2025-5-29- 12
Home > Archive>Volume 11, Issue 6, 2019 >638-650. DOI:10.13878/j.cnki.jnuist.2019.06.002
PDF HTML XML Export Cite reminder
A survey of single object tracking methods
Author:
  • Article
    • | |
  • Metrics
    • |
  • Reference [77]
    • |
  • Related [20]
    • | | |
  • Comments
    Abstract:

    Visual object tracking is always a fundamental block in the field of computer vision.The task scenarios of object tracking technology include single object tracking and multi-object tracking.In this work,we contribute the comprehensive and most recent review on the problem of single object tracking.First,a thorough review on these algorithms in recent decades is shown.Then,existing approaches,which have been proposed to tackle this problem of single object tracking,are divided into different categories,and each category is discussed in detail for the principles,representative models,advances and drawbacks.What's more,this work also provides a discussion about the difficulties and some interesting directions which could possibly become a potential research hotspot in the future.This work can be an effective reference for researchers in this field to quickly learn about the technology of single object tracking.

    Reference
    [1] Wang T S,Gu I Y H,Shi P F.Object tracking using incremental 2D-PCA learning and ML estimation[C]//IEEE International Conference on Acoustics,Speech and Signal Processing,2007,DOI:10.1109/ICASSP.2007.366062
    [2] Ojala T,Pietikainen M,Maenpaa T.Multiresolution gray-scale and rotation invariant texture classification with local binary patterns[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(7):971-987
    [3] Bradski G R.Real time face and object tracking as a component of a perceptual user interface[C]//Proceedings of the Fourth IEEE Workshop on Applications of Computer Vision,1998:732882
    [4] Comaniciu D,Ramesh V,Meer P.Kernel-based object tracking[J].IEEE Transactions on Pattern Analysisand Machine Intelligence,2003,25(5):564-577
    [5] Ning J F,Zhang L,Zhang D,et al.Robust object tracking using joint color-texture histogram[J].International Journal of Pattern Recognition and Artificial Intelligence,2009,23(7):1245-1263
    [6] Porikli F.Integral histogram:a fast way to extract histograms in Cartesian spaces[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2005,DOI:10.1109/CVPR.2005.188
    [7] Porikli F,Tuzel O,Meer P.Covariance tracking using model update based on Lie algebra[C]//IEEE Computer Society Conference on Computer Visionand Pattern Recognition(Volume 1),2006,DOI:10.1109/CVPR.2006.94
    [8] Zhou H Y,Yuan Y,Shi C M.Object tracking using SIFT features and mean shift[J].Computer Vision and Image Understanding,2009,113(3):345-352
    [9] Wu Q Q,Yan Y,Liang Y J,et al.DSNet:deep and shallow feature learning for efficient visual tracking[M]//Computer Vision-ACCV 2018.Cham:Springer International Publishing,2019:119-134.DOI:10.1007/978-3-030-20873-8_8
    [10] Kang K,Bae C,Yeung H W F,et al.A hybrid gravitational search algorithm with swarm intelligence and deep convolutional feature for object tracking optimization[J].Applied Soft Computing,2018,66:319-329
    [11] 程旭,张毅锋,刘袁,等.基于深度特征的目标跟踪算法[J].东南大学学报(自然科学版),2017,47(1):1-5 CHENG Xu,ZHANG Yifeng,LIU Yuan,et al.Object tracking algorithm based on deep feature[J].Journal of Southeast University (Natural Science Edition),2017,47(1):1-5
    [12] Li H X,Li Y,Porikli F.DeepTrack:learning discriminative feature representations online for robust visual tracking[J].IEEE Transactions on Image Processing,2016,25(4):1834-1848
    [13] Bertinetto L,Valmadre J,HenriquesJ F,et al.Fully-convolutional Siamese networks for object tracking[M]//Lecture Notes in Computer Science.Cham:Springer International Publishing,2016:850-865.DOI:10.1007/978-3-319-48881-3_56
    [14] Zhu Z,Wang Q,Li B,et al.Distractor-aware Siamese networks for visual object tracking[M]//Computer Vision-ECCV 2018.Cham:Springer International Publishing,2018:103-119.DOI:10.1007/978-3-030-01240-3_7
    [15] Zhang Z P,Peng H W.Deeper and wider Siamese networks for real-time visual tracking[J].IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2019:4591-4600
    [16] Wang Q,Zhang L,Bertinetto L,et al.Fast online object tracking and segmentation:a unifying approach[J].arXiv eprint,2018,arXiv:1812.05050
    [17] Salmond D J,Birch H.A particle filter for track-before-detect[C]//Proceedings of the 2001 American Control Conference,2001,DOI:10.1109/ACC.2001.946220
    [18] Aidala V.Kalman filter behavior in bearings-only tracking applications[J].IEEE Transactions on Aerospace and Electronic Systems,2007,15(1):29-39
    [19] Milan A,Roth S,Schindler K.Continuous energy minimization for multitarget tracking[J].IEEE Transactions on Pattern Analysisand Machine Intelligence,2014,36(1):58-72
    [20] Yang B,Nevatia R.An online learned CRF model for multi-target tracking[C]//IEEE Conference on Computer Vision and Pattern Recognition,2012,DOI:10.1109/CVPR.2012.6247907
    [21] Kuo C H,Nevatia R.How does person identity recognition help multi-person tracking?[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2011,DOI:10.1109/CVPR.2011.5995384
    [22] Yang B,Nevatia R.Multi-target tracking by online learning of non-linear motion patterns and robust appearance models[C]//IEEE Conference on Computer Vision and Pattern Recognition,2012,DOI:10.1109/CVPR.2012.6247892
    [23] Collins R T,Liu Y,Leordeanu M.Online selection of discriminative tracking features[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,27(10):1631-1643
    [24] Bolme D,Beveridge J R,Draper B A,et al.Visual object tracking using adaptive correlation filters[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2010,DOI:10.1109/CVPR.2010.5539960
    [25] Henriques J F,Caseiro R,Martins P,et al.Exploiting the circulant structure of tracking-by-detection with kernels[M]//Computer Vision-ECCV 2012.Berlin,Heidelberg:Springer Berlin Heidelberg,2012:702-715.DOI:10.1007/978-3-642-33765-9_50
    [26] 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
    [27] Danelljan M,Khan F S,Felsberg M,et al.Adaptive color attributes for real-time visual tracking[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2014:1090-1097
    [28] Danelljan M,Häger G,Shahbaz Khan F,et al.Accurate scale estimation for robust visual tracking[C]//Proceedings of the British Machine Vision Conference,2014,DOI:10.5244/C.28.65
    [29] Li Y,Zhu J K.A scale adaptive kernel correlation filter tracker with feature integration[M]//Computer Vision-ECCV 2014 Workshops.Cham:Springer International Publishing,2015:254-265
    [30] Danelljan M,Hager G,Khan F S,et al.Learning spatially regularized correlation filters for visual tracking[C]//IEEE International Conference on Computer Vision (ICCV),2015:4310-4318
    [31] Bertinetto L,Valmadre J,Golodetz S,et al.Staple:complementary learners for real-time tracking[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016:1401-1409
    [32] Li B,Yan J,Wu W,et al.High performance visual tracking with Siamese region proposal network[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2018:8971-8980
    [33] Li B,Wu W,Wang Q,et al.SiamRPN++:evolution of Siamese visual tracking with very deep networks[J].arXiv eprint,2018,arXiv:1812.11703
    [34] Ross D A,Lim J,Lin R S,et al.Incremental learning for robust visual tracking[J].International Journal of Computer Vision,2008,77(1/2/3):125-141
    [35] Kwon J,Lee K M.Visual tracking decomposition[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2010,DOI:10.1109/CVPR.2010.5539821
    [36] Kwon J,Lee K M.Tracking by sampling trackers[C]//International Conference on Computer Vision,2011,DOI:10.1109/ICCV.2011.6126369
    [37] Oron S,Bar-Hillel A,Levi D,et al.Locally orderless tracking[J].International Journal of Computer Vision,2015,111(2):213-228
    [38] Mei X,Ling H B.Robust visual tracking using l minimization[C]//IEEE 12th International Conference on Computer Vision,2009,DOI:10.1109/ICCV.2009.5459292
    [39] Ulam N M.The Monte Carlo method[J].Journal of the American Statistical Association,1949,44(247):335-341
    [40] Welch G,Bishop G.An introduction to the Kalman filter[R].Chapel Hill,NC,USA:University of North Carolina,1995
    [41] Isard M,Blake A.CONDENSATION-conditional density propagation for visual tracking[J].International Journal of Computer Vision,1998,29(1):5-28
    [42] Brasnett P,Mihaylova L,Bull D,et al.Sequential Monte Carlo tracking by fusing multiple cues in video sequences[J].Imageand Vision Computing,2007,25(8):1217-1227
    [43] Wu Y,Huang T S.Robust visual tracking by integrating multiple cues based on co-inference learning[J].International Journal of Computer Vision,2004,58(1):55-71
    [44] Spengler M,Schiele B.Towards robust multi-cue integration for visual tracking[M]//Lecture Notes in Computer Science.Berlin,Heidelberg:Springer Berlin Heidelberg,2001:93-106.DOI:10.1007/3-540-48222-9_7
    [45] Ma Y,Gu X D,Wang Y Y.Feature fusion method for edge detection of color images[J].Systems Engineering and Electronic Technology,2009,20(2):394-399
    [46] Hu S,Jing Z.Principles and applications of particle filter[M].Beijing:Science Press,2010
    [47] Sun W,Guo B L,Zhu J J,et al.Robust object tracking via hierarchical particle filter[J].Acta Photonica Sinica,2010,39(5):0945
    [48] Gan M G,Cheng Y L,Wang Y N,et al.Hierarchical particle filter tracking algorithm based on multi-feature fusion[J].Systems Engineering and Electronics,2016,27(1):51-62
    [49] Qiao N,Yu J X.On particle filter and mean shift tracking algorithm based on multi-feature fusion[C]//Proceedings of the 33rd Chinese Control Conference,2014,DOI:10.1109/ChiCC.2014.6895734
    [50] Tang D,Zhang Y J.Combining mean-shift and particle filter for object tracking[C]//2011 Sixth International Conference on Image and Graphics,2011,DOI:10.1109/ICIG.2011.118
    [51] Yi S Y,He Z Y,You X G,et al.Single object tracking via robust combination of particle filter and sparse representation[J].Signal Processing,2015,110:178-187
    [52] 宫海洋,任红格,史涛,等.基于改进粒子滤波的稀疏子空间单目标跟踪算法[J].现代电子技术,2018,41(13):10-13 GONG Haiyang,REN Hongge,SHI Tao,et al.Sparse subspace single target tracking algorithm based on improved particle filtering[J].Modern Electronics Technique,2018,41(13):10-13
    [53] Qin W,Peng Q C.An improved particle filter algorithm based on neural network for visual tracking[C]//International Conference on Communications,Circuits and Systems,2007,DOI:10.1109/ICCCAS.2007.4348162
    [54] Cai Y F,Wang H,Sun X Q,et al.Visual vehicle tracking based on deep representation and semisupervised learning[J].Journal of Sensors,2017:1-6
    [55] Xin J,Du X,Zhang J.Deep learning for robust outdoor vehicle visual tracking[C]//IEEE International Conference on Multimedia and Expo (ICME),2017,DOI:10.1109/ICME.2017.8019329
    [56] 杨欣,刘加,周鹏宇,等.基于多特征融合的粒子滤波自适应目标跟踪算法[J].吉林大学学报(工学版),2015,45(2):533-539 YANG Xin,LIU Jia,ZHOU Pengyu,et al.Adaptive particle filter for object tracking based on fusing multiple features[J].Journal of Jilin University (Engineering and Technology Edition),2015,45(2):533-539
    [57] Dou J F,Li J X.Robust visual tracking base on adaptively multi-feature fusion and particle filter[J].Optik,2014,125(5):1680-1686
    [58] 朱志宇.粒子滤波算法及其应用[M].北京:科学出版社,2010 ZHU Zhiyu.Particle filter algorithm and its application[M].Beijing:Science Press,2010
    [59] Coifman R R,Wickerhauser M V.Entropy-based algorithms for best basis selection[J].IEEE Transactions on Information Theory,1992,38(2):713-718
    [60] Mei X,Ling H B,Wu Y,et al.Minimum error bounded efficient L1 tracker with occlusion detection[C]//Computer Vision & Pattern Recognition,2011,DOI:10.1109/CVPR.2011.5995421
    [60] Mei X,Ling H B,Wu Y,et al.Minimum error bounded efficient L1 tracker with occlusion detection[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2011,DOI:10.1109/CVPR.2011.5995421
    [61] Yang H X,Shao L,Zheng F,et al.Recent advances and trends in visual tracking:a review[J].Neurocomputing,2011,74(18):3823-3831
    [62] Liu H P,Sun F C.Visual tracking using sparsity induced similarity[C]//2010 20th International Conference on Pattern Recognition,2010,DOI:10.1109/ICPR.2010.421
    [63] Bao C L,Wu Y,Ling H B,et al.Real time robust L1 tracker using accelerated proximal gradient approach[C]//2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2012,DOI:10.1109/CVPR.2012.6247881
    [64] Zhang T Z,Ghanem B,Liu S,et al.Robust visual tracking via structured multi-task sparse learning[J].International Journal of Computer Vision,2013,101(2):367-383
    [65] Jia X,Lu H,Yang M H.Visual tracking via adaptive structural local sparse appearance model[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2012,DOI:10.1109/CVPR.2012.6247880
    [66] Mei X,Hong Z B,Prokhorov D,et al.Robust multitask multiview tracking in videos[J].IEEE Transactions on Neural Networks and Learning Systems,2015,26(11):2874-2890
    [67] Ma C,Huang J B,Yang X K,et al.Hierarchical convolutional features for visual tracking[C]//IEEE International Conference on Computer Vision (ICCV),2015,DOI:10.1109/ICCV.2015.352
    [68] Gladh S,Danelljan M,Khan F S,et al.Deep motion features for visual tracking[C]//2016 23rd International Conference on Pattern Recognition (ICPR),2016,DOI:10.1109/ICPR.2016.7899807
    [69] Cui Z,Xiao S T,Feng J S,et al.Recurrently target-attending tracking[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016,DOI:10.1109/CVPR.2016.161
    [70] Choi J,Chang H J,Yun S,et al.Attentional correlation filter network for adaptive visual tracking[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017,DOI:10.1109/CVPR.2017.513
    [71] Yun S,Choi J,Yoo Y,et al.Action-decision networks for visual tracking with deep reinforcement learning[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017,DOI:10.1109/CVPR.2017.148
    [72] Choi J,Kwon J,Lee K M.Real-time visual tracking by deep reinforced decision making[J].Computer Visionand Image Understanding,2018,171:10-19
    [73] Ma C,Yang X K,Zhang C Y,et al.Learning a temporally invariant representation for visual tracking[C]//IEEE International Conference on Image Processing (ICIP),2015,DOI:10.1109/ICIP.2015.7350921
    [74] Krizhevsky A,Sutskever I,Hinton G E.ImageNet classification with deep convolutional neural networks[J].Communications of the ACM,2017,60(6):84-90
    [75] Simonyan K,Zisserman A.Very deep convolutional networks for large-scale image recognition[J].arXiv eprint,2014,arXiv:1409.1556
    [76] He K M,Zhang X Y,Ren S Q,et al.Deep residual learning for image recognition[C]//IEEE Conference on Computer Vision and Pattern Recognition,2016,DOI:10.1109/CVPR.2016.90
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

FU Jie, XU Changsheng. A survey of single object tracking methods[J]. Journal of Nanjing University of Information Science & Technology,2019,11(6):638-650

Copy
Share
Article Metrics
  • Abstract:591
  • PDF: 2074
  • HTML: 0
  • Cited by: 0
History
  • Received:October 09,2019
  • Online: January 19,2020
Article QR Code

Address：No. 219, Ningliu Road, Nanjing, Jiangsu Province

Postcode：210044

Phone：025-58731025