[15] Keraner J K, Thompson W B, Boley D L. Optical flow estimation: an error analysis of gradient-based methods with local optimization [J]. IEEE Transaction on Patten and Analysis Machine Intelligence, 1987, 9(2): 229-244.
[18] Chris S. Adaptive background mixture models for real-time tracking [C]. Fort Collins: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1999.
[20] Brutzer S, Hoferlin B, Heidemann G. Evaluation of background subtraction techniques for video surveillance [C]. Ajmer: Computer Vision and Pattern Recognition, 2011.
[22] Olivier B.ViBe: A powerful random technique to estimate the background in video sequences [C]. Taipei: IEEE International Conference on Acoustics, Speech and Signal Processing, 2009.
[23] Olivier B,Marc V D. ViBe: A universal background subtraction algorithm for video sequences [J]. IEEE Transactions on Image Processing, 2011, 20(6): 1709-1724.
[27] Bouwmans T. Recent advanced statistical back-ground modelling for foreground detection: a systematic survey [J]. Recent Patents on Computer Science, 2011, 4(3): 146-176.
[28] Maddalena L, Petrosino A. A self-organizing approach to background subtraction for visual surveillance applications [J]. IEEE Transactions on Image Processing, 2008, 17(7): 1168-1177.
[29] Ma L, Zhang X H.Relationship between saturation and brightness value in HSV colour space [J].Journal of Computer-Aided Design & Computer Graphics, 2014, 26(8): 1272-1278.