On the Plausibility of Virtual Body Animation Features in Virtual Reality.

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.

Agency Deficits in a Human Genetic Model of Schizophrenia: Insights From 22q11DS Patients.

Schizophrenia is a chronic and disabling mental illness characterized by a disordered sense of self. Current theories suggest that deficiencies in the sense of control over one's actions (Sense of Agency, SoA) may underlie some of the symptoms of schizophrenia. However, it is not clear if agency deficits are a precursor or a result of psychosis. Here, we investigated full body agency using virtual reality in a cohort of 22q11 deletion syndrome participants with a genetic propensity for schizophrenia. In two experiments employing virtual reality, full body motion tracking, and online feedback, we investigated SoA in two separate domains. Our results show that participants with 22q11DS had a considerable deficit in monitoring their actions, compared to age-matched controls in both the temporal and spatial domain. This was coupled with a bias toward erroneous attribution of actions to the self. These results indicate that nonpsychotic 22q11DS participants have a domain general deficit in the conscious sensorimotor mechanisms underlying the bodily self. Our data reveal an abnormality in the SoA in a cohort with a genetic predisposition for schizophrenia, but without psychosis, providing evidence that deficits in delineation of the self may be a precursor rather than a result of the psychotic state.

The Critical Role of Self-Contact for Embodiment 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.

Egocentric Mapping of Body Surface Constraints.

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.

Anatomic hepatectomy planning through mobile display visualization and interaction.

Hepatectomies are resections in which segments of the liver are extracted. While medical images are fundamental in the surgery planning procedure, the process of analysis of such images slice-by-slice is still tedious and inefficient. In this work we propose a strategy to efficiently and semi-automatically segment and classify patient-specific liver models in 3D through a mobile display device. The method is based on volume visualization of standard CT datasets and allows accurate estimation of functional remaining liver volume. Experiments showing effectiveness of the method are presented, and quantitative and qualitative results are discussed.