In this paper, we present a fully automatic pipeline for generating and stylizing high geometric and textural quality facial rigs. They are automatically rigged with facial blendshapes for animation, and can be used across platforms for applications including virtual reality, augmented reality, remote collaboration, gaming and more. From a set of input facial photos, our approach is to be able to create a photorealistic, fully rigged character in less than seven minutes. The facial mesh reconstruction is based on state-of-the art photogrammetry approaches. Automatic landmarking coupled with ICP registration with regularization provide direct correspondence and registration from a given generic mesh to the acquired facial mesh. Then, using deformation transfer, existing blendshapes are transferred from the generic to the reconstructed facial mesh. The reconstructed face is then fit to the full body generic mesh. Extra geometry such as jaws, teeth and nostrils are retargeted and transferred to the character. An automatic iris color extraction algorithm is performed to colorize a separate eye texture, animated with dynamic UVs. Finally, an extra step applies a style to the photorealis-tic face to enable blending of personalized facial features into any other character. The user's face can then be adapted to any human or non-human generic mesh. A pilot user study was performed to evaluate the utility of our approach. Up to 65% of the participants were successfully able to discern the presence of one's unique facial features when the style was not too far from a humanoid shape.

Current virtual reality systems enable users to explore virtual worlds, fully embodied in avatars. This new type of immersive experience requires specific authoring tools. The traditional ones used in the movie and the video games industries were modified to support immersive visual and audio content. However, few solutions exist to edit haptic content, especially when the whole user's body is involved. To tackle this issue we propose HFX Studio, a haptic editor based on haptic perceptual models. Three models of pressure, vibration and temperature were defined to allow the spatialization of haptic effects on the user's body. These effects can be designed directly on the body (egocentric approach), or specified as objects of the scene (allocentric approach). The perceptual models are also used to describe capabilities of haptic devices. This way the created content is generic, and haptic feedback is rendered on the available devices. The concept has been implemented with the Unity®game engine, a tool already used in VR production. A qualitative pilot user study was conducted to analyze the usability of our tool with expert users. Results shows that the edition of haptic feedback is intuitive for these users.

This paper investigates the role of the embodiment in an immersive video experience. A system allowing to play back omnidirectional videos enhanced with real-time 3D content is presented. It enables the user to be embodied in an avatar and to interact with 3D objects added to the video. A user study was conducted to understand the impact of this embodiment on the user experience. Four different avatars were compared (none, human, ghost and astronaut) as well as three levels of user control on the avatar, and also the possibility to interact with the content. Results show that being embodied has benefits on the user experience but requires the representation to be in line with the story and the avatar to be fully controllable. Indeed a misadapted embodiment may decrease the experience.

Summary form only given. The CORVETTE project aims at producing significant innovations in the field of collaborative virtual training. For that purpose, CORVETTE combines various technologies to enhance the effective collaboration between users and virtual humans performing a common task. First, CORVETTE proposes a model of collaborative interaction in virtual environments allowing actors to efficiently collaborate as a team whether they are controlled by a user or by a virtual human [4]. Moreover, the environment is simulated in real-time, at real scale and is using physics as well as physically-based humanoids to improve the realism of the training. Second, thanks to the interaction model, we defined a protocol of exchange of avatars [5, 3, 2]. Thus, an actor can dynamically exchange the control of his/her avatar with the one controlled by another user or by a virtual agent. Moreover, to improve the exchange protocol, we designed a new knowledge model embedded in each avatar. It allows users and virtual humans to retrieve knowledge previously gathered by an avatar following an exchange. The preservation of knowledge is indeed especially crucial for teamwork. Finally, we handle verbal communication between users and virtual humans with speech recognition and synthesis. Actors' knowledge is enhanced through dialogue and used for decision-making and conversation [1].

ABSTRACT Virtual agents are a real asset in collaborative virtual environment for training (CVET) as they can replace missing team members. Collaboration between such agents and users, however, is generally limited. We present here a whole integrated model of CVET focusing on the abstraction of the real or virtual nature of the actor to define a homogenous collaboration model. First, we define a new collaborative model of interaction. This model notably allows to abstract the real or virtual nature of a teammate. Moreover, we propose a new role exchange approach so that actors can swap their roles during training. The model also permits the use of physically based objects and characters animation to increase the realism of the world. Second, we design a new communicative agent model, which aims at improving collaboration with other actors using dialog to coordinate their actions and to share their knowledge. Finally, we evaluated the proposed model to estimate the resulting benefits for the users and we show that this is integrated in existing CVET applications. Copyright © 2014 John Wiley & Sons, Ltd.

The exchange of avatars, i.e. the actual fact of changing once avatar with another one, is a promising trend in multi-actor virtual environments. It provides new opportunities for users, such as controlling a different avatar for a specific action, retrieving knowledge belonging to a particular avatar, solving conflicts and deadlocks situations or even helping another user. Virtual Environments for Training are especially affected by this trend as a specific role derived from a scenario is usually assigned to a unique avatar. Despite the increasing use of avatar exchange, users' perception and understanding of this mechanism have not been studied. In this paper, we propose two complementary user-centered evaluations that aim at comparing several representations for the exchange of avatars; these are termed exchange metaphors. Our first experiment focuses on the perception of an exchange by a user who is not involved in the exchange, and the second experiment analyzes the perception of an exchange triggered by the user. Results show that the use of visual feedback globally aids better understanding of the exchange mechanism in both cases. Our first experiment suggests, however, that visual feedback is less efficient than a simple popup notification in terms of task duration. In addition, the second experiment shows that much simpler metaphors with no visual effect are generally preferred because of their efficiency.

ABSTRACT Navigation is a critical task for agents populating virtual worlds. In the last years, numerous solutions have been proposed to solve the path planning problem in order to enhance the autonomy of virtual agents. Those solutions mainly focused on static environments, eventually populated with dynamic obstacles. However, dynamic objects are usually more than just obstacles as they can be used by an agent to reach new locations. In this paper, we propose an online path planning algorithm in dynamically changing environments with unknown evolution such as physically based‐environments. Our method represents objects in terms of obstacles but also in terms of navigable surfaces. This representation allows our algorithm to find temporal paths through disconnected and moving platforms. We will also show that the proposed method also enables several kinds of adaptations such as avoiding moving obstacles or adapting the agent postures to environmental constraints. Copyright © 2012 John Wiley & Sons, Ltd.