[1] Peng J L, Zhao Y L, Wang L M. Research on video abnormal behavior detection based on deep learning[J]. Laser & Optoelectronics Progress, 58, 0600004(2021).

[2] Ma Y Y, Li X W, Liu Y F. Study on hierarchical summary generation system of massive surveillance video[J]. Modern Electronics Technique, 40, 34-37(2017).

[3] Zhang Y Z, Tao R, Wang Y. Motion-state-adaptive video summarization via spatiotemporal analysis[J]. IEEE Transactions on Circuits and Systems for Video Technology, 27, 1340-1352(2017).

[4] Wang Y P, Li R W, Liu X. Extraction method of surveillance video synopsis combines objects and keyframes[J]. Industrial Control Computer, 28, 11-13(2015).

[5] Su Y T, Qian R R, Ji Z. Surveillance video sequence segmentation based on moving object detection[C], 534-537(2009).

[6] Murtaza F, Yousaf M H, Velastin S A. PMHI: proposals from motion history images for temporal segmentation of long uncut videos[J]. IEEE Signal Processing Letters, 25, 179-183(2018).

[7] Shen J B, Peng J T, Shao L. Submodular trajectories for better motion segmentation in videos[J]. IEEE Transactions on Image Processing, 27, 2688-2700(2018).

[8] Wang W S, Huang Z Q, Wang W D et al. Research on video segmentation and key frame extraction algorithm[J]. Natural Science Journal of Xiangtan University, 40, 75-80(2018).

[9] Souza M R E, Pedrini H. Visual rhythms for qualitative evaluation of video stabilization[J]. EURASIP Journal on Image and Video Processing, 2020, 19(2020).

[10] Chen Y, Zhu M, Li Z Z. Remote sensing digital image enhancement based on Gaussian mixture modeling[J]. Chinese Journal of Lasers, 41, 1209002(2014).

[11] Xu Y, Wang P G, Yang Q et al. Moving target detection algorithm based on spatiotemporal correlation multi-channel clustering[J]. Acta Physica Sinica, 68, 164203(2019).

[12] Zhu W J, Wang G L, Tian J et al. Spatio-temporal adaptive mixture of Gaussians for moving objects detection in complex background scenes[J]. Transactions of Beijing Institute of Technology, 38, 165-172(2018).

[13] Du X J, Zhang M O. Based on fusing optical flow method and background modeling for lane line recognition[J]. Journal of Chongqing University of Technology (Natural Science), 35, 39-35, 99(2021).

[14] Reddy V, Sanderson C, Lovell B C. Improved foreground detection via block-based classifier cascade with probabilistic decision integration[J]. IEEE Transactions on Circuits and Systems for Video Technology, 23, 83-93(2013).

[15] Stauffer C, Grimson W E L. Adaptive background mixture models for real-time tracking[C], 246-252(1999).

[16] Huang C R, Chung P C J, Yang D K et al. Maximum a posteriori probability estimation for online surveillance video synopsis[J]. IEEE Transactions on Circuits and Systems for Video Technology, 24, 1417-1429(2014).

[17] Zhang B, Liu G. Research on target tracking algorithm based on similarity feature estimation[J]. Laser & Optoelectronics Progress, 57, 241005(2020).

[18] Guo F, Wang W G, Shen Z Y et al. Motion-aware rapid video saliency detection[J]. IEEE Transactions on Circuits and Systems for Video Technology, 30, 4887-4898(2020).

[19] Wu J W, Wang S Y. Statistical-based adaptive background modeling algorithm for grayscale video[J]. Chinese Journal of Lasers, 48, 0309001(2021).

[20] Ejaz N, Mehmood I, Baik S W. Efficient visual attention based framework for extracting key frames from videos[J]. Signal Processing: Image Communication, 28, 34-44(2013).