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Insect swarms are common phenomena in nature and therefore have been activelypursued in computer animation. Realistic insect swarm simulation is difficultdue to two challenges: high-fidelity behaviors and large scales, which make thesimulation practice subject to laborious manual work and excessivetrial-and-error processes. To address both challenges, we present a noveldata-driven framework, FASTSWARM, to model complex behaviors of flying insectsbased on real-world data and simulate plausible animations of flying insectswarms. FASTSWARM has a linear time complexity and achieves real-timeperformance for large swarms. The high-fidelity behavior model of FASTSWARMexplicitly takes into consideration the most common behaviors of flyinginsects, including the interactions among insects such as repulsion andattraction, the self-propelled behaviors such as target following and obstacleavoidance, and other characteristics such as the random movements. To achievescalability, an energy minimization problem is formed with different behaviorsmodelled as energy terms, where the minimizer is the desired behavior. Theminimizer is computed from the real-world data, which ensures the plausibilityof the simulation results. Extensive simulation results and evaluations showthat FASTSWARM is versatile in simulating various swarm behaviors, highfidelity measured by various metrics, easily controllable in inducing usercontrols and highly scalable.

FASTSWARM: A Data-driven FrAmework for Real-time Flying InSecT SWARM Simulation