This work introduces PERCEPT-PIETON, a project aiming to understand through the use of virtual reality and inertial motion capture, perceptual-motor and cognitive mechanisms involved during driver-pedestrian interactions from the driver’s point of view. We are be particularly interested in how drivers regulate their behaviour and predict pedestrian’s intentions based on individual (age, gender,...) and behavioural (walking speed, trajectory,...) characteristics of the latter. The objective is threefold : (i) a theoretical scientific contribution to obstacle avoidance literature; (ii) applied scientific knowledge for public decision-makers; and (iii) the creation of a free access library of biological pedestrians movements.

In a virtual reality public speaking training system, it is essential to control the audience’s nonverbal behavior in order to simulate different attitudes. The virtual audience’s social attitude is generally represented by a two-dimensional valence-arousal model describing the opinion and engagement of virtual characters. In this article, we argue that the valence-arousal representation is not sufficient to describe the user’s perception of a virtual character’s social attitude. We propose a three-dimensional model by dividing the valence axis into two dimensions representing the epistemic and affective stance of the virtual character, reflecting the character’s agreement and emotional reaction. To assess the perception of the virtual characters’ nonverbal behavior on these two new dimensions, we conducted a perceptive study in virtual reality with 44 participants who evaluated 50 animations combining multimodal nonverbal behavioral signals such as head movements, facial expressions, gaze direction and body posture. The results of our experiment show that, in fact, the valence axis should be divided into two axes to take into account the perception of the virtual character’s epistemic and affective stance. Furthermore, the results show that one behavioral signal is predominant for the evaluation of each dimension: head movements for the epistemic dimension and facial expressions for the affective dimension. These results provide useful guidelines for designing the nonverbal behavior of a virtual audience for social attitudes’ simulation.

In this article, we present a new open-source tool, called OUTCOME Virtual, to automatically replicate humans’ behaviors on virtual characters. The tool takes as input a human video and extracts action units, head movements, and gaze direction to animate a virtual character’s face and head with the synchronized speech in Unity. The tool is designed to be easily configured, in particular concerning the association between actions units and blend shapes, and with a user-friendly interface to select the appearance of virtual characters, the lip synchronization and the noise-correction option. The tool is illustrated in this paper with the generation of listener feedback.

In this article, we present a new tool called REVITALISE (viRtual bEhaVioral skIlls TrAining for pubLIc SpEaking) which enables the user to practice public speaking in front of a virtual audience in virtual reality. The tool is specially designed to simulate different virtual audiences to vary the user experiences. The virtual environments as well as the genders of the virtual characters and their non-verbal behaviors can be easily set-up in REVITALISE. Moreover, the motion capture-based animations, validated through a perceptive studies, enable to simulate and combine different social attitudes of the virtual audience.