Abstract:

Background modeling is a critical task in video processing, and it is the foundation of subsequent detection, recognition and tracking of moving objects. Considering the existing problems in background modeling methods, we propose a twolayer background model method based on codebook and running average. Firstly, we extract brightness and color features in the first layer and build the codebook model using the method of clustering. Then in the second layer we construct the running average model, and  through the effective combination of the two background models we achieve a fast and accurate moving object segmentation. Experimental results show that the background modeling method has advantages of low computation complexity, strong antinoise ability and fast background update speed, and it can also adapt to light change, thus applicable to moving object detection in complex environments.

Key words: background modeling;codebook;running average;segmentation;antinoise ability