An end-to-end deep learning background subtraction with updating background modeling

摘要

The conventional deep background subtraction method without background updating is sensitive to unseen videos where backgrounds change frequently.In this paper,we propose a deep background subtraction method with background updating.Our proposed method can reduce the mis detection of foregrounds by introducing a feedback loop for updating our background model.