3-D eye movement analysis.

This tutorial provides instruction on how to use the eye tracking technology built into virtual reality (VR) headsets, emphasizing the analysis of head and eye movement data when an observer is situated in the center of an omnidirectional environment. We begin with a brief description of how VR eye movement research differs from previous forms of eye movement research, as well as identifying some outstanding gaps in the current literature. We then introduce the basic methodology used to collect VR eye movement data both in general and with regard to the specific data that we collected to illustrate different analytical approaches. We continue with an introduction of the foundational ideas regarding data analysis in VR, including frames of reference, how to map eye and head position, and event detection. In the next part, we introduce core head and eye data analyses focusing on determining where the head and eyes are directed. We then expand on what has been presented, introducing several novel spatial, spatio-temporal, and temporal head-eye data analysis techniques. We conclude with a reflection on what has been presented, and how the techniques introduced in this tutorial provide the scaffolding for extensions to more complex and dynamic VR environments.

Investigating movement through smoke in virtual reality

Benign paroxysmal positioning vertigo (BPPV), and nystagmus (BPPN) is the commonest type of rotational vertigo. Typical BPPN is generally believed to arise from one posterior semicircular canal. If this is true, the syndrome would offer the unique possibility to study vestibular responses when just one single semicircular canal is excited. In this study we used search coils to measure 3-D eye positions in 3 patients with BPPN. We present a complete 3-D description of the eye movements induced in BPPN. We found that in our patients the eyes rotate rather precisely in the plane of one posterior semicircular canal, suggesting that BPPN in our cases is indeed solely produced by the posterior semicircular canal.

This paper describes the development of a binocular eye tracking Virtual Reality system for aircraft inspection training. The aesthetic appearance of the environment is driven by standard graphical techniques augmented by realistic texture maps of the physical environment. A "virtual flashlight" is provided to simulate a tool used by inspectors. The user's gaze direction, as well as head position and orientation, are tracked to allow recording of the user's gaze locations within the environment. These gaze locations, or scanpaths, are calculated as gaze/polygon intersections, enabling comparison of fixated points with stored locations of artificially generated defects located in the environment interior. Recorded scanpaths provide a means of comparison of the performance of experts to novices, thereby gauging the effects of training.

Research investigating gaze in natural scenes has identified a number of spatial biases in where people look, but it is unclear whether these are partly due to constrained testing environments (e.g., a participant with their head restrained and looking at a landscape image framed within a computer monitor). We examined the extent to which image shape (square vs. circle), image rotation, and image content (landscapes vs. fractal images) influence eye and head movements in virtual reality (VR). Both the eyes and head were tracked while observers looked at natural scenes in a virtual environment. In line with previous work, we found a bias for saccade directions parallel to the image horizon, regardless of image shape or content. We found that, when allowed to do so, observers move both their eyes and head to explore images. Head rotation, however, was idiosyncratic; some observers rotated a lot, whereas others did not. Interestingly, the head rotated in line with the rotation of landscape but not fractal images. That head rotation and gaze direction respond differently to image content suggests that they may be under different control systems. We discuss our findings in relation to current theories on head and eye movement control and how insights from VR might inform more traditional eye-tracking studies.

As VR becomes increasingly popular in the entertainment industry, VR locomotion, a technique that allows users to navigate virtual environments beyond the spatial confines of the real world, is being increasingly studied by developers and researchers. Previous work has examined the effects of locomotion methods on various aspects of users, such as user experience, motion sickness, and task performance. However, how locomotion methods affect users' eye movements that might indicate cognitive load has not yet been in-vestigated, although several relevant works have addressed these effects as being important to study. To contribute to this area of research, in this work we investigate the evaluation of five common gait-free locomotion methods using eye movements during VR nav-igation. The results show that locomotion methods significantly affect participants' eye movement behavior (i.e., blinks, fixations, and saccades), suggesting that different cognitive responses were elicited with different locomotion methods. Our research provides a viable tool for future studies evaluating locomotion methods, thus providing further in-depth insights for developing more effective and enjoyable VR locomotion methods.

With the rise of virtual reality technology and eye movement tracking, the cognitive classification of eye movement emotion combined with virtual reality technology was a research hotspot recently. In this research, 96 pictures were selected from the Chinese Affective Picture System (CAPS), and 35 subjects were stimulated with pictures in virtual scene. The corresponding eye movement data were tracked synchronously. Eye movement data were progressed with blink data reconstruction and baseline correction, after which time and frequency domain features were extracted. Finally, for three emotion model dimensions including valence, arousal and dominance expressed as high, medium and low, models are trained with Support Vector Machine (SVM), with the highest classification accuracy of single person reaches 78.1%. The results of this paper are instructive for the processing of eye movement data, and the eye tracking data combined with virtual reality technology can be used for emotion recognition research through the proposed preprocessing methods and feature extraction.

Extended reality (XR), here jointly referring to virtual, augmented, and mixed (VR, AR, MR) reality, is becoming more common in everyday working life. This paper presents a systematic literature review of academic publications on XR indicating changes in practical organization of work. We analyse both application areas of XR and theoretical and methodological approaches of XR research. The review process followed the PRISMA statement. Design, remote collaboration, and training were the main application areas of XR. XR enabled overcoming of obstacles set by time and space, safety, and resources by mediating experience of space. Research on XR applications in actual working life settings is yet relatively rare and covers primarily three areas: collaboration, evaluation of knowledge transfer, and work practices. Virtual reality was the most common form of applied XR, although the hardware used varied case by case. We identified four research areas regarding XR: collaboration, work practices, and evaluation of knowledge transfer, which somewhat followed the application areas. We did not find XR-specific methodologies in the reviewed articles, only few recent studies used novel ways of collecting research material, such as recording the movement in virtual reality. For now, XR still holds significant potential rather than clearly confirmed general advantages in working life.

A Cave Automatic Virtual Environment (CAVE) is an enclosed virtual reality room that uses multiple projectors to display images across its surfaces. It uses one or more computers to synchronise and combine the images and allows users to control virtual worlds using a host of interaction devices. Traditionally, a CAVE is used by a single user at any one time and by utilising some form of motion sensing, the user's head position can be tracked to allow for first virtual perception. The images are then displayed in stereographic 3D in order to complete the virtual reality effect. Professional CAVE installations are expensive and can cost upwards of several hundred thousand euros. This tends to act as a significant barrier to their propagation, however, as the reduction in cost of high specification computers, projectors and graphics cards continues apace, it has sparked a renewed interest in CAVE environments and given rise to the realistic possibility of setting up low cost, amateur CAVEs. Unfortunately, one of the greatest disadvantages of CAVE systems is the lack of inexpensive, easy to use, specialised software. In this paper we present an open source and easy to use CAVE software toolkit called SCReen Adjusted Panoramic Effect or SCRAPE for short. We believe that SCRAPE is the first major piece in a longer-term vision that aims to bring easy to setup, easy to use, portable CAVE systems to all types of non-expert users.

We recorded three-dimensional eye and head movements during circular, horizontal, vertical, and torsional head shaking in six human subjects with normal vestibular function. With circular head shaking, the stimulation of the canals by the termination of the head movement is similar to that following a step in velocity about the naso-occipital axis. A large torsional nystagmus with slow phase eye velocity of about 20 degrees/s was observed upon cessation of circular head shaking. The three-dimensional eye movements expected from stimulation of the semicircular canals by the head-shaking maneuvers were calculated. The predicted activation of the canals was determined by projecting the head velocity (in head coordinates) into the canal planes and then processing the signal with the transfer function of the canals. The torsional eye velocity components predicted by the stimulation of the canals matched the recorded ones. We observed small horizontal eye velocities that could not be predicted by the stimulation of the canals alone. No eye movements were observed after the end of head shaking about a fixed horizontal or vertical axis. The eye velocities following the termination of head oscillations in the roll plane were small. The analysis methods developed for this study may be useful in the investigation of eye movements elicited by other types of three-dimensional head movements.

Virtual Reality (VR) technology has become ever more popular with consumers in recent years. However, dizziness brought by VR greatly affects its experience, especially VR motion sickness. Therefore, the industry needs in order to study how to improve the comfort of VR motion pictures. The subject conducts subjective evaluation experiments through the constructed virtual 3D scene. The relationship between the height and speed of the VR camera, as well as the gender of the audience and VR motion sickness, is considered by subjective evaluation experiments. Viewer’s VR motion sickness is the least obvious when the viewer is close to the height and average pace, and women are more likely to be dizzy to VR than men, which are proved by experimental results.

Extensive research conducted in controlled laboratory settings has prompted an inquiry into how results can be generalized to real-world situations influenced by the subjects' actions. Virtual reality lends itself ideally to investigating complex situations but requires accurate classification of eye movements, especially when combining it with time-sensitive data such as EEG. We recorded eye-tracking data in virtual reality and classified it into gazes and saccades using a velocity-based classification algorithm, and we cut the continuous data into smaller segments to deal with varying noise levels, as introduced in the REMoDNav algorithm. Furthermore, we corrected for participants' translational movement in virtual reality. Various measures, including visual inspection, event durations, and the velocity and dispersion distributions before and after gaze onset, indicate that we can accurately classify the continuous, free-exploration data. Combining the classified eye-tracking with the EEG data, we generated fixation-onset event-related potentials (ERPs) and event-related spectral perturbations (ERSPs), providing further evidence for the quality of the eye-movement classification and timing of the onset of events. Finally, investigating the correlation between single trials and the average ERP and ERSP identified that fixation-onset ERSPs are less time sensitive, require fewer repetitions of the same behavior, and are potentially better suited to study EEG signatures in naturalistic settings. We modified, designed, and tested an algorithm that allows the combination of EEG and eye-tracking data recorded in virtual reality.

Differences in eye movements while viewing images with various levels of restorativeness

HoloTabletop is a low-cost holographic-like tabletop interactive system. This system analyzes user's head position and gaze location in a real time setting and computes the corresponding anamorphic illusion image. The anamorphic illusion image is displayed on a 2D horizontally-located monitor, yet offers stereo vision to the user. The user is able to view and interact with the 3D virtual objects without wearing any special glasses or devices. The experimental results and user studies verify that the proposed HoloTabletop system offers excellent stereo vision while no visual fatigue will be caused to human eyes. This system is a great solution for many interactive applications such as 3D board games and stereo map browsing.

The paper presents an analysis of visual attention to subtitles within immersive media. We implement a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$360^{\circ}$</tex> video rendering with eye movements recorded in Virtual Reality. Position and color of im-mersive subtitles are compared in terms of perceived task load and cognitive processing of the content. Results show that head-locked subtitles afford more focal visual inspection of the scene and pre-sumably better comprehension. This type of in-depth analysis would not be possible without the eye movement analyses.