The expression of human emotion is integral to social interaction, and in virtual reality it is increasingly common to develop virtual avatars that attempt to convey emotions by mimicking these visual and aural cues, i.e. the facial and vocal expressions. However, errors in (or the absence of) facial tracking can result in the rendering of incorrect facial expressions on these virtual avatars. For example, a virtual avatar may speak with a happy or unhappy vocal inflection while their facial expression remains otherwise neutral. In circumstances where there is conflict between the avatar's facial and vocal expressions, it is possible that users will incorrectly interpret the avatar's emotion, which may have unintended consequences in terms of social influence or in terms of the outcome of the interaction. In this paper, we present a human-subjects study (N = 22) aimed at understanding the impact of conflicting facial and vocal emotional expressions. Specifically we explored three levels of emotional valence (unhappy, neutral, and happy) expressed in both visual (facial) and aural (vocal) forms. We also investigate three levels of head scales (down-scaled, accurate, and up-scaled) to evaluate whether head scale affects user interpretation of the conveyed emotion. We find significant effects of different multimodal expressions on happiness and trust perception, while no significant effect was observed for head scales. Evidence from our results suggest that facial expressions have a stronger impact than vocal expressions. Additionally, as the difference between the two expressions increase, the less predictable the multimodal expression becomes. For example, for the happy-looking and happy-sounding multimodal expression, we expect and see high happiness rating and high trust, however if one of the two expressions change, this mismatch makes the expression less predictable. We discuss the relationships, implications, and guidelines for social applications that aim to leverage multimodal social cues.

Various reasons exist why humans desire to magnify portions of our visually perceived surroundings, e.g., because they are too far away or too small to see with the naked eye. Different technologies are used to facilitate magnification, from telescopes to microscopes using monocular or binocular designs. In particular, modern digital cameras capable of optical and/or digital zoom are very flexible as their high-resolution imagery can be presented to users in real-time with displays and interfaces allowing control over the magnification. In this paper, we present a novel design space of intuitive augmented reality (AR) magnifications where an AR head-mounted display is used for the presentation of real-time magnified camera imagery. We present a user study evaluating and comparing different visual presentation methods and AR interaction techniques. Our results show different advantages for unimanual, bimanual, and situated AR magnification window interfaces, near versus far vergence distances for the image presentation, and five different user interfaces for specifying the scaling factor of the imagery.

When medical caregivers transfer patients to another person’s care (a patient handoff), it is essential they effectively communicate the patient’s condition to ensure the best possible health outcomes. Emergency situations caused by mass casualty events (e.g., natural disasters) introduce additional difficulties to handoff procedures such as environmental noise. We created a projected mixed reality simulation of a handoff scenario involving a medical evacuation by air and tested how low, medium, and high levels of helicopter noise affected participants’ handoff experience, handoff performance, and behaviors. Through a human-subjects experimental design study (N = 21), we found that the addition of noise increased participants’ subjective stress and task load, decreased their self-assessed and actual performance, and caused participants to speak louder. Participants also stood closer to the virtual human sending the handoff information when listening to the handoff than they stood to the receiver when relaying the handoff information. We discuss implications for the design of handoff training simulations and avenues for future handoff communication research.

Previous research on distance estimation in virtual reality (VR) has well established that even for geometrically accurate virtual objects and environments users tend to systematically mis-estimate distances. This has implications for Social VR, where it introduces variables in personal space and proxemics behavior that change social behaviors compared to the real world. One yet unexplored factor is related to the trend that avatars' embodied cues in Social VR are often scaled, e.g., by making one's head bigger or one's voice louder, to make social cues more pronounced over longer distances. In this paper we investigate how the perception of avatar distance is changed based on two means for scaling embodied social cues: visual head scale and verbal volume scale. We conducted a human-subject study employing a mixed factorial design with two Social VR avatar representations (full-body, head-only) as a between factor as well as three visual head scales and three verbal volume scales (up-scaled, accurate, down-scaled) as within factors. For three distances from social to far-public space, we found that visual head scale had a significant effect on distance judgments and should be tuned for Social VR, while conflicting verbal volume scales did not, indicating that voices can be scaled in Social VR without immediate repercussions on spatial estimates. We discuss the interactions between the factors and implications for Social VR.

Virtual reality (VR) technologies provide a shared platform for collaboration among users in a spatial context. To enhance the quality of social signals during interaction between users, researchers and practitioners started augmenting users’ interpersonal space with different types of virtual embodied social cues. A prominent example is commonly referred to as the "Big Head" technique, in which the head scales of virtual interlocutors are slightly increased to leverage more of the display’s visual space to convey facial social cues. While beneficial in improving interpersonal social communication, the benefits and thresholds of human perception of facial cues and comfort in such Big Head environments are not well understood, limiting their usefulness and subjective experience.In this paper, we present a human-subject study that we conducted to understand the impact of an increased or decreased head scale in social VR on participants’ ability to perceive facial expressions as well as their sense of comfort and feeling of "uncanniness." We explored two head scaling methods and compared them with respect to perceptual thresholds and user preferences. We further show that the distance to interlocutors has an important effect on the results. We discuss implications and guidelines for practical applications that aim to leverage VR-enhanced social cues.

Modern augmented reality (AR) head-mounted displays comprise a multitude of sensors that allow them to sense the environment around them. We have extended these capabilities by mounting two heat-wavelength infrared cameras to a Microsoft HoloLens, facilitating the acquisition of thermal data and enabling stereoscopic thermal overlays in the user's augmented view. The ability to visualize live thermal information opens several avenues of investigation on how that thermal awareness may affect a user's thermoception. We present a human-subject study, in which we simulated different temperature shifts using either heat vision overlays or 3D AR virtual effects associated with thermal cause-effect relationships (e.g., flames burn and ice cools). We further investigated differences in estimated temperatures when the stimuli were applied to either the user's body or their environment. Our analysis showed significant effects and first trends for the AR virtual effects and heat vision, respectively, on participants' temperature estimates for their body and the environment though with different strengths and characteristics, which we discuss in this paper.

Domestic animals have a long history of enriching human lives physically and mentally by filling a variety of different roles, such as service animals, emotional support animals, companions, and pets. Despite this, technological realizations of such animals in augmented reality (AR) are largely underexplored in terms of their behavior and interactions as well as effects they might have on human users' perception or behavior. In this paper, we describe a simulated virtual companion animal, in the form of a dog, in a shared AR space. We investigated its effects on participants' perception and behavior, including locomotion related to proxemics, with respect to their AR dog and other real people in the environment. We conducted a 2 by 2 mixed factorial human-subject study, in which we varied (i) the AR dog's awareness and behavior with respect to other people in the physical environment and (ii) the awareness and behavior of those people with respect to the AR dog. Our results show that having an AR companion dog changes participants' locomotion behavior, proxemics, and social interaction with other people who can or can not see the AR dog. We also show that the AR dog's simulated awareness and behaviors have an impact on participants' perception, including co-presence, animalism, perceived physicality, and dog's perceived awareness of the participant and environment. We discuss our findings and present insights and implications for the realization of effective AR animal companions.

Embodied virtual agents serving as patient simulators are widely used in medical training scenarios, ranging from physical patients to virtual patients presented via virtual and augmented reality technologies. Physical-virtual patients are a hybrid solution that combines the benefits of dynamic visuals integrated into a human-shaped physical form that can also present other cues, such as pulse, breathing sounds, and temperature. Sometimes in simulation the visuals and shape do not match. We carried out a human-participant study employing graduate nursing students in pediatric patient simulations comprising conditions associated with matching/non-matching of the visuals and shape.

We explore whether a peripheral observation of apparent mutual social presence between a real human (RH) and a virtual human (VH) can in turn increase a subject's sense of social presence with the VH. In other words, we explore whether social presence can “transfer” from one RH-VH interaction to another. Specifically, we carried out an experiment where human subjects were asked to play a game with a VH. As they entered the game room, approximately half of the subjects were exposed to a brief but apparently engaging conversation between an RH and the VH. The subjects who were exposed to the brief RH-VH interaction had significantly higher measures of both emotional connection and the attentional allocation dimension of social presence for the VH, compared to those who were not. We describe the motivation, the experiment, and the results.

While performing everyday interactions, we often incidentally touch and move objects in subtle ways. These objects are not necessarily directly related to the task at hand, and the movement of an object might even be entirely unintentional. If another person is touching the object at the same time, the movement can transfer through the object and be experienced — however subtly — by the other person. For example, when one person hands a drink to another, at some point both individuals will be touching the glass, and consequently exerting small (often unnoticed) forces on the other person. Despite the frequency of such subtle incidental movements of shared objects in everyday interactions, few have examined how these movements affect human-virtual human (VH) interaction. We ran an experiment to assess how presence and social presence are affected when a person experiences subtle, incidental movement through a shared real-virtual object. We constructed a real-virtual room with a table that spanned the boundary between the real and virtual environments. The participant was seated on the real side of the table, which visually extended into the virtual world via a projection screen, and the VH was seated on the virtual side of the table. The two interacted by playing a game of “Twenty Questions,” where one player asked the other a series of 20 yes/no questions to deduce what object the other player was thinking about. During the game, the “wobbly” group of subjects experienced subtle incidental movements of the real-virtual table: the entire real-virtual table tilted slightly away/toward the subject when the virtual/real human leaned on it. The control group also played the same game, except the table did not wobble. Results indicate that the wobbly group had higher presence and social presence with the virtual human in general, with statistically significant increases in presence, co-presence, and attentional allocation. We present the experiment and results, and discuss some potential implications for virtual human systems and some potential future studies.

The typical registration process in augmented reality CAR) consists of three independent consecutive stages: static calibration, dynamic tracking, and graphics overlay. The result is that the real-virtual registration is “open loop”-inaccurate calibration or tracking leads to misregistration that is seen by the users but not the system. To cope with this, we propose a general approach to “close the loop” in the displayed appearance by using the visual feedback of registration for pose tracking to achieve accurate registration. Specifically, a model-based method is introduced to simultaneously track and augment real objects in a closed-loop fashion, where the model is comprised of the combination of the real object to be tracked and the virtual object to be rendered. This method is applicable to paradigms including video-based AR, projector-based AR, and diminished reality. Both qualitative and quantitative experiments are presented to demonstrate the feasibility and effectiveness of our approach.

Tracking and augmentation are usually handled in independent consecutive stages in augmented reality (AR). The result is that the real-virtual registration is “open loop”-inaccurate tracking leads to misregistration that is seen by the users but not the system. We propose a general approach to “close the loop” in the displayed appearance by using the visual feedback of registration for tracking. Specifically, a model-based method is introduced to simultaneously track and augment real objects in a closed-loop fashion, where the model is comprised of the combination of the real object to be tracked and the virtual object to be rendered. This method is applicable to paradigms including video-based AR, projector-based AR, and diminished reality.