A Mixture of Gaussian-Based Method for Detecting Foreground Object in Video Surveillance

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 107)


This chapter presents a novel MoG based method for foreground detection and segmentation in video surveillance. Normal MoG is difficult to deal with the foreground objects stay in the scene for a long time and segment different foreground objects from one blob. We improve MoG by adopting posterior feedback information of object tracking based on statistics to robustly modeling the background and to perfect the foreground segmentation result. Experiments and comparisons show that our method is robust and accurate for detecting foreground object in video surveillance.


Video surveillance Mixture of Gaussian Posterior information Statistics Tracking 



This work is supported in part by Zhejiang natural science key foundation (Grant No.Z1101243 and No.Y1111017), national natural science foundation of China (Grant No.61003188), and Zhejiang Prior Themes and Social Development Project (Grand No.2009C03015-2).


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.College of Computer Science and Information EngineeringZhejiang Gongshang UniversityHangzhouChina

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