University of Oulu

Liu, X., & Zhao, G. (2019). Background subtraction using Multi-Channel Fused Lasso. Electronic Imaging, 2019(11), 269-1-269–6.

Background subtraction using multi-channel fused lasso

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Author: Liu, Xin1; Zhao, Guoying1
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.4 MB)
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Language: English
Published: Society for Imaging Science & Technology, 2019
Publish Date: 2020-04-24


Background subtraction is a fundamental problem in computer vision. Despite having made significant progress over the past decade, accurate foreground extraction in complex scenarios is still challenging. Recently, sparse signal recovery has attracted a considerable attention due to the fact that moving objects in videos are sparse. Considering the coherent of the foreground in spatial and temporal domain, many works use the structured sparsity or fused sparsity to regularize the foreground signals. However, existing methods ignore the group prior of foreground signals on multi-channels (such as the RGB). In fact, a pixel should be considered as a multi-channel signal. If a pixel is equal to the adjacent ones that means all the three RGB coefficients should be equal. In this paper, we propose a Multi-Channel Fused Lasso regularizer to explore the smoothness of multi-channels signals. The proposed method is validated on various challenging video sequences. Experiments demonstrate that our approach effectively works on a wide range of complex scenarios, and achieves a state-of-the-art performance.

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Series: IS&T International Symposium on Electronic Imaging
ISSN: 2470-1173
ISSN-E: 2470-1173
ISSN-L: 2470-1173
Pages: 269-1 - 269-6
DOI: 10.2352/ISSN.2470-1173.2019.11.IPAS-269
Host publication: Proceedings of the IS&T 2019 International Symposium on Electronic Imaging (EI): Image Processing: Algorithms and Systems XVII, 2019, 13-17 Janyuary 2019, Burlingame, USA
Host publication editor: Agaian, Sos S.
Egiazarian, Karen O.
Gotchev, Atanas P.
Conference: IS&T International Symposium on Electronic Imaging
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: This work was supported by Academy of Finland, Tekes Fidipro Program, Tekes Project, Infotech, National Natural Science Foundation of China, Tekniikan Edistamissaatio, Nokia Foundation, Otto A. Malm Foundation, Tauno Tonning Foundation, and Riitta Ja Jorma J. Takanen Foundation.
Copyright information: © 2019, Society for Imaging Science and Technology. Reprinted with permission of IS&T: The Society for Imaging Science and Technology sole copyright owners of the Electronic Imaging, Image Processing: Algorithms and systems XVII.