Human Computer Interaction

Prof. Dr. Enkelejda Kasneci

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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 - 74015
Telefax
+49 - (0) 70 71 - 29 - 50 62
E-Mail
enkelejda.kasneci@uni-tuebingen.de
Office
Sand 14, C221
Office hours
on appointment

Publications on Google Scholar

Research Interests

  • Eye-tracking methods and applications, especially eye tracking in the wild
  • Applied machine learning
  • Eye movements and driving
  • Autonomous driving and Driver Observation Technology
  • Eye movements and VR/AR

Academic Career

  • since 12/2015 Junior Professorship for Perception Engineering, Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • 09/2013 -11/2015 Senior Researcher Margarete-von-Wrangell-Fellowship, Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • 09/2008 - 09/2013 PhD defense in September 2013, Research assistant, Computer Engineering, Department of Computer Science, University of Tübingen, Tübingen, Germany.
  • 05/2007 - 09/2008 Research Assistant, Simulation of Large Systems, University of Stuttgart, Stuttgart, Germany
  • 04/2005 - 08/2005 Electronic Systems and Devices Group (Prof. B. Al-Hashimi), University of Southampton, UK.
  • 10/2001 - 03/2007 Studies of Computer Science, University of Stuttgart.

Invited Talks

  • 2017: Eye-Tracking während des Fahrens, OCG Jahresopening 2017, Vienna
  • 2016: It’s in your eyes – How eye tracking will shape our future, Ada-Lovelace-Festival, Berlin
  • 2016: Maschinelles Lernen und Eye-Tracking-Technologie zur Erforschung der Mechanismen der visuellen Wahrnehmung, INFORMATIK2016, Klagenfurt
  • 2015: Eye tracking in natural settings - Challenges and opportunities, Institut für Neuro- und Bioinformatik, Universität zu Lübeck
  • 2015: Arbitrarily shaped areas of interest based on gaze density gradient, European Conference on Eye Movements, ECEM 2015, Vienna
  • 2015: Exploiting the potential of eye movements analysis in the driving context, Perceptual User Interfaces Group, Max Planck Institute for Informatics, Saarbrücken
  • 2015: Eye movements and driving, Volkswagen Research Center, Wolfsburg
  • 2014: Online Eye-Tracking Data Analysis, SMI Vision, Research Center Berlin
  • 2013: Towards the Automated Recognition of Assistance Need for Drivers with Impaired Visual Field, Mercedes-Benz Technology Center Sindelfingen

Scholarships, Awards and Administrative Functions

Publications

Training Decision Trees as Replacement for Convolution Layers

by W. Fuhl, G. Kasneci, W. Rosenstiel, and E. Kasneci

In Conference on Artificial Intelligence, AAAI, 2020.

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Encodji: Encoding Gaze Data Into Emoji Space for an Amusing Scanpath Classification Approach ;)

by Wolfgang Fuhl, Efe Bozkir, Benedikt Hosp, Nora Castner, David Geisler, Thiago C., and Enkelejda Kasneci

In Eye Tracking Research and Applications, 2019.

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Person Independent, Privacy Preserving, and Real Time Assessment of Cognitive Load using Eye Tracking in a Virtual Reality Setup

by E. Bozkir, D. Geisler, and E. Kasneci

In The IEEE Conference on Virtual Reality and 3D User Interfaces (VR) Workshops, 2019.

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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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Get a Grip: Slippage-Robust and Glint-Free Gaze Estimation for Real-Time Pervasive Head-Mounted Eye Tracking

by T. Santini, D. Niehorster, and E. Kasneci

In Proceedings of the 2019 ACM Symposium on Eye Tracking Research & Applications (ETRA), 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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500,000 images closer to eyelid and pupil segmentation

by W. Fuhl, W. Rosenstiel, and E. Kasneci

In Computer Analysis of Images and Patterns, CAIP, 2019.

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RemoteEye: An Open Source remote Eye Tracker

by B. Hosp, S. Evazi, M. Maurer, W. Fuhl, and E. Kasneci

In Behavior Research Methods, BRM, 2019.

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The applicability of Cycle GANs for pupil and eyelid segmentation, data generation and image refinement

by W. Fuhl, D. Geisler, W. Rosenstiel, and E. Kasneci

In International Conference on Computer Vision Workshops, ICCVW, 2019.

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Learning to validate the quality of detected landmarks

by W. Fuhl and E. Kasneci

In International Conference on Machine Vision, ICMV, 2019.

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Assessment of Driver Attention During a Safety Critical Situation in VR to Generate VR-based Training

by E. Bozkir, D. Geisler, and E. Kasneci

In ACM Symposium on Applied Perception 2019, 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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Real-time 3D Glint Detection in Remote Eye Tracking Based on Bayesian Inference

by David Geisler, Dieter Fox, and Enkelejda Kasneci

In International Conference on Robotics and Automation (ICRA), 2018.

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PuRe: Robust Pupil Detection for Real-Time Pervasive Eye Tracking

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

In Elsevier Computer Vision and Image Understanding To Appear, 2018.

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The Art of Pervasive Eye Tracking: Unconstrained Eye Tracking in the Austrian Gallery Belvedere

by T. Santini, H. Brinkmann, L. Reistätter, H. Leder, R. Rosenberg, W. Rosenstiel, and E. Kasneci

In Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA): Adjunct publication – PETMEI 2018, 2018.

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Teachers’ Perception in the Classroom

by Ö. Sümer, P. Goldberg, K. Stürmer, T. Seidel, P. Gerjets, U. Trautwein, and E. Kasneci

In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2018.

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PuReST: Robust Pupil Tracking for Real-Time Pervasive Eye Tracking

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

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

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Overlooking: The nature of gaze behavior and anomaly detection in expert dentists

by Nora Castner, Solveig Klepper, Lena Kopnarski, Fabian Hüttig, Constanze Keutel, Katharina Scheiter, Juliane Richter, T. Eder, and Enkelejda Kasneci

In Workshop on Modeling Cognitive Processes from Multimodal Data (MCPMD’18 ), 2018.

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CBF:Circular binary features for robust and real-time pupil center detection

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

In ACM Symposium on Eye Tracking Research & Applications, 2018.

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Teachers’ Perception in the Classroom

by Ö. Sümer, P. Goldberg, K. Stürmer, T. Seidel, P. Gerjets, U. Trautwein, and E. Kasneci

In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2018.

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Development and Evaluation of a Gaze Feedback System Integrated into EyeTrace

by K. Otto, N. Castner, D. Geisler, and E. Kasneci

In Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA) , 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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MAM: Transfer learning for fully automatic video annotation and specialized detector creation

by W. Fuhl, N. Castner, L. Zhuang, M. Holzer, W. Rosenstiel, and E. Kasneci

In International Conference on Computer Vision Workshops, ICCVW, 2018.

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Eye movement velocity and gaze data generator for evaluation, robustness testing and assess of eye tracking software and visualization tools

by W. Fuhl and E. Kasneci

In Poster at Egocentric Perception, Interaction and Computing, EPIC, 2018.

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BORE: Boosted-oriented edge optimization for robust, real time remote pupil center detection

by W. Fuhl, S. Eivazi, B. Hosp, A. Eivazi, W. Rosenstiel, and E. Kasneci

In Eye Tracking Research and Applications, ETRA, 2018.

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Rule based learning for eye movement type detection

by W. Fuhl, N. Castner, and E. Kasneci

In International Conference on Multimodal Interaction Workshops, ICMIW, 2018.

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Histogram of oriented velocities for eye movement detection

by W. Fuhl, N. Castner, and E. Kasneci

In International Conference on Multimodal Interaction Workshops, ICMIW, 2018.

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Eye tracking as a tool to evaluate functional ability in everyday tasks in glaucoma

by E. Kasneci, A. A., and J. M.

In Journal of Ophthalmology Article ID 6425913, 2017.

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Saliency Sandbox: Bottom-Up Saliency Framework

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

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

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EyeRecToo: Open-Source Software for Real-Time Pervasive Head-Mounted Eye-Tracking

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

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

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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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Fast and Robust Eyelid Outline and Aperture Detection in Real-World Scenarios

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

In IEEE Winter Conference on Applications of Computer Vision (WACV 2017), 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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CalibMe: Fast and Unsupervised Eye Tracker Calibration for Gaze-Based Pervasive Human-Computer Interaction

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

In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017.

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Towards pervasive eye tracking

by E. Kasneci

In it-Information Technology, De Gruyter Oldenbourg, 2017.

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Using Eye Tracking to Evaluate and Develop Innovative Teaching Strategies for Fostering Image Reading Skills of Novices in Medical Training

by N. Castner, S. Eivazi, K. Scheiter, and E. Kasneci

In Eye Tracking Enhanced Learning (ETEL2017), 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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Towards Intelligent Surgical Microscopes: Surgeons Gaze and Instrument Tracking

by Shahram Eivazi, Wolfgang Fuhl, and Enkelejda Kasneci

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

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Towards automatic skill evaluation in microsurgery

by Shahram Eivazi, Michael Slupina, Wolfgang Fuhl, Hoorieh Afkari, Ahmad Hafez, and Enkelejda Kasneci

In Proceedings of the 22st International Conference on Intelligent User Interfaces, IUI 2017. ACM, 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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PupilNet v2.0: Convolutional Neural Networks for Robust Pupil Detection

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

In CoRR, 2017.

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Fast camera focus estimation for gaze-based focus control

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

In CoRR, 2017.

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Optimal eye movement strategies: a comparison of neurosurgeons gaze patterns when using a surgical microscope

by S. Eivazi, A. Hafez, W. Fuhl, H. Afkari, E. Kasneci, M. Lehecka, and R. Bednarik

In Acta Neurochirurgica, 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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3D Gaze Estimation Using Eye Vergence

by E.G. Mlot, H. Bahmani, S. Wahl, and E. Kasneci

In 9th International Conference on Health Informatics, Healthinf 2016, 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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On the necessity of adaptive eye movement classification in conditionally automated driving scenarios

by C. Braunagel, D. Geisler, W. Stolzmann, W. Rosenstiel, and E. Kasneci

In ACM Symposium on Eye Tracking Research & 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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Pupil detection for head-mounted eye tracking in the wild: An evaluation of the state of the art

by Wolfgang Fuhl, Marc Tonsen, Andreas Bulling, and Enkelejda Kasneci

In Machine Vision and Applications, pages 1-14, 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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Brightness- and Motion-Based Blink Detection for Head-Mounted Eye Trackers

by T. Appel, T. Santini, 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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Non-Intrusive Practitioner Pupil Detection for Unmodified Microscope Oculars

by W. Fuhl, T. Santini, C. Reichert, D. Claus, A. Herkommer, H. Bahmani, K. Rifai, S. Wahl, and E. Kasneci

In Elsevier Computers in Biology and Medicine 79: 36-44, 2016.

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Evaluation of State-of-the-Art Pupil Detection Algorithms on Remote Eye Images

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

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

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Feature-based attentional influences on the accommodation response

by H. Bahmani, W. Fuhl, E. Gutierrez, G. Kasneci, E. Kasneci, and S. Wahl

In Vision Sciences Society Annual Meeting Abstract, 2016.

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PupilNet: Convolutional Neural Networks for Robust Pupil Detection

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

In CoRR, 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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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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Driver-Activity Recognition in the Context of Conditionally Autonomous Driving

by C. Braunagel, E. Kasneci, W. Stolzmann, and W. Rosenstiel

In 18th International IEEE Conference on Intelligent Transportation Systems (ITSC 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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Driving with Binocular Visual Field Loss? A Study on a Supervised On-road Parcours with Simultaneous Eye and Head Tracking

by E. Kasneci, K. Sippel, K. Aehling, M. Heister, W. Rosenstiel, U. Schiefer, and E. Papageorgiou

In PLoS ONE 9(2): e87470, 2014.

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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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Binocular Glaucomatous Visual Field Loss and Its Impact on Visual Exploration - A Supermarket Study

by K. Sippel, E. Kasneci, K. Aehling, M. Heister, W. Rosenstiel, U. Schiefer, and E. Papageorgiou

In PLoS ONE 9(8): e106089, 2014.

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Homonymous Visual Field Loss and its Impact on Visual Exploration - A Supermarket Study

by E. Kasneci, K. Sippel, K. Aehling, M. Heister, W. Rosenstiel, U. Schiefer, and E. Papageorgiou

In Translational Vision Science & Technology In Press, 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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A New Method for Assessing the Exploratory Field of View (EFOV)

by E. Tafaj, S. Hempel, M. Heister, K. Aehling, J. Dietzsch, F. Schaeffel, W. Rosenstiel, and U. Schiefer

In 6th International Conference on Health Informatics, HEALTHINF 2013, 2013.

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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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Towards the Automated Recognition of Assistance Need for Drivers with Impaired Visual Field

by E. Kasneci

PhD thesis. Universität Tübingen, 2013.

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Erste Ergebnisse der TUTOR-Pilotstudie: Binokulare Gesichtsfeldausfälle und deren Auswirkungen auf die visuelle Exploration

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

In Ophthalmologische Nachrichten, 09.2012, 2012.

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Bayesian Online Clustering of Eye-Tracking Data

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

In Eye Tracking Research and Applications (ETRA 2012), 2012.

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Reliable Classification of visual field defects in automated perimetry using clustering

by E. Tafaj, J. Dietzsch, U. Schiefer, W. Rosenstiel, and M. Bogdan

In Proceedings 8th IASTED/IEEE International Conference on Biomedical Engineering, pages 446 - 451, 2011.

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Methode zur Messung der physiologischen Blendung im Fahrsimulator

by V. Melcher, M. Aust, O. Stefani, E. Lösch, H. Wilhelm, and E. Tafaj

In 57. Frühjahrskongress der Gesellschaft für Arbeitswissenschaft e. V.: "Mensch, Technik, Organisation - Vernetzung im Produktentstehungs- und -herstellungsprozess", Chemnitz, 03/2011, 2011.

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Fast extraction of neuron morphologies from large-scale electron-microscopic image stacks

by S. Lang, P. Drouvelis, E. Tafaj, P. Bastian, and B. Sakmann

In Journal of Computational Neuroscience, 2011.

[BIB]

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Zukünftige Fahrzeuge adaptieren sich auf den Fahrer: Identifikation charakteristischer Verhaltensmerkmale von Fahrzeugführern unter demographischen Gesichtspunkten

by E. Tafaj, P. Rumbolz, M. Bogdan, J. Wiedemann, and W. Rosenstiel

In GMM-Fachbericht Band 69 zur Tagung Automotive meets Electronics 2011, Dortmund, 2011.

[BIB]

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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.

[BIB]

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Mobile and fast detection of visual field defects for elderly drivers as a necessary input into driver assistance systems for mobility maintenance

by E. Tafaj, C. Uebber, J. Dietzsch, U. Schiefer, M. Bogdan, and W. Rosenstiel

In GMM-Fachbericht Band 64, AmE 2010 - Automotive meets Electronics, pages 47-52, 2010.

[BIB]

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Introduction of a Portable Campimeter Based on a Laptop/Tablet PC

by E. Tafaj, C. Uebber, J. Dietzsch, U. Schiefer, M. Bogdan, and W. Rosenstiel

In Proceedings of the 19th Imaging and Perimetry Society (IPS), Tenerife, Spain, 2010.

[BIB]

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Fahrzeugentwicklung für eine Gesellschaft im demografischen Wandel. H. Häfner, K. Beyreuther, W. Schlicht (Hrsg.). Altern gestalten, Medizin, Technik, Umwelt

by J. Wiedemann, M. Horn, W. Rosenstiel, and E. Tafaj

, pages 109-120. Springer-Verlag Berlin Heidelberg 2010, 2010.

[BIB]

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Research

Blink Detection

Blinks are an indicator for fatigue or drowsiness and can assist in the diagnose of mental disorders, such as schizophrenia. Additionally, a blink that obstructs the pupil impairs the performance of other eye-tracking algorithms, such as pupil detection, and often results in noise to the gaze estimation. The algorithm presented here, is tailored towards head-mounted eye trackers and is robust to calibration-based variations like translation or rotation of the eye. The proposed approach reached 96,35% accuracy for a realistic and challenging data set and in real-time even on low-end devices, rendering the proposed method suited for pervasive eye tracking.

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Eye labeling tool

Ground truth data is an important prerequisite for the development and evaluation of many algorithms in the area of computer vision, especially when these are based on convolutional neural networks or other machine learning approaches that unfold their power mostly by supervised learning. This learning relies on ground truth data, which is laborious, tedious, and error prone for humans to generate. In this paper, we contribute a labeling tool (EyeLad) specifically designed for remote eye-tracking data to enable researchers to leverage machine learning based approaches in this field, which is of great interest for the automotive, medical, and human-computer interaction applications. The tool is multi platform and supports a variety of state-of-theart detection and tracking algorithms, including eye detection, pupil detection, and eyelid coarse positioning.

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Eye Movements Identification

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EyeRecToo

Head-mounted eye tracking offers remarkable opportunities for research and applications regarding pervasive health monitoring, mental state inference, and human computer interaction in dynamic scenarios. Although a plethora of software for the acquisition of eye-tracking data exists, they often exhibit critical issues when pervasive eye tracking is considered, e.g., closed source, costly eye tracker hardware dependencies, and requiring a human supervisor for calibration. In this paper, we introduce EyeRecToo, an open-source software for real-time pervasive head-mounted eye-tracking. Out of the box, EyeRecToo offers multiple real-time state-of-the-art pupil detection and gaze estimation methods, which can be easily replaced by user implemented algorithms if desired. A novel calibration method that allows users to calibrate the system without the assistance of a human supervisor is also integrated. Moreover, this software supports multiple head-mounted eye-tracking hardware, records eye and scene videos, and stores pupil and gaze information, which are also available as a real-time stream. Thus, EyeRecToo serves as a framework to quickly enable pervasive eye-tracking research and applications.

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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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Intelligent Surgical Microscope

Head-mounted eye tracking offers remarkable opportunities for research and applications regarding pervasive health monitoring, mental state inference, and human computer interaction in dynamic scenarios. Although a plethora of software for the acquisition of eye-tracking data exists, they often exhibit critical issues when pervasive eye tracking is considered, e.g., closed source, costly eye tracker hardware dependencies, and requiring a human supervisor for calibration. In this paper, we introduce EyeRecToo, an open-source software for real-time pervasive head-mounted eye-tracking. Out of the box, EyeRecToo offers multiple real-time state-of-the-art pupil detection and gaze estimation methods, which can be easily replaced by user implemented algorithms if desired. A novel calibration method that allows users to calibrate the system without the assistance of a human supervisor is also integrated. Moreover, this software supports multiple head-mounted eye-tracking hardware, records eye and scene videos, and stores pupil and gaze information, which are also available as a real-time stream. Thus, EyeRecToo serves as a framework to quickly enable pervasive eye-tracking research and applications.

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Robust Pupil Detection and Gaze Estimation

The reliable estimation of the pupil position in eye images is perhaps the most important prerequisite in gaze-based HMI applications. While there are many approaches that enable accurate pupil tracking under laboratory conditions, tracking the pupil in real-world images is highly challenging due to changes in illumination, reflections on glasses or on the eyeball, off-axis camera position, contact lenses, and many more.

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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
Eye Movements and Visual Perception Winter 2016
Eye Movements and Visual Perception Winter 2019
Grundlagen der Multimediatechnik Winter 2019
Praktikum zu Grundlagen der Multimediatechnik Winter 2019
Programmieren mobiler eingebetteter Systeme Winter 2016
Programmieren mobiler eingebetteter Systeme Winter 2013
Programmieren mobiler eingebetteter Systeme Winter 2011
Programmieren mobiler eingebetteter Systeme Winter 2015
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
Seminar: Advanced Topics in Perception Engineering Summer 2019
Eye Tracking in Mobile Computing and Virtual Reality Winter 2016

Open Thesis Topics

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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News

New Website

The Perception Engineerung Group moves to a new website.

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