Video background subtracion using improved Adaptive-K Gaussian Mixture Model

ICACTE 2010 - 2010 3rd International Conference on Advanced Computer Theory and Engineering, Proceedings

Volumn 5, Issue , 2010, Pages

  Zhou, Hao ^a   Zhang, Xuejie ^a   Gao, Yun ^a   Yu, Pengfei ^a  

^a YUNNAN UNIVERSITY   (China)

Author keywords

Adaptive K Gaussian Mixture Model; Background subtraction

Indexed keywords

EID: 78149355623     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICACTE.2010.5579536     Document Type: Conference Paper

References (7)

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3. Power, P.W., Schoonees, lA, 2002. Understanding background mixture models for foreground segmentation. In: Proc. of the Image and Vision Computing New Zealand.
4. Lee, D.-S., 2005. Effective Gaussian Mixture learning for video background subtraction. IEEE Trans. Pattern AnaL Mach. Intell. 27 (5),827-832.)
5. Z Zivkovic and F. V. der Heijden. Efficient adaptive density estimation per image pixel for the task of background subtraction. Pat. Rec. Letters, 27(7) 773-780, 2006.
6. Shimada, A. Arita, D. Taniguchi, R. Dynamic Control of Adaptive Mixture-of-Gaussians Background Model Video and Signal Based Surveillance, 2006. AVSS '06. IEEE International Conference on Issue Date: Nov. 2006
7. Matej Kristan, Danijel et.al Incremental learning with Gaussian mixture models Computer Vision Winter Workshop 2008 page 25-32