Motion detection with pyramid structure of background model for intelligent surveillance systems

This paper proposes a pyramidal background matching structure for motion detection. The proposed method utilizes spectral, spatial, and temporal features to generate a pyramidal structure of the background model. After performing the background subtraction based on the proposed background model, the moving targets can be accurately detected at each frame of the video sequence. In order to produce high accuracy for the motion detection, the proposed method also further includes a noise filter based on Bezier curve to smooth noise pixels, after which the binary motion mask can be computed by the proposed threshold function. Experimental results demonstrate that the proposed method substantially outperforms existing methods by perceptional evaluation.