Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
409669 | Neurocomputing | 2013 | 11 Pages |
In this paper, we address the difficult task of moving objects segmentation and matting in dynamic scenes. Toward this end, we propose a new automatic way to integrate a background subtraction (BGS) and an alpha matting technique via a heuristic seeds selection scheme. Specifically, our method can be divided into three main steps. First, we use a novel BGS method as attention mechanisms, generating many possible foreground pixels by tuning it for low false-positives and false-negatives as much as possible. Second, a connected components algorithm is used to give the bounding boxes of the labeled foreground pixels. Finally, matting of the object associated to a given bounding box is performed using a heuristic seeds selection scheme. This matting task is guided by top-down knowledge. Experimental results demonstrate the efficiency and effectiveness of our method.