Juiciness is visual pizzazz used to improve player experience and engagement in games. Most research has focused on juicy particle effects. However, text effects are also commonly used in games, albeit not always juiced up. One type is onomatopoeia, a well-defined element of human language that has been translated to visual media, such as comic books and games. Another is semantic text, often used to provide performance feedback in games. In this work, we explored the relationship between juiciness and text effects, aiming to replicate juicy user experiences with text-based juice and combining particle and text juice. We show in a multi-phase within-subjects experiment that users rate juicy text effects similarly to particles effects, with comparable performance, and more reliable feedback. We also hint at potential improvement in user experience when both are combined, and how text stimuli may be perceived differently than other visual ones. We contribute empirical findings on the juicy-text connection in the context of visual effects for interactive media.

When humans generate stimuli voluntarily, they perceive the stimuli more weakly than those produced by others, which is called sensory attenuation (SA). SA has been investigated in various body parts, but it is unclear whether an extended body induces SA. This study investigated the SA of audio stimuli generated by an extended body. SA was assessed using a sound comparison task in a virtual environment. We prepared robotic arms as extended bodies, and the robotic arms were controlled by facial movements. To evaluate the SA of robotic arms, we conducted two experiments. Experiment 1 investigated the SA of the robotic arms under four conditions. The results showed that robotic arms manipulated by voluntary actions attenuated audio stimuli. Experiment 2 investigated the SA of the robotic arm and innate body under five conditions. The results indicated that the innate body and robotic arm induced SA, while there were differences in the sense of agency between the innate body and robotic arm. Analysis of the results indicated three findings regarding the SA of the extended body. First, controlling the robotic arm with voluntary actions in a virtual environment attenuates the audio stimuli. Second, there were differences in the sense of agency related to SA between extended and innate bodies. Third, the SA of the robotic arm was correlated with the sense of body ownership.

Weathering phenomena are ubiquitous in urban environments, where it is easy to observe severely degraded old buildings as a result of water penetration. Despite being an important part of any realistic city, this kind of phenomenon has received little attention from the Computer Graphics community compared to stains resulting from biological or flow effects on the building exteriors. In this paper, we present physically-inspired deep weathering effects, where the penetration of humidity (i.e., water particles) and its interaction with a building’s internal structural elements result in large, visible degradation effects. Our implementation is based on a particle-based propagation model for humidity propagation, coupled with a spring-based interaction simulation that allows chemical interactions, like the formation of rust, to deform and destroy a building’s inner structure. To illustrate our methodology, we show a collection of deep degradation effects applied to urban models involving the creation of rust or of ice within walls.

Virtual Reality (VR) lets us experiment embodiment. Here we investigate dual embodiment under the prism of dual motor adaptation. We asked participants (N=21) to perform reaching motions in VR with opposite gradual visuomotor perturbations. The participants sequentially switched between 2 VR bodies and had to adapt to the VR body’s perturbation (up to +15° for the VR bodyA, and-15° for the VR bodyB). We then designed a 2$\times$2 within-subject study: 1 factor being the perspective (1stperson or 3rdperson), and 1 factor being the head rotation (without head rotation before the reaching motion or with head rotation before the reaching motion). We found that by providing strong visual cues between bodies (alternating symmetric perspective and/or symmetric head rotation), participants had little awareness of the perturbations, good adaptation, and large aftereffects in both VR bodies. Those elements are consistent with implicit dual adaptation. In contrast, a naive 1st person perspective resulted in little to no adaptation with a high cognitive load and no aftereffects.

Makeup (i.e., cosmetics) has long been used to transform not only one’s appearance but also their self-representation. Previous studies have demonstrated that visual transformations can induce a variety of effects on self-representation. Herein, we introduce Digital Speech Makeup (DSM), the novel concept of using voice conversion (VC) based auditory feedback to transform human self-representation. We implemented a proof-of-concept system that leverages a state-of-the-art algorithm for near real-time VC and bone-conduction headphones for resolving speech disruptions caused by delayed auditory feedback. Our user study confirmed that conversing for a few dozen minutes using the system influenced participants’ speech ownership and implicit bias. Furthermore, we reviewed the participants’ comments about the experience of DSM and gained additional qualitative insight into possible future directions for the concept. Our work represents the first step towards utilizing VC to design various interpersonal interactions, centered on influencing the users’ psychological state.

In comics, Textual Sound Effects (TE) can describe sounds, but also actions, events, etc. TE could be used in Virtual Environment to efficiently create an easily recognizable scene and add more information to objects at a relatively low design cost. We investigate the impact of TE in a Virtual Environment on objects’ material perception (on category and properties) and on sound perception (on volume [dB] and spatial position). Participants (N=13, repeated measures) categorized metallic and wooden spheres and significantly changed their reaction time depending on the TE congruence with the spheres’ material/sound. They then rated a sphere’s properties (i.e., wetness, warmness, softness, smoothness, and dullness) and significantly changed their rating depending on the TE. When comparing 2 sound volumes, they perceived a sound associated with a shrinking TE as less loud and a sound associated with a growing TE as louder. When locating an audio source location, they located it significantly closer to a TE.

This paper presents development on a conceptual method to remap supernumerary limbs using Virtual Reality (VR) as a platform for experimentation. Our VR system allows users to control a third arm through their own limbs such as their head, arms, and feet with the ability to switch between them. To realize and experiment with our remapping method, we used the Oculus Rift in conjunction with OptiTrack to track users in a room-scaled virtual environment. We present some initial findings from a small pilot study and conclude with suggestions for future work.

With advancements in robotics, systems featuring wearable robotic arms teleoperated by a third party are appearing. An important aspect of these systems is the visual feedback provided to the third party operator. This can be achieved by placing a wearable camera on the robotic arm's “host,” or Main Body Operator (MBO), but such a setup makes the visual feedback dependant on the movements of the main body. Here we introduce a VR system called Parasitic Body to explore a VR shared body concept representative of the wearable robotic arms “host” (the MBO) and of the teleoperator (here called the Parasite Body Operator (PBO)). 2 users jointly operate a shared virtual body with a third arm: The MBO controls the main body and the PBO controls a third arm sticking out from the left shoulder of the main body. We focused here on the perspective dependency of the PBO (indeed, the PBO view is dependant of the movement of the MBO) in a “finding and reaching” task.

Robot assistance can reduce the user's workload of a task. However, the robot needs to be programmed or trained on how to assist the user. Virtual Reality (VR) can be used to train and validate the actions of the robot in a safer and cheaper environment. In this paper, we examine how a robotic arm can be trained using Coloured Petri Nets (CPN) and Partial Least Squares Regression (PLSR). Based upon these algorithms, we discuss the concept of using the user's acceleration and rotation as a sufficient means to train a robotic arm for a procedural task in VR. We present a work-in-progress system for training robotic limbs using VR as a cost effective and safe medium for experimentation. Additionally, we propose PLSR data that could be considered for training data analysis.

In this paper we present an immersive virtual reality user study aimed at investigating how customers perceive and if they would purchase non-standard (i.e. misshaped) fruits and vegetables (FaVs) in supermarkets and hypermarkets. Indeed, food waste is a major issue for the retail sector and a recent trend is to reduce it by selling non-standard goods. An important question for retailers relates to the FaVs' “level of abnormality” that consumers would agree to buy. However, this question cannot be tackled using “classical” marketing techniques that perform user studies within real shops since fresh produce such as FaVs tend to rot rapidly preventing studies to be repeatable or to be run for a long time. In order to overcome those limitations, we created a virtual grocery store with a fresh FaVs section where 142 participants were immersed using an Oculus Rift DK2 HMD. Participants were presented either “normal”, “slightly misshaped”, “misshaped” or “severely misshaped” FaVs. Results show that participants tend to purchase a similar number of FaVs whatever their deformity. Nevertheless participants' perceptions of the quality of the FaV depend on the level of abnormality.