Hierarchical Model for Real Time Simulation of Virtual Human Crowds
IEEE Transactions on Visualization and Computer Graphics
Crowdbrush: interactive authoring of real-time crowd scenes
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Fastest Mixing Markov Chain on a Graph
SIAM Review
Scalable pedestrian simulation for virtual cities
Proceedings of the ACM symposium on Virtual reality software and technology
ACM SIGGRAPH 2004 Course Notes
Optimized stochastic policies for task allocationin swarms of robots
IEEE Transactions on Robotics
Smart events and primed agents
IVA'10 Proceedings of the 10th international conference on Intelligent virtual agents
CAROSA: a tool for authoring NPCs
MIG'10 Proceedings of the Third international conference on Motion in games
Interactive hybrid simulation of large-scale traffic
Proceedings of the 2011 SIGGRAPH Asia Conference
Event-Centric control for background agents
ICIDS'11 Proceedings of the 4th international conference on Interactive Digital Storytelling
Crowd simulation using Discrete Choice Model
VR '12 Proceedings of the 2012 IEEE Virtual Reality
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Crowd activities are often randomized to create the appearance of heterogeneity. However, the parameters that control randomization are frequently hard to tune because it is unclear how changes at the character level affect the high-level appearance of the crowd. We propose a method for computing randomization parameters that supports direct animator control. Given details about the environment, available activities, timing information and the desired high-level appearance of the crowd, we model the problem as a graph, formulate a convex optimization problem, and solve for a set of stochastic transition rates which satisfy the constraints. Unlike the use of heuristics for adding randomness to crowd activities, our approach provides guarantees on convergence to the desired result, allows for decentralized simulation, and supports a variety of constraints. In addition, because the rates can be pre-computed, no additional runtime processing is needed during simulation.