1 research outputs found
Co-occurrence Background Model with Superpixels for Robust Background Initialization
Background initialization is an important step in many high-level
applications of video processing,ranging from video surveillance to video
inpainting.However,this process is often affected by practical challenges such
as illumination changes,background motion,camera jitter and intermittent
movement,etc.In this paper,we develop a co-occurrence background model with
superpixel segmentation for robust background initialization. We first
introduce a novel co-occurrence background modeling method called as
Co-occurrence Pixel-Block Pairs(CPB)to generate a reliable initial background
model,and the superpixel segmentation is utilized to further acquire the
spatial texture Information of foreground and background.Then,the initial
background can be determined by combining the foreground extraction results
with the superpixel segmentation information.Experimental results obtained from
the dataset of the challenging benchmark(SBMnet)validate it's performance under
various challenges