Background Image Estimation with MRF and DBSCAN Algorithms

Pavel V  Skribtsov; Sergey O  Surikov and Michael A  Yakovlev

doi:10.17485/ijst/2015/v8iS10/85409

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Background Image Estimation with MRF and DBSCAN Algorithms

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8iS10/85409

Year: 2015, Volume: 8, Issue: Supplementary 10, Pages: 1-6

Original Article

Background Image Estimation with MRF and DBSCAN Algorithms

Pavel V. Skribtsov^* , Sergey O. Surikov and Michael A. Yakovlev

PAWLIN Technologies Ltd, Dubna, Russian Federation; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

New simple and fast method for robust background image estimation from video stream is offered. The method is based on Markov Random Field, Belief Propagation and DBSCAN algorithms. The usage of cyclic graph MRF model of nonoverlapping image patches with narrow set of background hypotheses generated by DBSCAN algorithm provides faster convergence of Belief Propagation with accuracy comparable to the state-of-art methods.
Keywords: Background Estimation, Belief Propagation, DBSCAN, Markov Random Field