Foreground-Adaptive Motion Detection in Broad Surveillance Environments
In this letter we propose a novel motion detection method in order to accurately perform the detection of moving objects in the automatic video surveillance system. Based on the proposed Background Generation Mechanism the presence of either moving object or background in formation is firstly checked in order to supply the selective updating of the high quality adaptive background model which facilitates the further motion detection using the Laplacian distribution model. The overall results of the detection accuracy will be demonstrated that our proposed method attains a substantially higher degree of efficacy outperforming the state of the art method by average Similarity accuracy rates of up to 56 64% 27 78% 50 04% 43 33% and 44 09% respectively.
video surveillance motion detection background model