A robust algorithm for reading detection
Christopher S. Campbell, Paul P. Maglio · 2001
As video cameras become cheaper and more pervasive, there is now increased opportunity for user interfaces to take advantage of user gaze data. Eye movements provide a powerful source of information that can be used to determine user intentions and interests. In this paper, we develop and test a method for recognizing when users are reading text based solely on eye-movement data. The experimental results show that our reading detection method is robust to noise, individual differences, and variations in text difficulty. Compared to a simple detection algorithm, our algorithm reliably, quickly, and accurately recognizes and tracks reading. Thus, we provide a means to capture normal user activity, enabling interfaces that incorporate more natural interactions of human and computer.