TY - GEN
T1 - Implementing position-based real-time simulation of large crowds
AU - Weiss, Tomer
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Various methods have been proposed for simulating crowds of agents in recent years. Regrettably, not all are computational scalable as the number of simulated agents grows. Such quality is particularly important for virtual production, gaming, and immersive reality platforms. In this work, we provide an open-source implementation for the recently proposed Position-based dynamics approach to crowd simulation. Position-based crowd simulation was proven to be real-Time, and scalable for crowds of up to 100k agents, while retaining dynamic agent and group behaviors. We provide both non-parallel, and GPU-based implementations. Our implementation is demonstrated on several scenarios, including examples from the original work. We witness interactive computation run-Times, as well as visually realistic collective behavior.
AB - Various methods have been proposed for simulating crowds of agents in recent years. Regrettably, not all are computational scalable as the number of simulated agents grows. Such quality is particularly important for virtual production, gaming, and immersive reality platforms. In this work, we provide an open-source implementation for the recently proposed Position-based dynamics approach to crowd simulation. Position-based crowd simulation was proven to be real-Time, and scalable for crowds of up to 100k agents, while retaining dynamic agent and group behaviors. We provide both non-parallel, and GPU-based implementations. Our implementation is demonstrated on several scenarios, including examples from the original work. We witness interactive computation run-Times, as well as visually realistic collective behavior.
KW - Collisions avoidance
KW - Con straints
KW - Crowd simulation
UR - http://www.scopus.com/inward/record.url?scp=85078028016&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078028016&partnerID=8YFLogxK
U2 - 10.1109/AIVR46125.2019.00071
DO - 10.1109/AIVR46125.2019.00071
M3 - Conference contribution
AN - SCOPUS:85078028016
T3 - Proceedings - 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019
SP - 306
EP - 307
BT - Proceedings - 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019
Y2 - 9 December 2019 through 11 December 2019
ER -