The objective of this research was to explore whether virtual reality can be used to study individual food consumer decision-making and behavior through a public health lens by developing a simulation of an urban food environment that included a street-level scene and three prototypical stores. Twelve participants completed the simulation and a survey. Preliminary results showed that 72.7% of participants bought food from the green grocer, 18.2% from the fast food store, and 9.1% from the supermarket. The mean presence score was 38.9 out of 49 and the mean usability score was 85.9 out of 100. This experiment demonstrates that virtual reality should be further considered as a tool for studying food consumer behavior within a food environment.

There are outstanding questions regarding the fidelity of realistic look-alike avatars that show that there is still substantial development to be done, especially as the virtual world plays a more vital role in our education, work and recreation. The use of look-alike avatars could completely change how we interact virtually. This paper investigates which features of other people’s look-alike avatars influence our perceived realism. Four levels of avatar representations were assessed in this pilot study: a static avatar, a static avatar with lip sync corresponding to an audio recording, full face animation with audio and a full body animation. Results show that full-face and body animations are very important in increasing the perceived realism of avatars. More importantly, participants found the lip sync animation more unsettling (uncanny valley effect) than any of the other animations. The results have implications for the perception of other people’s look-alike avatars in collaborative virtual environments.

Two studies explored the potential of virtual reality (VR) in bystander-focused bullying prevention campaigns. An experiment compared responses to three versions of a bullying scenario in which users (N = 78) were placed in the perspective of a bystander: customized VR, non-customized VR, and video. Measures included empathy, attitudes toward bullying victims and bullying, anticipated future behavior, presence, and other perceptions of bullying. The only significant effects observed were on feelings of empathy, with scores in the video condition higher than in the other two conditions, and on perceptions of bullying as a problem in participants' schools, again with scores highest in the video condition. These results were further explored in a follow-up qualitative focus group study (N = 10). Findings from both studies suggest that to elicit empathy-related responses, VR simulations should use photorealistic graphics, employ interactive features, and make customization prominent and carefully tailored. Lessons learned could inform the use of virtual reality in future campaigns.

In the BEAMING project we have been extending the scope of collaborative mixed reality to include the representation of users in multiple modalities, including augmented reality, situated displays and robots. A single user (a visitor) uses a high-end virtual reality system (the transporter) to be virtually teleported to a real remote location (the destination). The visitor may be tracked in several ways including emotion and motion capture. We reconstruct the destination and the people within it (the locals). In achieving this scenario, BEAMING has integrated many heterogeneous systems. In this paper, we describe the design and key implementation choices in the Beaming Scene Service (BSS), which allows the various processes to coordinate their behaviour. The core of the system is a light-weight shared object repository that allows loose coupling between processes with very different requirements (e.g. embedded control systems through to mobile apps). The system was also extended to support the notion of presence awareness. We demonstrate two complex applications built with the BSS.

An emerging form of telecollaboration utilizes situated or mobile displays at a physical destination to virtually represent remote visitors. An example is a personal telepresence robot, which acts as a physical proxy for a remote visitor, and uses cameras and microphones to capture its surroundings, which are transmitted back to the visitor. We propose the use of spherical displays to represent telepresent visitors at a destination. We suggest that the use of such 360 degree displays in a telepresence system has two key advantages: it is possible to understand the identity of the visitor from any viewpoint; and with suitable graphical representation, it is possible to tell where the visitor is looking from any viewpoint. In this paper, we investigate how to optimally represent a visitor as an avatar on a spherical display by evaluating how varying representations are able to accurately convey head gaze.

ABSTRACT Autonomous virtual characters (AVCs) are becoming more prevalent both for real‐time interaction and also as digital actors in film and TV production. AVCs require believable virtual human animations, accompanied by natural attention generation, and thus the software that controls the AVCs needs to model when and how to interact with the objects and other characters that exist in the virtual environment. This paper models automatic attention behaviour using a saliency model that generates plausible targets for combined gaze and head motions. The model was compared with the default behaviour of the Second Life (SL) system in an object observation scenario while it was compared with real actors' behaviour in a conversation scenario. Results from a study run within the SL system demonstrate a promising attention model that is not just believable and realistic but also adaptable to varying task, without any prior knowledge of the virtual scene. Copyright © 2011 John Wiley & Sons, Ltd.

Abstract When compared to gaze, animation of the eyelids has been largely overlooked in the computer graphics literature. Eyelid movement plays an important part both in conveying accurate gaze direction and in improving the visual appearance of virtual characters. Eyelids have two major motion components: lid saccades that follow the vertical rotation the eyes, and blinking. Derived from literature in ophthalmology and psychology, this paper presents parametric models for both motion types, and emphasizes their dynamic temporal behaviour. Experimental validation classifies model‐generated animation as similar to that encoded from expensive motion captured data, and significantly exceeding linearly interpolated animation. Copyright © 2010 John Wiley & Sons, Ltd.

Eye gaze is an important and widely studied non-verbal resource in co-located social interaction. When we attempt to support tele-presence between people, there are two main technologies that can be used today: video-conferencing (VC) and collaborative virtual environments (CVEs). In VC, one can observe eye-gaze behaviour but practically the targets of eye-gaze are only correct if the participants remain relatively still. We attempt to support eye-gaze behaviour in an unconstrained manner by integrating eye-trackers into an Immersive CVE (ICVE) system. This paper aims to show that while both ICVE and VC allow people to discern being looked at and what else is looked at, when someone gazes into their space from another location, ICVE alone can continue to do this as people move. The conditions of aligned VC, ICVE, eye-gaze enabled ICVE and co-location are compared. The impact of factors of alignment, lighting, resolution, and perspective distortion are minimised through a set of pilot experiments, before a formal experiment records results for optimal settings. Results show that both VC and ICVE support eye-gaze in constrained situations, but only ICVE supports movement of the observer. We quantify the mis-judgements that are made and discuss how our findings might inform research into supporting eye-gaze through interpolated free viewpoint video based methods.

In face-to-face collaboration, eye gaze is used both as a bidirectional signal to monitor and indicate focus of attention and action, as well as a resource to manage the interaction. In remote interaction supported by immersive collaborative virtual environments (ICVEs), embodied avatars representing and controlled by each participant share a virtual space. We report on a study designed to evaluate methods of avatar eye gaze control during an object-focused puzzle scenario performed between three networked CAVEtrade-like systems. We compare tracked gaze, in which avatars' eyes are controlled by head-mounted mobile eye trackers worn by participants, to a gaze model informed by head orientation for saccade generation, and static gaze featuring non-moving eyes. We analyse task performance, subjective user experience, and interactional behaviour. While not providing statistically significant benefit over static gaze, tracked gaze is observed as the highest performing condition. However, the gaze model resulted in significantly lower task performance and increased error rate.

Complex interactions occur in virtual reality systems, requiring the modelling of next-generation attention models to obtain believable virtual human animations. This paper presents a saliency model that is neither domain nor task specific, which is used to animate the gaze of virtual characters. A critical question is addressed: What types of saliency attract attention in virtual environments and how can they be weighted to drive an avatar's gaze? Saliency effects were measured as a function of their total frequency. Scores were then generated for each object in the field of view within each frame to determine the most salient object within the virtual environment. This paper compares the resulting saliency gaze model to tracked gaze, in which avatars' eyes are controlled by head-mounted mobile eye-trackers worn by human subjects, random gaze model informed by head-orientation for saccade generation, and static gaze featuring non-moving centered eyes. Results from the evaluation experiment and graphical analysis demonstrate a promising saliency gaze model that is not just believable and realistic but also target-relevant and adaptable to varying tasks. Furthermore, the saliency model does not use any prior knowledge of the content or description of the virtual scene.

Eye tracking presents an adaptive approach that can capture the user's current needs and tailor the retrieval accordingly. Applying eye tracking to image retrieval requires that new strategies be devised that can use visual and algorithmic data to obtain natural and rapid retrieval of images. Recent work showed that the eye is faster than the mouse as a source of visual input in a target image identification task [Oyekoya and Stentiford 2005]. We explore the viability of using the eye to drive an image retrieval interface. In a visual search task, users are asked to find a target image in a database and the number of steps to the target image are counted. It is reasonable to believe that users will look at the objects in which they are interested during a search [Oyekoya and Stentiford 2004] and this provides the machine with the necessary information to retrieve a succession of plausible candidate images for the user.