The growing availability of affordable Virtual Reality (VR) hardware and the increasing interest in the Metaverse are driving the expansion of Social VR (SVR) platforms. These platforms allow users to embody avatars in immersive social virtual environments, enabling real-time interactions using consumer devices. Beyond merely replicating real-life social dynamics, SVR platforms offer opportunities to surpass real-world constraints by augmenting these interactions. One example of such augmentation is Artificial Facial Mimicry (AFM), which holds significant potential to enhance social experiences. Mimicry, the unconscious imitation of verbal and non-verbal behaviors, has been shown to positively affect human-agent interactions, yet its role in avatar-mediated human-to-human communication remains under-explored. AFM presents various possibilities, such as amplifying emotional expressions, or substituting one emotion for another to better align with the context. Furthermore, AFM can address the limitations of current facial tracking technologies in fully capturing users' emotions. To investigate the potential benefits of AFM in SVR, an automated AM system was developed. This system provides AFM, along with other kinds of head mimicry (nodding and eye contact), and it is compatible with consumer VR devices equipped with facial tracking. This system was deployed within a test-bench immersive SVR application. A between-dyads user study was conducted to assess the potential benefits of AFM for interpersonal communication while maintaining avatar behavioral naturalness, comparing the experiences of pairs of participants communicating with AFM enabled against a baseline condition. Subjective measures revealed that AFM improved interpersonal closeness, aspects of social attraction, interpersonal trust, social presence, and naturalness compared to the baseline condition. These findings demonstrate AFM's positive impact on key aspects of social interaction and highlight its potential applications across various SVR domains.

Cybersickness (CS) represents one of the oldest problems affecting Virtual Reality (VR) technology. In an attempt to resolve or at least limit this form of discomfort, an increasing number of mitigation techniques have been proposed by academic and industrial researchers. However, the validation of such techniques is often carried out without grounding on a common methodology, making the comparison between the various works in the state of the art difficult. To address this issue, the present article proposes a novel testbed for studying CS in immersive VR and, in particular, methods to mitigate it. The testbed consists of four virtual scenarios, which have been designed to elicit CS in a targeted and predictable manner. The scenarios, grounded on available literature, support the extraction of objective metrics about user's performance. The testbed additionally integrates an experimental protocol that employs standard questionnaires as well as measurements typically adopted in state-of-the-art practice to assess levels of CS and other subjective aspects regarding User Experience. The article shows a possible use case of the testbed, concerning the evaluation of a CS mitigation technique that is compared with the absence of mitigation as baseline condition.

Abstract With the development of metaverse(s), industry and academia are searching for the best ways to represent users' avatars in shared virtual environments (VEs), where real‐time communication between users is required. The expressiveness of avatars is crucial for transmitting emotions that are key for social presence and user experience, and are conveyed via verbal and non‐verbal facial and body signals. In this paper, two real‐time modalities for conveying expressions in virtual reality (VR) via realistic, full‐body avatars are compared by means of a user study. The first modality uses dedicated hardware (i.e., eye and facial trackers) to allow a mapping between the user's facial expressions/eye movements and the avatar model. The second modality relies on an algorithm that, starting from an audio clip, approximates the facial motion by generating plausible lip and eye movements. The participants were requested to observe, for both the modalities, the avatar of an actor performing six scenes involving as many basic emotions. The evaluation considered mainly social presence and emotion conveyance. Results showed a clear superiority of facial tracking when compared to lip sync in conveying sadness and disgust. The same was less evident for happiness and fear. No differences were observed for anger and surprise.

A common operation performed in Virtual Reality (VR) environments is locomotion. Although real walking can represent a natural and intuitive way to manage displacements in such environments, its use is generally limited by the size of the area tracked by the VR system (typically, the size of a room) or requires expensive technologies to cover particularly extended settings. A number of approaches have been proposed to enable effective explorations in VR, each characterized by different hardware requirements and costs, and capable to provide different levels of usability and performance. However, the lack of a well-defined methodology for assessing and comparing available approaches makes it difficult to identify, among the various alternatives, the best solutions for selected application domains. To deal with this issue, this article introduces a novel evaluation testbed which, by building on the outcomes of many separate works reported in the literature, aims to support a comprehensive analysis of the considered design space. An experimental protocol for collecting objective and subjective measures is proposed, together with a scoring system able to rank locomotion approaches based on a weighted set of requirements. Testbed usage is illustrated in a use case requesting to select the technique to adopt in a given application scenario.

Although passive haptic interfaces have been shown to be capable to enhance the user's sense of presence in Mixed Reality experiences, their use is still constrained by the need to rely on exact replicas of virtual objects or on custom-made devices mimicking the original ones. Unfortunately, the former are not flexible enough in terms of reconfigurability, whereas the latter may be difficult to reproduce. To tackle these issues, this paper explores the possibility to build passive haptic interfaces using off-the-shelf toy construction bricks. Bricks can be assembled to provide the intended feedback in more than one task. Moreover, they may be reassembled in another application to mimic completely new objects and support totally different tasks.