Human Computer Interaction

Dr. Thomas Kübler

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University of Tübingen
Dpt. of Computer Science
Human-Computer Interaction
Sand 14
72076 Tübingen
Germany

Telephone
+49 - (0) 70 71 - 29 - 78996
Telefax
+49 - (0) 70 71 - 29 - 50 62
E-Mail
thomas.kuebler@uni-tuebingen.de
Office
Sand 14, C205a
Office hours
on appointment

My research concerns all aspects of eye-tracking, from the design of a physical recording device, the necessary image processing steps via classical computer vision as well as DNNs, to the high-level interpretation of recorded gaze sequences through machine learning. I work on assessing data quality, visualization and gaze analysis tools in various applications in the medical, educational, automotive and art historian fields.

With my Spin-Off Look! we develop eye-tracking solutions for automotive applications as well as in-vehicle head-mounted devices for driving schools and instructor teaching.

Our algorithms for the registration and analysis of gaze data are well suited to infer cognitive processes such as attention and vigilance solely from the movement of the eyes - and are therefore an excellent complementary factor to traditional measures such as perclos, head movements or gaze-on-road. This adds to robustness and sensitivity of driver monitoring systems by enabling the vehicle to sense the current attentional state of the driver.

Driving instructors are enabled by our head-mounted eye-tracking devices to see the streets through the eyes of their students. That way they can provide efficient feedback and speed up the learning process by making students aware of the importance of correct visual exploration of their surroundings.

Research Interests

  • Gaze-based driver assistance and monitoring systems
  • Computational models of human gaze behavior
  • Algorithms for the comparison of exploratory gaze sequences
  • Eye-tracking data quality in real-world applications
  • Algorithms and tools for the analysis and visualization of eye-tracking data
  • Head-mounted eye-tracking hardware

Publications

The Perception Engineer’s Toolkit for Eye-Tracking data analysis

by Thomas C Kübler

In Eye Tracking Research and Applications. ACM, 2020.

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Deep semantic gaze embedding and scanpath comparison for expertise classification during OPT viewing

by Nora Castner, Thomas C Kübler, Juliane Richter, Therese Eder, Fabian Huettig, Constanze Keutel, and Enkelejda Kasneci

In Eye Tracking Research and Applications. ACM, 2020.

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Improving Real-Time CNN-Based Pupil Detection Through Domain-Specific Data Augmentation

by S. Eivazi, T. Santini, A. Keshavarzi, T. C. Kübler, and A. Mazzei

In Proceedings of the 2019 ACM Symposium on Eye Tracking Research & Applications (ETRA) – To Appear, 2019.

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Ferns for area of interest free scanpath classification

by W. Fuhl, N. Castner, T. C. Kübler, A. Lotz, W. Rosenstiel, and E. Kasneci

In Proceedings of the 2019 ACM Symposium on Eye Tracking Research & Applications (ETRA) , 2019.

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Eye-Hand Behavior in Human-Robot Shared Manipulation

by R. M., T. Santini, T. C. Kübler, E. Kasneci, S. Srinivasa, and H. Admoni

In Proceedings of the 13th Annual ACM/IEEE International Conference on Human Robot Interaction, 2018.

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An Inconspicuous and Modular Head-Mounted Eye Tracker

by S. Eivazi, T. Kübler, T. Santini, and E. Kasneci

In Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA) , 2018.

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Automatic generation of saliency-based areas of interest

by W. Fuhl, T. Kübler, T. Santini, and E. Kasneci

In Symposium on Vision, Modeling and Visualization (VMV), 2018.

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Region of interest generation algorithms for eye tracking data

by W. Fuhl, T. C. Kübler, H. Brinkmann, R. Rosenberg, W. Rosenstiel, and E. Kasneci

In Third Workshop on Eye Tracking and Visualization (ETVIS), in conjunction with ACM ETRA, 2018.

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Scanpath comparison in medical image reading skills of dental students

by N. Castner, E. Kasneci, T. C. Kübler, K. Scheiter, and J. Richter

In Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA), 2018.

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EyeLad: Remote Eye Tracking Image Labeling Tool

by W. Fuhl, T. Santini, D. Geisler, T. C. Kübler, and E. Kasneci

In 12th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), 2017.

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Algorithms for the comparison of visual scan patterns

by T. C. Kübler

PhD thesis. University of Tübingen, 2017.

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Aggregating physiological and eye tracking signals to predict perception in the absence of ground truth

by E. Kasneci, T. C. Kübler, K. Broelemann, and G. Kasneci

In Computers in Human Behavior, Elsevier 68: 450-455, 2017.

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Ways of improving the precision of eye tracking data: Controlling the influence of dirt and dust on pupil detection

by W. Fuhl, T. C. Kübler, D. Hospach, O. Bringmann, W. Rosenstiel, and E. Kasneci

In Journal of Eye Movement Research 10(3), 2017.

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Automatic Mapping of Remote Crowd Gaze to Stimuli in the Classroom

by T. Santini, T. C. Kübler, L. Draghetti, P. Gerjets, W. Wagner, U. Trautwein, and E. Kasneci

In Eye Tracking Enhanced Learning (ETEL2017), 2017.

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Monitoring Response Quality During Campimetry Via Eye-Tracking

by G. Dambros, J. Ungewiss, T. C. Kübler, E. Kasneci, and M. Spüler

In Proceedings of the 22st International Conference on Intelligent User Interfaces, IUI 2017, ACM, 2017.

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EyeRec: An Open-source Data Acquisition Software for Head-mounted Eye-tracking

by T. Santini, W. Fuhl, T. C. Kübler, and E. Kasneci

In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) 3: VISAPP: 386–391, 2016.

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Rendering refraction and reflection of eyeglasses for synthetic eye tracker images

by T. C. Kübler, T. Rittig, J. Ungewiss, C. Krauss, and E. Kasneci

In ACM Symposium on Eye Tracking Research and Applications, ETRA 2016, 2016.

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ElSe: Ellipse Selection for Robust Pupil Detection in Real-World Environments

by W. Fuhl, T. Santini, T. C. Kübler, and E. Kasneci

In Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications (ETRA), pages 123–130, 2016.

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Bayesian Identification of Fixations, Saccades, and Smooth Pursuits

by T. Santini, W. Fuhl, T. C. Kübler, and E. Kasneci

In Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications (ETRA), pages 163–170, 2016.

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SubsMatch 2.0: Scanpath comparison and classification based on subsequence frequencies

by T. C. Kübler, C. Rothe, U. Schiefer, W. Rosenstiel, and E. Kasneci

In Behavior Research Methods online first: 1-17, 2016.

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Eyes Wide Open? Eyelid Location and Eye Aperture Estimation for Pervasive Eye Tracking in Real-World Scenarios

by W. Fuhl, T. Santini, D. Geisler, T. C. Kübler, W. Rosenstiel, and E. Kasneci

In ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct publication – PETMEI 2016, 2016.

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Novel methods for analysis and visualization of saccade trajectories

by T. C. Kübler, W. Fuhl, R. Rosenberg, W. Rosenstiel, and E. Kasneci

3. ECCV Workshop VISART 2016, 2016.

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Towards Automated Scan Pattern Analysis for Dynamic Scenes

by J. Ungewiss, T. C. Kübler, D.R. Bukenberger, E. Kasneci, and U. Schiefer

In The Eye, The Brain And The Auto 2015, 2015.

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Online Recognition of Fixations, Saccades, and Smooth Pursuits for Automated Analysis of Traffic Hazard Perception

by E. Kasneci, G. Kasneci, T. C. Kübler, and W. Rosenstiel

4: 411-434. Artificial Neural Networks - Springer Series in Bio-/Neuroinformatics (Ed. Petia Koprinkova-Hristova, Valeri Mladenov, Nikola K. Kasabov), Springer International Publishing, 2015.

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Analysis of eye movements with Eyetrace

by T. C. Kübler, K. Sippel, W. Fuhl, G. Schievelbein, J. Aufreiter, R. Rosenberg, W. Rosenstiel, and E. Kasneci

574: 458-471. Biomedical Engineering Systems and Technologies. Communications in Computer and Information Science (CCIS). Springer International Publishing, 2015.

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Eyetrace2014: Eyetracking Data Analysis Tool

by K. Sippel, T. C. Kübler, W. Fuhl, G. Schievelbein, R. Rosenberg, and W. Rosenstiel

In 8th International Conference on Health Informatics, Healthinf 2015, 2015.

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Exploiting the potential of eye movements analysis in the driving context

by E. Kasneci, T. C. Kübler, C. Braunagel, W. Fuhl, W. Stolzmann, and W. Rosenstiel

In 15. Internationales Stuttgarter Symposium Automobil- und Motorentechnik. Springer Fachmedien Wiesbaden, 2015.

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ExCuSe: Robust Pupil Detection in Real-World Scenarios

by W. Fuhl, T. C. Kübler, K. Sippel, W. Rosenstiel, and E. Kasneci

In 16th International Conference on Computer Analysis of Images and Patterns (CAIP 2015), 2015.

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Automated Comparison of Scanpaths in Dynamic Scenes

by T. C. Kübler and E. Kasneci

In Pfeiffer, Thies ; Essig, Kai (Hrsg.): Proceedings of the 2nd International Workshop on Solutions for Automatic Gaze Data Analysis 2015 (SAGA 2015), 2015.

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Automated Visual Scanpath Analysis Reveals the Expertise Level of Micro-neurosurgeons

by T. C. Kübler, S. Eivazi, and E. Kasneci

In MICCAI 15 Workshop on Interventional Microscopy, 2015.

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Driving with Glaucoma: Task Performance and Gaze Movements

by T. C. Kübler, E. Kasneci, K. Aehling, M. Heister, W. Rosenstiel, U. Schiefer, and E. Papageorgiou

In Optometry and Vision Science 92(11): 1037-1046, 2015.

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Driving with Homonymous Visual Field Defects: Driving Performance and Compensatory Gaze Movements

by T. C. Kübler, E. Kasneci, W. Rosenstiel, K. Aehling, M. Heister, K. Nagel, U. Schiefer, and E. Papageorgiou

In Journal of Eye Movement Research 8(5): 1-11, 2015.

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Arbitrarily shaped areas of interest based on gaze density gradient

by W. Fuhl, T. C. Kübler, K. Sippel, W. Rosenstiel, and E. Kasneci

In European Conference on Eye Movements, ECEM 2015, 2015.

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The Applicability of Probabilistic Methods to the Online Recognition of Fixations and Saccades in Dynamic Scenes

by E. Kasneci, G. Kasneci, T. C. Kübler, and W. Rosenstiel

In Proceedings of the 8th Symposium on Eye Tracking Research and Applications, ETRA 2014, pages 323-326, 2014.

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SubsMatch: Scanpath Similarity in Dynamic Scenes based on Subsequence Frequencies

by T. C. Kübler, E. Kasneci, and W. Rosenstiel

In Proceedings of the 8th Symposium on Eye Tracking Research and Applications, ETRA 2014, pages 319-322, 2014.

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Rule-based classification of visual field defects

by E. Kasneci, G. Kasneci, U. Schiefer, and W. Rosenstiel

In 7th International Conference on Health Informatics (HEALTHINF 2014), 2014.

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Gaze guidance for the visually impaired

by T. C. Kübler, E. Kasneci, and W. Rosenstiel

In Proceedings of the 8th Symposium on Eye Tracking Research and Applications, ETRA 2014, pages 383-384, 2014.

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Stress-indicators and exploratory gaze for the analysis of hazard perception in patients with visual field loss

by T. C. Kübler, E. Kasneci, W. Rosenstiel, U. Schiefer, K. Nagel, and E. Papageorgiou

In Transportation Research Part F: Traffic Psychology and Behaviour 24: 231 - 243, 2014.

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Towards automated comparison of eye-tracking recordings in dynamic scenes

by T. C. Kübler, D. R., J. Ungewiss, A. Wörner, C. Rothe, U. Schiefer, W. Rosenstiel, and E. Kasneci

In EUVIP 2014, 2014.

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Online Classification of Eye Tracking Data for Automated Analysis of Traffic Hazard Perception

by E. Tafaj, T. C. Kübler, G. Kasneci, W. Rosenstiel, and M. Bogdan

In Artificial Neural Networks and Machine Learning (ICANN 2013), 2013.

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Auswirkungen des visuellen Explorationsverhaltens von Patienten mit binokularen Gesichtsfelddefekten auf alltagsrelevante Tätigkeiten - Ergebnisse der TUTOR-Studie

by U. Schiefer, T. C. Kübler, M. Heister, K. Aehling, K. Sippel, E. Papageorgiou, W. Rosenstiel, and E. Tafaj

In 111. DOG-Kongress, 2013.

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Vishnoo - An Open-Source Software for Vision Research

by E. Tafaj, T. C. Kübler, J. Peter, U. Schiefer, and M. Bogdan

In 24th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2011), Bristol, UK, 2011.

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Research

Eyetrace

Eyetrace is a tool for analysis of eye-tracking data. It has the approach to bunch a variety of different evaluation methods for a large share of eye trackers supporting scientific work and medical diagnosis. To allow EyeTrace to be compatible to different eye trackers, an additional tool called Eyetrace Butler is used. The Eyetrace Butler performs a data preprocessing and conversion for analysis with Eyetrace. It provides plugins for different eye trackers and converts their data into a format that can be imported and used by Eyetrace.

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Scanpath Comparison

Our eye movements are driven by a continuous trade-off between the need for detailed examination of objects of interest and the necessity to keep an overview of our surrounding. In consequence, behavioral patterns that are characteristic for our actions and their planning are typically manifested in the way we move our eyes to interact with our environment. Identifying such patterns from individual eye movement measurements is however highly challenging.

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Vishnoo - A Visual Search Examination Tool

Vishnoo (Visual Search Examination Tool) is an integrated framework that combines configurable search tasks with gaze tracking capabilities, thus enabling the analysis of both, the visual field and the visual attention.

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Teaching

Course Term
Advanced Topics in Perception Engineering Summer 2017
Computational Models of Visual Attention Summer 2016
Technische Anwendungen der Informatik: Hard- und Software aktueller Eye-Tracking-Systeme Summer 2017
Technische Anwendungen der Informatik: Hard- und Software aktueller Eye-Tracking-Systeme Summer 2019
Technische Anwendungen der Informatik: Hard- und Software aktueller Eye-Tracking-Systeme Summer 2016
Eye Tracking in Mobile Computing and Virtual Reality Winter 2016

Open Thesis Topics

Saccade Bundles

This project is about applying (and probably adjusting) a linear time clustering algorithm for brain fiber activity to work with saccadic trajectories. The result will be a clustering of saccades (= saccade bundle).

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Gaze Counter

Während in der Online-Werbebranche die Erfolgskontrolle für eine bestimmte Werbeanzeige z.B. durch die Anzahl der Klicks oder eine Klick/Kauf-Rate relativ einfach durchgeführt werden kann, ist dies für Offline-Medien nicht immer ganz so einfach: Wie oft wird beispielsweise ein bestimmtes Plakat pro Tag betrachtet? Erregt ein Design mehr Aufmerksamkeit, als ein anderes? Ist ein höherer Preis für einen bestimmten Plakatstandort gerechtfertigt? Das Blickverhalten ist in der Werbebranche ein gängiger Indikator. Eye-Tracking Studien sind aber teuer und aufwändig auszuwerten.

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Crowd attention tracking

We want to be able to track eye and head movements of a crowd of people, such as a whole classroom. Thereby we can infer measures about current attentional focus, e.g. whether students pay attention to the lecture material and when attention decreases. Therefore we will record high resolution videos of multiple persons in a naturalistic setting, including a variety of head poses and eye positions.

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Automatisierter Scanpath Vergleich

Menschen können ihre Aufmerksamkeit gezielt lenken. Eine Methode diese Aufmerksamkeitszuweisung aufzuzeichnen sind Eye-Tracking Aufnahmen: Objekte, die momentan interessant sind, werden mit den Augen fixiert. Oftmals ist es nicht nur interessant, wohin einzelne Individuen ihre Aufmerksamkeit lenken, sondern auch ein Vergleich zwischen Individuen oder verschiedenen Zeitpunkten. Hierzu werden diese auf einfache Elemente reduziert: Fixationen und Sakkaden (schnelle Augenbewegungen). Die zeitliche Abfolge und räumliche Position von Fixationen und Sakkaden nennt man Scanpath. Aktuelle Vergleichsmetoden basieren auf zwei verschiedenen Ansätzen:

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Finished Thesis Topics

Vein extraction and eye rotation determination

The first step is setting up an recording environment with fixed subject position. This environment is used for data acquisition with predefined head rotations of the subjects. Based on this data an algorithm has to be developed measuring the eyeball rotation of the subject. The resulting angle is then compared and validated based on the head rotation.

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EyeTrace CUDA extesion

EyeTrace is a software for gaze data visualization and analysis. Due to the increasing amount of data these visualizations need more computation time. In this thesis existing visualizations should be implemented using CUDA for GPU computations. Additionally this includes a data storage model making it possible to shift the data between the GPU and the host computer. Due to the fact that nowadays not all computers have a CUDA capable card the modul should also allow CPU computations. This should be determined automatically by the module.

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Ein Dashboard für Eyetrace

Die Eyetrace Software bietet eine Vielzahl an Visualisierungsmöglchkeiten für Eye-Tracking Daten. In diesem Projekt soll eine grafisch ansprechende Übersicht über die momentan ins Programm geladenen Daten erzeugt werden.

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3D Eyeball generation based on vein motion

The first step is robust feature extraction. This can be done using SURF, SIFT, BRISK or MSER features if sufficient. Those features have to be mapped on features found in consecutive images. Based on the displacement a 3D model has to be computed. This model is used afterwards for gaze position estimation.

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