Comparative study of background subtraction algorithms

Y. Benezeth; Pierre-Marc Jodoin; Bruno Emile; Helene Laurent; Christophe Rosenberger

doi:10.1117/1.3456695

1 July 2010 Comparative study of background subtraction algorithms

Y. Benezeth; Pierre-Marc Jodoin; Bruno Emile; Helene Laurent; Christophe Rosenberger

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J. of Electronic Imaging, 19(3), 033003 (2010). https://doi.org/10.1117/1.3456695

Abstract

We present a comparative study of several state-of-the-art background subtraction methods. Approaches ranging from simple background subtraction with global thresholding to more sophisticated statistical methods have been implemented and tested on different videos with ground truth. The goal is to provide a solid analytic ground to underscore the strengths and weaknesses of the most widely implemented motion detection methods. The methods are compared based on their robustness to different types of video, their memory requirements, and the computational effort they require. The impact of a Markovian prior as well as some postprocessing operators are also evaluated. Most of the videos used come from state-of-the-art benchmark databases and represent different challenges such as poor SNR, multimodal background motion, and camera jitter. Overall, we not only help to better understand for which type of videos each method best suits but also estimate how, sophisticated methods are better compared to basic background subtraction methods.

Citation Download Citation

Y. Benezeth, Y. Benezeth, Pierre-Marc Jodoin, Pierre-Marc Jodoin, Bruno Emile, Bruno Emile, Helene Laurent, Helene Laurent, Christophe Rosenberger, Christophe Rosenberger, } "Comparative study of background subtraction algorithms," Journal of Electronic Imaging 19(3), 033003 (1 July 2010). https://doi.org/10.1117/1.3456695 . Submission:

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