[2] XU Y KZHOU X L CHEN S Yet al.Deep learning for multiple object tracking:a survey［J］.IET Computer Vision201913(4):355-368.

[3] HAN BCOMANICIU DYING Zet al.Sequential kernel density approximation and its application to real-time visual tracking［J］.IEEE Transactions on Pattern Analysis and Machine Intelligence200830(7):1186-1197.

[4] AVOLIO MFUDULI A.A semiproximal support vector machine approach for binary multiple instance learning［J］.IEEE Transactions on Neural Networks and Learning Systems202031:1-12.

[5] MALDONADO SMERIG JMIRANDA J.IOWA-SVM:a density-based weighting strategy for SVM classification via OWA operators［J］.Journal of Robotics & Machine Learning202028(9):2143-2150.

[6] KALAL ZMIKOLAJCZYK KMATAS J.Tracking-learning-detection［J］.IEEE Transactions on Pattern Analysis and Machine Intelligence201234(7):1409-1422.

[7] JIN YLI H YZHANG D Det al.Compressive tracking combined with sample weights and adaptive learning factor［J］.Concurrency and Computation:Practice and Experience201830(23):e4398.1-e4398.9.

[8] DANELLJAN MHGER GKHAN F Set al.Discriminative scale space tracking［J］.IEEE Transactions on Pattern Analysis and Machine Intelligence201739(8):1561-1575.

[9] XIA F.Improved MOSSE tracking algorithm based on dimensional analysis［J］.International Core Journal of Engineering20056(5):88-94.

[11] LIAN Z CFENG C JLIU Z Get al.A novel scale insensitive KCF tracker based on HOG and color features［J］.Journal of CircuitsSystems and Computers2020 29(11).doi:10.1142/S021812662050/832.

[13] GALOOGAHI H KFAGG ALUCEY S.Learning background-aware correlation filters for visual tracking［C］//IEEE International Conference on Computer Vision 2017:1144-1152.

[14] LI W GWANG WHAN Qet al.Collaborating visual tracker based on particle filter and correlation filter［J］.Concurrency and Computation:Practice and Experience 201931(12):e4665.1-e4665.13.

[15] MICHEAL A AVANI KSANJEEVI Set al.A tool to enhance the capacity for deep learning based object detection and tracking with UAV data［C］//ISPRS-International Archives of the PhotogrammetryRemote Sensing and Spatial Information Sciences2020:221-226.

[16] WANG NLI SGUPTA Aet al.Transferring rich feature hierarchies for robust visual tracking［J/OL］.Computer Science2015［2020-08-10］.https://www.arxiv-vanity.com/papers/1501.04587.

[17] BI F KLEI M YWANG Y P.Context-aware MDNet for target tracking in UAV remote sensing videos［J］.International Journal of Remote Sensing202041(10).doi:10.1080/01431161.2019.1708500.

[18] BERTINETTO LVALMADRE JHENRIQUES J Fet al.Fully-convolutional siamese networks for object tracking［C］//European Conference on Computer Vision 2016:850-865.

[19] NAM HHAN B.Learning multi-domain convolutional neural networks for visual tracking［C］//IEEE Conference on Computer Vision and Pattern Recognition 2016:4293-4302.

[20] JIN RKIM J.Tracking feature extraction techniques with improved SIFT for video identification［J］.Multimedia Tools and Applications201776(4):5927-5936.

[21] SON SJEON JLEE Jet al.Optical flow-based unmanned aerial vehicles tracking［C］//International Conference on Future Information & Communication Engineering2019:295-297.