Understanding the relationship between head, hand, scene, and gaze information is relevant
for many research areas and applications.
Here, we present OpenNEEDS, the first large-scale, high frame rate, comprehensive, and open-source
dataset of Non-Eye and Eye data captured during exploration in open-ended VR environments.
Given the widespread utility of eye-tracking technology, we demonstrated OpenNEEDS utility
in the context of gaze estimation.
We show that all non-eye sensor models exhibited improved performance over all baseline models,
and we hope that OpenNEEDS can continue to support research progress in many areas and applications
We present Gaze+lip, a complementary multimodal hands free interface
combining gaze input and silent speech Commands for Hands-free Smart
TV Control.
Gaze has been shown very fast and efficient
for selecting targets at a distance
However, it is still a challenge to guarantee accurate selections using gaze only method.
Our technique utilizes gaze for fast selection
silent speech command for expressive and accurate operations
and also requires less effort.
Understanding Urban Devotion through the Eyes of the observer
Thank you!
Eye-tracking requires calibration to estimate the point-of-gaze in advance.
Therefore, we propose a method for estimating the focused target
based on the similarity between smooth pursuit eye movements and object movement in the real world
We confirmed the feasibility through comparative experiments
using four different methods.
Hello everyone
To enhance the precisoin of eye trackers, we propose a new mathematical formulation
based on modified kalman filter
which effectively combines information from eye tracking system, such as p minus cr with
iris features based velocity estimation methods.
With this approach we can improve precision and the ability to study various eye movements,
such as micro saccades or smooth pursuit.
Please visit our poster for additional details.
Hello my name is Wolfgang Fuhl
and I will present the paper A Multimodal Eye Movement Dataset and a Multimodal Eye
Movement Segmentation Analysis
which is about a huge dataset
for eye movement classification
it is from real world recordings during driving
and contains a lot of different features
which can be extracted from the eye images
In this work, we present a lightweight, mobile system for simultaneous head and eye tracking
outside the lab.
The system consists of the Intel RealSense T265, the Pupil Core eye tracker, and a 3D-printed
mounting bracket.
A set of open source plugins for the Pupil
Core software suite can be used to calibrate the system
and record tracking data.
We demonstrate the system‘s ability to measure head and eye movements with a fixation task
and a real-world walking task.
My name is Martin Prinzler from the University of Bremen in Germany.
I present to you the paper "Visualizing Prediction Correctness of Eye
Tracking Classifiers".
We take trajectories of eye tracking experiments
and train classifiers to identify users.
From the classification probabilities we calculate our score:
The Prediction Correctness Value.
For a single participant we can color the trajectory,
to see what is helpful for the used classifier.
For multiple participants we can combine the information to heatmaps,
showing beneficial areas.
For more information check this QR Code or visit our poster.
In a world with difficult research questions and complex
cognitive demands, we need methods that are able to scale
to the complexity but simplify the output and provide focused
and actionable feedback to the researchers.
We use the Tracer method to identify strategies in Overwatch
that could be easily trained by Esports coaches.
If you're interested in finding out about this effective
method, come see my poster session.
Thank you.
Hi everyone.
This is Takashi Hirata from Chubu University in Japan.
The title of our poster is Pupillary response reflects vocabulary comprehension.
In this study, we recorded pupillary response in 3 situations,
before-study, during-study, and after study.
Then we compare pupillary response between
high-performers who got high score in Test and low-performers who got low score in Test.
As the result, low-performer showed grater pupillary dilation than hight-performer.
Thank you.
we provided real-time feedback on pupil diameter in the lab to investigate if it's
possible to control pupil size changes and to
apply this measure as an input option in hci.
afterwards participants walked across the campus and evaluated the potential
of pupil control in various indoor and outdoor locations.
however results are quite sobering indicating a
high amount of unintended dilations especially in noisy environments.
Eye-tracking methods using multiple light sources have been studied for high precision
and robust gaze estimation.
However, Identifying the glint IDs using these methods is a problem.
Therefore, we propose a polarized near-infrared light emission.
We succeeded in identifying the ID correctly and curbing the influence of glints in pupil
detection
How to measure reward expectation during a card game?
EEG or fMRI?
Pupil size and Eye movements including Microsaccade were applied
to evaluate the participant's reward expectation during a controlled poker game.
Some metrics, in particular pupil size,
responded the individual betting values during the game.
Also, pupil dilated in the 12 seconds before betting.
The detailed are presented in the poster.
Thanks.
We propose an eye gaze estimation, using the high-speed display.
The binary patterns becomes imperceptible, by switching them faster than the flicker
fusion rate.
Therefore, it is not required to attach near-infrared LEDs to the display, and we succeeded in estimating
the point-of-gaze, using the imperceptible markers.