  In this work we present the modular Crowd Simulation Evaluation through
Composition framework (CSEC) which provides a quantitative comparison between
different pedestrian and crowd simulation approaches. Evaluation is made based
on the comparison of source footage against synthetic video created through
novel composition techniques. The proposed framework seeks to reduce the
complexity of simulation evaluation and provide a platform from which the
comparison of differing simulation algorithms as well as parametric tuning can
be conducted to improve simulation accuracy or providing measures of similarity
between crowd simulation algorithms and source data. Through the use of
features designed to mimic the Human Visual System (HVS), specific simulation
properties can be evaluated relative to sample footage. Validation was
performed on a number of popular crowd datasets and through comparisons of
multiple pedestrian and crowd simulation algorithms.
