Dynamic background discrimination with belief propagation
Jieyu Zhao · 2005
A probabilistic graphical model is proposed for the complex video foreground and background discrimination. The model learns the temporal and the spatial correlation from the video input data. The inference of the graphical model is achieved with the generalized belief propagation algorithm. Experiments have shown that the proposed method is able to model the dynamic backgrounds containing swaying trees, bushes and moving ocean waves. The final segmentation results are very promising.