EyeScout: Active Eye Tracking for Position and Movement Independent Gaze Interaction with Large Public Displays

While gaze holds a lot of promise for hands-free interaction with public displays, remote eye trackers with their confined tracking box restrict users to a single stationary position in front of the display. We present EyeScout, an active eye tracking system that combines an eye tracker mounted on a rail system with a computational method to automatically detect and align the tracker with the user's lateral movement. EyeScout addresses key limitations of current gaze-enabled large public displays by offering two novel gaze-interaction modes for a single user: In "Walk then Interact" the user can walk up to an arbitrary position in front of the display and interact, while in "Walk and Interact" the user can interact even while on the move. We report on a user study that shows that EyeScout is well perceived by users, extends a public display's sweet spot into a sweet line, and reduces gaze interaction kick-off time to 3.5 seconds -- a 62% improvement over state of the art solutions. We discuss sample applications that demonstrate how EyeScout can enable position and movement-independent gaze interaction with large public displays

GazeTouchPass: Multimodal Authentication Using Gaze and Touch on Mobile Devices

We propose a multimodal scheme, GazeTouchPass, that combines gaze and touch for shoulder-surfing resistant user authentication on mobile devices. GazeTouchPass allows passwords with multiple switches between input modalities during authentication. This requires attackers to simultaneously observe the device screen and the user's eyes to find the password. We evaluate the security and usability of GazeTouchPass in two user studies. Our findings show that GazeTouchPass is usable and significantly more secure than single-modal authentication against basic and even advanced shoulder-surfing attacks

VRpursuits: Interaction in Virtual Reality Using Smooth Pursuit Eye Movements

Gaze-based interaction using smooth pursuit eye movements (Pursuits) is attractive given that it is intuitive and overcomes the Midas touch problem. At the same time, eye tracking is becoming increasingly popular for VR applications. While Pursuits was shown to be effective in several interaction contexts, it was never explored in-depth for VR before. In a user study (N=26), we investigated how parameters that are specific to VR settings influence the performance of Pursuits. For example, we found that Pursuits is robust against different sizes of virtual 3D targets. However performance improves when the trajectory size (e.g., radius) is larger, particularly if the user is walking while interacting. While walking, selecting moving targets via Pursuits is generally feasible albeit less accurate than when stationary. Finally, we discuss the implications of these findings and the potential of smooth pursuits for interaction in VR by demonstrating two sample use cases: 1) gaze-based authentication in VR, and 2) a space meteors shooting game

Hidden Pursuits: Evaluating Gaze-selection via Pursuits when the Stimuli's Trajectory is Partially Hidden

The idea behind gaze interaction using Pursuits is to leverage the human's smooth pursuit eye movements performed when following moving targets. However, humans can also anticipate where a moving target would reappear if it temporarily hides from their view. In this work, we investigate how well users can select targets using Pursuits in cases where the target's trajectory is partially invisible (HiddenPursuits): e.g., can users select a moving target that temporarily hides behind another object? Although HiddenPursuits was not studied in the context of interaction before, understanding how well users can perform HiddenPursuits presents numerous opportunities, particularly for small interfaces where a target's trajectory can cover area outside of the screen. We found that users can still select targets quickly via Pursuits even if their trajectory is up to 50% hidden, and at the expense of longer selection times when the hidden portion is larger. We discuss how gaze-based interfaces can leverage HiddenPursuits for an improved user experience

EyePACT: eye-based parallax correction on touch-enabled interactive displays

The parallax effect describes the displacement between the perceived and detected touch locations on a touch-enabled surface. Parallax is a key usability challenge for interactive displays, particularly for those that require thick layers of glass between the screen and the touch surface to protect them from vandalism. To address this challenge, we present EyePACT, a method that compensates for input error caused by parallax on public displays. Our method uses a display-mounted depth camera to detect the user's 3D eye position in front of the display and the detected touch location to predict the perceived touch location on the surface. We evaluate our method in two user studies in terms of parallax correction performance as well as multi-user support. Our evaluations demonstrate that EyePACT (1) significantly improves accuracy even with varying gap distances between the touch surface and the display, (2) adapts to different levels of parallax by resulting in significantly larger corrections with larger gap distances, and (3) maintains a significantly large distance between two users' fingers when interacting with the same object. These findings are promising for the development of future parallax-free interactive displays

GazeDrone: Mobile Eye-Based Interaction in Public Space Without Augmenting the User

Gaze interaction holds a lot of promise for seamless human-computer interaction. At the same time, current wearable mobile eye trackers require user augmentation that negatively impacts natural user behavior while remote trackers require users to position themselves within a confined tracking range. We present GazeDrone, the first system that combines a camera-equipped aerial drone with a computational method to detect sidelong glances for spontaneous (calibration-free) gaze-based interaction with surrounding pervasive systems (e.g., public displays). GazeDrone does not require augmenting each user with on-body sensors and allows interaction from arbitrary positions, even while moving. We demonstrate that drone-supported gaze interaction is feasible and accurate for certain movement types. It is well-perceived by users, in particular while interacting from a fixed position as well as while moving orthogonally or diagonally to a display. We present design implications and discuss opportunities and challenges for drone-supported gaze interaction in public

DialPlate: Enhancing the Detection of Smooth Pursuits Eye Movements Using Linear Regression

We introduce and evaluate a novel approach for detecting smooth pursuit eye movements that increases the number of distinguishable targets and is more robust against false positives. Being natural and calibration-free, Pursuits has been gaining popularity in the past years. At the same time, current implementations show poor performance when more than eight on-screen targets are being used, thus limiting its applicability. Our approach (1) leverages the slope of a regression line, and (2) introduces a minimum signal duration that improves both the new and the traditional detection method. After introducing the approach as well as the implementation, we compare it to the traditional correlation-based Pursuits detection method. We tested the approach up to 24 targets and show that, if accepting a similar error rate, nearly twice as many targets can be distinguished compared to state of the art. For fewer targets, accuracy increases significantly. We believe our approach will enable more robust pursuit-based user interfaces, thus making it valuable for both researchers and practitioners

DialPlates: Enabling Pursuits-based User Interfaces with Large Target Numbers

In this paper we introduce a novel approach for smooth pursuits eye movement detection and demonstrate that it allows up to 160 targets to be distinguished. With this work we advance the well-established smooth pursuits technique, which allows gaze interaction without calibration. The approach is valuable for researchers and practitioners, since it enables novel user interfaces and applications to be created that employ a large number of targets, for example, a pursuits-based keyboard or a smart home where many different objects can be controlled using gaze. We present findings from two studies. In particular, we compare our novel detection algorithm based on linear regression with the correlation method. We quantify its accuracy for around 20 targets on a single circle and up to 160 targets on multiple circles. Finally, we implemented a pursuits-based keyboard app with 108 targets as proof-of-concept

Calibration-free Text Entry Using Smooth Pursuit Eye Movements

In this paper, we propose a calibration-free gaze-based text entry system that uses smooth pursuit eye movements. We report on our implementation, which improves over prior work on smooth pursuit text entry by 1) eliminating the need of calibration using motion correlation, 2) increasing input rate from 3.34 to 3.41 words per minute, 3) featuring text suggestions that were trained on 10,000 lexicon sentences recommended in the literature. We report on a user study (N=26) which shows that users are able to eye type at 3.41 words per minutes without calibration and without user training. Qualitative feedback also indicates that users positively perceive the system. Our work is of particular benefit for disabled users and for situations when voice and tactile input are not feasible (e.g., in noisy environments or when the hands are occupied)

Designing gaze-based interaction for pervasive public displays

The last decade witnessed an increasing adoption of public interactive displays. Displays can now be seen in many public areas, such as shopping malls, and train stations. There is also a growing trend towards using large public displays especially in airports, urban areas, universities and libraries. Meanwhile, advances in eye tracking and visual computing promise straightforward integration of eye tracking on these displays for both: 1) monitoring the user's visual behavior to evaluate different aspects of the display, such as measuring the visual attention of passersby, and for 2) interaction purposes, such as allowing users to provide input, retrieve content, or transfer data using their eye movements. Gaze is particularly useful for pervasive public displays. In addition to being natural and intuitive, eye gaze can be detected from a distance, bringing interactivity to displays that are physically unreachable. Gaze reflects the user's intention and visual interests, and its subtle nature makes it well-suited for public interactions where social embarrassment and privacy concerns might hinder the experience. On the downside, eye tracking technologies have traditionally been developed for desktop settings, where a user interacts from a stationary position and for a relatively long period of time. Interaction with public displays is fundamentally different and hence poses unique challenges when employing eye tracking. First, users of public displays are dynamic; users could approach the display from different directions, and interact from different positions or even while moving. This means that gaze-enabled displays should not expect users to be stationary at a specific position, but instead adapt to users' ever-changing position in front of the display. Second, users of public displays typically interact for short durations, often for a few seconds only. This means that contrary to desktop settings, public displays cannot afford requiring users to perform time-consuming calibration prior to interaction. In this publications-based dissertation, we first report on a review of challenges of interactive public displays, and discuss the potential of gaze in addressing these challenges. We then showcase the implementation and in-depth evaluation of two applications where gaze is leveraged to address core problems in today's public displays. The first presents an eye-based solution, EyePACT, that tackles the parallax effect which is often experienced on today's touch-based public displays. We found that EyePACT significantly improves accuracy even with varying degrees of parallax. The second is a novel multimodal system, GTmoPass, that combines gaze and touch input for secure user authentication on public displays. GTmoPass was found to be highly resilient to shoulder surfing, thermal attacks and smudge attacks, thereby offering a secure solution to an important problem on public displays. The second part of the dissertation explores specific challenges of gaze-based interaction with public displays. First, we address the user positioning problem by means of active eye tracking. More specifically, we built a novel prototype, EyeScout, that dynamically moves the eye tracker based on the user's position without augmenting the user. This, in turn, allowed us to study and understand gaze-based interaction with public displays while walking, and when approaching the display from different positions. An evaluation revealed that EyeScout is well perceived by users, and improves the time needed to initiate gaze interaction by 62% compared to state-of-the-art. Second, we propose a system, Read2Calibrate, for calibrating eye trackers implicitly while users read text on displays. We found that although text-based calibration is less accurate than traditional methods, it integrates smoothly while reading and thereby more suitable for public displays. Finally, through our prototype system, EyeVote, we show how to allow users to select textual options on public displays via gaze without calibration. In a field deployment of EyeVote, we studied the trade-off between accuracy and selection speed when using calibration-free selection techniques. We found that users of public displays value faster interactions over accurate ones, and are willing to correct system errors in case of inaccuracies. We conclude by discussing the implications of our findings on the design of gaze-based interaction for public displays, and how our work can be adapted for other domains apart from public displays, such as on handheld mobile devices.In den letzten zehn Jahren wurden vermehrt interaktive Displays in öffentlichen Bereichen wie Einkaufszentren, Flughäfen und Bahnhöfen eingesetzt. Große öffentliche Displays finden sich zunehmend in städtischen Gebieten, beispielsweise in Universitäten und Bibliotheken. Fortschritte in der Eye-Tracking-Technologie und der Bildverarbeitung versprechen eine einfache Integration von Eye-Tracking auf diesen Displays. So kann zum einen das visuelle Verhalten der Benutzer verfolgt und damit ein Display nach verschiedenen Aspekten evaluiert werden. Zum anderen eröffnet Eye-Tracking auf öffentlichen Displays neue Interaktionsmöglichkeiten. Blickbasierte Interaktion ist besonders nützlich für Bildschirme im allgegenwärtigen öffentlichen Raum. Der Blick bietet mehr als eine natürliche und intuitive Interaktionsmethode: Blicke können aus der Ferne erkannt und somit für Interaktion mit sonst unerreichbaren Displays genutzt werden. Aus der Interaktion mit dem Blick (Gaze) lassen sich Absichten und visuelle Interessen der Benutzer ableiten. Dadurch eignet es sich besonders für den öffentlichen Raum, wo Nutzer möglicherweise Datenschutzbedenken haben könnten oder sich bei herkömmlichen Methoden gehemmt fühlen würden in der Öffentlichkeit mit den Displays zu interagieren. Dadurch wird ein uneingeschränktes Nutzererlebnis ermöglicht. Eye-Tracking-Technologien sind jedoch in erster Linie für Desktop-Szenarien entwickelt worden, bei denen ein Benutzer für eine relativ lange Zeitspanne in einer stationären Position mit dem System interagiert. Die Interaktion mit öffentlichen Displays ist jedoch grundlegend anders. Daher gilt es völlig neuartige Herausforderungen zu bewältigen, wenn Eye-Tracking eingesetzt wird. Da sich Nutzer von öffentlichen Displays bewegen, können sie sich dem Display aus verschiedenen Richtungen nähern und sogar währenddessen mit dem Display interagieren. Folglich sollten "Gaze-enabled Displays" nicht davon ausgehen, dass Nutzer sich stets an einer bestimmten Position befinden, sondern sollten sich an die ständig wechselnde Position des Nutzers anpassen können. Zum anderen interagieren Nutzer von öffentlichen Displays üblicherweise nur für eine kurze Zeitspannen von ein paar Sekunden. Eine zeitaufwändige Kalibrierung durch den Nutzer vor der eigentlichen Interaktion ist hier im Gegensatz zu Desktop-Szenarien also nicht adäquat. Diese kumulative Dissertation überprüft zunächst die Herausforderungen interaktiver öffentlicher Displays und diskutiert das Potenzial von blickbasierter Interaktion zu deren Bewältigung. Anschließend wird die Implementierung und eingehende Evaluierung von zwei beispielhaften Anwendungen vorgestellt, bei denen Nutzer durch den Blick mit öffentlichen Displays interagieren. Daraus ergeben sich weitere greifbare Vorteile der blickbasierten Interaktion für öffentliche Display-Kontexte. Bei der ersten Anwendung, EyePACT, steht der Parallaxeneffekt im Fokus, der heutzutage häufig ein Problem auf öffentlichen Displays darstellt, die über Berührung (Touch) gesteuert werden. Die zweite Anwendung ist ein neuartiges multimodales System, GTmoPass, das Gaze- und Touch-Eingabe zur sicheren Benutzerauthentifizierung auf öffentlichen Displays kombiniert. GTmoPass ist sehr widerstandsfähig sowohl gegenüber unerwünschten fremden Blicken als auch gegenüber sogenannten thermischen Angriffen und Schmierangriffen. Es bietet damit eine sichere Lösung für ein wichtiges Sicherheits- und Datenschutzproblem auf öffentlichen Displays. Der zweite Teil der Dissertation befasst sich mit spezifischen Herausforderungen der Gaze-Interaktion mit öffentlichen Displays. Zuerst wird der Aspekt der Benutzerpositionierung durch aktives Eye-Tracking adressiert. Der neuartige Prototyp EyeScout bewegt den Eye-Tracker passend zur Position des Nutzers, ohne dass dieser dafür mit weiteren Geräten oder Sensoren ausgestattet werden muss. Dies ermöglicht blickbasierte Interaktion mit öffentlichen Displays auch in jenen Situationen zu untersuchen und zu verstehen, in denen Nutzer in Bewegung sind und sich dem Display von verschiedenen Positionen aus nähern. Zweitens wird das System Read2Calibrate präsentiert, das Eye-Tracker implizit kalibriert, während Nutzer Texte auf Displays lesen. Der Prototyp EyeVote zeigt, wie man die Auswahl von Textantworten auf öffentlichen Displays per Blick ohne Kalibrierung ermöglichen kann. In einer Feldstudie mit EyeVote wird der Kompromiss zwischen Genauigkeit und Auswahlgeschwindigkeit unter der Verwendung kalibrierungsfreier Auswahltechniken untersucht. Die Implikationen der Ergebnisse für das Design von blickbasierter Interaktion öffentlicher Displays werden diskutiert. Abschließend wird erörtert wie die verwendete Methodik auf andere Bereiche, z.B. auf mobilie Geräte, angewendet werden kann