Learn More
In the everyday exercise of controlling their locomotion, humans rely on their optic flow of the perceived environment to achieve collision-free navigation. In crowds, in spite of the complexity of the environment made of numerous obstacles, humans demonstrate remarkable capacities in avoiding collisions. Cognitive science work on human locomotion states(More)
An interaction occurs between two humans when they walk with converging trajectories. They need to adapt their motion in order to avoid and cross one another at respectful distance. This paper presents a model for solving interactions between virtual humans. The proposed model is elaborated from experimental interactions data. We first focus our study on(More)
Virtual walking, a fundamental task in Virtual Reality (VR), is greatly influenced by the locomotion interface being used, by the specificities of input and output devices, and by the way the virtual environment is represented. No matter how virtual walking is controlled, the generation of realistic virtual trajectories is absolutely required for some(More)
Figure 1: Parameter Optimization Applied to Crowd Data (a) motion capture session for recording reference trajectories for six human agents (b) reference data plot (circles are initial positions) (c) paths taken by simulated agents with default parameters (d) paths taken by simulated agents with optimized parameters. The stock parameters of a simulation(More)
This study investigated collision avoidance between two walkers by focusing on the conditions that lead to avoidance manoeuvres in locomotor trajectories. Following the hypothesis of a reciprocal interaction, we suggested a mutual variable as a continuous function of the two walkers' states, denoted minimum predicted distance (MPD). This function predicts(More)
This paper studies strategies for collision avoidance between two persons walking along crossing trajectories. It has been previously demonstrated that walkers are able to anticipate the risk of future collision and to react accordingly. The avoidance task has been described as a mutual control of the future distance of closest approach, MPD (i.e., Mininum(More)
The use of Virtual Reality (VR) in sports training is now widely studied with the perspective to transfer motor skills learned in virtual environments (VEs) to real practice. However precision motor tasks that require high accuracy have been rarely studied in the context of VE, especially in Large Screen Image Display (LSID) platforms. An example of such a(More)
The performance of an interactive virtual crowd system for entertainment purposes can be greatly improved by setting a level-of-details (LOD) strategy: in distant areas, collision avoidance can even be stealthy disabled to drastically speed-up simulation and to handle huge crowds. The greatest difficulty is then to select LODs to progressively simplify(More)
When avoiding a group, a walker has two possibilities: either he goes through it or around it. Going through very dense groups or around huge ones would not seem natural and could break any sense of presence in a virtual environment. This paper aims to enable crowd simulators to handle such situations correctly. To this end, we need to understand how real(More)