In May 2024, Inria (Fortun) contributed to the prize-giving ceremony of the Mathematics Olympiad. During her speech, she presented the CrowdDNA project and the experiments carried out by the partners to about 50 high school students and teachers
This deliverable describes the efforts done during Period 1, Period 2 and part of Period 3 in the Work Package 2 of the CrowdDNA project towards developing a new crowd simulator algorithm tailored to model both macro and micro-level crowd characteristics. As a reminder, the overall objective of WP2 is to deliver a new generation of crowd simulation techniques that can predict crowd behaviours at macroscopic scales from numerical models of physical interactions.
This report details the work completed to achieve deliverable D1.3-Numerical Dataset. The data presented consists of two modalities: first, a dataset of interactions between two people that was captured with MoCap suits at the INRIA facilities; and second, a dataset of dense 3D crowd motions that were synthetically simulated using state-of-the-art crowd simulation software and then lifted to 3D by rigging 3D characters following the trajectories obtained by the simulator.
Inria presented work related to CrowdDNA at Laval Virtual 2024.
T. Chatagnon, S. Feldmann, J. Adrian, A.-H. Olivier, C. Pontonnier, L. Hoyet and J. Pettre
S. Feldmann, T. Chatagnon, J. Adrian, J. Pettre and A. Seyfried
S. Feldmann, J. Adrian and M. Boltes
Jiangbei Yue, Baiyi Li, Julien Pettre, Armin Seyfried, He Wang
Helena Lügering, Anna Sieben
Discover crowd modelling with our new video! 🎥 Have you always wanted to understand how it’s possible to move from reality to the virtual world? Dan Casas, Marc Comino, Melania Prieto Martin and Gonzalo Gomez from Universidad Rey Juan Carlos explain how they model humans as part of the CrowdDNA project.
CrowdDNA © 2021. All rights reserved. | Designed by ArtificialIdeas
This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 899739.