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Background initialization is an important step in many high-levelapplications of video processing,ranging from video surveillance to videoinpainting.However,this process is often affected by practical challenges suchas illumination changes,background motion,camera jitter and intermittentmovement,etc.In this paper,we develop a co-occurrence background model withsuperpixel segmentation for robust background initialization. We firstintroduce a novel co-occurrence background modeling method called asCo-occurrence Pixel-Block Pairs(CPB)to generate a reliable initial backgroundmodel,and the superpixel segmentation is utilized to further acquire thespatial texture Information of foreground and background.Then,the initialbackground can be determined by combining the foreground extraction resultswith the superpixel segmentation information.Experimental results obtained fromthe dataset of the challenging benchmark(SBMnet)validate it's performance undervarious challenges.

Co-occurrence Background Model with Superpixels for Robust Background Initialization