We present two experiments to assess the relative impact of different levels of body animation fidelity on plausibility illusion (Psi). The first experiment presents a virtual character that is not controlled by the user ( n=13), while the second experiment presents a user-controlled virtual avatar ( n=24, all male). Psi concerns how realistic and coherent the events in a virtual environment look and feel and is part of Slater's proposition of two orthogonal components of presence in virtual reality (VR). In the experiments, the face, hands, upper and lower bodies of the character or self-avatar were manipulated to present different degrees of animation fidelity, such as no animation, procedural animation, and motion captured animation. Participants started the experiment experiencing the best animation configuration. Then, animation features were reduced to limit the amount of captured information made available to the system. Participants had to move from this basic animation configuration towards a more complete one, and declare when the avatar animation realism felt equivalent to the initial and most complete configuration, which could happen before all animation features were maxed out. Participants in the self-avatar experiment were also asked to rate how each animation feature affected their sense of control of the virtual body. We found that a virtual body with upper and lower body animated using eight tracked rigid bodies and inverse kinematics (IK) was often perceived as equivalent to a professional capture pipeline relying on 53 markers. Compared to what standard VR kits in the market are offering, i.e., a tracked headset and two hand controllers, we found that foot tracking, followed by mouth animation and finger tracking, were the features that added the most to the sense of control of a self-representing avatar. In addition, these features were often among the first to be improved in both experiments.

We present an assessment of asymmetric interactions in Collaborative Virtual Environments (CVEs). In our asymmetric setup, two co-located users interact with virtual 3D objects, one in immersive Virtual Reality (VR) and the other in mobile Augmented Reality (AR). We conducted a study with 36 participants to evaluate performance and collaboration aspects of pair work, and compare it with two symmetric scenarios, either with both users in immersive VR or mobile AR. To perform this experiment, we adopt a collaborative AR manipulation technique from literature and develop and evaluate a VR manipulation technique of our own. Our results indicate that pairs in asymmetric VR-AR achieved significantly better performance than the AR symmetric condition, and similar performance to VR symmetric. Regardless of the condition, pairs had similar work participation indicating a high cooperation level even when there is a visualization and interaction asymmetry between the participants.

In this paper, we describe a user study in which pairs of users watch a video trailer and interact with each other, using two social Virtual Reality (sVR) systems, as well as in a face-to-face condition. The sVR systems are: Facebook Spaces, based on puppet-like customized avatars, and a video-based sVR system using photo-realistic virtual user representations. We collect subjective and objective data to analyze users' Quality of Experience (QoE) and compare their interaction in VR to that observed during the real-life scenario. Our results show that the experience delivered by the video-based sVR system is comparable with real-life settings, while the puppet-based avatars limit the perceived quality of the interaction. Our protocol for QoE assessment is fully documented to allow replication in similar experiments.

We investigate the self-attribution of distorted pointing movements in immersive virtual reality. Participants had to complete a multidirectional pointing task in which the visual feedback of the tapping finger could be deviated in order to increase or decrease the motor size of a target relative to its visual appearance. This manipulation effectively makes the task easier or harder than the visual feedback suggests. Participants were asked whether the seen movement was equivalent to the movement they performed, and whether they have been successful in the task. We show that participants are often unaware of the movement manipulation, even when it requires higher pointing precision than suggested by the visual feedback. Moreover, subjects tend to self-attribute movements that have been modified to make the task easier more often than movements that have not been distorted. We discuss the implications and applications of our results.

We present a visualization tool for human motion analysis in augmented reality. Our tool builds upon our previous work on joint biomechanical modelling for kinematic analysis, based on optical motion capture and personalized anatomical reconstruction of joint structures from medical imaging. It provides healthcare professionals with the in situ visualization of joint movements, where bones are accurately rendered as a holographic overlay on the subject - like if the user has an “X-ray vision” - and in real-time as the subject performs the movement. Currently, hip and knee joints are supported.

We describe a calibration procedure to track consumer Head Mounted Displays (HMD) using a 3rd party tracking solution. The calibration consists of registering the center of projection of the rendering hardware to a 3rd party tracked object attached to it, and is performed by matching motion datasets from the HMD built-in and 3rd party tracking solutions. We demonstrate this calibration with an augmented reality optical see-Through HMD, where the correctness of the alignment is critical to the visual match of a real object by a virtual overlay. We assessed a mean error of 3mm (SD = 1mm) for objects at a distance of 70cm in the projected overlay image.

We present the design of a handheld-based interface for collaborative manipulations of 3D objects in mobile augmented reality. Our approach combines touch gestures and device movements for fast and precise control of 7-DOF transformations. Moreover, the interface creates a shared medium where several users can interact through their point-of-view and simultaneously manipulate 3D virtual augmentations. We evaluated our collaborative solution in two parts. First, we assessed our interface in single user mode, comparing the user task performance in three conditions: touch gestures, device movements and hybrid. Then, we conducted a study with 30 participants to understand and classify the strategies that arise while working in pairs, when partners are free to make their task organization. Furthermore, we investigated the effectiveness of simultaneous manipulations compared with the individual approach.

In the context of the 3DUI Contest promoted by the IEEE VR 2018, we propose 3D interaction techniques that address three distinct tasks in a virtual environment setup: climbing a ladder, controlling a quadcopter in a first-person view flight, and building a tower by stacking a series of objects. The interaction techniques were developed so the player, our 3D-athlete, has control over the events in each task, following metaphors that facilitate the use of the interface, and having status and spatial awareness supported by clear feedback cues. Thus, the player should be able to execute the tasks with precision and agility.

This study explores the extent to which individuals embodied in Virtual Reality tend to self-attribute the movements of their avatar. More specifically, we tested subjects performing goal-directed movements and distorted the mapping between user and avatar movements by decreasing or increasing the amplitude of the avatar hand movement required to reach for a target, while maintaining the apparent amplitude – visual distance – fixed. In two experiments, we asked subjects to report whether the movement that they have seen matched the movement that they have performed, or asked them to classify whether a distortion was making the task easier or harder to complete. Our results show that subjects perform poorly in detecting discrepancies when the nature of the distortion is not made explicit and that subjects are biased to self-attributing distorted movements that make the task easier. These findings, in line with previous accounts on the sense of agency, demonstrate the flexibility of avatar embodiment and open new perspectives for the design of guided interactions in Virtual Reality.

With the broad range of motion capture devices available on the market, it is now commonplace to directly control the limb movement of an avatar during immersion in a virtual environment. Here, we study how the subjective experience of embodying a full-body controlled avatar is influenced by motor alteration and self-contact mismatches. Self-contact is in particular a strong source of passive haptic feedback and we assume it to bring a clear benefit in terms of embodiment. For evaluating this hypothesis, we experimentally manipulate self-contacts and the virtual hand displacement relatively to the body. We introduce these body posture transformations to experimentally reproduce the imperfect or incorrect mapping between real and virtual bodies, with the goal of quantifying the limits of acceptance for distorted mapping on the reported body ownership and agency. We first describe how we exploit egocentric coordinate representations to perform a motion capture ensuring that real and virtual hands coincide whenever the real hand is in contact with the body. Then, we present a pilot study that focuses on quantifying our sensitivity to visuo-tactile mismatches. The results are then used to design our main study with two factors, offset (for self-contact) and amplitude (for movement amplification). Our main result shows that subjects' embodiment remains important, even when an artificially amplified movement of the hand was performed, but provided that correct self-contacts are ensured.

The relative location of human body parts often materializes the semantics of on-going actions, intentions and even emotions expressed, or performed, by a human being. However, traditional methods of performance animation fail to correctly and automatically map the semantics of performer postures involving self-body contacts onto characters with different sizes and proportions. Our method proposes an egocentric normalization of the body-part relative distances to preserve the consistency of self contacts for a large variety of human-like target characters. Egocentric coordinates are character independent and encode the whole posture space, i.e., it ensures the continuity of the motion with and without self-contacts. We can transfer classes of complex postures involving multiple interacting limb segments by preserving their spatial order without depending on temporal coherence. The mapping process exploits a low-cost constraint relaxation technique relying on analytic inverse kinematics; thus, we can achieve online performance animation. We demonstrate our approach on a variety of characters and compare it with the state of the art in online retargeting with a user study. Overall, our method performs better than the state of the art, especially when the proportions of the animated character deviate from those of the performer.

Object manipulation in 3D virtual environments demands a combined coordination of rotations, translations and scales, as well as the camera control to change the user's viewpoint. Then, for many manipulation tasks, it would be advantageous to share the interaction complexity among team members. In this paper we propose a novel 3D manipulation interface based on a collaborative action coordination approach. Our technique explores a smartphone -- the touchscreen and inertial sensors -- as input interface, enabling several users to collaboratively manipulate the same virtual object with their own devices. We first assessed our interface design on a docking and an obstacle crossing tasks with teams of two users. Then, we conducted a study with 60 users to understand the influence of group size in collaborative 3D manipulation. We evaluated teams in combinations of one, two, three and four participants. Experimental results show that teamwork increases accuracy when compared with a single user. The accuracy increase is correlated with the number of individuals in the team and their work division strategy.

This project investigates the impact of a virtual zero gravity experience on the human gravity model. In the planned experiment, subjects are immersed with HMD and full body motion capture in a virtual world exhibiting either normal gravity or the apparent absence of gravity (i.e. body and objects floating in space). The study evaluates changes in the subjects' gravity model by observing changes on motor planning of actions dependent on gravity. Our goal is to demonstrate that a virtual reality exposure can induce some modifications to the humans internal gravity model, analogous to those resulting from real exposure (e.g. parabolic flights), even if users remain under normal gravity condition in reality.

In this paper we evaluate the use of non-planar projections as a means to increase the Field of View (FoV) in embodied Virtual Reality (VR). Our main goal is to bring the virtual body into the user's FoV and to understand how this affects the virtual body/environment relation and quality of interaction. Subjects wore a Head Mounted Display (HMD) and were instructed to perform a selection and docking task while using either Perspective (≈ 106 ° vertical FoV), Hammer or Equirectangular (≈ 180 ° vertical FoV for both) projection. The increased FoV allowed for a shorter search time as well as less head movements. However, quality of interaction was generally inferior, requiring more time to dock, increasing docking error and producing more body/environment collisions. We also assessed cybersickness and the sense of embodiment toward the virtual body through questionnaires, for which the difference between projections seemed to be less pronounced.

We present Disambiguation canvas, a technique for selection by progressive refinement using a mobile device and consisting of two steps. During the first, the user defines a subset of objects through the orientation sensors of the device and a volume-casting pointing technique. The subsequent step consists of the disambiguation of the desired target among the previously-defined subset of objects, and is accomplished using the mobile device touchscreen. By relying on the touchscreen for the last step the user can disambiguate among hundreds of objects at once, previous progressive refinement techniques do not scale as well as ours. Disambiguation canvas is mainly developed for easy, accurate and fast selection of small objects, or objects inside cluttered virtual environments. User tests show that our technique performs faster than ray-casting for targets with ≈ 0.53° of angular size, and is also much more accurate for all the tested target sizes.