Dynamic Background Video Forgery Detection using Gaussian Mixture Model

Author(s):  
Nugroho Satriyanto ◽  
Rinaldi Munir ◽  
Harlili
2011 ◽  
Vol 63-64 ◽  
pp. 350-354 ◽  
Author(s):  
Li Li Lin ◽  
Neng Rong Chen

The background modeling method based on the Gaussian mixture model (GMM) is usually used to detect the moving objects in static background. But when applied to dynamic background, for example caused by camera jitter, the wrong detection rate of moving objects is high, and thus affects the follow-up tracking. In addition, the method with GMM can not effectively remove the moving objects shadow region. This paper proposes a moving object detection method based on GMM and visual saliency maps, which not only can remove the disturbance caused by camera jitter, but also can effectively solve the shadow problem and achieve stable moving objects detection.


2018 ◽  
Vol 30 (4) ◽  
pp. 642
Author(s):  
Guichao Lin ◽  
Yunchao Tang ◽  
Xiangjun Zou ◽  
Qing Zhang ◽  
Xiaojie Shi ◽  
...  

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