A comparison of background subtraction algorithms evaluated with BMC dataset
Gongyan Wang, Jing Xu, Ming Fang · 2016
Many background subtraction algorithms have been proposed in the last fifteen years and an important issue is to provide a way to evaluate and compare most popular models according to criteria. This paper present a comparison among the eleven models using BMC dataset and give a guideline to choose different algorithms in different scenes by computing the F-measure, Peak Signal-Noise Ratio, Structural Similarity and D-Score in the experiment.