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Technical University of Munich

Evaluating and benchmarking webcam-based eye-tracking technologies

Key words: Webcam-based eye-tracking, benchmarking, comparative study

Eye-tracking allows to collect data of eye movements, which can be used to analyse cognitive processes such as reading difficulties. However, most high-quality eye-tracking technologies rely on dedicated hardware, limiting their accessibility and scalability. This is particularly challenging in educational technologies, where eye-tracking-based tools for learning and especially reading assessment should ideally function on standard consumer devices such as laptops or tablets, without sacrificing accuracy. In these areas, it is essential to obtain high-quality data using webcam-based eye-tracking systems. 

This thesis will conduct a comparative study comprising the following:

  • comprehensive systematic review of state-of-the-art webcam-based eye-tracking technologies
  • evaluating technologies with respect to their accuracy, data quality, accessibility, practical applicability, etc.
  • designing and conducting a small study to collect data from different technologies
  • benchmarking technologies based on collected data
  • optional: evaluation of respective potential in application domains such as educational technologies, particularly reading assessment

Prerequisites:

  • Computer Vision: Basic understanding of facial and eye movement detection, tracking algorithms, and video processing
  • Data Analysis: Basic knowledge of processing techniques for spatiotemporal data as well as fundamental skills in handling, analysing and interpreting eye-tracking data.
  • Software Development: Experience with programming languages (e.g. python, C++) and, optional but beneficial, common image processing libraries (e.g. OpenCV)
  • Ability to work on tasks independently, complete them in a structured and precise way, as well as present and discuss results comprehensible
  • Interested in learning (more) about eye-tracking technologies and their application in educational technologies

After completing this project, you’ll have

  • refined your skills in data analysis, benchmarking, academic literature review, and scientific writing
  • gained hands-on experience in designing, implementing, and conducting user studies for comparative evaluation
  • expanded and deepened your knowledge on online eye-tracking technologies, spatiotemporal data processing, and educational technologies

If you are interested in working on this project, please contact us with your CV and current ToR.

Franziska Kaltenberger (franziska.kaltenberger[at]tum.de)

Enkeleda Thaqi (enkeleda.thaqi[at]tum.de)

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