[1] Black M J, Jepson A D. EigenTracking: robust matching and tracking of articulated objects using a view-based representation[M]. ∥Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 329-342(1996).
[2] Li G, Qiu S B, Lin L et al. New moving target detection method based on background differencing and coterminous frames differencing[J]. Chinese Journal of Scientific Instrument, 27, 961-964(2006).
[3] Gavrila D M, Giebel J, Munder S. Vision-based pedestrian detection: the protector system. [C]∥IEEE Intelligent Vehicles Symposium, 2004, Parma, Italy. IEEE(2004).
[4] Zhu X B, Che J. Person re-identification algorithm based on feature fusion and subspace learning[J]. Laser & Optoelectronics Progress, 56, 021503(2019).
[5] Yang M. Research on pedestrian detection technology based on support vector machine[D]. Beijing: University of Chinese Academy of Sciences(2018).
[6] Chen B, Zha Y F, Li Y Q et al. Person re-identification based on convolutional neural network discriminative feature learning[J]. Acta Optica Sinica, 38, 0720001(2018).
[7] Redmon J, Divvala S, Girshick R et al. You only look once: unified, real-time object detection. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016. Las Vegas, NV, USA. IEEE, 779-788(2016).
[8] Mumford D, Shah J. Optimal approximations by piecewise smooth functions and associated variational problems[J]. Communications on Pure and Applied Mathematics, 42, 577-685(1989).
[9] Ye K Q, Zhan Y W. Image segmentation algorithm based on mathematical morphology and active edgeless contour model without edges[J]. Journal of Computer Applications, 29, 2398-2401, 2405(2009).
[10] Bagautdinov T, Fleuret F, Fua P. Probability occupancy maps for occluded depth images. [C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015. Boston, MA, USA. IEEE, 2829-2837(2015).
