A non-parametric pixel-based background modeling for dynamic scenes

Background modeling is one of the most important parts of visual surveillance systems. However, making the pixels background model can be problematic, especially in high resolution video sequences of dynamic scenes. We proposed an efficient non-parametric method for modeling which consumes little computational resources and memory. In our method, the history of each pixel is modeled by a 2timesK_p matrix, where K_p changes adaptively with complexity of that pixel. Experimental results demonstrate the effectiveness of the algorithm when applied in complex real-world sequences.