An Improved Algorithm for Real-Time Moving Target Detection Based on Gaussian Mixture Model

Author:

Chen Xue Yuan1,Lv Xia Fu1,Liu Jie1

Affiliation:

1. Chongqing University of Post and Telecommunications

Abstract

Gaussian Mixture Model is a popular method to detect moving targets for static cameras. Since the traditional Gaussian Mixture Model has a poor adaptability when the illumination is changing in the scene and has passive learning rate, this paper describes a method that can detect illumination variation and update the learning rate adaptively. It proposes an approach which uses the color histogram matching algorithm and adjusts the learning rate automatically after introducing illumination variation factor and model parameters. Furthermore, the proposed method can select the number of describing model component adaptively, so this method reduced the computation complexity and improved the real-time performance. The experiment results indicate that the detection system gets better robustness, adaptability and stability.

Publisher

Trans Tech Publications, Ltd.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Key Algorithms of Video Target Detection and Recognition in Intelligent Transportation Systems;International Journal of Pattern Recognition and Artificial Intelligence;2019-12-16

2. Moving target detection based on features matching of RGB on a foggy day;SPIE Proceedings;2016-08-29

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