TextPursuits

Abstract

Figure 1. We explore the use of text-based stimuli to enable gaze interaction with public displays using the Pursuits technique [47]. Motivated by the fact that much of the content on large displays is text, we investigate two use cases: (a) Users can spontaneously interact with text-based content without calibration. A sample application could be a survey where answers in the form of text are selected by reading them (left). (b) An eye tracker can be calibrated implicitly as users read text on the screen (right). After calibration, fine-grained information on the user's gaze point are obtained. ABSTRACTIn this paper we show how reading text on large display can be used to enable gaze interaction in public space. Our research is motivated by the fact that much of the content on public displays includes text. Hence, researchers and practitioners could greatly benefit from users being able to spontaneously interact as well as to implicitly calibrate an eye tracker while simply reading this text. In particular, we adapt Pursuits, a technique that correlates users' eye movements with moving on-screen targets. While prior work used abstract objects or dots as targets, we explore the use of Pursuits with text (read-and-pursue). Thereby we address the challenge that eye movements performed while reading interfere with the pursuit movements. Results from two user studies (N=37) show that Pursuits with text is feasible and can achieve similar accuracy as non text-based pursuit approaches. While calibration is less accurate, it integrates smoothly with reading and allows areas of the display the user is looking at to be identified.

VRpursuits

“…Pursuits was extensively studied in different interaction settings, including on public displays [17], wearables [5], and smart environments [35]. Virtual reality differs from these in a number of ways.…”

DialPlates

“…Similarly, Celebi et al [3] used Pursuits for eye tracker calibration. Khamis et al [19] used gradually revealing text to calibrate the eye tracker while users read-and-pursue.…”

Hidden pursuits

“…We used the Pearson correlation coefficient since it was shown to be robust to calibration errors and was widely tested in previous work [Khamis et al 2015[Khamis et al , 2016aVidal et al 2013]. Works that employ this approach consider the moving target to be gazed at if the correlation between the target's positions and the user's gaze are above a certain threshold.…”

“…Works that employ this approach consider the moving target to be gazed at if the correlation between the target's positions and the user's gaze are above a certain threshold. Similar to previous implementations of Pursuits [Esteves et al 2015;Khamis et al 2015Khamis et al , 2017Khamis et al , 2016aKosch et al 2018;Velloso et al 2017Velloso et al , 2016Vidal et al 2013], we use gaze estimates obtained using an uncalibrated eye tracker. We used the correlation coefficient to see how far the eye movements deviate from the target's trajectory while it is hiding.…”

“…We used the correlation coefficient to see how far the eye movements deviate from the target's trajectory while it is hiding. Inspired by previous work (e.g., [Khamis et al 2015[Khamis et al , 2016aVidal et al 2013]), we used a window size of 500 ms. All possible windows of 500 ms inside the entire cycle are considered. To avoid overlapping data, we take all gaze points into account that are within 500 ms until the condition switches from hidden to visible or vice versa.…”