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Automatic foreground detection based on KDE and binary classification
2019
Indonesian Journal of Electrical Engineering and Computer Science
In the recent decades, several methods have been developed to extract moving objects in the presence of dynamic background. However, most of them use a global threshold, and ignore the correlation between neighboring pixels. To address these issues, this paper presents a new approach to generate a probability image based on Kernel Density Estimation (KDE) method, and then apply the Maximum A Posteriori in the Markov Random Field (MAP-MRF) based on probability image, so as to generate an energy
doi:10.11591/ijeecs.v15.i1.pp517-526
fatcat:zdisjmis5vazzlow7h4r555rjy