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In this work we present the modular Crowd Simulation Evaluation throughComposition framework (CSEC) which provides a quantitative comparison betweendifferent pedestrian and crowd simulation approaches. Evaluation is made basedon the comparison of source footage against synthetic video created throughnovel composition techniques. The proposed framework seeks to reduce thecomplexity of simulation evaluation and provide a platform from which thecomparison of differing simulation algorithms as well as parametric tuning canbe conducted to improve simulation accuracy or providing measures of similaritybetween crowd simulation algorithms and source data. Through the use offeatures designed to mimic the Human Visual System (HVS), specific simulationproperties can be evaluated relative to sample footage. Validation wasperformed on a number of popular crowd datasets and through comparisons ofmultiple pedestrian and crowd simulation algorithms.

A Human and Group Behaviour Simulation Evaluation Framework utilising Composition and Video Analysis