The Relational Properties among Results of Background Subtraction

Many background subtraction techniques have been proposed to detect changes such as moving objects in videos. In this paper, we classify them into two approaches according to forms of the regions detected as moving object. The first one is using frame difference and the second one is exploiting background model. We show characteristics of the two approaches and the relational properties among their products. Then we also show these properties can be used for estimating another result from one approach and identifying the region should be updated in adaptive background model.