Real-Time Post-Processing for Online Video Segmentation
Zhong Fan · Chinese Journal of Computers · 2009
Applications of online video segmentation usually need to do post-processing in order to remove mis-segmentation and suppress flicking.Traditional matting-based methods are too slow,while simply blur the(foreground/background) boundary not only cause over-blur but also can't remove mis-segmentation.This paper proposes a novel post-processing method.For each pixel around the boundary,a local color model is first estimated through a new fast clustering algorithm,which is designed specially for color clustering.Mis-segmentation is then removed by re-estimating the alpha value for each pixel according to its local color model.In order to improve the consistence of result,an adaptive edge model is applied as a smooth constraint.The edge model can adjust the center and width of the transition region according to the local context of each pixel,and this way prevents the boundary from being over-blurred.The proposed method is very fast,and can meet the requirement of online video segmentation very well.