GMM Background Modeling Method Based on Grubbs Criterion
XU Hongke
QIN Yanyan
Abstract：When vehicle detection in video is practiced ,it is easy to be interfered by vehicle foreground of initial time in the background modeling phase ,w hich makes background model have a lot of information of foreground so as to have negative impact on vehicle detection .Therefore ,this paper considered the grey values of each pixel point in initial 10 frames as the sequence values in the time domain to eliminate the ab‐normal grey values that reflected foreground with Grubbs criterion .Then ,background mode was built via calculating mean and variance of grey values that reflected background for each pixel point .The experimen‐tal results showed that the methods put forward by this paper had better performance than GMM back‐ground modeling and was preferably used in video vehicle detection system .
Keywords：video vehicle detection systemGaussian mixture modelbackground modelingGrubbs criterion
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 15-18,70 )