Fine-level moving object detection using region-based background/foreground model

Background subtraction forms the first stage in an automated visual surveillance system. Most fine-level background subtraction techniques are based on the analysis of pixel-based distribution, while region-based models are more robust to dynamic backgrounds. Hence, it is reasonable to refine the coarse foreground extracted by region-based subtraction, so that detailed shape information can be available just like the result of pixel-based subtraction. In this paper, we propose a method for the fine processing of coarse foreground block.