Virtual reality has a number of advantages for analyzing sports interactions such as the standardization of experimental conditions, stereoscopic vision, and complete control of animated humanoid movement. Nevertheless, in order to be useful for sports applications, accurate perception of simulated movement in the virtual sports environment is essential. This perception depends on parameters of the synthetic character such as the number of degrees of freedom of its skeleton or the levels of detail (LOD) of its graphical representation. This study focuses on the influence of this latter parameter on the perception of the movement. In order to evaluate it, this study analyzes the judgments of immersed handball goalkeepers that play against a graphically modified virtual thrower. Five graphical representations of the throwing action were defined: a textured reference level (L0), a nontextured level (L1), a wire-frame level (L2), a moving point light display (MLD) level with a normal-sized ball (L3), and a MLD level where the ball is represented by a point of light (L4). The results show that judgments made by goalkeepers in the L4 condition are significantly less accurate than in all the other conditions ( p < .001). This finding means that the goalkeepers' perception of the movement is influenced more by the size of the ball during the judgment task than the graphical LOD of the throwing action. The MLD representation of the movement thus appears to be sufficient for a sports duel analysis in virtual environments.

Virtual humans are more and more used in VR applications, but their animation is still a challenge, especially if complex tasks must be carried out in interaction with the user. In many applications with virtual humans, credible virtual characters play a major role in presence. Motion editing techniques assume that the natural laws are intrinsically encoded in prerecorded trajectories and that modifications may preserve these natural laws, leading to credible autonomous actors. However, a complete knowledge of all the constraints is required to ensure continuity or to synchronize and blend several actions necessary to achieve a given task. We propose a framework capable of performing these tasks in an interactive environment that can change at each frame, depending on the user’s orders. This framework enables VR applications to animate from dozens of characters in real time for complex constraints, to hundreds of characters if only ground adaptation is performed. It offers the following capabilities: motion synchronization, blending, retargeting, and adaptation thanks to enhanced inverse kinetics and kinematics solver. To evaluate this framework, we have compared the motor behavior of subjects in real and in virtual environments.

Virtual reality offers new tools for human motion understanding. Several applications have been widely used in teleoperation, military training, driving and flying simulators, and so forth. We propose to test if virtual reality is a valid training tool for the game of handball. We focused on the duel between a handball goalkeeper and a thrower. To this end, we defined a pilot experiment divided into two steps: an experiment with real subjects and another one with virtual throwers. The throwers' motions were captured in order to animate their avatar in a reality center. In this paper, we focused on the evaluation of presence when a goalkeeper is confronting these avatars. To this end, we compared the goalkeeper's gestures in the real and in the virtual experiment to determine if virtual reality engendered the same movements for the same throw. Our results show that gestures did not differ between the real and virtual environment. As a consequence, we can say that the virtual environment offered enough realism to initiate natural gestures. Moreover, as in real games, we observed the goalkeeper's anticipation to allow us to use virtual reality in future work as a way to understand the goalkeeper and thrower interactions. The main originality of this work was to measure presence in a sporting application with new evaluation methods based on motion capture.