Robust background modeling via standard variance feature

In this paper, a novel standard variance feature is proposed for background modeling in dynamic scenes involving waving trees and ripples in water. The standard variance feature is the standard variance of a set of pixels´ feature values, which captures mainly co-occurrence statistics of neighboring pixels in an image patch. The background modeling method based on standard variance feature includes two main components. First, we divide image into patches and represent each image patch as a standard variance feature. Then, assuming that standard variance feature fits a mixture of Gaussians distribution, we use mixture of Gaussians models to model it. Experimental results on several challenging video sequences demonstrate the effectiveness of our method.