• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Noisy Videos Background Subtraction Algorithm Based on Dictionary Learning

Vol. 8, No. 6, June 26, 2014
10.3837/tiis.2014.06.008, Download Paper (Free):

Abstract

Most background subtraction methods focus on dynamic and complex scenes without considering robustness against noise. This paper proposes a background subtraction algorithm based on dictionary learning and sparse coding for handling low light conditions. The proposed method formulates background modeling as the linear and sparse combination of atoms in the dictionary. The background subtraction is considered as the difference between sparse representations of the current frame and the background model. Assuming that the projection of the noise over the dictionary is irregular and random guarantees the adaptability of the approach in large noisy scenes. Experimental results divided in simulated large noise and realistic low light conditions show the promising robustness of the proposed approach compared with other competing methods.


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Cite this article

[IEEE Style]
H. Xiao, Y. Liu, S. Tan, J. Duan and M. Zhang, "A Noisy Videos Background Subtraction Algorithm Based on Dictionary Learning," KSII Transactions on Internet and Information Systems, vol. 8, no. 6, pp. 1946-1963, 2014. DOI: 10.3837/tiis.2014.06.008.

[ACM Style]
Huaxin Xiao, Yu Liu, Shuren Tan, Jiang Duan, and Maojun Zhang. 2014. A Noisy Videos Background Subtraction Algorithm Based on Dictionary Learning. KSII Transactions on Internet and Information Systems, 8, 6, (2014), 1946-1963. DOI: 10.3837/tiis.2014.06.008.

[BibTeX Style]
@article{tiis:20538, title="A Noisy Videos Background Subtraction Algorithm Based on Dictionary Learning", author="Huaxin Xiao and Yu Liu and Shuren Tan and Jiang Duan and Maojun Zhang and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2014.06.008}, volume={8}, number={6}, year="2014", month={June}, pages={1946-1963}}