Chris S, Grimson W. Adaptive background mixture models for real-time tracking[C]//IEEE Conference on Computer Vision and Pattern Recognition, Fort Collins. 1999: 246-252.
[2]
Elgammal D H, Davis L. Non-parametric model for background subtraction[C]//6th European Conference on Computer Vision. Dublin: [s.n.], 2000: 751-767.
[3]
Kim K, Chalidabhongseb T H, Harwooda D, et al. Real-time foreground-background segmentation using codebook model[J]. Real-Time Imaging, 2005, 11(3): 172-185.
[4]
Heikkila M, Pietikainen M. A texture-based method for modeling the background and detecting moving objects[J]. IEEE Transection on Pattern Analysis and Machine Intelligence, 2006, 28(4): 657-662.
[5]
Liao Shengcai, Zhao Guoying, Kellokumpu V, et al. Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes[C]//IEEE Conference on Computer Vision and Pattern Recognition. San Francisco: [s.n.], 2010: 1301-1306.
[6]
Pajares. A hopfield neural network for image change detection[J]. IEEE Transection on Neural Network, 2006, 17(5): 1250-1264.
[7]
Chacon M M I, Gonzalez D S. An adaptive neural-fuzzy approach for object detection in dynamic backgrounds for surveillance systems[J]. IEEE Transection on Industry Electronic, 2010, 59(8): 3286-3298.
[8]
Culibrk D, Marques O, Socek D, et al. Neural network approach to background modeling for video object segmentation[J]. IEEE Transection on Neural Network, 2007, 18(6): 1614-1627.