This paper presents the use of Virtual Reality (VR) for movie actors rehearsal of VFX-enhanced scenes. The impediment behind VFX scenes is that actors must be filmed in front of monochromatic green or blue screens with hardly any cue to the digital scenery that is supposed to surround them. The problem is worsens when the scene includes interaction with digital partners. The actors must pretend they are sharing the set with imaginary creatures when they are, in fact, on their own on an empty set. To support actors in this complicated task, we introduce the use of VR for acting rehearsals not only to immerse actors in the digital scenery but to provide them with advanced features for rehearsing their play. Indeed, our approach combines a fully interactive environment with a dynamic scenario feature to allow actors to become familiar with the virtual elements while rehearsing dialogue and action at their own speed. The interactive and creative rehearsals enabled by the system can be either single-user or multi-user. Moreover, thanks to the wide range of supported platforms, VR rehearsals can take place either on-set or off-set. We conducted a preliminary study to assess whether VR training can replace classical training. The results show that VR-trained actors deliver a performance just as good as ordinarily trained actors. Moreover, all the subjects in our experiment preferred VR training to classic training.

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.