[1] Yuan C P, Yu S W. Preliminary study on the application of footprint analysis in video investigation[J]. Guangdong Gongan Keji, 25, 61-63, 74(2017).

[2] Xu L, Li Z H, Li Z G et al. A murder case investigated and solved by applying the simulation experiment into the collected video[J]. Forensic Science and Technology, 43, 330-333(2018).

[3] Wang X, Liu Y, Li G Y. Moving object detection algorithm based on improved visual background extractor algorithm[J]. Laser & Optoelectronics Progress, 56, 011007(2019).

[4] Chen C, Xuan S B, Xu J G. Pedestrian detection and segmentation under background clutter[J]. Computer Engineering and Applications, 48, 177-181(2012).

[5] Wu C Y, Ding J J. Occluded face recognition using low-rank regression with generalized gradient direction[J]. Pattern Recognition, 80, 256-268(2018).

[6] Weng R L, Lu J W, Hu J L et al. Robust feature set matching for partial face recognition. [C]∥2013 IEEE International Conference on Computer Vision, December 1-8, 2013, Sydney, Australia. New York: IEEE, 601-608(2013).

[7] Ali Akber Dewan M, Granger E, Marcialis G L et al. . Adaptive appearance model tracking for still-to-video face recognition[J]. Pattern Recognition, 49, 129-151(2016).

[8] Alotaibi M, Mahmood A. Improved gait recognition based on specialized deep convolutional neural networks. [C]∥2015 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), October 13-15, 2015, Washington DC., USA. New York: IEEE, 15888701(2015).

[9] Wu Z F, Huang Y Z, Wang L et al. A comprehensive study on cross-view gait based human identification with deep CNNs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 209-226(2017).

[10] Roberts L G[M]. Machine perception of three-dimensional solids(1965).

[11] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. [C]∥Proceedings of the 25th International Conference on Neural Information Processing Systems, December 3-6, 2012, Lake Tahoe, Nevada, USA. USA: NIPS, 1097-1105(2012).

[12] Du J, Hu B L, Zhang Z F. Gastric carcinoma classification based on convolutional neural network and micro-hyperspectral imaging[J]. Acta Optica Sinica, 38, 0617001(2018).

[13] Simonyan K. -04-10)[ 2018-12-17]. https:∥arxiv., org/abs/1409, 1556(2015).

[14] Sun Y, Wang X G. -12-03)[ 2018-12-17]. https:∥arxiv., org/abs/1412, 1265(2014).

[15] Taigman Y, Yang M, Ranzato M et al. DeepFace: closing the gap to human-level performance in face verification. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition(CVPR), June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 1701-1708(2014).

[16] Kumar N, Berg A C, Belhumeur P N et al. Attribute and simile classifiers for face verification. [C]∥2009 IEEE 12th International Conference on Computer Vision, September 29-October 2, 2009, Kyoto, Japan. New York: IEEE, 365-372(2009).

[17] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 770-778(2016).

[18] Li S M, Lei G Q, Fan R. Depth map super-resolution reconstruction based on convolutional neural networks[J]. Acta Optica Sinica, 37, 1210002(2017).

[19] Xiao J S, Liu E Y, Zhu L et al. Improved image super-resolution algorithm based on convolutional neural network[J]. Acta Optica Sinica, 37, 0318011(2017).

[20] Szegedy C, Liu W, Jia Y Q et al. Going deeper with convolutions. [C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 15523970(2015).

[21] Wang L. Research on human action recognition based on sparse spatio-temporal features[D]. Suzhou: Soochow University, 29-36(2015).