(This paper has been published in the 2020 ACM SIGGRAPH Conference on Motion, Interaction and Games.) Abstract: In highly dense crowds of humans, collisions between people occur often. It is common to simulate such a crowd as one fluid-like entity (macroscopic), and not as a set of individuals (microscopic, agent-based).…
(This paper will appear in the 2020 ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games.) Abstract: To simulate the low-level (‘microscopic’) behavior of human crowds, a local navigation algorithm computes how a single person (‘agent’) should move based on its surroundings. Many algorithms for this purpose have been proposed,…
(This paper has been published in the 2020 IEEE VR conference.) Abstract: This paper explores the use of VR to study human-robot interactions during navigation tasks. In our case, not only human perception is concerned, but also the one of the robot which requires to be simulated to perceive…
(This paper has been published in the 2019 ACM SIGGRAPH Conference on Motion, Interaction and Games.) Abstract: We present a novel topology-driven method for improving the navigation of agents in virtual environments. In agent-based crowd simulations, the combination of global path planning and local collision avoidance can cause conflicts and…
(This paper has been published in the 2019 ACM SIGGRAPH Conference on Motion, Interaction and Games.) Abstract: This paper introduces the use of numerical optical flow (OF) in vision-based steering techniques – that control characters locomotion trajectories by using a simulation of their visual perception. In contrast with synthetic OF…
(This paper has been published in the 2019 International Conference on Computer Animation and Social Agents.) Abstract: This paper presents a novel data-driven crowd simulation method that can mimic the observed traffic of pedestrians in a given environment. Given a set of observed trajectories, we use a recent form of…
(This paper has been published in the workshops of the 2019 Computer Vision and Pattern Recognition Conference.) Abstract: A novel approach for predicting the motion of pedestrians interacting with others. It uses a Generative Adversarial Network (GAN) to sample plausible predictions for any agent in the scene. As GANs are…
Overview: The objective of microscopic crowd simulation algorithms is to calculate the motion of a large number of agents. The movement of agents results from a set of control laws that allow them to perform actions in their environment, such as reaching a destination, or to perform interactions with other…
