[1] [1] Li S J, Fan X, Zhu B, et al. A method for small infrared targets detection based on the technology of motion blur recovery［J］. Acta Optica Sinica, 2017, 37(6): 0610001.

[2] [2] Ren S Q, He K M, Girshick R, et al. Faster R-CNN: towards real-time object detection with region proposal networks［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(6): 1137-1149.

[3] [3] Liu W, Anguelov D, Erhan D, et al. SSD: single shot multibox detector［C］∥European Conference on Computer Vision, 2016:21-37.

[4] [4] Li A D, Lin Z P, An W, et al. Infrared small target detection in compressive domain based on self-adaptive parameter configuration［J］. Chinese Journal of Lasers, 2015, 42(10): 1008003.

[5] [5] Zhang L J, Zhou Z P. An improved discrete-continuous energy minimization for multi-target tracking［J］. Laser & Optoelectronics Progress, 2017, 54(11): 111502.

[6] [6] Kim C, Li F, Ciptadi A, et al. Multiple hypothesis tracking revisited: blending in modern appearance model［C］∥IEEE International Conference on Computer Vision, 2015: 4696-4704.

[7] [7] Milan A, Schindler K, Roth S. Detection- and trajectory-level exclusion in multiple object tracking［C］∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2013: 3682-3689.

[8] [8] Bae S H, Yoon K.Robust online multi-object tracking based on tracklet confidence and online discriminative appearance learning［C］∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2014: 1218-1225.

[9] [9] Dicle C, Camps O I, Sznaier M. The way they move: tracking multiple targets with similar appearance［C］∥IEEE International Conference on Computer Vision, 2013: 2304-2311.

[10] [10] Yoon J H, Yang M, Lim J, et al. Bayesian multi-object tracking using motion context from multiple objects［C］∥IEEE Conference on Applications of Computer Vision, 2015: 33-40.

[11] [11] Yu F, Li W, Li Q, et al. POI: multiple object tracking with high performance detection and appearance feature［C］∥European Conference on Computer Vision, 2016: 36-42.

[12] [12] Szegedy C, Liu W, Jia Y Q, et al. Going deeper with convolutions［C］∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2015: 1-9.

[13] [13] Kuhn H W. The Hungarian method for the assignment problem［J］. Naval Research Logistics, 2004, 52(1): 7-21.

[14] [14] Henriques J F, Caseiro R, Martins P, et al. High-speed tracking with kernelized correlation filters［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(3): 583-596.

[15] [15] Yang Y, Zhou H Y,Wang S Y. Saliency tracking algorithm based on fusing multiple features［J］. Science Technology and Engineering, 2017, 17(26): 74-80.

[16] [16] zuysal M, Fua P, Lepetit V. Fast keypoint recognition in ten lines of code［C］∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2007: 1-8.

[17] [17] Milan A, Lealtaixe L, Reid I D, et al. MOT16: a benchmark for multi-object tracking［EB/OL］. ［2018-03-20］https:∥arxiv.org/pdf/1603.00831.pdf.

[18] [18] Geiger A, Lauer M, Wojek C, et al. 3D traffic scene understanding from movable platforms［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(5): 1012-1025.

[19] [19] Felzenszwalb P F, Girshick R B, McAllester D, et al. Object detection with discriminatively trained part-based models［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(9): 1627-1645.

[20] [20] Choi W. Near-online multi-target tracking with aggregated local flow descriptor［C］∥IEEE International Conference on Computer Vision, 2015: 3029-3037.

[21] [21] Bewley A, Ge Z, Ott L, et al. Simple online and realtime tracking［C］. IEEE International Conference on Image Processing, 2016: 3464-3468.