A Novel Background Subtraction Method Based on ViBe

摘要

In recent years, a large number of background subtraction methods have been proposed. Among these methods, the visual background subtraction method (ViBe) receives much attention due to its high efficiency and good performance. However, it can not work well in complex environments. Therefore, in this paper, we propose a novel background subtraction method based on ViBe, including a new foreground object detection strategy, a bilateral aperture detection strategy, and two effective strategies for foreground noise detection and ghost region detection. The proposed method can effectively alleviate the problems caused by foreground aperture, dynamic backgrounds and ghosts in background subtraction. Experiments on the benchmark dataset show that, the proposed method not only obtains better results compared with a couple of ViBe-based variants, but also achieves competitive results against several state-of-the-art methods.