Private Reader
Kirill Ragozin, Yun Suen Pai, Olivier Augereau, Koichi Kise, Jochen Kerdels, Kai S. Kunze · 2019
Reading in public spaces can often be tricky if we wish to keep the contents away from the prying eye. We propose Private Reader, an eye-tracking approach towards maintaining privacy while reading by rendering only the portion of text that is gazed by the reader. We conducted a user study by evaluating for both the reader and observer in terms of privacy, reading comfort, and reading speed for three reading modes; normal, underscored, and scrambled text. "Scrambled" performs best in terms of perceived effort and frustration for the shoulder surfer. Our contribution is threefold; we developed a system to preserve privacy by rendering only the text at gaze-point of the reader, we conducted a user study to evaluate user preferences and subjective task load, and we suggested several scenarios where Private Reader is useful in public spaces.