Background subtraction via incremental maximum margin criterion: a discriminative subspace approach-Reference-Cited by-同舟云学术

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Background subtraction via incremental maximum margin criterion: a discriminative subspace approach

Published:2012-03-24 Issue:6 Volume:23 Page:1083-1101
ISSN:0932-8092
Container-title:Machine Vision and Applications
language:en
Short-container-title:Machine Vision and Applications

Author:

Farcas Diana,Marghes Cristina,Bouwmans Thierry

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

http://link.springer.com/content/pdf/10.1007/s00138-012-0421-9.pdf

Reference80 articles.

1. Allili, M., Bouguila, N., Ziou, D.: A robust video foreground segmentation by using generalized Gaussian mixture modeling. In: Fourth Canadian Conference on Computer and Robot Vision, CRV 2007, pp. 503–509 (2007)

2. Bell A., Sejnowski T.: An information-maximization approach to blind separation and blind deconvolution. Neural Comput. 7(11), 1129–1159 (1995)

3. Bouwmans T., El Baf F.: Modeling of dynamic backgrounds by type-2 fuzzy Gaussians mixture models. MASAUM J. Basics Appl. Sci. 1(2), 265–277 (2009)

4. Bouwmans, T., El Baf, F., Vachon, B.: Statistical background modeling for foreground detection: a survey. In: Handbook of Pattern Recognition and Computer Vision, vol. 4(2), pp. 181–189. World Scientific Publishing, Singapore (2010)

5. Bucak S., Gunsel B.: Incremental subspace learning and generating sparse representations via non-negative matrix factorization. Pattern Recognit. 42(5), 788–797 (2009)

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