Prof. Dr. Enkelejda Kasneci
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
- enkelejda.kasneci@uni-tuebingen.de
- Office
- Sand 14, C221
- Office hours
- on appointment
Enkelejda Kasneci is a Professor of Computer Science at the University of Tübingen, Germany, where she leads the Human-Computer Interaction Lab. As a BOSCH scholar, she received her M.Sc. degree in Computer Science from the University of Stuttgart in 2007. In 2013, she received her PhD in Computer Science from the University of Tübingen. For her PhD research, she was awarded the research prize of the Federation Südwestmetall in 2014. From 2013 to 2015, she was a postdoctoral researcher and a Margarete-von-Wrangell Fellow at the University of Tübingen. Her research evolves around the application of machine learning for intelligent and perceptual human-computer interaction. She served as academic editor for PlosOne and as a TPC member and reviewer for several major conferences and journals.
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
Invited Talks
- 2020: ECCV 2020 OpenEyes: Eye Gaze in AR, VR and in the wild
- 2020: Closing Keynote at Augmented Human, AH 2020
- 2019: Machine Learning in Education, FernUni Hagen
- 2019: Keynote at the ACM Symposium on Eye Tracking Research and Applications, ETRA 2019
- 2019: Opening Keynote European Conference on Eye Movements, ECEM 2019
- 2018: Keynote on Cognitive Interfaces, Ada-Lovelace-Festival, Berlin
- 2018: Global Female Leaders Summit, Berlin
- 2017: Hub.Berlin
- 2017: Ada-Lovelace-Festival, Berlin
- 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
- 2020 Ruf auf eine W3 Professur an der TU Chemnitz (abgelehnt)
- Since 2019 Full member of DFG Cluster of Excellence - Machine Learning of Science
- since 2016 Associated Member of the Learning, Educational Achievement, and Life Course Development (LEAD), Graduate School and Research Network
- since 2016 Junior Fellow of the German Informatics Society (Gesellschaft für Informatik e.V. (GI))
- since 2016 Fast Track program of the Robert Bosch Stiftung (Excellence and Leadership Skills for Outstanding Women in Science)
- 2016 NVIDIA Hardware Grant
- 2014 - 2015 Margarete-von-Wrangell-Fellowship
- 2014 Südwestmetall-Förderpreis 2014 für Nachwuchswissenschaftler
- 2001-2007 Scholarship of the Robert-Bosch-Stiftung
Publications
Distilling Location Proposals of Unknown Objects Through Gaze Information for Human-Robot Interaction
2020
by Daniel Weber, Thiago Santini, Andreas Zell, and Enkelejda Kasneci
RemoteEye: An open-source high-speed remote eye tracker
mar, 2020
by Benedikt Hosp, Shahram Eivazi, Maximilian Maurer, Woflgang Fuhl, David Geisler, and Enkelejda Kasneci
Deep semantic gaze embedding and scanpath comparison for expertise classification during OPT viewing
2020
by Nora Castner, Thomas C Kübler, Juliane Richter, Therese Eder, Fabian Huettig, Constanze Keutel, and Enkelejda Kasneci
Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework
2020
by Efe Bozkir, Ali B. Uenal, Mete Akguen, Enkelejda Kasneci, and Nico Pfeifer
A Novel -Eye-Tracking Sensor for AR Glasses Based on Laser Self-Mixing Showing Exceptional Robustness Against Illumination
2020
by Johannes Meyer, Thomas Schlebusch, Hans Spruit, Jochen Hellmig, and Enkelejda Kasneci
Exploiting the GBVS for Saliency aware Gaze Heatmaps
2020
by David Geisler, Daniel Weber, Nora Castner, and Enkelejda Kasneci
A MinHash approach for fast scanpath classification
2020
by David Geisler, Nora Castner, Gjergji Kasneci, and Enkelejda Kasneci
Training Decision Trees as Replacement for Convolution Layers
feb, 2020
by W. Fuhl, G. Kasneci, W. Rosenstiel, and E. Kasneci
Tiny convolution, decision tree, and binary neuronal networks for robust and real time pupil outline estimation
jan, 2020
by W. Fuhl, H. Gao, and E. Kasneci
Neural networks for optical vector and eye ball parameter estimation
jan, 2020
by W. Fuhl, H. Gao, and E. Kasneci
A Novel Camera-Free Eye Tracking Sensor for Augmented Reality based on Laser Scanning
jul, 2020
by Johannes Meyer, Thomas Schlebusch, Wolfgang Fuhl, and Enkelejda Kasneci
Fully Convolutional Neural Networks for Raw Eye Tracking Data Segmentation, Generation, and Reconstruction
2020
by Wolfgang Fuhl, Yao Rong, and Kasneci Enkelejda
Explainable Online Validation of Machine Learning Models for Practical Applications
aug, 2020
by Wolfgang Fuhl and Enkelejda Kasneci
Multi Layer Neural Networks as Replacement for Pooling Operations
aug, 2020
by Wolfgang Fuhl, Yao Rong, Thomas Motz, Michael Scheidt, Andreas Hartel, Andreas Koch, and Enkelejda Kasneci
Reinforcement learning for the privacy preservation and manipulation of eye tracking data
aug, 2020
by Wolfgang Fuhl, Efe Bozkir, and Enkelejda Kasneci
Weight and Gradient Centralization in Deep Neural Networks
aug, 2020
by Wolfgang Fuhl and Enkelejda Kasneci
Rotated Ring, Radial and Depth Wise Separable Radial Convolutions
aug, 2020
by Wolfgang Fuhl and Enkelejda Kasneci
Pupil diameter differentiates expertise in dental radiography visual search
may, 2020
by Nora Castner, Tobias Appel, Thérése Eder, Juliane Richter, Katharina Scheiter, Constanze Keutel, Fabian Hüttig, Andrew Duchowski, and Enkelejda Kasneci
Driver Intention Anticipation Based on In-Cabin and Driving Scene Monitoring
2020
by Rong Yao, Akata Zeynep, and Kasneci Enkelejda
The display makes a difference: A mobile eye tracking study on the perception of art before and after a museum’s rearrangement
jun, 2020
by L. Reitstätter, H. Brinkmann, T. Santini, E. Specker, Z. Dare, F. Bakondi, A. Miscená, E. Kasneci, H. Leder, and R. Rosenberg
Camera-Free Eye Tracking Sensor for Augmented Reality based on Laser Scanning
jul, 2020
by J. Meyer, T. Schlebusch, W. Fuhl, and E. Kasneci
Encodji: Encoding Gaze Data Into Emoji Space for an Amusing Scanpath Classification Approach ;)
2019
by Wolfgang Fuhl, Efe Bozkir, Benedikt Hosp, Nora Castner, David Geisler, Thiago C., and Enkelejda Kasneci
Person Independent, Privacy Preserving, and Real Time Assessment of Cognitive Load using Eye Tracking in a Virtual Reality Setup
mar, 2019
by E. Bozkir, D. Geisler, and E. Kasneci
Improving Real-Time CNN-Based Pupil Detection Through Domain-Specific Data Augmentation
jun, 2019
by S. Eivazi, T. Santini, A. Keshavarzi, T. C. Kübler, and A. Mazzei
Get a Grip: Slippage-Robust and Glint-Free Gaze Estimation for Real-Time Pervasive Head-Mounted Eye Tracking
jun, 2019
by T. Santini, D. Niehorster, and E. Kasneci
Ferns for area of interest free scanpath classification
jun, 2019
by W. Fuhl, N. Castner, T. C. Kübler, A. Lotz, W. Rosenstiel, and E. Kasneci
500,000 images closer to eyelid and pupil segmentation
nov, 2019
by W. Fuhl, W. Rosenstiel, and E. Kasneci
RemoteEye: An Open Source remote Eye Tracker
dec, 2019
by B. Hosp, S. Evazi, M. Maurer, W. Fuhl, and E. Kasneci
The applicability of Cycle GANs for pupil and eyelid segmentation, data generation and image refinement
nov, 2019
by W. Fuhl, D. Geisler, W. Rosenstiel, and E. Kasneci
Assessment of Driver Attention During a Safety Critical Situation in VR to Generate VR-based Training
sep, 2019
by E. Bozkir, D. Geisler, and E. Kasneci
Eye-Hand Behavior in Human-Robot Shared Manipulation
mar, 2018
by R. M., T. Santini, T. C. Kübler, E. Kasneci, S. Srinivasa, and H. Admoni
Real-time 3D Glint Detection in Remote Eye Tracking Based on Bayesian Inference
may, 2018
by David Geisler, Dieter Fox, and Enkelejda Kasneci
PuRe: Robust Pupil Detection for Real-Time Pervasive Eye Tracking
may, 2018
by T. Santini, W. Fuhl, and E. Kasneci
The Art of Pervasive Eye Tracking: Unconstrained Eye Tracking in the Austrian Gallery Belvedere
jun, 2018
by T. Santini, H. Brinkmann, L. Reistätter, H. Leder, R. Rosenberg, W. Rosenstiel, and E. Kasneci
Teachers’ Perception in the Classroom
jun, 2018
by Ö. Sümer, P. Goldberg, K. Stürmer, T. Seidel, P. Gerjets, U. Trautwein, and E. Kasneci
PuReST: Robust Pupil Tracking for Real-Time Pervasive Eye Tracking
jun, 2018
by T. Santini, W. Fuhl, and E. Kasneci
Overlooking: The nature of gaze behavior and anomaly detection in expert dentists
oct, 2018
by Nora Castner, Solveig Klepper, Lena Kopnarski, Fabian Hüttig, Constanze Keutel, Katharina Scheiter, Juliane Richter, T. Eder, and Enkelejda Kasneci
CBF:Circular binary features for robust and real-time pupil center detection
jun, 2018
by W. Fuhl, D. Geisler, T. Santini, T. Appel, W. Rosenstiel, and E. Kasneci
Teachers’ Perception in the Classroom
jun, 2018
by Ö. Sümer, P. Goldberg, K. Stürmer, T. Seidel, P. Gerjets, U. Trautwein, and E. Kasneci
Development and Evaluation of a Gaze Feedback System Integrated into EyeTrace
jun, 2018
by K. Otto, N. Castner, D. Geisler, and E. Kasneci
An Inconspicuous and Modular Head-Mounted Eye Tracker
jun, 2018
by S. Eivazi, T. Kübler, T. Santini, and E. Kasneci
Automatic generation of saliency-based areas of interest
sep, 2018
by W. Fuhl, T. Kübler, T. Santini, and E. Kasneci
Region of interest generation algorithms for eye tracking data
jun, 2018
by W. Fuhl, T. C. Kübler, H. Brinkmann, R. Rosenberg, W. Rosenstiel, and E. Kasneci
Scanpath comparison in medical image reading skills of dental students
jun, 2018
by N. Castner, E. Kasneci, T. C. Kübler, K. Scheiter, and J. Richter
MAM: Transfer learning for fully automatic video annotation and specialized detector creation
2018
by W. Fuhl, N. Castner, L. Zhuang, M. Holzer, W. Rosenstiel, and E. Kasneci
Eye movement velocity and gaze data generator for evaluation, robustness testing and assess of eye tracking software and visualization tools
2018
by W. Fuhl and E. Kasneci
BORE: Boosted-oriented edge optimization for robust, real time remote pupil center detection
2018
by W. Fuhl, S. Eivazi, B. Hosp, A. Eivazi, W. Rosenstiel, and E. Kasneci
Rule based learning for eye movement type detection
2018
by W. Fuhl, N. Castner, and E. Kasneci
Histogram of oriented velocities for eye movement detection
2018
by W. Fuhl, N. Castner, and E. Kasneci
Eye movement simulation and detector creation to reduce laborious parameter adjustments
2018
by W. Fuhl, T. Santini, T. Kuebler, N. Castner, W. Rosenstiel, and E. Kasneci
Online recognition of driver-activity based on visual scanpath classification
2017
by Christian Braunagel, David Geisler, Wolfgang Rosenstiel, and Enkelejda Kasneci
Eye tracking as a tool to evaluate functional ability in everyday tasks in glaucoma
2017
by E. Kasneci, A. A., and J. M.
Saliency Sandbox: Bottom-Up Saliency Framework
feb, 2017
by D. Geisler, W. Fuhl, T. Santini, and E. Kasneci
EyeRecToo: Open-Source Software for Real-Time Pervasive Head-Mounted Eye-Tracking
feb, 2017
by T. Santini, W. Fuhl, D. Geisler, and E. Kasneci
EyeLad: Remote Eye Tracking Image Labeling Tool
feb, 2017
by W. Fuhl, T. Santini, D. Geisler, T. C. Kübler, and E. Kasneci
Fast and Robust Eyelid Outline and Aperture Detection in Real-World Scenarios
mar, 2017
by W. Fuhl, T. Santini, and E. Kasneci
Aggregating physiological and eye tracking signals to predict perception in the absence of ground truth
mar, 2017
by E. Kasneci, T. C. Kübler, K. Broelemann, and G. Kasneci
Ways of improving the precision of eye tracking data: Controlling the influence of dirt and dust on pupil detection
may, 2017
by W. Fuhl, T. C. Kübler, D. Hospach, O. Bringmann, W. Rosenstiel, and E. Kasneci
CalibMe: Fast and Unsupervised Eye Tracker Calibration for Gaze-Based Pervasive Human-Computer Interaction
may, 2017
by T. Santini, W. Fuhl, and E. Kasneci
Using Eye Tracking to Evaluate and Develop Innovative Teaching Strategies for Fostering Image Reading Skills of Novices in Medical Training
sep, 2017
by N. Castner, S. Eivazi, K. Scheiter, and E. Kasneci
Automatic Mapping of Remote Crowd Gaze to Stimuli in the Classroom
sep, 2017
by T. Santini, T. C. Kübler, L. Draghetti, P. Gerjets, W. Wagner, U. Trautwein, and E. Kasneci
Towards Intelligent Surgical Microscopes: Surgeons Gaze and Instrument Tracking
mar, 2017
by Shahram Eivazi, Wolfgang Fuhl, and Enkelejda Kasneci
Towards automatic skill evaluation in microsurgery
mar, 2017
by Shahram Eivazi, Michael Slupina, Wolfgang Fuhl, Hoorieh Afkari, Ahmad Hafez, and Enkelejda Kasneci
Monitoring Response Quality During Campimetry Via Eye-Tracking
mar, 2017
by G. Dambros, J. Ungewiss, T. C. Kübler, E. Kasneci, and M. Spüler
PupilNet v2.0: Convolutional Neural Networks for Robust Pupil Detection
2017
by W. Fuhl, T. Santini, G. Kasneci, and E. Kasneci
Fast camera focus estimation for gaze-based focus control
2017
by W. Fuhl, T. Santini, and E. Kasneci
Optimal eye movement strategies: a comparison of neurosurgeons gaze patterns when using a surgical microscope
2017
by S. Eivazi, A. Hafez, W. Fuhl, H. Afkari, E. Kasneci, M. Lehecka, and R. Bednarik
EyeRec: An Open-source Data Acquisition Software for Head-mounted Eye-tracking
feb, 2016
by T. Santini, W. Fuhl, T. C. Kübler, and E. Kasneci
3D Gaze Estimation Using Eye Vergence
feb, 2016
by E.G. Mlot, H. Bahmani, S. Wahl, and E. Kasneci
Rendering refraction and reflection of eyeglasses for synthetic eye tracker images
mar, 2016
by T. C. Kübler, T. Rittig, J. Ungewiss, C. Krauss, and E. Kasneci
On the necessity of adaptive eye movement classification in conditionally automated driving scenarios
mar, 2016
by C. Braunagel, D. Geisler, W. Stolzmann, W. Rosenstiel, and E. Kasneci
ElSe: Ellipse Selection for Robust Pupil Detection in Real-World Environments
mar, 2016
by W. Fuhl, T. Santini, T. C. Kübler, and E. Kasneci
Bayesian Identification of Fixations, Saccades, and Smooth Pursuits
mar, 2016
by T. Santini, W. Fuhl, T. C. Kübler, and E. Kasneci
Pupil detection for head-mounted eye tracking in the wild: An evaluation of the state of the art
jun, 2016
by Wolfgang Fuhl, Marc Tonsen, Andreas Bulling, and Enkelejda Kasneci
SubsMatch 2.0: Scanpath comparison and classification based on subsequence frequencies
jul, 2016
by T. C. Kübler, C. Rothe, U. Schiefer, W. Rosenstiel, and E. Kasneci
Eyes Wide Open? Eyelid Location and Eye Aperture Estimation for Pervasive Eye Tracking in Real-World Scenarios
sep, 2016
by W. Fuhl, T. Santini, D. Geisler, T. C. Kübler, W. Rosenstiel, and E. Kasneci
Brightness- and Motion-Based Blink Detection for Head-Mounted Eye Trackers
sep, 2016
by T. Appel, T. Santini, and E. Kasneci
Novel methods for analysis and visualization of saccade trajectories
oct, 2016
by T. C. Kübler, W. Fuhl, R. Rosenberg, W. Rosenstiel, and E. Kasneci
Non-Intrusive Practitioner Pupil Detection for Unmodified Microscope Oculars
dec, 2016
by W. Fuhl, T. Santini, C. Reichert, D. Claus, A. Herkommer, H. Bahmani, K. Rifai, S. Wahl, and E. Kasneci
Evaluation of State-of-the-Art Pupil Detection Algorithms on Remote Eye Images
sep, 2016
by W. Fuhl, D. Geisler, T. Santini, and E. Kasneci
Feature-based attentional influences on the accommodation response
2016
by H. Bahmani, W. Fuhl, E. Gutierrez, G. Kasneci, E. Kasneci, and S. Wahl
PupilNet: Convolutional Neural Networks for Robust Pupil Detection
2016
by W. Fuhl, T. Santini, G. Kasneci, and E. Kasneci
Towards Automated Scan Pattern Analysis for Dynamic Scenes
2015
by J. Ungewiss, T. C. Kübler, D.R. Bukenberger, E. Kasneci, and U. Schiefer
Online Recognition of Fixations, Saccades, and Smooth Pursuits for Automated Analysis of Traffic Hazard Perception
2015
by E. Kasneci, G. Kasneci, T. C. Kübler, and W. Rosenstiel
Analysis of eye movements with Eyetrace
2015
by T. C. Kübler, K. Sippel, W. Fuhl, G. Schievelbein, J. Aufreiter, R. Rosenberg, W. Rosenstiel, and E. Kasneci
Exploiting the potential of eye movements analysis in the driving context
mar, 2015
by E. Kasneci, T. C. Kübler, C. Braunagel, W. Fuhl, W. Stolzmann, and W. Rosenstiel
ExCuSe: Robust Pupil Detection in Real-World Scenarios
sep, 2015
by W. Fuhl, T. C. Kübler, K. Sippel, W. Rosenstiel, and E. Kasneci
Driver-Activity Recognition in the Context of Conditionally Autonomous Driving
sep, 2015
by C. Braunagel, E. Kasneci, W. Stolzmann, and W. Rosenstiel
Automated Visual Scanpath Analysis Reveals the Expertise Level of Micro-neurosurgeons
oct, 2015
by T. C. Kübler, S. Eivazi, and E. Kasneci
Driving with Glaucoma: Task Performance and Gaze Movements
nov, 2015
by T. C. Kübler, E. Kasneci, K. Aehling, M. Heister, W. Rosenstiel, U. Schiefer, and E. Papageorgiou
Driving with Homonymous Visual Field Defects: Driving Performance and Compensatory Gaze Movements
dec, 2015
by T. C. Kübler, E. Kasneci, W. Rosenstiel, K. Aehling, M. Heister, K. Nagel, U. Schiefer, and E. Papageorgiou
Arbitrarily shaped areas of interest based on gaze density gradient
aug, 2015
by W. Fuhl, T. C. Kübler, K. Sippel, W. Rosenstiel, and E. Kasneci
Driving with Binocular Visual Field Loss? A Study on a Supervised On-road Parcours with Simultaneous Eye and Head Tracking
feb, 2014
by E. Kasneci, K. Sippel, K. Aehling, M. Heister, W. Rosenstiel, U. Schiefer, and E. Papageorgiou
The Applicability of Probabilistic Methods to the Online Recognition of Fixations and Saccades in Dynamic Scenes
mar, 2014
by E. Kasneci, G. Kasneci, T. C. Kübler, and W. Rosenstiel
SubsMatch: Scanpath Similarity in Dynamic Scenes based on Subsequence Frequencies
mar, 2014
by T. C. Kübler, E. Kasneci, and W. Rosenstiel
Rule-based classification of visual field defects
mar, 2014
by E. Kasneci, G. Kasneci, U. Schiefer, and W. Rosenstiel
Gaze guidance for the visually impaired
mar, 2014
by T. C. Kübler, E. Kasneci, and W. Rosenstiel
Stress-indicators and exploratory gaze for the analysis of hazard perception in patients with visual field loss
may, 2014
by T. C. Kübler, E. Kasneci, W. Rosenstiel, U. Schiefer, K. Nagel, and E. Papageorgiou
Binocular Glaucomatous Visual Field Loss and Its Impact on Visual Exploration - A Supermarket Study
aug, 2014
by K. Sippel, E. Kasneci, K. Aehling, M. Heister, W. Rosenstiel, U. Schiefer, and E. Papageorgiou
Homonymous Visual Field Loss and its Impact on Visual Exploration - A Supermarket Study
sep, 2014
by E. Kasneci, K. Sippel, K. Aehling, M. Heister, W. Rosenstiel, U. Schiefer, and E. Papageorgiou
Towards automated comparison of eye-tracking recordings in dynamic scenes
dec, 2014
by T. C. Kübler, D. R., J. Ungewiss, A. Wörner, C. Rothe, U. Schiefer, W. Rosenstiel, and E. Kasneci
A New Method for Assessing the Exploratory Field of View (EFOV)
feb, 2013
by E. Tafaj, S. Hempel, M. Heister, K. Aehling, J. Dietzsch, F. Schaeffel, W. Rosenstiel, and U. Schiefer
Online Classification of Eye Tracking Data for Automated Analysis of Traffic Hazard Perception
sep, 2013
by E. Tafaj, T. C. Kübler, G. Kasneci, W. Rosenstiel, and M. Bogdan
Auswirkungen des visuellen Explorationsverhaltens von Patienten mit binokularen Gesichtsfelddefekten auf alltagsrelevante Tätigkeiten - Ergebnisse der TUTOR-Studie
sep, 2013
by U. Schiefer, T. C. Kübler, M. Heister, K. Aehling, K. Sippel, E. Papageorgiou, W. Rosenstiel, and E. Tafaj
Towards the Automated Recognition of Assistance Need for Drivers with Impaired Visual Field
oct, 2013
by E. Kasneci
Erste Ergebnisse der TUTOR-Pilotstudie: Binokulare Gesichtsfeldausfälle und deren Auswirkungen auf die visuelle Exploration
2012
by U. Schiefer, K. Sippel, M. Heister, K. Aehling, C. Heine, K. Januschowski, E. Papageorgiou, W. Rosenstiel, and E. Tafaj
Bayesian Online Clustering of Eye-Tracking Data
2012
by E. Tafaj, G. Kasneci, W. Rosenstiel, and M. Bogdan
Reliable Classification of visual field defects in automated perimetry using clustering
feb, 2011
by E. Tafaj, J. Dietzsch, U. Schiefer, W. Rosenstiel, and M. Bogdan
Methode zur Messung der physiologischen Blendung im Fahrsimulator
mar, 2011
by V. Melcher, M. Aust, O. Stefani, E. Lösch, H. Wilhelm, and E. Tafaj
Fast extraction of neuron morphologies from large-scale electron-microscopic image stacks
mar, 2011
by S. Lang, P. Drouvelis, E. Tafaj, P. Bastian, and B. Sakmann
Zukünftige Fahrzeuge adaptieren sich auf den Fahrer: Identifikation charakteristischer Verhaltensmerkmale von Fahrzeugführern unter demographischen Gesichtspunkten
apr, 2011
by E. Tafaj, P. Rumbolz, M. Bogdan, J. Wiedemann, and W. Rosenstiel
Vishnoo - An Open-Source Software for Vision Research
jun, 2011
by E. Tafaj, T. C. Kübler, J. Peter, U. Schiefer, and M. Bogdan
Mobile and fast detection of visual field defects for elderly drivers as a necessary input into driver assistance systems for mobility maintenance
2010
by E. Tafaj, C. Uebber, J. Dietzsch, U. Schiefer, M. Bogdan, and W. Rosenstiel
Introduction of a Portable Campimeter Based on a Laptop/Tablet PC
2010
by E. Tafaj, C. Uebber, J. Dietzsch, U. Schiefer, M. Bogdan, and W. Rosenstiel
Fahrzeugentwicklung für eine Gesellschaft im demografischen Wandel. H. Häfner, K. Beyreuther, W. Schlicht (Hrsg.). Altern gestalten, Medizin, Technik, Umwelt
2010
by J. Wiedemann, M. Horn, W. Rosenstiel, and E. Tafaj
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.
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.
Eye Movements Identification
In this paper, we use fully convolutional neural networks for the semantic segmentation of eye tracking data. We also use these networks for reconstruction, and in conjunction with a variational auto-encoder to generate eye movement data. The first improvement of our approach is that no input window is necessary, due to the use of fully convolutional networks and therefore any input size can be processed directly. The second improvement is that the used and generated data is raw eye tracking data (position X, Y and time) without preprocessing. This is achieved by pre-initializing the filters in the first layer and by building the input tensor along the z axis. We evaluated our approach on three publicly available datasets and compare the results to the state of the art.
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.
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.
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.
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.
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.
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.
