计算机科学 ›› 2020, Vol. 47 ›› Issue (10): 136-144.doi: 10.11896/jsjkx.200200041
龚轩1, 乐孜纯2, 王慧1, 武玉坤1
GONG Xuan1, LE Zi-chun2, WNAG Hui1, WU Yu-kun1
摘要: 目标跟踪一直都是计算视觉领域研究的热点课题之一,作为计算视觉的基础学科,其应用已经渗透到各个领域,包括智能监控、智能人机交互、无人驾驶以及军事等方面。目标跟踪从跟踪对象的数量角度可分为单目标跟踪和多目标跟踪,其中单目标跟踪相对简单,除了需要解决与多目标跟踪共性的问题(如遮挡、形变等)外,单目标跟踪不需要考虑目标的数据关联问题。然而,在多目标跟踪系统中,场景更为复杂,跟踪目标的数量和类别往往是不确定的,因此数据关联在整个跟踪系统中就显得尤为重要。数据关联是多目标跟踪过程中的一个重要阶段,国内外很多学者甚至将多目标跟踪问题看成数据关联问题,试图从数据关联过程中寻求多目标跟踪研究方法。文中重点对多目标跟踪过程中的数据关联技术进行了综述,系统地介绍了多目标跟踪中的数据关联技术。首先,对目标跟踪,尤其是多目标跟踪进行了概述,并对数据关联的研究现状做了描述;其次,详细介绍了数据关联的概念及其需要解决的问题;然后,对各种数据关联技术进行了分析总结,包括传统的NNDA算法、JPDA算法、基于Tracking-By-Detecting 的多目标跟踪框架的数据关联技术以及多目标多相机跟踪(Multi-Target Multi-Camera Tracking,MTMCT)的数据关联;最后,对未来多目标跟踪的数据关联技术的研究方向进行了展望。
中图分类号:
[1]MENG L,YANG X.A Survey of Object Tracking Algorithms[J].Acat Automatica Sinica,2019,45(7):1244-260. [2]WANG X.Intelligent multi-camera video surveillance:A review[J].Pattern Recognit.Lett.,2013,34(1):3-19. [3]PFISTER T,CHARLES J,ZISSERMAN A.Flowing convnets for human pose estimation in videos[C]//Proceedings of the IEEE International Conference on Computer Vision(ICCV).Piscataway,NJ:IEEE Press,2015:1913-1921. [4]CHOI W,SAVARESE S.A unified framework for multi-target tracking and collective activity recognition[C]//European Conference on Computer Vision.Switzerland:Springer,Cham,2012:215-230. [5]HU W,TAN T,WANG L,et al.A survey on visual surveillanceof object motion and behaviors[J].IEEE Trans.Syst.Man Cybern.Part C-Appl.Rev.,2004,34(3):334-352. [6]XU H,YU H W,DONG M C,et al.Overview of UAV Object Tracking[J].Journal of Network New Media,2019,8(5):11-20. [7]YANG H X,SHAO L,ZHENG F,et al.Recent advances and trends in visual tracking:a review[J].Neurocom-puting,2011,74(18):3823-3831. [8]SMEULDERS A W M,CHU D M,CUCCHIARA R,et al.Visual tracking:an experimental survey[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2014,36(7):1442-1468. [9]HENRIQUES J F,RUI C,MARTINS P,et al.Exploiting thecirculant structure of tracking-by—detection with kernels[C]//European Conference on Computer Vision.Switzerland:Springer,Cham,2012:702-715. [10]HENRIQUES J F,CASEIRO R,et al.High-Speed Trackingwith Kernelized Correlation Filters[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2014,37(3):583 - 596. [11]MARTIN D,GUSTAV H,FAHAD K,et al.Accurate Scale Estimation for Robust Visual Tracking[C]// British Machine Vision Conference 2014.Nottingham,UK:BMVA Press,2014. [12]MARTIN D,GUSTAV H,FAHAD K,et al.DiscriminativeScale Space Tracking[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2016,39(8):1561-1575. [13]BOLME D S,BEVERIDGE J R,DRAPER B,et a1.Visual object tracking using adaptive correlation filters[C]// 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2010:2544-2550. [14]ALEX B,GE Z Y,LIONEL O,et al.Simple online and realtime tracking[C]//2016 IEEE International Conference on Image Processing.Piscataway,NJ:IEEE Press,2016:3464-3468. [15]NICOLAI W,ALEX B,DIETRICH P.Simple online and real-time tracking with a deep association metric[C]//2017 IEEE International Conference on Image Processing (ICIP).Piscataway,NJ:IEEE Press,2017:3645-3649. [16]KIM C,LI F,CIPTADI A,et al.Multiple Hypothesis Tracking Revisited[C]// 2015 IEEE International Conference on Computer Vision (ICCV).Piscataway,NJ:IEEE Press,2015:4696-4704. [17]CHU Q,YANG W O,LI H,et al.Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanism[C]//2017 IEEE International Conference on Computer Vision (ICCV).Piscataway,NJ:IEEE Press,2017:4846-4855. [18]YU F W,LI W B,LI Q Q,et al.POI:Multiple Object Tracking with High Performance Detection and Appearance Feature[C]//European Conference on Computer Vision,2016.Switzerland:Springer,Cham,2016:36-42. [19]NIMA M,SEYED M A,MOHAMMAD R.Multi-target trac-king using cnn-based features:Cnnmtt[J].Multimedia Tools and Applications,2019,78(6):7077-7096. [20]WAN X Y,WANG J J,ZHOU S P.An online and flexible multi-object tracking framework using long short-term memory[C]//2018 IEEE CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).Piscataway,NJ:IEEE Press,2018:1230-1238. [21]LI M H,LIU Z X,XIONG Y Y,et al.Multi-person tracking by discriminative affinity model and hierarchical association[C]//2017 3rd IEEE International Conference on Computer and Communications (ICCC).Piscataway,NJ:IEEE Press,2017:1741-1745. [22]LUO W H,XING J L,ANTON M,et al.Multiple Object Tracking:A Literature Review[J].ArXiv Preprint ArXiv:1409.7618,2014. [23]HU H G,ZHOU L L,GUAN Q,et al.An automatic tracking method for multiple cells based on multi-feature fusion[J].IEEE Access,2018,6:69782-69793. [24]FIAZ M,MAHMOOD A,JUNG S K.Tracking noisy targets:A review of recent object tracking approaches[J].arXiv:1802.03098. [25]FIAZ M,MAHMOOD A,JAVED S,et al.Handcrafted and deep trackers:Recent visual object tracking approaches and trends[J].ACM Computing Surveys,2019,52(2):1-44. [26]LI P,WANG D,WANG L,et al.Deep visual tracking:Review and experimental comparison[J].Pattern Recognition,2018,76(4):323-338. [27]BOSE B,WANG X,GRIMSON E.Multi-class object trackingalgorithm that handles fragmentation and grouping[C]//2007 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2007:1-8. [28]SONG B,JEN T Y,STAUDT G E,et al.A stochastic graph evolution framework for robust multi-target tracking[C]//In Proc.Eur.Conf.Comput.Vis.,BERLIN:SPRINGER-VERLAG,2010:605-619. [29]GIOELE C,FRANCISCO L S,SIHAM T,et al.Deep learning in video multi-object tracking:A survey[J].Neurocomputing,2020,381(2):61-88. [30]HU W,LI X,LUO W,et al.Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model[J].IEEE Trans.Pattern Anal.Mach.Intel.,2012,34(12):2420-2440. [31]ZHANG L,VAN DER M L.Structure preserving object tracking[C]//2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Piscataway,NJ:IEEE Press,2013:1838-1845. [32]ZHANG J,PRESTI L L,SCLAROFF S.Online multi-persontracking by tracker hierarchy[C]// 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance.Piscataway,NJ:IEEE Press,2012:379-385. [33]XIANG Y,ALAHI A,SAVERESE S.Learning to track:Online multi-object tracking by decision making[C]// 2015 IEEE International Conference on Computer Vision (ICCV).Piscataway,NJ:IEEE Press,2015:4705-4713. [34]KUO C H,HUANG C,NEYATIA R.Multi-target tracking by on-line learned discriminative appearance models[C]//2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2010:685-692. [35]HENRIQUES J F,CASEIRO R,BATISTA J.Globally optimal solution to multi-object tracking with merged measurements[C]//International Conference on Computer Vision.Piscataway,NJ:IEEE Press,2011:2470-2477. [36]SUGIMURA D,KITANI K M,OKABE T,et al.Using individuality to track individuals:Clustering individual trajectories in crowds using local appearance and frequency trait[C]//IEEE 12th International Conference on Computer Vision.Piscataway,NJ:IEEE Press,2009:1467-1474. [37]CHOI W,SAVARESE S.Multiple target tracking in world coordinate with single,minimally calibrated camera[C]// ECCV’10 Proceedings of the 11th European Conference on Computer Vision.Berlin:Springer,2010:553-567. [38]HONG S,KWAK S,HHAN B.Orderless tracking throughmodel-averaged posterior estimation[C]//2013 IEEE International Conference on Computer Vision.Piscataway,NJ:IEEE Press,2013:2296-2303. [39]WANG M M,LI X F.Research on key technologies of multiple object tracking based on data association[D].Chengdu:University of Electronic Science and Technology of China,2017. [40]WU J X.Research on data association algorithm of multi-target tracking[D].Xi’an:Xidian University,2013. [41]WANG Y,CUI Y T,CEHN W.Data association algorithm of multi-target tracking[J].Digital Communication World,2019(9):263-263. [42]LI Y F,ZHOU S R.Survey of online multi-object video tracking algorithms[J].Computing Technology and Automation,2018,37(1):73-82. [43]YANG F D.Summary of data association methods in Multi-target tracking[J].Science& Technology Vision,2016,6(6):164-194. [44]SINGGR R A,SEA R G,HOUSEWRIGHT K B.A new Filter for Optimal Tracking in Dense Multitarget Environment[C]//Proccedings of the Ninth Allerton Conference on Circuit and System Theory,Urbana-Champaign.USA:University of Illinois,1971:201-211. [45]SINGER R A,STEIN J J.An Optimal Tracking Filter for Processing Sensor Data of Imprecisely Determined Origin in Surveillance Systems[C]// Proceedings of the Tenth IEEE Conference on Decision and Control.IEEE Press,1971:171-175. [46]QUAN T F.New theory and technology of target tracking[M].Natioinal Defense Industry Press,2009:55-72. [47]JAFFER A J,BAR SHALOM Y.On optimal tracking in multiple target environments [C]// Proceedings of the third Symposium on Non-Linear Estimation Theory and Its Applications.1972:112-117. [48]BAR-SHALOM Y.Extension of the Probabilistic Data Association Filter in Multitarget Tracking[C]//Proceedings of the Fifth Symposium on Non-Linear Estimation.1974:16-21. [49]WANG Z,ZHENG L,LIU Y,et al.Towards Real-Time Multi-Object Tracking[J].arXiv:1909.12605,2019. [50]WELCH G,BISHOP G.An Introduction to the Kalman Filter [EB/OL].http://www.cs.unc.edu/~tracker/ref/s2001/kalman/index.html. [51]NUMMIARO K,KOLLER-MEIER E,VAN GOOL L.Anadaptive color-based particle filter[J].Image and Vision Computing,2003,21(1):99-110. [52]KUHN H W.The hungarian method for the assignment problem[J].Naval Research Logistics Quarterly,1955,2(1/2):83-97. [53]RAN N,KONG L T,WANG Y H,et al.A robust multi-athlete tracking algorithm by exploiting discriminant features and long-term dependencies[C]//International Conference on Multimedia Modeling.Switzerland:Springer,Cham,2019:411-423. [54]CHEN L T,PENG X J,REN M W.Recurrent metric networks and batch multiple hypothesis for multi-object tracking[J].IEEE Access,2019,7:3093-3105. [55]XIANG J,ZHANG G S,HOU J H.Online multi-object tracking based on feature representation and bayesian filtering within a deep learning architecture[J].IEEE Access,2019,7:27923-27935. [56]KWANGJIN Y,DU Y K,YOUNG-CHUL Y,et al.Data association for multi-object tracking via deep neural networks[J].Sensors,2019,19(3):559. [57]ZHENG Z Z,YANG X D,YU Z D,et al.Joint Discriminative and Generative Learning for Person Re-identification[C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).Piscataway,NJ:IEEE Press,2019:2133-2142. [58]RISTANI E,TOMASI C.Features for multi-target multi-camera tracking and re-identification[C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE Press,2018:6036-6046. [59]ZHANG Z M,WU J N,ZHANG X,et al.Multi-target,multi-camera tracking by hierarchical clustering:Recent progress on dukemtmc project[J].arXiv preprint arXiv:1712.09531,2017. [60]ERGYS R,FRANCESCO S,ROGER Z,et al.Performancemeasures and a data set for multi-target,multi-camera tracking[C]//European Conference on Computer Vision.Switzerland:Springer,Cham,2016:17-35. [61]TESFAYE Y T,ZEMENE E,PRATI A,et al.Multi-targettracking in multiple non-overlapping cameras using fast-constrained dominant sets[J].International Journal of Computer Vision,2019,127(9):1303-1320. [62]HOU Y,ZHENG L,WANG Z,et al.Locality Aware Appearance Metric for Multi-Target Multi-Camera Tracking[J].arXiv:1911.12037,2019. |
[1] | 沈祥培, 丁彦蕊. 多检测器融合的深度相关滤波视频多目标跟踪算法 Multi-detector Fusion-based Depth Correlation Filtering Video Multi-target Tracking Algorithm 计算机科学, 2022, 49(8): 184-190. https://doi.org/10.11896/jsjkx.210600004 |
[2] | 文成宇, 房卫东, 陈伟. 多目标跟踪的对象初始化综述 Object Initialization in Multiple Object Tracking:A Review 计算机科学, 2022, 49(3): 152-162. https://doi.org/10.11896/jsjkx.210200048 |
[3] | 刘彦, 秦品乐, 曾建朝. 基于YOLOv3与分层数据关联的多目标跟踪算法 Multi-object Tracking Algorithm Based on YOLOv3 and Hierarchical Data Association 计算机科学, 2021, 48(11A): 370-375. https://doi.org/10.11896/jsjkx.201000115 |
[4] | 胡海根, 周莉莉, 周乾伟, 陈胜勇, 张俊康. 基于CNN的相衬显微图像序列的癌细胞多目标跟踪 Multi-target Tracking of Cancer Cells under Phase Contrast Microscopic Images Based on Convolutional Neural Network 计算机科学, 2019, 46(5): 279-285. https://doi.org/10.11896/j.issn.1002-137X.2019.05.043 |
[5] | 王正宁, 周阳, 吕侠, 曾凡伟, 张翔, 张锋军. 一种基于2D和3D联合信息的改进MDP跟踪算法 Improved MDP Tracking Method by Combining 2D and 3D Information 计算机科学, 2019, 46(3): 97-102. https://doi.org/10.11896/j.issn.1002-137X.2019.03.013 |
[6] | 赵广辉, 卓松, 徐晓龙. 基于卡尔曼滤波的多目标跟踪方法 Multi-object Tracking Algorithm Based on Kalman Filter 计算机科学, 2018, 45(8): 253-257. https://doi.org/10.11896/j.issn.1002-137X.2018.08.045 |
[7] | 袁大龙,纪庆革. 协同运动状态估计的多目标跟踪算法 Multiple Object Tracking Algorithm via Collaborative Motion Status Estimation 计算机科学, 2017, 44(Z11): 154-159. https://doi.org/10.11896/j.issn.1002-137X.2017.11A.032 |
[8] | 闫林,阮宁,闫硕,高伟. 相关集的数据关联描述及实例讨论 Description of Data Association Occurring in Related Sets and Specific Example 计算机科学, 2017, 44(1): 283-288. https://doi.org/10.11896/j.issn.1002-137X.2017.01.052 |
[9] | 陈金广,秦晓姗,马丽丽. 快速多目标跟踪GM-PHD滤波算法 Fast GM-PHD Filter for Multi-target Tracking 计算机科学, 2016, 43(3): 317-321. https://doi.org/10.11896/j.issn.1002-137X.2016.03.060 |
[10] | 杨国亮,张进辉. 分层关联的多目标跟踪算法研究 Research on Multi-object Tracking Using Hierarchical Data Association 计算机科学, 2014, 41(9): 306-310. https://doi.org/10.11896/j.issn.1002-137X.2014.09.059 |
[11] | 马炳先,崔纪鹏,张正明. 面向组合的Web服务间数据关联定位方法研究 Research on Data Association Location Method for Web Services Composition 计算机科学, 2014, 41(8): 130-134. https://doi.org/10.11896/j.issn.1002-137X.2014.08.029 |
[12] | 金鑫,梁雪春,袁晓龙. 复杂情况下的多目标跟踪统计技术 Multi-target Tracking Statistical Techniques in Complex Case 计算机科学, 2013, 40(6): 268-271. |
[13] | 朱晓钢,杨兵,许华杰. 支持无线传感器网络多目标跟踪的聚类数据关联算法研究 Clustering Data Association Algorithm to Support Multi-target Tracl}ing in WSN 计算机科学, 2012, 39(Z6): 24-27. |
[14] | 周维,许海霞,郑金华. 基于RJMCMC的视觉多目标跟踪算法 Multi-object Visual Tracking Based on Reversible Jump Markov Chain Monte Carlo 计算机科学, 2012, 39(7): 270-275. |
[15] | 朱晓钢,杨兵,许华杰. 支持无线传感器网络多目标跟踪的最邻近数据关联算法研究 Nearest Neighbor Method Data Association Algorithm to Support Multi-target Tracking in WSN 计算机科学, 2011, 38(5): 67-70. |
|