. I want the gaze point with respect to the dashcam. How do I do this?

I can share sample images if needed

what do you think about attaching some marker to the Pupil Invisible?

How can I export a movie in Recordings (Pupil Cloud) including gaze location, fixations and saccades (like in the preview)? I am only able to export raw data.

Hi I’m trying to live stream to my pad using the QR code which worked the last time in the same setting but but each time it say safari could not open the page because the server stopped responding. Thanks Gary

Hello, I was wondering if there was a way to pull surface gaze data using the updated API? I recall this was possible with the previous network API framework using zmq. I wasn't very successful finding anything that might say it's possible in the API documentation.

Hi Mark you were spot on, there was an undetected problem with the university’s internet system which has now been rectified. Thanks for your help.

For Pupil Core and the old NDSI (the old real-time API) real-time surface tracking was available. This is because the surface tracking could be computed in Pupil Capture, which then published it to the network. The companion phone can however currently not take over the duty of calculating the surface tracking, so this is not immediately possible.

I can point you to this demo script however, which uses the API to receive gaze and scene video data on a computer, and uses the open-source surface tracking code to do real-time surface tracking on the computer. This would not make the surface tracking data available on the network, but on the computer that is executing the script. Note, that the README file is slightly out of date. You do no longer have to create an API token for this script to work and you can skip the according setup steps. https://gist.github.com/papr/40d332498bfacb5980a754c5692068ec

Hello @user-e3f20f, the April tags we have that are placed on a physical board are not being recognized by our world view camera despite them working just fine yesterday. We have gone through the documentation and have ensured that there is enough white space around each tag. Do you have any suggestions on how to resolve this suggestion?

Thank you for checking in, I am not sure what happened yesterday, but it is working fine now! I did, however, come across another question. We have two square AOIs set on our board (one on the left and one on the right) and in the center of the AOI squares there is a target light. We recorded some data where the user looked at the center of the right side AOI square and then looked at the left side AOI square all in one go. After processing our data and creating two respective surfaces for the right and left sides we exported the data. When opening the gaze_position_on_surface_Left and Right files I noticed that the right side file had around 250 data points and the left side file had only 35 data points. I am not sure why the right-side surface file would have more data points than the left-side surface file since it is pulling data all from the same recording. We are specifically interested in the on_surf column of these files as we want to see when the gaze of the participant falls out/in the AOIs.

Hi. I downloaded a recording from Pupil Cloud and dragged it into the Pupil Player and I get the following message.

Is there a way to calculate or get the amount, and maybe even the duration, of saccades that were made within a recording?

Hello, I understand that the cameras don't start at the exact same time and record at different sampling rates. However, can I assume that the timestamp (and frame index) given by the annotation plugin corresponds to the nearest timestamp (and world index) in the pupil_positions.csv file? For example, If the annotation for the onset of an image starts at 7100.4801 (frame index 617), does the pupil diameter around that time (given by the timestamp column in pupil_positions) correspond to the onset of the image (given by the annotation marker) - is that pupil diameter time-locked to that annotation event? Thanks for your help!

Hi @user-ced35b! First off, are you using Pupil Invisible (rather than Pupil Core) for your recordings? In case you do, please note that measuring pupillometry data with Pupil Invisible in Pupil Capture is not recommended and that you will most likely get low quality data.

Besides that, all data streams made by Pupil Invisible and Core are 1) independent and 2) timestamped. "Independent" means, as you mention, that the according sensors run separately with different start times and sampling rates. Thus, samples from different data streams are never made at the exact same time. The timestamps allow you to match the data up to the level of tolerance you desire. E.g. given the 200 Hz pupil signal and the 30 Hz world video you could match all pupil samples to the closest respective video frame. Then, every frame would match with a set of pupil samples.

The world index columns provided by Pupil Capture do exactly this: they tell you which world video frame is the closest available one. So if you are interested in the pupil diameter value at a specific point in time, and you have annotated that point, such that you know the corresponding world frame, you are correct in selecting the pupil diameter value with the same world frame index. However, there will be multiple pupil diamter values associated to the same frame. You have to choose if you want to take their mean, or compare the timestamps in more detail to find the closest single pupil diameter sample.

Please see also Pupil Captures export documentation here: https://docs.pupil-labs.com/core/software/pupil-player/#pupil-positions-csv

And this how-to guide on sensor syncing and timestamp matching, which also discusses this problem: https://docs.pupil-labs.com/invisible/how-tos/advanced-analysis/syncing-sensors/

Hello everyone! my name is idan and i’m part of Menuling. our goal i to improve profits for restaurants by engineering the menu According to behavioral economics Models and other statistics Methods. we are looking for best ways to use the glasses for this. performing experiments with the glassess on subjects reading a menu for the first time and analyzinf gace focus and heatmap, to know where he looked first, where did he focused the most, and how long did he stays on each focus point for exapmle, anyone had any expereince analyzing text gaze for exapmlt or something similar?

Hi @user-87b92a! If you are interested, feel free to reach out to [email removed] to schedule a meeting with one of our product specialists to discuss your use case and how it might be possible with our products in detail.

I can point you to a few resources that might be helpful. These blog post are about an example study we did in an art gallery. It's analysing gaze behaviour on paintings rather than menus, but the metrics calculated are somewhat similar: https://pupil-labs.com/blog/news/demo-workspace-walkthrough-part1/ https://pupil-labs.com/blog/news/demo-workspace-walkthrough-part2/

The key tool in the analysis process would likely be the Reference Image Mapper, which would allow you to map gaze data to your menus: https://docs.pupil-labs.com/invisible/explainers/enrichments/#reference-image-mapper

Hi all, yesterday I've done a measurement with Pupil Invisible and during this measurement the cable between the phone and glasses disconnected. After this happened, I reconnected the cable again and started a new measurement. Right now I can see that the duration of that measurement was 14 minutes (which is true), but in Pupil Player it only shows me 34 seconds. Can this recording still be saved or do I only have 34 seconds now?

Can you clarify if you explicitly stopped the running recording and started a new one when the cable disconnected?

I think what happened is the following: Generally, the app is able to handle disconnects of the glasses. In some cases, there can be USB errors on the operating system level which are difficult to catch for the Android application. As a result, the scene video recording might have been aborted, leaving the file in a corrupted state. Could you please share the broken and the following working recording with [email removed] It might be possible to recover the corrupted video file.

Hi! I have two questions: Is there an advantage for using ns over regular seconds in eye tracking data? I think for starting I would prefer using seconds, is there an option to convert the time before downloading the csv files? My second question is the following: I have 2 defined events, start and end of recording. However, I cannot find both timestamps in my gaze.csv file. How can that be?

ah yes! this makes sense. Do you have an idea regarding the events though? The respective time stamps do not appear in the gaze datafile, is this due to the recording frequency?

Okay I understand. But even when defining an random event after a few seconds, I cannot find the exact time within the time column. Is What could be the mistake that I made?

Hello Marc, yes I confirm there is no error messages shown by the app. Sometimes the gaze point appears in the preview of the Companion app like in the picture but you cannot do any calibration with it and is fixed in this place, sometimes either not appear in the screen. How can I give you permission to see in my cloud app?

"I give you permission to Pupil Labs access my recording with the ID [email removed] investigate the issue I have reported"

hi Pupil Labs team - I wanted to follow up on an old topic thread and see if anyone has thoughts: https://discord.com/channels/285728493612957698/633564003846717444/996770110750601267

At a high level, I am hoping to enable the OnePlus hotspot and interface with the RTSP API from a second battery-operated device without any public internet connection or a third device (e.g. a personal cell phone) serving as a router/hot spot. It sounds like the challenge might be related to DNS, in which case I'd be happy with a solution that just uses an IP address. Even device discovery isn't entirely necessary if the Companion app can report its IP.

From the message I was replying to, it sounds like other users may also have this need. Thank you for your consideration!

So a stable head-pose would be equal to a stationary head-pose? I am not sure if I understood this correct :). Would it be an issue if the participants are moving their heads, if one were interested in calculating saccades?

@user-4f01fd Thank you for the workspace invite! We believe we were able to locate the issue. It seems like the "camera intrinsic values" saved in the app are broken, which causes the live preview to not show gaze properly. In Pupil Cloud, the correct intrinsic values are used, so everything works fine there.

To confirm that this is the problem, we'd like to inspect what values the Companion app has saved. To facilitate this, could you please collect and share this data with us? The steps for doing so are as follows: 1) Connect the phone to a computer via USB cable. See also this guide on how this works: https://docs.pupil-labs.com/invisible/how-tos/data-collection-with-the-companion-app/transfer-recordings-via-usb.html

2) Navigate to Phone storage/Documents/Pupil Invisible. This folder should contain one or multiple folders whose names start with persist e.g. persist, persist.1, persist.2. Share all of those folders with us.

Once we have confirmed that this is the issue, it will be easy to fix!

Hi guys, New to pupil Labs and just bought a pair of invisibles. Does anyone know if it is possible to use use two recorder units (oneplus8) and one pair of glasses? I am afraid the battery will run out if I just use one pair while doing fieldwork. Cheers Jørn

Yes please, if you could shed some light on how to set a USB C hub as well that would be great. And also any tips on which USB c hub would be great👍

This makes a lot of sense! I think I get it now. Is there a way to still calculate saccades in dynamic i.e. non stationary scenarios? Maybe via a plugin or a pipeline? Or even by setting events in the recordings, meaning saccades are detected manually? I am fairly new to eye tracking data and the invisible glasses, so please forgive me the many questions. Best 🙂

@user-ace7a4 There are various algorithms that can be used for segmentation of fixations and saccade but during my work in eye tracking for 2 years, I have never seen a paper explicitly mentioning any algorithm as very accuracte. This paper might help, Link: https://www.researchgate.net/publication/220811146_Identifying_fixations_and_saccades_in_eye-tracking_protocols

@user-ace7a4 I myself take the raw trajectories and use an algorithm called I-VT for the segmentation. It also depends what your use case requires, I use it for 'Biometrics using eye movements data'

Thanks a lot for the input @user-e91538! The fixation detection algorithm used in Pupil Cloud is actually a derivative of the I-VT algorithm too! It is adding head movement compensation to it, trying to make it more robust against VOR in dynamic settings. We are currently in the process of publishing a white paper on the algorithm and now I wish I could already link to it 😅

Thank you both so much! I will look into everything mentioned and will probably return!

Hi guys 🙂

I have problems with blink detection. When there are quick vertical eye movements ("saccades"), it is often counted as blinks. I am guessing it is because the AI is not trained for these types of acrobatic movements. Am I right ? / Is there something I can do about it ?

I joined a graph of the detected blinks (only read the black line, which is 1=blink, 0=no blink detected) and the associated video is here https://we.tl/t-WKDGYd7NMn. When you compare both, you see that the first blink is correctly detected, whereas the subsequent blinks are just eye movements that should not be categorized as blinks.

ndsi is a whole different API and has

Great, please share it with [email removed] Thanks!

Thanks for sharing the folder! This does confirm the issue. The fix to the problem is for you to

1) delete the persist folder 2) restart the app by going to App Info (Tap and hold the app icon -> App Info) and select "force stop". Then open the app again.

This will trigger the app to create the folder again and re-download the correct intrinsic values. You may have to re-new your login to the app, but besides that nothing should change, e.g. no recording data will be deleted.

Ok thanks 😦 Are you planning on enlarging the data base with sport data for AI training? If yes, is there a way we can share our data with you to help improve the product in the future?