Real-Time Binary Descriptor Based Background Modeling

In this paper, we propose a new binary descriptor based background modeling approach which is robust to lighting changes and dynamic backgrounds in the environment. Instead of using traditional parametric models, our background models are constructed by background instances using binary descriptors computed from observed backgrounds. As shown in the experiments, our method can achieve better foreground detection results and fewer false alarms compared to the state-of-the-art methods.