[1] Morris G, Angelov P. Real-time novelty detection in video using background subtraction techniques: state of the art a practical review[C], 537-543(2014).
[2] Spampinato C, Palazzo S, Kavasidis I. A texton-based kernel density estimation approach for background modeling under extreme conditions[J]. Computer Vision and Image Understanding, 122, 74-83(2014).
[3] Hamad A M, Tsumura N. Background subtraction based on time-series clustering and statistical modeling[J]. Optical Review, 19, 110-120(2012).
[4] Tsai D M, Lai S C. Independent component analysis-based background subtraction for indoor surveillance[J]. IEEE Transactions on Image Processing, 18, 158-167(2009).
[5] Piccardi M. Background subtraction techniques: a review[C], 3099-3104(2004).
[6] Wren C R, Azarbayejani A, Darrell T et al. Pfinder: real-time tracking of the human body[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19, 780-785(1997).
[7] Stauffer C, Grimson W E L. Adaptive background mixture models for real-time tracking[C], 246-252(1999).
[8] Lee D S, Hull J J, Erol B. A Bayesian framework for Gaussian mixture background modeling[C], 973-976(2003).
[9] Elgammal A, Duraiswami R, Harwood D et al. Background and foreground modeling using nonparametric kernel density estimation for visual surveillance[J]. Proceedings of the IEEE, 90, 1151-1163(2002).
[10] Zhang S P, Yao H X, Liu S H. Spatial-temporal nonparametric background subtraction in dynamic scenes[C], 518-521(2009).
[11] Li L Y, Huang W M, Gu I Y H et al. Statistical modeling of complex backgrounds for foreground object detection[J]. IEEE Transactions on Image Processing, 13, 1459-1472(2004).
[12] Heikkilä M, Pietikäinen M, Heikkilä J. A texture-based method for detecting moving objects[C], 187-196(2004).
[13] Tan X Y, Triggs B. Enhanced local texture feature sets for face recognition under difficult lighting conditions[J]. IEEE Transactions on Image Processing, 19, 1635-1650.
[14] Wu H F, Liu N, Luo X N et al. Real-time background subtraction-based video surveillance of people by integrating local texture patterns[J]. Signal, Image and Video Processing, 8, 665-676(2014).
[15] Zhang S P, Yao H X, Liu S H. Dynamic background modeling and subtraction using spatio-temporal local binary patterns[C], 1556-1559(2008).
[16] Heikklä M, Pietikäinen M. A texture-based method for modeling the background and detecting moving objects[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28, 657-662(2006).
[17] Zhou S R, Yin J P. LBP texture feature based on Haar characteristics[J]. Journal of Software, 24, 1909-1926(2013).
[18] Yao J, Odobez J M. Multi-layer background subtraction based on color and texture[C](2007).
[19] Zhang Z, Wang C H, Xiao B H et al. Multi-scale fusion of texture and color for background modeling[C], 154-159(2012).
[20] Liao S C, Zhao G Y, Kellokumpu V et al. Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes[C], 1301-1306(2010).
[21] Jin J, Dang J W, Zhai F W et al. Moving target detection based on KDE combining local texture feature[J]. Journal of Jilin University (Engineering and Technology Edition), 49, 647-655(2019).
[22] Tang M A, Wang C Y. Moving object detection in static scene based on improved ViBe algorithm[J]. Laser & Optoelectronics Progress, 58, 1410011(2021).
[23] Zhang C, Meng Q H, Jing T. Video flame detection algorithm based on improved GMM and multi-feature fusion[J]. Laser & Optoelectronics Progress, 58, 0410006(2021).
[24] Wang Y, Jodoin P M, Porikli F et al. CDnet 2014: an expanded change detection benchmark dataset[C], 393-400(2014).