Human Computer Interaction

Dr. Shahram Eivazi

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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 - 70494
Telefax
+49 - (0) 70 71 - 29 - 50 62
E-Mail
shahram.eivazi@uni-tuebingen.de
Office
Sand 14, C220
Office hours
on appointment

Research Interests

  • Eye tracking
  • Machine vision
  • Machine learning
  • HCI and Human factors
  • Medical technology
  • Micro-neurosurgery
  • Robotic

Current Projects

  1. EyeMic, a binocular eye tracker that can be attached on top of any microscope ocular. (Video link)
    This is the first step towards unrestricted eye tracking in microscopy procedures for development of future gaze-contingent microscope control systems.
    EyeMic, a binocular eye tracker that can be attached on top of any microscope ocular
    Video

  2. A Head and Eye Tracking method for Hands-free Control of a Robotic system. (video link)
    We are developing a head and gaze-contingent robotic exoscope for camera viewpoint automation. A Head and Eye Tracking method for Hands-free Control of a Robotic system
    Video

  3. Gaze-Telesurgery for the SECTIO CHIRURGICA platform. Here we are developing a live gaze tracking system to be used for online training of surgeons.
    Gaze-Telesurgery for the SECTIO CHIRURGICA platform

Publications

2020

RemoteEye: An open-source high-speed remote eye tracker

Benedikt Hosp, Shahram Eivazi, Maximilian Maurer, Woflgang Fuhl, David Geisler, and Enkelejda Kasneci. Behavior Research Methods, pages 1–15. Springer, 2020.

PDF BIB

Eye Tracking Data Collection Protocol for VR for Remotely Located Subjects using Blockchain and Smart Contracts

Efe Bozkir, Shahram Eivazi, Mete Akgün, and Enkelejda Kasneci. IEEE International Conference on Artifical Intelligence and Virtual Reality (AIVR), – To Appear in Work-in-Progress papers, 2020.

BIB

2019

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

S. Eivazi, T. Santini, A. Keshavarzi, T. C. Kübler, and A. Mazzei. Proceedings of the 2019 ACM Symposium on Eye Tracking Research & Applications (ETRA) – To Appear, 2019.

PDF BIB

2018

An Inconspicuous and Modular Head-Mounted Eye Tracker

S. Eivazi, T. Kübler, T. Santini, and E. Kasneci. Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA) , 2018.

BIB

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

W. Fuhl, S. Eivazi, B. Hosp, A. Eivazi, W. Rosenstiel, and E. Kasneci. Eye Tracking Research and Applications, ETRA, 2018.

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2017

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

N. Castner, S. Eivazi, K. Scheiter, and E. Kasneci. Eye Tracking Enhanced Learning (ETEL2017), 2017.

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Towards Intelligent Surgical Microscopes: Surgeons Gaze and Instrument Tracking

Shahram Eivazi, Wolfgang Fuhl, and Enkelejda Kasneci. Proceedings of the 22st International Conference on Intelligent User Interfaces, IUI 2017. ACM, 2017.

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Towards automatic skill evaluation in microsurgery

Shahram Eivazi, Michael Slupina, Wolfgang Fuhl, Hoorieh Afkari, Ahmad Hafez, and Enkelejda Kasneci. Proceedings of the 22st International Conference on Intelligent User Interfaces, IUI 2017. ACM, 2017.

PDF BIB

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

S. Eivazi, A. Hafez, W. Fuhl, H. Afkari, E. Kasneci, M. Lehecka, and R. Bednarik. Acta Neurochirurgica, 2017.

PDF BIB

2015

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

T. C. Kübler, S. Eivazi, and E. Kasneci. MICCAI 15 Workshop on Interventional Microscopy, 2015.

PDF BIB

Research

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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