[1] Sobral A, Vacavant A. A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos[J]. Computer Vision and Image Understanding, 2014, 122(5): 4-21.

[2] Barnich O, Van Droogenbroeck M. ViBe: a universal background subtraction algorithm for video sequences[J]. IEEE Transactions on Image Processing, 2011, 20(6): 1709-1724.

[6] HAN X, GAO Y, LU Z, et al. Research on moving object detection algorithm based on improved three frame difference method and optical flow[C]//Fifth International Conference on Instrumentation & Measurement, 2015: 580 - 584.

[9] ZHAO D W, TAN J J, YANG W B, et al. An improved vibe algorithm for fast suppression of ghosts and static objects[C]//IEEE International Conference on Mechatronics and Automation(ICMA), 2018: 889 - 893.

[10] Girshick R. Fast R-CNN[C]//IEEE International Conference on Computer Vision, 2015: 1440-1448.

[11] Redmon J Farhadi A. YOLO v3 anincremental improvement[EB/OL]. [2018-04-08][2022-02-08]. https://arxiv.org/abs/1804.02767.

[12] HUANG G, LIU Z, Weinberger K Q, et al. Densely connected convolutional networks[C]//IEEE Conference on Computer Vision and Pattern Recognition, 2017: 2261-2269.

[13] HE K M, ZHANG X Y, REN S Q, et al. Spatial pyramid pooling in deep convolutional networks for visual Recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(9): 1904-1916.

[14] PETS2006. http://www.cvg.reading.ac.uk/PETS2006/data.html[DB/OL]. 2006.

[16] STAUFFER C, GRIM SON W. Learning patterns of activityusing real-time tracking[J]. IEEE Translations on Pattern Analysis and Machine Intelligence, 2000, 22(8): 747-757.

[17] Goyette N, Jodoin P M, Porikli F, et al. Change detection.net: a new change detection benchmark dataset[C]//Computer Vision and Pattern Recognition Workshops, 2012: 1-8.