Eye Gaze Interaction Research Articles

Introduction to the Special Thematic Issue "Virtual Reality and Eye Tracking".

Technological advancements have made it possible to integrate eye tracking in virtual reality (VR) and augmented reality (AR). Many new VR/AR headsets already include eye tracking as a standard feature. While its application previously has been mostly limited to research, we now see installations of eye tracking into consumer level VR products in entertainment, training, and therapy. The combination of eye tracking and VR creates new opportunities for end users, creators, and researchers alike: The high level of immersion – while shielded from visual distractions of the physical environment – leads to natural behavior inside the virtual environment. This enables researchers to study how humans perceive and interact with three-dimensional environments in experimentally controlled, ecologically valid settings. Simultaneously, eye tracking in VR poses new challenges to gaze analyses and requires the establishment of new tools and best practices in gaze interaction and psychological research from controlling influence factors, such as simulator sickness, to adaptations of algorithms in various situations. This thematic special issue introduces and discusses novel applications, challenges and possibilities of eye tracking and gaze interaction in VR from an interdisciplinary perspective, including contributions from the fields of psychology, human-computer interaction, human factors, engineering, neuroscience, and education. It addresses a variety of issues and topics, such as practical guidelines for VR-based eye tracking technologies, exploring new research avenues, evaluation of gaze-based assessments, and training interventions.

Cognitive offloading benefits eye gaze interaction

AbstractFor some people with strong motor impairments, controlling a computer with the eyes is the only possibility for human‐computer interaction. In addition, gaze control is becoming a new option as an input device for the general population as well because of the increasing availability of eye‐tracking technology. Yet, little is known about additional cognitive demands involved in gaze control and how to handle potentially high demands when using the eyes not only for perception but also for action. The present study shows that cognitive offloading improves performance when using gaze control. Memory for to‐be‐studied items benefitted significantly from saving another set of items just studied before for later restudy. Employing cognitive offloading in a targeted manner may be a useful means to assist in mastering eye‐gaze control.

A combination of eye-gaze and head-gaze interactions improves efficiency and user experience in an object positioning task in virtual environments

Eye-gaze and head-gaze are two hands-free interaction modes in virtual reality, each of which has demonstrated different strengths. Selecting suitable interaction modes in different scenarios is important to achieve efficient interaction in virtual scenes. This study compared the movement time in an object positioning task by examining eye-gaze interaction and head-gaze interaction in various conditions. In turn, it identified the superior zones for each mode, respectively. Based on this information, we designed a combination mode – utilizing eye-gaze interaction at the acceleration phase and deceleration phase and head-gaze interaction at the correction phase – to achieve the optimal interaction mode, which has allowed us to obtain higher efficiency and subjective satisfaction. This study provides a comprehensive analysis of the characteristics of the eye-gaze and head-gaze interaction modes and provides valuable insights into selecting the appropriate interaction modes for virtual reality applications.

Improving User Experience of Eye Tracking-Based Interaction

Eye tracking systems have greatly improved in recent years, being a viable and affordable option as digital communication channel, especially for people lacking fine motor skills. Using eye tracking as an input method is challenging due to accuracy and ambiguity issues, and therefore research in eye gaze interaction is mainly focused on better pointing and typing methods. However, these methods eventually need to be assimilated to enable users to control application interfaces. A common approach to employ eye tracking for controlling application interfaces is to emulate mouse and keyboard functionality. We argue that the emulation approach incurs unnecessary interaction and visual overhead for users, aggravating the entire experience of gaze-based computer access. We discuss how the knowledge about the interface semantics can help reducing the interaction and visual overhead to improve the user experience. Thus, we propose the efficient introspection of interfaces to retrieve the interface semantics and adapt the interaction with eye gaze. We have developed a Web browser, GazeTheWeb, that introspects Web page interfaces and adapts both the browser interface and the interaction elements on Web pages for gaze input. In a summative lab study with 20 participants, GazeTheWeb allowed the participants to accomplish information search and browsing tasks significantly faster than an emulation approach. Additional feasibility tests of GazeTheWeb in lab and home environment showcase its effectiveness in accomplishing daily Web browsing activities and adapting large variety of modern Web pages to suffice the interaction for people with motor impairment.

Methods to Eye Gaze Interaction for Authentication

One of the methods touted to reduce shoulder surfing during onscreen authentication is eye gaze input. Eye gaze authentication methods have thus far relied on a few methods for selection of on screen objects, namely dwell time, blinking, eye gestures and pursuit of moving objects. This paper surveys the literature on the various approaches. From analysis of the advantages and drawbacks of the surveyed approaches, we find that the dwell method has advantages in security and usability. We then describe a method designed previously by the authors that enhances the dwell method by making use of peripheral vision. The proposed method is in the ideation stage.

Evaluation of the Tobii EyeX Eye tracking controller and Matlab toolkit for research

The Tobii Eyex Controller is a new low-cost binocular eye tracker marketed for integration in gaming and consumer applications. The manufacturers claim that the system was conceived for natural eye gaze interaction, does not require continuous recalibration, and allows moderate head movements. The Controller is provided with a SDK to foster the development of new eye tracking applications. We review the characteristics of the device for its possible use in scientific research. We develop and evaluate an open source Matlab Toolkit that can be employed to interface with the EyeX device for gaze recording in behavioral experiments. The Toolkit provides calibration procedures tailored to both binocular and monocular experiments, as well as procedures to evaluate other eye tracking devices. The observed performance of the EyeX (i.e. accuracy < 0.6°, precision < 0.25°, latency < 50 ms and sampling frequency ≈55 Hz), is sufficient for some classes of research application. The device can be successfully employed to measure fixation parameters, saccadic, smooth pursuit and vergence eye movements. However, the relatively low sampling rate and moderate precision limit the suitability of the EyeX for monitoring micro-saccadic eye movements or for real-time gaze-contingent stimulus control. For these applications, research grade, high-cost eye tracking technology may still be necessary. Therefore, despite its limitations with respect to high-end devices, the EyeX has the potential to further the dissemination of eye tracking technology to a broad audience, and could be a valuable asset in consumer and gaming applications as well as a subset of basic and clinical research settings.

Target Expansion as a Means to Facilitate Eye-based Selection

Recent evidence about positive impact of expanding targets on user performance during manual pointing raises a provocativequestion whether a similar effect can be expected for eye gaze interaction. We present an experiment designed to examine the benefitsof target expansion during an eye-controlled selection task. The experiment involved twelve participants and a head-mounted eyetracking system EyeLink used as the input device. Our results suggest that both movement time to an expanding target and selectionerror rate are reciprocal functions of expansion factor and monotonic functions of distance to the target. Furthermore, movement time isa quasi-linear function of dwell time on the target, whereas error rate is invariant with respect to dwell time. Finally, movementdirection has an effect on error rate, but not on movement time. Overall, the results confirm the boosting effect of target expansion bothin terms of pointing speed and accuracy. These findings indicate that target expansion has the potential of making eye gaze input moresuitable for practical applications. Ill. 7, bibl. 6 (in English; summaries in Lithuanian, English, Russian).

Integrating Click-Through and Eye-Tracking Logs for Decision-Making Process Mining

In current software every click of the users is logged, therefore a wealth of click-through information exists. Besides, recent technologies have made eye-tracking affordable and an alternative to other human-computer interaction means (e.g. mouse, touchscreens). A big challenge is to make sense of all this data and convert it into useful information. This paper introduces a possible solution placed in the context of decision-making processes. We show how the decision maker's activity can be traced using two means: mouse tracing (i.e. clicks) and eye-tracking (i.e. eye fixations). Then, we discuss a mining approach, based on the log, which extracts a Decision Data Model (DDM). We use the DDM to determine, post-hoc, which decision strategy was employed. The paper concludes with a validation based on a controlled experiment.Keywords: Decision-Making Process Model, Data-Flow Model, Decision Process Mining1 IntroductionThis paper aims to show how decision-making process models can be automatically extracted from human-computer interaction logs. Since our research is placed in IT, most of the interaction with a software is performed my mouse and by looking at a computer screen. Therefore, the traces leftby the user interacting with the software are mouse clicks (an additional data like values typed from the keyboard) as well as screen objects (e.g. menus, textboxes) at which the user stared. Aggregating those two data sources as well as making sense of this new data is the main focus of this paper.Modern software stores more and more data about everything connected to it. For example, Google sores information about searches of each user, about pages visited, about links opened, etc. Also, any web-shop stores data on products viewed as well as any click performed during each visit (e.g. Amazon sends personalized e-mails with price updates if a user just looked at the details of certain products, let alone added anything in the shopping cart and then discarded it). ERP systems also log the activities of users, and even go as far as storing information on changes made to the tables storing data. Therefore, we think that there is enough support to claim that click-through data may be, or is, stored by any software.Eye-tracking is a technique used to output the point of a stimulus where a subject looks at. For our research, the stimulus is the interface of software displayed on a computer screen. Eye-tracking hardware follows the physical movements of the eye (most common technique is to film the pupils with video cameras). Eye-tracking software converts the physical movements into (computer screen) coordinates and matches them to object in the interface. Therefore, a log of objects (e.g. buttons, menu items, textboxes, etc.) that capture user's attention is available. Eye tracking becomes cheaper and more and more implementations are available. The most common example is the use of eye-tracking in current smartphones. For example, Samsung Galaxy S4 uses the front camera and dedicated software to determine if the user is looking at the bottom of the page so it will automatically scroll documents or if the user is looking away from the screen so it will pause running videos. Also, eye-tracking systems are integrated into laptops on the market (Lenovo laptop presented at CeBit 2011) or soon to be put on the market (Tobii ultrabook presented at CeBit 2013). Those implementations seek to replace 'classical' interaction methods like mouse, touchpad or touchscreens with eye-gaze interaction (e.g. user clicks a button just by looking at it).Having established there is a wealth of logged data on the behavior of users interacting with software, we wish to argue that it can be mined for building models. This is the drive behind process mining research area. Activity logs are mined in order to extract the control-flow perspective of business processes. We got inspiration to apply the same approach to the decision making research. …

Using brain signals patterns for biometric identity verification systems

In the natural human computer interaction filed, researchers started to consider the other interaction modalities for diversity of applications. Among these modalities are the speech interaction systems, eye gaze interaction systems and recently Brain Computer Interfacing (BCI) systems. In BCI systems, the tools are deployed to manipulate the brain activity to produce signals that can be used to control computers or communication devices. Implementing this technology in real life varies from: entertainment systems to control layers through the user thoughts, to disability assistive devices to reduce care given. Currently the BCI technologies are developed for the purposes of boosting the disability assistive devices especially in the command controlled systems. In addition, the currently demanding research emphasis is to use brain signals for personal identifications and verification; known as biometric verification. Biometric verification was first used in as an authentication technique for systems operating devices in real environment. At that time, authentication was based on unimodal biometric identity verification systems, which compare only one trait or biometrical feature (such as voice, iris, or fingerprint) to a previous sample. However, the performance of such modals varies depending on the presence of outside factors such as background noises in a speech recognition system, or the illumination problems for a face recognition system. Another cause of pitfalls in these models is their dependency on the health of the authenticated user. In order to overcome the weaknesses of the unimodal biometric system, a multimodal biometric system was introduced.

Performing Locomotion Tasks in Immersive Computer Games with an Adapted Eye-Tracking Interface

Young people with severe physical disabilities may benefit greatly from participating in immersive computer games. In-game tasks can be fun, engaging, educational, and socially interactive. But for those who are unable to use traditional methods of computer input such as a mouse and keyboard, there is a barrier to interaction that they must first overcome. Eye-gaze interaction is one method of input that can potentially achieve the levels of interaction required for these games. How we use eye-gaze or the gaze interaction technique depends upon the task being performed, the individual performing it, and the equipment available. To fully realize the impact of participation in these environments, techniques need to be adapted to the person’s abilities. We describe an approach to designing and adapting a gaze interaction technique to support locomotion, a task central to immersive game playing. This is evaluated by a group of young people with cerebral palsy and muscular dystrophy. The results show that by adapting the interaction technique, participants are able to significantly improve their in-game character control.

Performing Locomotion Tasks in Immersive Computer Games with an Adapted Eye-Tracking Interface

Young people with severe physical disabilities may benefit greatly from participating in immersive computer games. In-game tasks can be fun, engaging, educational, and socially interactive. But for those who are unable to use traditional methods of computer input such as a mouse and keyboard, there is a barrier to interaction that they must first overcome. Eye-gaze interaction is one method of input that can potentially achieve the levels of interaction required for these games. How we use eye-gaze or the gaze interaction technique depends upon the task being performed, the individual performing it, and the equipment available. To fully realize the impact of participation in these environments, techniques need to be adapted to the person’s abilities. We describe an approach to designing and adapting a gaze interaction technique to support locomotion, a task central to immersive game playing. This is evaluated by a group of young people with cerebral palsy and muscular dystrophy. The results show that by adapting the interaction technique, participants are able to significantly improve their in-game character control.