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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.

We present the results of an MTurk survey (n = 383) on the reasons for using and not using biometric authentication systems on smartphones. We focused on Apple's Touch ID as well as Android's Face Unlock as they are the most prevalent systems on the market. For both systems, we categorized the participants as a) current users, b) former users that deactivated it at some point and c) nonusers. The results show that usability is one of the main factors that influences the decision on whether or not to use biometric verification on the smartphone. To our surprise and as opposed to previous research on biometric authentication, privacy and trust issues were not among the most important decision factors.

It is expected that projector phones (mobile phones with built-in pico projectors) will hit the market by 2010. Such phones provide a completely new way to display information and interaction techniques. The system presented in this paper allows the simulation of these projector phones as the real devices are not yet available. Through this, we demonstrate that it is currently possible to design, develop and evaluate applications for projector phones. The system supports three different modalities in order to compare when which display (phone display, projection) should be used. This prototype system was used for the implementation of two applications in order to test the advantages and disadvantages of projector phones for two common scenarios, picture browsing and map interaction. This demonstration paper describes the hardware used for the simulation of projector phones and the two developed prototypes. These prototypes were used for two different studies discussed in [1] and [2].

We describe three scenarios in which fallback authentication on smartphones can occur and evaluate their real-life occurrences in an online survey (n=244) and complementing interviews (n=12). The results provide first insights into frequencies, reasons, countermeasures taken and problems of lockout experiences. Overall, study participants were satisfied with current fallback schemes, but at the same time, fallback authentication was aggravated when special circumstances applied and thus, leave room for improvements. Based on this, we propose an alternative concept for fallback authentication that quizzes users about installed and not installed apps on their device. Authentication succeeds, when users identify a certain number of apps correctly. Our evaluation showed that the concept yields an overall accuracy of 95%.