An Improved Gaussian Mixture Model Method for Moving Object Detection
Abstract: Aiming at the
shortcomings of Gaussian mixture model background method, a moving object detection
method mixed with adaptive iterative block and interval frame difference method
in the Gaussian mixture model is proposed. In this method, the video sequences
are divided into different size pieces in order to reduce the amount of
calculation of the algorithm. It not only effectively solves the problem that
the traditional Gaussian mixture model algorithm cannot detect large and slow
moving object accurately, but also solves empty and no connection problems due
to the introduction of block thought. The experimental results show that the
improved algorithm has faster processing speed, better effect and better
environment adaptability compared with the background of the Gaussian mixture
model method. And it can detect moving object more accurately and completely.
Keywords: Moving object
detection, Gaussian mixture model, block thought, interval frame difference method
Author: Weiwei Dong
Journal Code: jptkomputergg160039
