ETRA 2021 Tutorials

Schedule: May 27, 2021 10:00 -13:00

Abstract: Recently deep learning has become a hype word in computer science. Many problems, which till now could be solved only using sophisticated algorithms, can be now solved with specially developed neural networks. Deep learning also becomes more and more popular in the eye-tracking world. It may be used in any place where some kind of classification, clustering, or regression is needed. The tutorial aims to show the potential applications (like calibration, event detection, gaze data analysis, and so on), and – what is more important – to show how to apply deep learning frameworks in such research. There is a common belief that to use neural networks a strong mathematical background is necessary as there is much theory that must be understood before starting working. There is also a belief that, because most deep learning frameworks are just libraries in programming languages, it is necessary to be a programmer and know the programming language used. While both abilities are beneficial because they may help achieve better results, this tutorial aims to prove that deep networks may be used even by people who know only a little about the theory. I will show you ready-to-use networks written using the Keras library in Python with exemplary eye movement datasets and explain the most critical issues you will have to solve when preparing your own experiments. After the tutorial, you will probably not become an expert in deep learning, but you will know how to use it in practice with your eye movement data.

Scope: The tutorial is divided into four parts:
(1) Introduction to Machine Learning (problems, algorithms, measures, examples)
(2) Neural networks (architectures, implementations, Keras/Tensorflow, examples)
(3) Convolutional Neural Networks (idea, advantages, examples)
(4) Recurrent Neural Networks (sequences, architectures, examples)
All examples are given in Python 3 with the usage of scikit-learn, opencv, tensorflow and keras libraries.

Audience: The tutorial is addressed to every person interested in deep learning; no special skills are required apart from some knowledge about eye tracking and eye movement analysis. However, minimal programming skills are welcome and may help in better understanding the problem.

Teachers: Paweł Kasprowski is an Associate Professor at the Silesian University of Technology, Poland. He received his Ph.D. in Computer Science in 2004 under the supervision of Prof. Jozef Ober – one of the precursors of eye-tracking. In 2019 he obtained habilitation (D.Sc.) for his contribution to the analysis and applications of an eye movement signal. He has experience in both eye-tracking and data mining. His primary research interest includes using data mining methods to analyze eye movement signals. Paweł Kasprowski teaches data mining at the university as well as during commercial courses. At the same time, he is an author of numerous publications concerning eye movement analysis.

Contact Email address: pawel.kasprowski@polsl.pl

Schedule: May 27, 2021 15:00 -18:00

Abstract: This tutorial gives a short introduction to experimental design in general and with regard to eye tracking studies in particular. Additionally, the design of three different eye tracking studies (using stationary as well as mobile eye trackers) will be presented and the strengths and limitations of their designs will be discussed. Further, the tutorial presents details of a Python-based gaze analytics pipeline developed and used by Drs. Duchowski and Gehrer. The gaze analytics pipeline consists of Python scripts for extraction of raw eye movement data, analysis and event detection via velocity-based filtering, collation of events for statistical evaluation, analysis and visualization of results using R. Attendees of the tutorial will have the opportunity to run the scripts of an analysis of gaze data collected during categorization of different emotional expressions while viewing faces. The tutorial covers basic eye movement analytics, e.g., fixation count and dwell time within AOIs, as well as advanced analysis using gaze transition entropy. Newer analytical tools and techniques such as microsaccade detection and the Index of Pupillary Activity will be covered with time permitting.

Audience: The tutorial welcomes attendees at all levels of experience and expertise, from those just beginning to study eye movements and interested in the basics of experimental design to those well practiced in the profession who might wish to consider adopting use of Python and R scripts, possibly wishing to contribute to, expand on, and improve the pipeline.

Teachers: Dr. Duchowski is a professor of Computer Science at Clemson University. He received his baccalaureate (1990) from Simon Fraser University, Burnaby, Canada, and doctorate (1997) from Texas A&M University, College Station, TX, both in Computer Science. His research and teaching interests include visual attention and perception, eye tracking, computer vision, and computer graphics. He is a noted research leader in the field of eye tracking, having produced a corpus of papers and a monograph related to eye tracking research, and has delivered courses and seminars on the subject at international conferences. He maintains Clemson's eye tracking laboratory, and teaches a regular course on eye tracking methodology attracting students from a variety of disciplines across campus.
Nina Gehrer is a clinical psychologist and postdoc at the University of Tübingen, Germany. She received her PhD in 2020. Her main research interest lies in studying face and emotion processing using eye tracking and a preferably wide range of analytic methods. As a clinical psychologist, she is particularly interested in possible alterations related to psychological disorders. She began working with Dr. Duchowski in 2016. Since then, they have enhanced and implemented his gaze analytics pipeline in the analysis of several eye-tracking studies involving face and emotion processing. Recently, they have started to extend their eye-tracking research to social interactions and body perception.

Contact Email address: nina.gehrer@uni-tuebingen.de

Schedule: May 27, 2021 15:00 -18:00

Abstract: Causes of dizziness include benign inner ear conditions as well as more severe and dangerous brain disorders such as stroke. In patients affected with acute dizziness and vertigo, eye movement examination outperforms neuroimaging for diagnosing stroke. For this reason, eye movements are routinely examined and recorded in neurology and neuro-otology clinics around the world. The use of eye movements is widespread in many fields of clinical research, including neurology, psychology and psychiatry. However, in many occasions, eye movement recordings have remained restricted as research tools and have not made their way to the clinic. Here, instead, we will focus on use cases where eye movements directly provide information that can be diagnostic, either on their own or in combination with a few other pieces of data such as patient’s history. In some cases, clinician’s examination is just qualitative and consists in looking directly at the patient’s eyes. In other cases, eye movements are recorded, typically with video infrared goggles, and become part of the clinical record of the patient. This tutorial will describe the tests that are regularly performed in the clinic to aid physicians in the diagnosis of patients with dizziness, oscillopsia, or double vision. These tests include the head impulse test, the test of skew, Dix-Hallpike maneuver, interpretation of nystagmus, etc. To properly understand the rationale of these tests we will first cover the basic concepts of eye movement control together with the relevant anatomy and physiology.

Scope: The tutorial will review behavioral properties and the neural substrate for the fundamental types of eye movements: vestibular-optokinetic reflex, saccades, smooth pursuit, gaze holding and fixation, and vergence. Then, it will review the clinical tests most used in neurology, otolaryngology, and ophthalmology clinics to diagnose patients affected with dizziness, oscillopsia, and double vision. Interpretation of these tests allows the clinicians to identify the disease and, in some cases, localize the lesion with more accuracy than neuroimaging.

Audience: The tutorial audience will be anybody interested on basic properties of eye movements and the neural circuits responsible for their control as well as researchers interested in clinical applications of eye movement recordings.

Teachers: Jorge Otero-Millan is a postdoctoral fellow in the Department of Neurology at Johns Hopkins University currently working in the laboratory of David S. Zee, author of the book “The Neurology of Eye Movements”. In July 2020 Jorge will join the faculty of the University of California at Berkeley as an Assistant Professor in the School of Optometry. With a background in engineering, during his PhD and Postdoctoral training, Jorge has collaborated with Neurologists, Ophthalmologists, and Otolaryngologists analyzing eye movements of patients suffering from disorders affecting the brain, the eyes, or the inner ear.

Contact Email address: jom@berkeley.edu