Title: Investigation of mixture of Gaussians method for background subtraction in traffic surveillance

Authors: Boris Nikolov; Nikolay Kostov; Slava Yordanova

Addresses: Department of Communication Technologies, Faculty of Electronics, Technical University of Varna, Varna 9010, 1 Studentska Str., Bulgaria ' Department of Communication Technologies, Faculty of Electronics, Technical University of Varna, Varna 9010, 1 Studentska Str., Bulgaria ' Department of Computer Science and Engineering, Faculty of Computing and Automation, Technical University of Varna, Varna 9010, 1 Studentska Str., Bulgaria

Abstract: Many background subtraction techniques have been developed in the past years to improve the precision of motion detection in video surveillance systems. Separating the moving objects from the background is a goal in every modern video surveillance system. Mixture of Gaussians (MoG) is one of the most complex methods used for motion detection in video sequences. This paper further investigates the MoG method. The algorithm is implemented in MATLAB and a typical traffic video is estimated. The accuracy of the algorithm is measured as a function of each variable parameter. An optimal set of parameters along with a filter are proposed in order to increase the performance.

Keywords: mixture of Gaussians; MoG; motion detection; background subtraction; video surveillance; video sequences; traffic surveillance.

DOI: 10.1504/IJRIS.2013.058186

International Journal of Reasoning-based Intelligent Systems, 2013 Vol.5 No.3, pp.161 - 168

Published online: 09 Dec 2013 *

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