In 3D user interfaces, reaching out to grab and manipulate something works great until it is out of reach. Indirect techniques like gaze and pinch offer an alternative for distant interaction, but do not provide the same immediacy or proprioceptive feedback as direct gestures. To support direct gestures for faraway objects, we introduce SightWarp, an interaction technique that exploits eye-hand coordination to seamlessly summon object proxies to the user's fingertips. The idea is that after looking at a distant object, users either shift their gaze to the hand or move their hand into view-triggering the creation of a scaled near-space proxy of the object and its surrounding context. The proxy remains active until the eye-hand pattern is released. The key benefit is that users always have an option to immediately operate on the distant object through a natural, direct hand gesture. Through a user study of a 3D object docking task, we show that users can easily employ SightWarp, and that subsequent direct manipulation improves performance over gaze and pinch. Application examples illustrate its utility for 6DOF manipulation, overview-and-detail navigation, and world-in-miniature interaction. Our work contributes to expressive and flexible object interactions across near and far spaces.

Invisible fiducial markers are introduced for localization of Areas Of Interest (AOIs) in mobile eye tracking applications. Fiducial markers are made invisible through the use of film passing Infra-Red (IR) light while blocking the visible spectrum. An IR light source is used to illuminate the markers which are then detected by an IR-sensitive camera, but which are imperceptible by the human eye. We provide the first empirical study that demonstrates such invisible markers are not distracting to a given task, as demonstrated in a flight simulator where distraction of visible and invisible markers are compared between experienced and novice pilots. Fixation frequency and subjective distraction scores showed that visible markers disrupted natural gaze behaviour, particularly in novice pilots. Our findings show that invisible markers should be used when there is a need for them to remain inconspicuous.

Invisible fiducial markers are introduced for localization of Areas Of Interest (AOIs) in mobile eye tracking applications. Fiducial markers are made invisible through the use of film passing Infra-Red (IR) light while blocking the visible spectrum. An IR light source is used to illuminate the markers which are then detected by an IR-sensitive camera, but which are imperceptible by the human eye. We provide the first empirical study that demonstrates such invisible markers are not distracting to a given task, as demonstrated in a flight simulator where distraction of visible and invisible markers are compared between experienced and novice pilots. Fixation frequency and subjective distraction scores showed that visible markers disrupted natural gaze behaviour, particularly in novice pilots. Our findings show that invisible markers should be used when there is a need for them to remain inconspicuous.

Eye gaze is a fast and ergonomic modality for pointing but limited in precision and accuracy. In this work, we introduce BimodalGaze, a novel technique for seamless head-based refinement of a gaze cursor. The technique leverages eye-head coordination insights to separate natural from gestural head movement. This allows users to quickly shift their gaze to targets over larger fields of view with naturally combined eye-head movement, and to refine the cursor position with gestural head movement. In contrast to an existing baseline, head refinement is invoked automatically, and only if a target is not already acquired by the initial gaze shift. Study results show that users reliably achieve fine-grained target selection, but we observed a higher rate of initial selection errors affecting overall performance. An in-depth analysis of user performance provides insight into the classification of natural versus gestural head movement, for improvement of BimodalGaze and other potential applications.

Target disambiguation is a common problem in gaze interfaces, as eye tracking has accuracy and precision limitations. In 3D environments this is compounded by objects overlapping in the field of view, as a result of their positioning at different depth with partial occlusion. We introduce VOR depth estimation, a method based on the Vestibulo-ocular reflex of the eyes in compensation of head movement, and explore its application to resolve target ambiguity. The method estimates gaze depth by comparing the rotations of the eye and the head when the users look at a target and deliberately rotate their head. We show that VOR eye movement presents an alternative to vergence for gaze depth estimation, that is feasible also with monocular tracking. In an evaluation of its use for target disambiguation, our method outperforms vergence for targets presented at greater depth.

Gaze depth estimation presents a challenge for eye tracking in 3D. This work investigates a novel approach to the problem based on eye movement mediated by the vestibulo-ocular reflex (VOR). VOR stabilises gaze on a target during head movement, with eye movement in the opposite direction, and the VOR gain increases the closer the fixated target is to the viewer. We present a theoretical analysis of the relationship between VOR gain and depth which we investigate with empirical data collected in a user study (N=10). We show that VOR gain can be captured using pupil centres, and propose and evaluate a practical method for gaze depth estimation based on a generic function of VOR gain and two-point depth calibration. The results show that VOR gain is comparable with vergence in capturing depth while only requiring one eye, and provide insight into open challenges in harnessing VOR gain as a robust measure.

For head mounted displays, like they are used in mixed reality applications, eye gaze seems to be a natural interaction modality. EyeMRTK provides building blocks for eye gaze interaction in virtual and augmented reality. Based on a hardware abstraction layer, it allows interaction researchers and developers to focus on their interaction concepts, while enabling them to evaluate their ideas on all supported systems. In addition to that, the toolkit provides a simulation layer for debugging purposes, which speeds up prototyping during development on the desktop.

Various types of saccadic paradigms, in particular, Prosaccade and Antisaccade tests are widely used in Pathophysiology and Psychology. Despite been widely used, there has not been a standard tool for processing and analyzing the eye tracking data obtained from saccade tests. We describe an open-source software for extracting and analyzing the eye movement data of different types of saccade tests that can be used to extract and compare participants' performance and various task-related measures across participants. We further demonstrate the utility of the software by using it to analyze the data from an antisaccade, and a recent distractor experiment.

In 2D interfaces, actions are often represented by fixed tools arranged in menus, palettes, or dedicated parts of a screen, whereas 3D interfaces afford their arrangement at different depths relative to the user and the user can move them relative to each other. In this paper, we introduce EyeSeeThrough as a novel interaction technique that utilizes eye-tracking in VR. The user can apply an action to an intended object by visually aligning the object with the tool at the line-of-sight, and then issue a confirmation command. The underlying idea is to merge the two-step process of 1) selection of a mode in a menu and 2) applying it to a target, into one unified interaction. We present a user study where we compare the method to the baseline two-step selection. The results of our user study showed that our technique outperforms the two step selection in terms of speed and comfort. We further developed a prototype of a virtual living room to demonstrate the practicality of the proposed technique.

EyeGrip proposes a novel and yet simple technique of analysing eye movements for automatically detecting the user's objects of interest in a sequence of visual stimuli moving horizontally or vertically in front of the user's view. We assess the viability of this technique in a scenario where the user looks at a sequence of images moving horizontally on the display while the user's eye movements are tracked by an eye tracker. We conducted an experiment that shows the performance of the proposed approach. We also investigated the influence of the speed and maximum number of visible images in the screen, on the accuracy of EyeGrip. Based on the experiment results, we propose guidelines for designing EyeGrip-based interfaces. EyeGrip can be considered as an implicit gaze interaction technique with potential use in broad range of applications such as large screens, mobile devices and eyewear computers. In this paper, we demonstrate the rich capabilities of EyeGrip with two example applications: 1) a mind reading game, and 2) a picture selection system. Our study shows that by selecting an appropriate speed and maximum number of visible images in the screen the proposed method can be used in a fast scrolling task where the system accurately (87%) detects the moving images that are visually appealing to the user, stops the scrolling and brings the item(s) of interest back to the screen.

We investigate the gaze estimation error induced by pupil size changes using simulated data. We investigate the influence of pupil diameter changes on estimated gaze point error obtained by two gaze estimation models. Simulation data show that at wider viewing angles and at small eye-camera distances, error increases with increasing pupil sizes. The maximum error recorded for refracted pupil images is 2.4° of visual angle and 1.5° for non-refracted pupil projections.

In this paper we investigate the utility of an eye-based interaction technique (EyeGrip) for seamless interaction with scrolling contents on eyewear computers. EyeGrip uses Optokinetic Nystagmus (OKN) eye movements to detect object of interest among a set of scrolling contents and automatically stops scrolling for the user. We empirically evaluated the usability of EyeGrip in two different applications for eyewear computers: 1) a menu scroll viewer and 2) a Facebook newsfeed reader. The results of our study showed that the EyeGrip technique performs as good as keyboard which has long been a well-known input device. Moreover, the accuracy of the EyeGrip method for menu item selection was higher while in the Facebook study participants found keyboard more accurate.

A novel method for video-based head gesture recognition using eye information by an eye tracker has been proposed. The method uses a combination of gaze and eye movement to infer head gestures. Compared to other gesture-based methods a major advantage of the method is that the user keeps the gaze on the interaction object while interacting. This method has been implemented on a head-mounted eye tracker for detecting a set of predefined head gestures. The accuracy of the gesture classifier is evaluated and verified for gaze-based interaction in applications intended for both large public displays and small mobile phone screens. The user study shows that the method detects a set of defined gestures reliably.

This paper investigates the parallax error, which is a common problem of many video-based monocular mobile gaze trackers. The parallax error is defined and described using the epipolar geometry in a stereo camera setup. The main parameters that change the error are introduced and it is shown how each parameter affects the error. The optimum distribution of the error (magnitude and direction) in the field of view varies for different applications. However, the results can be used for finding the optimum parameters that are needed for designing a head-mounted gaze tracker. It has been shown that the difference between the visual and optical axes does not have a significant effect on the parallax error, and the epipolar geometry can be used for describing the parallax error in the HMGT.