Fast background subtraction algorithm using two-level sampling and silhouette detection
Dae-Youn Lee, Jae‐Kyun Ahn, Chang‐Su Kim · 2009
An efficient background subtraction algorithm using two-level sampling and silhouette detection is proposed in this work. In the two-level sampling, we identify moving objects at the block level and then at the pixel level. Then, in the silhouette detection, around each sampled foreground pixel, we refine the shapes of foreground objects. We also develop two fast modes for the silhouette detection, which utilizes the spatio-temporal coherence of moving foreground objects. Simulation results demonstrate that the proposed algorithm provides accurate segmentation results without flickering artifacts, while requiring a low computational load.