Real-time Objects Detection Using Layered Codebook Model

In surveillance system,it was challenging to improve real-time in the presence of dynamic background motions.We presented a real-time algorithm for foreground-background segmentation based on codebook model.Pixels were converted from RGB space to YCrCb space,background model used layered model.Firstly we established a basic codebook background model and then got rough background pixels by twice frame difference,and then only trained rough background pixels which have removed foreground pixels.Secondly the foreground was segmented from the background and we updated the background in real-time. The experimental results show that this method can save time of establishment of codebook background model and has small calculation and high accuracy in scenes such as illumination changes,swaying trees and stopped objects should be considered part of the background objects.