Guillaume Lavoué

Introduction. Multisensory exploration of materials plays a central role in our daily lives, influencing our perceptions, emotions, and decisions. Intermodal processes integrate and assemble each stimulus to form a unified and coherent sensory image. However, the contribution of each modality to the material experience is not clearly understood. In the case of visual and tactile modalities, the two sensory channels are closely linked, which complicates the analysis of the contribution of each modality. Faced with this complexity, we have developed a virtual reality (VR) device to separate the sources through unimodal and bimodal approaches. Understanding these integrations is essential to increase the knowledge on perceptual processes and innovate in design or immersive technologies fields. Method. VR device was developed to study the emotional reactions induced by contact with five emotional materials (fur, velvet, wood, sandpaper). The emotional reactions produced in the Unimodal-Tactile only and Bimodal-visio-tactile approaches were evaluated on a panel of 28 people. The emotional feeling is measured on two dimensions: valence (tactile pleasure from unpleasant to pleasant) and Arousal (intensity of the emotional response from low to high). The link between ‘emotion’ and ‘surface topography’ is evaluated using perceptual measures (hardness, roughness, stickiness) as well as an instrumental measurement performed with an artificial finger (Touchyfinger). Result. A first unimodal study conducted in both real life and VR allowed us to conclude that our VR configuration was suitable for carrying out a multimodal study. Then two VR experiments were conducted: Unimodal VR-tactile only mode vs Bimodal VR-visio-tactile mode. No significant differences were observed, indicating that in this context, visual information does not influence tactile experience. This result supports touch dominance , which is an attentional process known as biased competition -Colavita effect. Moreover, a very strong correlation was found between the estimated valence and (i) ‘hardness, roughness, stickiness measure’s describing the materials, and (ii) the ‘instrumental measurements’ made with an artificial finger which records the topographical properties of the materials. Conclusion. Our experiments seem to reveal the existence of a tactile dominance which could be due to the intermodal integration process which degrades the visual signals coming from the virtual environment in favor of tactile perceptions.

The vast majority of simplification algorithms are based roughly on the assumption that rendering time is related to the number of primitives, with the aim of reducing memory impact and rendering complexity. In this paper, we define more precisely the links between 3D object intrinsic characteristics and rendering time in order to provide a new tool for prediction and to guide these simplification methods. We conduct a large-scale experiment in a WebGL environment on multiple devices to measure the rendering time of a set of photo-reconstructed and textured 3D meshes. The results showed us the influence of features on rendering time and that the number of vertices is not the most relevant characteristic. We then trained a predictor capable of predicting the rendering performance of a 3D mesh. This predictor takes as input various characteristics of 3D objects as well as a set of device rendering performance features that we have introduced and achieves a prediction accuracy of 1.16 ± 0.09 ms on average (19.70 ± 2.44 % relative error). We also provide an analysis of the most important characteristics for the task of prediction.

Many studies have investigated how interpersonal differences between users influence their experience in Virtual Reality (VR) and it is now well recognized that user's subjective experiences and responses to the same VR environment can vary widely. In this study, we focus on player traits, which correspond to users’ preferences for game mechanics, arguing that players react differently when experiencing VR scenarios. We developed three scenarios in the same VR environment that rely on different game mechanics, and evaluate the influence of the scenarios, the player traits and the time of practice of the VR environment on users’ perceived flow. Our results show that 1) the type of scenario has an impact on specific dimensions of flow; 2) the scenarios have different effects on flow depending on the order they are performed, the flow preconditions being stronger when performed at last; 3) almost all dimensions of flow are influenced by the player traits, these influences depending on the scenario, 4) the Aesthetic trait has the most influences in the three scenarios. We finally discuss the findings and limitations of the present study that we believe have strong implications for the design of scenarios in VR experiences.

Food craving is a main pathological issue in Eating Disorders (ED), associated with binge eating such as bulimia nervosa and binge eating disorder. Common therapies are currently based on Cognitive and Behavioral Therapies (CBT). However, a significant number of patients are not receptive to conventional CBTs. Virtual Reality (VR) is now used as a variant of CBTs, especially VR based cue exposure therapy, but only food triggers are generally considered in this form of therapy. In this context, we developed the ReVBED environment: a semi-directed VR exposure scenario allowing the induction of food craving by including multimodal stimuli. The proposed paper presents the REVBED environment and scenario, and the planned clinical study of which aim is to evaluate its effectiveness for inducing food cravings in bulimia nervosa and binge eating disorder patients, with subjective and objective measurements.

This paper presents the concept of multisensory digital twins, a brief state of the art of existing techniques for both capturing and immersive rendering of multisensory stimuli, and a case study of multisensory digital twin creation for cultural heritage.

Over the past decade, three-dimensional (3D) graphics have become highly detailed to mimic the real world, exploding their size and complexity. Certain applications and device constraints necessitate their simplification and/or lossy compression, which can degrade their visual quality. Thus, to ensure the best Quality of Experience, it is important to evaluate the visual quality to accurately drive the compression and find the right compromise between visual quality and data size. In this work, we focus on subjective and objective quality assessment of textured 3D meshes. We first establish a large-scale dataset, which includes 55 source models quantitatively characterized in terms of geometric, color, and semantic complexity, and corrupted by combinations of five types of compression-based distortions applied on the geometry, texture mapping, and texture image of the meshes. This dataset contains over 343k distorted stimuli. We propose an approach to select a challenging subset of 3,000 stimuli for which we collected 148,929 quality judgments from over 4,500 participants in a large-scale crowdsourced subjective experiment. Leveraging our subject-rated dataset, a learning-based quality metric for 3D graphics was proposed. Our metric demonstrates state-of-the-art results on our dataset of textured meshes and on a dataset of distorted meshes with vertex colors. Finally, we present an application of our metric and dataset to explore the influence of distortion interactions and content characteristics on the perceived quality of compressed textured meshes.