Peripheral vision plays a significant role in human perception and orientation. However, its relevance for human-computer interaction, especially head-mounted displays, has not been fully explored yet. In the past, a few specialized appliances were developed to display visual cues in the periphery, each designed for a single specific use case only. A multi-purpose headset to exclusively augment peripheral vision did not exist yet. We introduce MoPeDT: Modular Peripheral Display Toolkit, a freely available, flexible, reconfigurable, and extendable headset to conduct peripheral vision research. MoPeDT can be built with a 3D printer and off-the-shelf components. It features multiple spatially configurable near-eye display modules and full 3D tracking inside and outside the lab. With our system, researchers and designers may easily develop and prototype novel peripheral vision interaction and visualization techniques. We demonstrate the versatility of our headset with several possible applications for spatial awareness, balance, interaction, feedback, and notifications. We conducted a small study to evaluate the usability of the system. We found that participants were largely not irritated by the peripheral cues, but the headset's comfort could be further improved. We also evaluated our system based on established heuristics for human-computer interaction toolkits to show how MoPeDT adapts to changing requirements, lowers the entry barrier for peripheral vision research, and facilitates expressive power in the combination of modular building blocks.

Virtual Reality (VR) provides new possibilities for modern knowledge work. However, the potential advantages of virtual work environments can only be used if it is feasible to work in them for an extended period of time. Until now, there are limited studies of long-term effects when working in VR. This paper addresses the need for understanding such long-term effects. Specifically, we report on a comparative study $i$, in which participants were working in VR for an entire week-for five days, eight hours each day-as well as in a baseline physical desktop environment. This study aims to quantify the effects of exchanging a desktop-based work environment with a VR-based environment. Hence, during this study, we do not present the participants with the best possible VR system but rather a setup delivering a comparable experience to working in the physical desktop environment. The study reveals that, as expected, VR results in significantly worse ratings across most measures. Among other results, we found concerning levels of simulator sickness, below average usability ratings and two participants dropped out on the first day using VR, due to migraine, nausea and anxiety. Nevertheless, there is some indication that participants gradually overcame negative first impressions and initial discomfort. Overall, this study helps lay the groundwork for subsequent research, by clearly highlighting current shortcomings and identifying opportunities for improving the experience of working in VR.

Virtual Reality experiences and games present believable virtual environments based on graphical quality, spatial audio, and interactivity. The interaction with in-game characters, controlled by computers (agents) or humans (avatars), is an important part of VR experiences. Pre-captured motion sequences increase the visual humanoid resemblance. However, this still precludes realistic social interactions (eye contact, imitation of body language), particularly for agents. We aim to make social interaction more realistic via social touch. Social touch is non-verbal, conveys feelings and signals (coexistence, closure, intimacy). In our research, we created an artificial hand to apply social touch in a repeatable and controlled fashion to investigate its effect on the perceived human-likeness of avatars and agents. Our results show that social touch is effective to further blur the boundary between computer- and human-controlled virtual characters and contributes to experiences that closely resemble human-to-human interactions.

Realistic, metrically accurate, 3D human avatars are useful for games, shopping, virtual reality, and health applications. Such avatars are not in wide use because solutions for creating them from high-end scanners, low-cost range cameras, and tailoring measurements all have limitations. Here we propose a simple solution and show that it is surprisingly accurate. We use crowdsourcing to generate attribute ratings of 3D body shapes corresponding to standard linguistic descriptions of 3D shape. We then learn a linear function relating these ratings to 3D human shape parameters. Given an image of a new body, we again turn to the crowd for ratings of the body shape. The collection of linguistic ratings of a photograph provides remarkably strong constraints on the metric 3D shape. We call the process crowdshaping and show that our Body Talk system produces shapes that are perceptually indistinguishable from bodies created from high-resolution scans and that the metric accuracy is sufficient for many tasks. This makes body "scanning" practical without a scanner, opening up new applications including database search, visualization, and extracting avatars from books.

We investigated the influence of body shape and pose on the perception of physical strength and social power for male virtual characters. In the first experiment, participants judged the physical strength of varying body shapes, derived from a statistical 3D body model. Based on these ratings, we determined three body shapes (weak, average, and strong) and animated them with a set of power poses for the second experiment. Participants rated how strong or powerful they perceived virtual characters of varying body shapes that were displayed in different poses. Our results show that perception of physical strength was mainly driven by the shape of the body. However, the social attribute of power was influenced by an interaction between pose and shape. Specifically, the effect of pose on power ratings was greater for weak body shapes. These results demonstrate that a character with a weak shape can be perceived as more powerful when in a high-power pose.