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Scalable Webcam Eye Tracking by Learning from User Interactions

Published:18 April 2015Publication History

ABSTRACT

Eye tracking systems are commonly used in a variety of research domains, but cost thousands of dollars. In my thesis I investigate a new approach to enable eye tracking for common webcams. The aim is to provide a natural experience to everyday users that are not restricted to laboratories and highly controlled studies. The accuracy of eye tracking webcams will be improved by user interactions which continuously calibrate the eye tracker during regular usage. Eye tracking can become a reality for many potential applications such as large-scale naturalistic user studies, online gaming, or enabling people to perform hands-free navigation of websites.

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  1. Scalable Webcam Eye Tracking by Learning from User Interactions

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    • Published in

      cover image ACM Conferences
      CHI EA '15: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems
      April 2015
      2546 pages
      ISBN:9781450331463
      DOI:10.1145/2702613

      Copyright © 2015 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 18 April 2015

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      Acceptance Rates

      CHI EA '15 Paper Acceptance Rate379of1,520submissions,25%Overall Acceptance Rate6,164of23,696submissions,26%

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      CHI '24
      CHI Conference on Human Factors in Computing Systems
      May 11 - 16, 2024
      Honolulu , HI , USA

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