16.6.2.4.3 Tracklet Based Target Tracking

Chapter Contents (Back)
Motion Prediction. Tracklet.
See also Target Tracking Techniques, Motion Model, Control.
See also Prediction for Tracking Techniques.
See also Target and Feature Tracking, Multi-Object, Multiple Objects, Multiple Target.

Gong, D.[Dian], Medioni, G.[Gérard], Zhao, X.M.[Xue-Mei],
Structured Time Series Analysis for Human Action Segmentation and Recognition,
PAMI(36), No. 7, July 2014, pp. 1414-1427.
IEEE DOI 1407
BibRef
And: A3, A1, A2:
Tracking Using Motion Patterns for Very Crowded Scenes,
ECCV12(II: 315-328).
Springer DOI 1210
Heuristic algorithms BibRef

Gong, D.[Dian], Medioni, G.[Gérard], Zhu, S.[Sikai], Zhao, X.M.[Xue-Mei],
Kernelized Temporal Cut for Online Temporal Segmentation and Recognition,
ECCV12(III: 229-243).
Springer DOI 1210
BibRef

Zhao, X.M.[Xue-Mei], Medioni, G.[Gerard],
Robust unsupervised motion pattern inference from video and applications,
ICCV11(715-722).
IEEE DOI 1201
Infer patterns and improve tracking. Tracklets. Tensor voting. BibRef

Chen, B.J.[Bor-Jeng], Medioni, G.[Gerard],
3-D Mediated Detection and Tracking in Wide Area Aerial Surveillance,
WACV15(396-403)
IEEE DOI 1503
Cameras BibRef

Prokaj, J.[Jan], Medioni, G.[Gerard],
Persistent Tracking for Wide Area Aerial Surveillance,
CVPR14(1186-1193)
IEEE DOI 1409
BibRef
Earlier:
Accurate efficient mosaicking for Wide Area Aerial Surveillance,
WACV12(273-280).
IEEE DOI 1203
regression; target tracking; wide area imagery BibRef

Prokaj, J.[Jan], Zhao, X.M.[Xue-Mei], Medioni, G.[Gerard],
Tracking many vehicles in wide area aerial surveillance,
CNWASA12(37-43).
IEEE DOI 1207
BibRef

Prokaj, J.[Jan], Medioni, G.[Gerard],
Using 3D scene structure to improve tracking,
CVPR11(1337-1344).
IEEE DOI 1106
BibRef

Prokaj, J.[Jan], Duchaineau, M.[Mark], Medioni, G.[Gerard],
Inferring tracklets for multi-object tracking,
WAVP11(37-44).
IEEE DOI 1106
BibRef

Bae, S.H.[Seung-Hwan], Yoon, K.J.[Kuk-Jin],
Robust Online Multiobject Tracking With Data Association and Track Management,
IP(23), No. 7, July 2014, pp. 2820-2833.
IEEE DOI 1407
BibRef
And:
Robust Online Multi-object Tracking Based on Tracklet Confidence and Online Discriminative Appearance Learning,
CVPR14(1218-1225)
IEEE DOI 1409
Bayes methods BibRef

Bae, S.H.[Seung-Hwan], Yoon, K.J.[Kuk-Jin],
Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking,
PAMI(40), No. 3, March 2018, pp. 595-610.
IEEE DOI 1802
Adaptation models, Learning systems, Machine learning, Robustness, Target tracking, Trajectory, Multi-object tracking, tracklet confidence BibRef

Yoon, J.H.[Ju Hong], Yang, M.H.[Ming-Hsuan], Lim, J.W.[Jong-Woo], Yoon, K.J.[Kuk-Jin],
Bayesian Multi-object Tracking Using Motion Context from Multiple Objects,
WACV15(33-40)
IEEE DOI 1503
Bayes methods BibRef

Topkaya, I.S.[Ibrahim Saygin], Erdogan, H.[Hakan], Porikli, F.M.[Fatih M.],
Tracklet clustering for robust multiple object tracking using distance dependent Chinese restaurant processes,
SIViP(10), No. 5, May 2016, pp. 795-802.
WWW Link. 1608
BibRef

Yoon, J.H.[Ju Hong], Lee, C.R.[Chang-Ryeol], Yang, M.H.[Ming-Hsuan], Yoon, K.J.[Kuk-Jin],
Structural Constraint Data Association for Online Multi-object Tracking,
IJCV(127), No. 1, January 2019, pp. 1-21.
Springer DOI 1901
BibRef
Earlier:
Online Multi-object Tracking via Structural Constraint Event Aggregation,
CVPR16(1392-1400)
IEEE DOI 1612
BibRef

Naiel, M.A.[Mohamed A.], Ahmad, M.O.[M. Omair], Swamy, M.N.S., Lim, J.W.[Jong-Woo], Yang, M.H.[Ming-Hsuan],
Online Multi-Object Tracking via Robust Collaborative Model and Sample Selection,
CVIU(154), No. 1, 2017, pp. 94-107.
Elsevier DOI 1612
Multi-object tracking
See also Real-Time Object Tracking Via Online Discriminative Feature Selection. BibRef

Naiel, M.A.[Mohamed A.], Ahmad, M.O.[M. Omair], Swamy, M.N.S., Wu, Y.[Yi], Yang, M.H.[Ming-Hsuan],
Online multi-person tracking via robust collaborative model,
ICIP14(431-435)
IEEE DOI 1502
Collaboration BibRef

Zhong, W.[Wei], Lu, H.C.[Hu-Chuan], Yang, M.H.[Ming-Hsuan],
Robust Object Tracking via Sparse Collaborative Appearance Model,
IP(23), No. 5, May 2014, pp. 2356-2368.
IEEE DOI 1405
BibRef
Earlier:
Robust object tracking via sparsity-based collaborative model,
CVPR12(1838-1845).
IEEE DOI 1208
Collaboration BibRef

Li, X.[Xi], Zhao, L.M.[Li-Ming], Ji, W.[Wei], Wu, Y.M.[Yi-Ming], Wu, F.[Fei], Yang, M.H.[Ming-Hsuan], Tao, D.C.[Da-Cheng], Reid, I.D.[Ian D.],
Multi-Task Structure-Aware Context Modeling for Robust Keypoint-Based Object Tracking,
PAMI(41), No. 4, April 2019, pp. 915-927.
IEEE DOI 1903
Object tracking, Task analysis, Robustness, Computational modeling, Coherence, Feature extraction, Keypoint tracking, context modeling, metric learning BibRef

Zhang, P.[Peng], Yu, S.J.[Shu-Jian], Xu, J.M.[Jia-Miao], You, X.G.[Xin-Ge], Jiang, X.B.[Xiu-Bao], Jing, X.Y.[Xiao-Yuan], Tao, D.C.[Da-Cheng],
Robust Visual Tracking Using Multi-Frame Multi-Feature Joint Modeling,
CirSysVideo(29), No. 12, December 2019, pp. 3673-3686.
IEEE DOI 1912
Target tracking, Visualization, Training, Correlation, Computational modeling, Histograms, correlation filters BibRef

Zha, Y.F.[Yu-Fei], Zhang, Y.Q.[Yuan-Qiang], Ku, T.[Tao], Huang, H.Q.[Han-Qiao], Huang, W.[Wei], Zhang, P.[Peng],
Multiple Instance Models Regression for Robust Visual Tracking,
CirSysVideo(31), No. 3, March 2021, pp. 1125-1137.
IEEE DOI 2103
Target tracking, Training, Computational modeling, Integrated circuit modeling, Data models, Robustness, reliability evaluation BibRef

Hong, Z.B.[Zhi-Bin], Wang, C.H.[Chao-Hui], Mei, X.[Xue], Prokhorov, D.[Danil], Tao, D.C.[Da-Cheng],
Tracking Using Multilevel Quantizations,
ECCV14(VI: 155-171).
Springer DOI 1408
BibRef

Hong, Z.B.[Zhi-Bin], Mei, X.[Xue], Prokhorov, D.[Danil], Tao, D.C.[Da-Cheng],
Tracking via Robust Multi-task Multi-View Joint Sparse Representation,
ICCV13(649-656)
IEEE DOI 1403
Multi-task; Multi-view; Outliers; Sparse Representation; Tracking BibRef

Yang, F.[Fan], Lu, H.C.[Hu-Chuan], Yang, M.H.[Ming-Hsuan],
Learning structured visual dictionary for object tracking,
IVC(31), No. 12, 2013, pp. 992-999.
Elsevier DOI 1312
Object tracking BibRef

Wang, D.[Dong], Lu, H.C.[Hu-Chuan], Bo, C.J.[Chun-Juan],
Fast and Robust Object Tracking via Probability Continuous Outlier Model,
IP(24), No. 12, December 2015, pp. 5166-5176.
IEEE DOI 1512
BibRef
Earlier: A1, A2, Only:
Visual Tracking via Probability Continuous Outlier Model,
CVPR14(3478-3485)
IEEE DOI 1409
Gaussian noise. Linear Representation;Outlier Model;Visual Tracking
See also Object Tracking via 2DPCA and L_1 -Regularization. BibRef

Jia, X.[Xu], Lu, H.C.[Hu-Chuan], Yang, M.H.[Ming-Hsuan],
Visual Tracking via Coarse and Fine Structural Local Sparse Appearance Models,
IP(25), No. 10, October 2016, pp. 4555-4564.
IEEE DOI 1610
BibRef
Earlier:
Visual Tracking Via Adaptive Structural Local Sparse Appearance Model,
CVPR12(1822-1829).
IEEE DOI 1208
compressed sensing
See also Visual Tracking via Sparse and Local Linear Coding. BibRef

Jia, X.[Xu], Wang, D.[Dong], Lu, H.C.[Hu-Chuan],
Fragment-based tracking using online multiple kernel learning,
ICIP12(393-396).
IEEE DOI 1302
BibRef

Wang, L.J.[Li-Jun], Lu, H.C.[Hu-Chuan], Wang, D.[Dong],
Visual Tracking via Structure Constrained Grouping,
SPLetters(22), No. 7, July 2015, pp. 794-798.
IEEE DOI 1412
image representation BibRef

Wang, L.J.[Li-Jun], Ouyang, W.L.[Wan-Li], Wang, X.G.[Xiao-Gang], Lu, H.C.[Hu-Chuan],
STCT: Sequentially Training Convolutional Networks for Visual Tracking,
CVPR16(1373-1381)
IEEE DOI 1612
BibRef
Earlier:
Visual Tracking with Fully Convolutional Networks,
ICCV15(3119-3127)
IEEE DOI 1602
Feature extraction BibRef

Li, F.[Fu], Lu, H.C.[Hu-Chuan], Wang, D.[Dong],
Robust Visual Tracking with Dual Group Structure,
ACCV14(IV: 614-629).
Springer DOI 1504
BibRef

Zhang, S., Lan, X.Y.[Xiang-Yuan], Qi, Y., Yuen, P.C.[Pong Chi],
Robust Visual Tracking via Basis Matching,
CirSysVideo(27), No. 3, March 2017, pp. 421-430.
IEEE DOI 1703
Dictionaries BibRef

Lan, X.Y.[Xiang-Yuan], Zhang, S.G.[Shen-Gping], Yuen, P.C.[Pong C.], Chellappa, R.[Rama],
Learning Common and Feature-Specific Patterns: A Novel Multiple-Sparse-Representation-Based Tracker,
IP(27), No. 4, April 2018, pp. 2022-2037.
IEEE DOI 1802
image representation, learning (artificial intelligence), object tracking, video signal processing, appearance modeling, sparse representation BibRef

Zhang, S., Qi, Y., Jiang, F., Lan, X.Y.[Xiang-Yuan], Yuen, P.C.[Pong C.], Zhou, H.,
Point-to-Set Distance Metric Learning on Deep Representations for Visual Tracking,
ITS(19), No. 1, January 2018, pp. 187-198.
IEEE DOI 1801
Feature extraction, Manifolds, Target tracking, Training, Visualization, Metric learning, point to set, visual tracking BibRef

Wang, S.F.[Shao-Fei], Fowlkes, C.C.[Charless C.],
Learning Optimal Parameters for Multi-target Tracking with Contextual Interactions,
IJCV(122), No. 3, May 2017, pp. 484-501.
Springer DOI 1704
BibRef
Earlier:
Learning Optimal Parameters For Multi-target Tracking,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Gwak, J.[Jeonghwan],
Multi-object tracking through learning relational appearance features and motion patterns,
CVIU(162), No. 1, 2017, pp. 103-115.
Elsevier DOI 1710
Multi-object tracking BibRef

Kang, B.[Bin], Zhu, W.P.[Wei-Ping], Liang, D.[Dong],
Robust multi-feature visual tracking via multi-task kernel-based sparse learning,
IET-IPR(11), No. 12, Decmeber 2017, pp. 1172-1178.
DOI Link 1712
BibRef

Zhou, H., Ouyang, W., Cheng, J., Wang, X., Li, H.,
Deep Continuous Conditional Random Fields With Asymmetric Inter-Object Constraints for Online Multi-Object Tracking,
CirSysVideo(29), No. 4, April 2019, pp. 1011-1022.
IEEE DOI 1904
Tracking, Trajectory, Visualization, Neural networks, Machine learning, Mathematical model, Feature extraction, asymmetric pairwise terms BibRef

Kang, B.[Bin], Zhu, W.P.[Wei-Ping], Liang, D.[Dong], Chen, M.[Mingkai],
Robust visual tracking via nonlocal regularized multi-view sparse representation,
PR(88), 2019, pp. 75-89.
Elsevier DOI 1901
Sparse representation, Visual tracking, Multi-view learning, Dual group structure BibRef

Yang, T.[Tao], Cappelle, C.[Cindy], Ruichek, Y.[Yassine], El Bagdouri, M.[Mohammed],
Online multi-object tracking combining optical flow and compressive tracking in Markov decision process,
JVCIR(58), 2019, pp. 178-186.
Elsevier DOI 1901
BibRef
Earlier:
Multi-object Tracking Using Compressive Sensing Features in Markov Decision Process,
ACIVS17(505-517).
Springer DOI 1712
Multi-object tracking, Markov decision process, Tracking-learning-detection, Compressive sensing features BibRef

Makhura, O.J.[Onalenna J.], Woods, J.C.[John C.],
Learn-select-track: An approach to multi-object tracking,
SP:IC(74), 2019, pp. 153-161.
Elsevier DOI 1904
Multi-object tracking, Object colours, Density-based clustering, Low level local features BibRef

Liu, M.J.[Ming-Jie], Jin, C.B.[Cheng-Bin], Yang, B.[Bin], Cui, X.N.[Xue-Nan], Kim, H.[Hakil],
Online multiple object tracking using confidence score-based appearance model learning and hierarchical data association,
IET-CV(13), No. 3, April 2019, pp. 312-318.
DOI Link 1904
BibRef

Mhalla, A.[Ala], Chateau, T.[Thierry], Ben Amara, N.E.[Najoua Essoukri],
Spatio-temporal object detection by deep learning: Video-interlacing to improve multi-object tracking,
IVC(88), 2019, pp. 120-131.
Elsevier DOI 1908
Multi-object tracking, Interlacing and inverse interlacing models, Specialization, Interlaced deep detector BibRef

Yu, H.Y.[Hong-Yang], Li, G.R.[Guo-Rong], Su, L.[Li], Zhong, B.N.[Bi-Neng], Yao, H.X.[Hong-Xun], Huang, Q.M.[Qing-Ming],
Conditional GAN based individual and global motion fusion for multiple object tracking in UAV videos,
PRL(131), 2020, pp. 219-226.
Elsevier DOI 2004
Multi-object tracking, Neural networks, UAV BibRef

Zhang, X.C.[Xing-Chen], Ye, P.[Ping], Peng, S.Y.[Sheng-Yun], Liu, J.[Jun], Xiao, G.[Gang],
DSiamMFT: An RGB-T fusion tracking method via dynamic Siamese networks using multi-layer feature fusion,
SP:IC(84), 2020, pp. 115756.
Elsevier DOI 2004
Object tracking, RGB-T fusion tracking, Dynamic Siamese networks, Deep learning, Image fusion BibRef

Li, P.X.[Pei-Xia], Chen, B.[Boyu], Wang, D.[Dong], Lu, H.C.[Hu-Chuan],
Visual tracking by dynamic matching-classification network switching,
PR(107), 2020, pp. 107419.
Elsevier DOI 2008
Visual Tracking, Deep Learning, Ensemble learning BibRef

Sharma, A.[Anil], Anand, S.[Saket], Kaul, S.K.[Sanjit K.],
Intelligent querying for target tracking in camera networks using deep Q-learning with n-step bootstrapping,
IVC(103), 2020, pp. 104022.
Elsevier DOI 2011
Camera networks, Deep reinforcement learning, Target tracking, Multi-camera tracking 2010 MSC: 00-01, 99-00 BibRef

Chuang, T.Y.[Tzu-Yi], Han, J.Y.[Jen-Yu], Jhan, D.J.[Deng-Jie], Yang, M.D.[Ming-Der],
Geometric Recognition of Moving Objects in Monocular Rotating Imagery Using Faster R-CNN,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link 2006
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Emami, P.[Patrick], Pardalos, P.M.[Panos M.], Elefteriadou, L.[Lily], Ranka, S.[Sanjay],
Machine Learning Methods for Data Association in Multi-Object Tracking,
Surveys(53), No. 4, August 2020, pp. xx-yy.
DOI Link 2010
deep learning, machine learning, Multi-object tracking, data association BibRef

Sun, S.J.[Shi-Jie], Akhtar, N.[Naveed], Song, H.S.[Huan-Sheng], Mian, A.[Ajmal], Shah, M.[Mubarak],
Deep Affinity Network for Multiple Object Tracking,
PAMI(43), No. 1, January 2021, pp. 104-119.
IEEE DOI 2012
Object tracking, Computational modeling, Deep learning, Detectors, Target tracking, Feature extraction, Multiple object tracking, on-line tracking BibRef

Ma, C.[Cong], Yang, F.[Fan], Li, Y.[Yuan], Jia, H.Z.[Hui-Zhu], Xie, X.D.[Xiao-Dong], Gao, W.[Wen],
Deep Human-Interaction and Association by Graph-Based Learning for Multiple Object Tracking in the Wild,
IJCV(129), No. 6, June 2021, pp. 1993-2010. 2106
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Ma, C.[Cong], Yang, F.[Fan], Li, Y.[Yuan], Jia, H.Z.[Hui-Zhu], Xie, X.D.[Xiao-Dong], Gao, W.[Wen],
Deep Trajectory Post-Processing and Position Projection for Single & Multiple Camera Multiple Object Tracking,
IJCV(129), No. 12, December 2021, pp. 3255-3278.
Springer DOI 2111
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Liu, Q.[Qiao], Li, X.[Xin], He, Z.Y.[Zhen-Yu], Fan, N.[Nana], Yuan, D.[Di], Wang, H.P.[Hong-Peng],
Learning Deep Multi-Level Similarity for Thermal Infrared Object Tracking,
MultMed(23), 2021, pp. 2114-2126.
IEEE DOI 2107
Object tracking, Semantics, Training, Task analysis, Adaptation models, Correlation, Feature extraction, Thermal infrared dataset BibRef

Liu, Q.[Qiao], Yuan, D.[Di], Fan, N.[Nana], Gao, P.[Peng], Li, X.[Xin], He, Z.Y.[Zhen-Yu],
Learning Dual-Level Deep Representation for Thermal Infrared Tracking,
MultMed(25), 2023, pp. 1269-1281.
IEEE DOI 2305
Object tracking, Biological system modeling, Task analysis, Correlation, Multitasking, Adaptation models, Feature extraction, Thermal infrared dataset BibRef

Jiang, B.[Bo], Zhang, Y.[Yuan], Luo, B.[Bin], Cao, X.C.[Xiao-Chun], Tang, J.[Jin],
STGL: Spatial-Temporal Graph Representation and Learning for Visual Tracking,
MultMed(23), 2021, pp. 2162-2171.
IEEE DOI 2107
Target tracking, Computational modeling, Visualization, Noise measurement, Semisupervised learning, Shape, graph learning BibRef

Wan, X.Y.[Xing-Yu], Cao, J.[Jiakai], Zhou, S.P.[San-Ping], Wang, J.J.[Jin-Jun], Zheng, N.N.[Nan-Ning],
Tracking Beyond Detection: Learning a Global Response Map for End-to-End Multi-Object Tracking,
IP(30), 2021, pp. 8222-8235.
IEEE DOI 2110
Trajectory, Target tracking, Object detection, Measurement, Task analysis, Feature extraction, Data models, deep neural network BibRef

Tu, Z.Z.[Zheng-Zheng], Lin, C.[Chun], Zhao, W.[Wei], Li, C.L.[Cheng-Long], Tang, J.[Jin],
M5L: Multi-Modal Multi-Margin Metric Learning for RGBT Tracking,
IP(31), 2022, pp. 85-98.
IEEE DOI 2112
Measurement, Robustness, Feature extraction, Fuses, Collaboration, Visualization, Task analysis, Deep metric learning, RGBT tracking BibRef

Li, S.W.[Sheng-Wu], Zhang, X.[Xuande], Xiong, J.[Jing], Ning, C.J.[Chen-Jing], Zhang, M.[Mingke],
Learning spatial self-attention information for visual tracking,
IET-IPR(16), No. 1, 2022, pp. 49-60.
DOI Link 2112
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Chen, Z.Z.[Zhong-Ze], Li, J.[Jing], Wu, J.[Jia], Chang, J.[Jun], Xiao, Y.[Yafu], Wang, X.T.[Xiao-Ting],
Drift-Proof Tracking With Deep Reinforcement Learning,
MultMed(24), 2022, pp. 609-624.
IEEE DOI 2202
Target tracking, Reinforcement learning, Training, Robustness, Object tracking, Measurement, Real-time systems, Object tracking, drift problems BibRef

Li, X.J.[Xiao-Jing], Huang, L.[Lei], Wei, Z.Q.[Zhi-Qiang],
A Twofold Convolutional Regression Tracking Network With Temporal and Spatial Mechanism,
CirSysVideo(32), No. 3, March 2022, pp. 1537-1551.
IEEE DOI 2203
Target tracking, Feature extraction, Visualization, Training, Correlation, Task analysis, Semantics, Visual tracking, spatial and temporal mechanism BibRef

Brasó, G.[Guillem], Cetintas, O.[Orcun], Leal-Taixé, L.[Laura],
Multi-Object Tracking and Segmentation Via Neural Message Passing,
IJCV(130), No. 12, December 2022, pp. 3035-3053.
Springer DOI 2211
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Ye, L.L.[Liang-Ling], Li, W.[Weida], Zheng, L.X.[Li-Xin], Zeng, Y.Y.[Yuan-Yue],
Lightweight and Deep Appearance Embedding for Multiple Object Tracking,
IET-CV(16), No. 6, 2022, pp. 489-503.
DOI Link 2208
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Saada, M.[Mohamad], Kouppas, C.[Christos], Li, B.H.[Bai-Hua], Meng, Q.G.[Qing-Gang],
A multi-object tracker using dynamic Bayesian networks and a residual neural network based similarity estimator,
CVIU(225), 2022, pp. 103569.
Elsevier DOI 2212
Multi-object tracking, Dynamic Bayesian networks, Residual neural networks, YOLO V5, MOTChallenge BibRef

Wang, M.[Mianzhao], Shi, F.[Fan], Zhao, M.[Meng], Jia, C.[Chen], Tian, W.W.[Wei-Wei], He, T.[Tian], Fu, Y.[Yu], Cheng, X.[Xu],
An Online Multiobject Tracking Network for Autonomous Driving in Areas Facing Epidemic,
ITS(23), No. 12, December 2022, pp. 25191-25200.
IEEE DOI 2212
Feature extraction, Correlation, Target tracking, Strain, Epidemics, Aggregates, Detectors, Multi-object tracking, epidemic areas, re-ID embedding BibRef

Zheng, Y.J.[Ya-Jing], Yu, Z.F.[Zhao-Fei], Wang, S.[Song], Huang, T.J.[Tie-Jun],
Spike-Based Motion Estimation for Object Tracking Through Bio-Inspired Unsupervised Learning,
IP(32), 2023, pp. 335-349.
IEEE DOI 2301
Cameras, Tracking, Neuromorphics, Vision sensors, Neurons, Motion estimation, Target tracking, Neuromorphic vision sensor, high-speed object tracking BibRef

Li, R.[Rui], Zhang, B.[Baopeng], Liu, J.[Jun], Liu, W.[Wei], Teng, Z.[Zhu],
Inference-Domain Network Evolution: A New Perspective for One-Shot Multi-Object Tracking,
IP(32), 2023, pp. 2147-2159.
IEEE DOI 2304
Task analysis, Feature extraction, Noise measurement, Cameras, Adaptation models, Annotations, data association BibRef


Huang, K.[Kaer], Lertniphonphan, K.[Kanokphan], Chen, F.[Feng], Li, J.[Jian], Wang, Z.[Zhepeng],
Multi-Object Tracking by Self-supervised Learning Appearance Model,
E2EAD23(3163-3169)
IEEE DOI 2309
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Qin, Z.[Zheng], Zhou, S.P.[San-Ping], Wang, L.[Le], Duan, J.H.[Jing-Hai], Hua, G.[Gang], Tang, W.[Wei],
MotionTrack: Learning Robust Short-Term and Long-Term Motions for Multi-Object Tracking,
CVPR23(17939-17948)
IEEE DOI 2309
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Zhang, Y.[Yuang], Wang, T.[Tiancai], Zhang, X.Y.[Xiang-Yu],
MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors,
CVPR23(22056-22065)
IEEE DOI 2309
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Chen, B.[Brian], Selvaraju, R.R.[Ramprasaath R.], Chang, S.F.[Shih-Fu], Niebles, J.C.[Juan Carlos], Naik, N.[Nikhil],
PreViTS: Contrastive Pretraining with Video Tracking Supervision,
WACV23(1560-1570)
IEEE DOI 2302
Training, Representation learning, Visualization, Video tracking, Video on demand, Computational modeling, Lighting BibRef

Nalaie, K.[Keivan], Zheng, R.[Rong],
AttTrack: Online Deep Attention Transfer for Multi-object Tracking,
WACV23(1654-1663)
IEEE DOI 2302
Training, Representation learning, Knowledge engineering, Degradation, Visual analytics, Surveillance, Object detection BibRef

Chen, X.[Xi], Zhang, Y.F.[Yi-Feng],
Multi-Object Tracking Based on Deep Path Aggregation Network,
ICIVC22(214-221)
IEEE DOI 2301
Location awareness, Target tracking, Object detection, Feature extraction, Real-time systems, Object tracking, real-time BibRef

Zhao, S.Y.[Shuang-Ye], Wu, Y.[Yubin], Wang, S.[Shuai], Ke, W.[Wei], Sheng, H.[Hao],
Mask Guided Spatial-Temporal Fusion Network for Multiple Object Tracking,
ICIP22(3231-3235)
IEEE DOI 2211
Target tracking, Neural networks, Feature extraction, Reliability, Object tracking, Multi-object tracking, tracking by detection, mask guided network BibRef

Pi, Z.X.[Zhi-Xiong], Wan, W.T.[Wei-Tao], Sun, C.[Chong], Gao, C.X.[Chang-Xin], Sang, N.[Nong], Li, C.[Chen],
Hierarchical Feature Embedding for Visual Tracking,
ECCV22(XXII:428-445).
Springer DOI 2211

WWW Link. BibRef

Song, L.C.[Liang-Chen], Gong, X.[Xuan], Planche, B.[Benjamin], Zheng, M.[Meng], Doermann, D.[David], Yuan, J.S.[Jun-Song], Chen, T.[Terrence], Wu, Z.Y.[Zi-Yan],
PREF: Predictability Regularized Neural Motion Fields,
ECCV22(XXII:664-681).
Springer DOI 2211
BibRef

Yu, S.Z.[Shu-Zhi], Wu, G.H.[Guan-Hang], Gu, C.H.[Chun-Hui], Fathy, M.E.[Mohammed E.],
TDT: Teaching Detectors to Track without Fully Annotated Videos,
L3D-IVU22(3939-3949)
IEEE DOI 2210
Training, Annotations, Detectors, Predictive models, Benchmark testing BibRef

He, J.W.[Jia-Wei], Huang, Z.[Zehao], Wang, N.Y.[Nai-Yan], Zhang, Z.X.[Zhao-Xiang],
Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Tracking,
CVPR21(5295-5305)
IEEE DOI 2111
Training, Deep learning, Image edge detection, Neural networks, Feature extraction, Object tracking, Quadratic programming BibRef

Wu, J.L.[Jia-Lian], Cao, J.L.[Jia-Le], Song, L.C.[Liang-Chen], Wang, Y.[Yu], Yang, M.[Ming], Yuan, J.S.[Jun-Song],
Track to Detect and Segment: An Online Multi-Object Tracker,
CVPR21(12347-12356)
IEEE DOI 2111
Solid modeling, Costs, Tracking, Motion segmentation, Neural networks, Object detection BibRef

Zhang, Z.P.[Zhi-Peng], Liu, Y.H.[Yi-Hao], Wang, X.[Xiao], Li, B.[Bing], Hu, W.M.[Wei-Ming],
Learn to Match: Automatic Matching Network Design for Visual Tracking,
ICCV21(13319-13328)
IEEE DOI 2203
Training, Degradation, Visualization, Codes, Statistical analysis, Oceans, Motion and tracking, BibRef

Zheng, J.[Jilai], Ma, C.[Chao], Peng, H.[Houwen], Yang, X.K.[Xiao-Kang],
Learning to Track Objects from Unlabeled Videos,
ICCV21(13526-13535)
IEEE DOI 2203
Training, Codes, Dynamic programming, Object recognition, Unsupervised learning, Optical flow, Motion and tracking, BibRef

Xie, F.[Fei], Wang, C.Y.[Chun-Yu], Wang, G.[Guangting], Yang, W.K.[Wan-Kou], Zeng, W.J.[Wen-Jun],
Learning Tracking Representations via Dual-Branch Fully Transformer Networks,
VOT21(2688-2697)
IEEE DOI 2112
Target tracking, Costs, Fuses, Computational modeling, Graphics processing units, Transformers, Feature extraction BibRef

Liu, C.X.[Cheng-Xin], Cao, Z.G.[Zhi-Guo], Li, W.[Wei], Xiao, Y.[Yang], Du, S.Y.[Shuai-Yuan], Zhu, A.[Angfan],
Exploiting Distilled Learning for Deep Siamese Tracking,
ICPR21(577-583)
IEEE DOI 2105
Power demand, Pipelines, Memory management, Benchmark testing, Mobile handsets, Pattern recognition BibRef

Dai, P.[Peng], Weng, R.L.[Ren-Liang], Choi, W.[Wongun], Zhang, C.S.[Chang-Shui], He, Z.P.[Zhang-Ping], Ding, W.[Wei],
Learning a Proposal Classifier for Multiple Object Tracking,
CVPR21(2443-2452)
IEEE DOI 2111
Deep learning, Detectors, Market research, Trajectory, Computational efficiency, Proposals BibRef

Xu, Y., sep, A., Ban, Y., Horaud, R., Leal-Taixé, L., Alameda-Pineda, X.,
How to Train Your Deep Multi-Object Tracker,
CVPR20(6786-6795)
IEEE DOI 2008
Loss measurement, Training, Standards, Target tracking, Optimization, Neural networks BibRef

Li, Z., Xiong, F., Zhou, J., Wang, J., Lu, J., Qian, Y.,
BAE-Net: A Band Attention Aware Ensemble Network for Hyperspectral Object Tracking,
ICIP20(2106-2110)
IEEE DOI 2011
Videos, Hyperspectral imaging, Target tracking, Image color analysis, Object tracking, Machine learning, Color, ensemble learning BibRef

Zhang, D., Zheng, Z.,
High Performance Visual Tracking With Siamese Actor-Critic Network,
ICIP20(2116-2120)
IEEE DOI 2011
Training, Feature extraction, Visualization, Real-time systems, Learning (artificial intelligence), Target tracking, Robustness, Object Tracking BibRef

Wang, J., Wang, Y., Zhang, S., Xu, C., Deng, C.,
Dictionary Learning for Visual Tracking with Dimensionality Reduction,
ICIVC20(251-255)
IEEE DOI 2009
Target tracking, Visualization, Dictionaries, Robustness, Video sequences, Training, Appearance variation, Visual tracking, Target representation BibRef

Harley, A.W.[Adam W.], Lakshmikanth, S.K.[Shrinidhi Kowshika], Schydlo, P.[Paul], Fragkiadaki, K.[Katerina],
Tracking Emerges by Looking Around Static Scenes, with Neural 3d Mapping,
ECCV20(XXVI:598-614).
Springer DOI 2011
BibRef

Jin, J.T.[Jia-Ting], Li, X.W.[Xing-Wei], Li, X.L.[Xin-Long], Guan, S.J.[Shao-Jie],
Online Multi-object Tracking with Siamese Network and Optical Flow,
ICIVC20(193-198)
IEEE DOI 2009
Kalman filters, Feature extraction, Optical flow, Trajectory, Target tracking, Multi-object tracking, Siamese Network, DeepSORT BibRef

Weng, X., Wang, Y., Man, Y., Kitani, K.M.,
GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking With 2D-3D Multi-Feature Learning,
CVPR20(6498-6507)
IEEE DOI 2008
Feature extraction, Tracking, Neural networks, Pipelines, Training BibRef

Voigtlaender, P., Luiten, J., Torr, P.H.S., Leibe, B.,
Siam R-CNN: Visual Tracking by Re-Detection,
CVPR20(6577-6587)
IEEE DOI 2008
Heuristic algorithms, Feature extraction, Target tracking, Head, Benchmark testing, Dynamic programming BibRef

Brasó, G., Leal-Taixé, L.,
Learning a Neural Solver for Multiple Object Tracking,
CVPR20(6246-6256)
IEEE DOI 2008
Trajectory, Image edge detection, Task analysis, Message passing, Object tracking, Optimization, Object detection BibRef

Ruiz, I.[Idoia], Porzi, L.[Lorenzo], Bulò, S.R.[Samuel Rota], Kontschieder, P.[Peter], Serrat, J.[Joan],
Weakly Supervised Multi-Object Tracking and Segmentation,
WACVW21(125-133) Autonomous Vehicle Vision
IEEE DOI 2105
Training, Location awareness, Heating systems, Measurement, Image edge detection, Benchmark testing BibRef

Porzi, L.[Lorenzo], Hofinger, M., Ruiz, I.[Idoia], Serrat, J.[Joan], Bulò, S.R.[Samuel Rota], Kontschieder, P.[Peter],
Learning Multi-Object Tracking and Segmentation From Automatic Annotations,
CVPR20(6845-6854)
IEEE DOI 2008
Videos, Training data, Task analysis, Image segmentation, Pipelines, Optical imaging, Semantics BibRef

Ardö, H., Nilsson, M.,
Multi Target Tracking from Drones by Learning from Generalized Graph Differences,
VisDrone19(46-54)
IEEE DOI 2004
autonomous aerial vehicles, graph theory, learning (artificial intelligence), object detection, Multi target tracking BibRef

He, Z.[Zhen], Li, J.[Jian], Liu, D.[Daxue], He, H.[Hangen], Barber, D.[David],
Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers,
CVPR19(1318-1327).
IEEE DOI 2002
BibRef

Maksai, A.[Andrii], Fua, P.[Pascal],
Eliminating Exposure Bias and Metric Mismatch in Multiple Object Tracking,
CVPR19(4634-4643).
IEEE DOI 2002
BibRef

Emambakhsh, M.[Mehryar], Bay, A.[Alessandro], Vazquez, E.[Eduard],
Deep Recurrent Neural Network for Multi-target Filtering,
MMMod19(II:519-531).
Springer DOI 1901
Results:
WWW Link. BibRef

Manh, H., Alaghband, G.,
Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking,
CRV18(150-157)
IEEE DOI 1812
Dictionaries, Sparse matrices, Robots, Video sequences, Feature extraction, Color, multi-target tracking, online appearance learning BibRef

Ren, L.L.[Liang-Liang], Lu, J.W.[Ji-Wen], Wang, Z.F.[Zi-Feng], Tian, Q.[Qi], Zhou, J.[Jie],
Collaborative Deep Reinforcement Learning for Multi-object Tracking,
ECCV18(III: 605-621).
Springer DOI 1810
BibRef

Wan, X., Wang, J., Zhou, S.,
An Online and Flexible Multi-object Tracking Framework Using Long Short-Term Memory,
PBVS18(1311-13118)
IEEE DOI 1812
Trajectory, Tracking, Computational modeling, Kalman filters, Optical flow, Logic gates BibRef

Wan, X., Wang, J., Kong, Z., Zhao, Q., Deng, S.,
Multi-Object Tracking Using Online Metric Learning with Long Short-Term Memory,
ICIP18(788-792)
IEEE DOI 1809
Trajectory, Target tracking, Computational modeling, Kalman filters, Optical flow, Multiple Object Tracking, Data Association BibRef

Ullah, M., Alaya Cheikh, F.,
Deep Feature Based End-to-End Transportation Network for Multi-Target Tracking,
ICIP18(3738-3742)
IEEE DOI 1809
Target tracking, Trajectory, Optimization, Transportation, Dynamic programming, Feature extraction, Transportation network, multi-target tracking BibRef

Cui, Y.W.[Ya-Wen], Zhang, B.[Bo], Yang, W.J.[Wen-Jing], Wang, Z.Y.[Zhi-Yuan], Li, Y.[Yin], Yi, X.D.[Xiao-Dong], Tang, Y.H.[Yu-Hua],
End-to-End Visual Target Tracking in Multi-Robot Systems Based on Deep Convolutional Neural Network,
CEFR-LCV17(1113-1121)
IEEE DOI 1802
Angular velocity, Cameras, Feature extraction, Robot vision systems, Target tracking BibRef

Anh, N.T.L., Khan, F.M., Negin, F., Bremond, F.,
Multi-Object tracking using multi-channel part appearance representation,
AVSS17(1-6)
IEEE DOI 1806
Gaussian processes, feature extraction, image representation, learning (artificial intelligence), object detection, Trajectory BibRef

Gaidon, A.[Adrien], Wang, Q.[Qiao], Cabon, Y.[Yohann], Vig, E.[Eleonora],
VirtualWorlds as Proxy for Multi-object Tracking Analysis,
CVPR16(4340-4349)
IEEE DOI 1612
Learning, synthetic data. BibRef

Kieritz, H., Hübner, W., Arens, M.,
Joint Detection and Online Multi-object Tracking,
Joint18(1540-15408)
IEEE DOI 1812
Detectors, Recurrent neural networks, History, Object tracking, Feature extraction, Multilayer perceptrons BibRef

Sadeghian, A., Alahi, A., Savarese, S.,
Tracking the Untrackable: Learning to Track Multiple Cues with Long-Term Dependencies,
ICCV17(300-311)
IEEE DOI 1802
learning (artificial intelligence), object detection, recurrent neural nets, sensor fusion, target tracking, Trajectory BibRef

Risse, B., Mangan, M., Webb, B., Pero, L.D.,
Visual Tracking of Small Animals in Cluttered Natural Environments Using a Freely Moving Camera,
Wildlife17(2840-2849)
IEEE DOI 1802
Animals, Cameras, Optimization, Target tracking, Visualization BibRef

Schulter, S., Vernaza, P., Choi, W., Chandraker, M.,
Deep Network Flow for Multi-object Tracking,
CVPR17(2730-2739)
IEEE DOI 1711
Bipartite graph, Cost function, Image edge detection, Neural networks, Trajectory BibRef

Dimou, A., Medentzidou, P., Álvarez García, F., Daras, P.,
Multi-target detection in CCTV footage for tracking applications using deep learning techniques,
ICIP16(928-932)
IEEE DOI 1610
Cameras BibRef

Chau, D.P.[Duc Phu], Subramanian, K., Brémond, F.[François],
Adaptive Neuro-Fuzzy Controller for Multi-object Tracker,
CVS15(466-476).
Springer DOI 1507
BibRef

Luo, W.H.[Wen-Han], Kim, T.K.[Tae-Kyun], Stenger, B.[Bjorn], Zhao, X.W.[Xiao-Wei], Cipolla, R.[Roberto],
Bi-label Propagation for Generic Multiple Object Tracking,
CVPR14(1290-1297)
IEEE DOI 1409
Multiple object tracking;clustered multi-task learning BibRef

Yan, W.[Wang], Han, X.Y.[Xiao-Ye], Pavlovic, V.[Vladimir],
Structured Learning for Multiple Object Tracking,
BMVC12(48).
DOI Link 1301
BibRef

Li, M.[Min], Chen, W.[Wei], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Multi-Target Tracking by Learning Class-Specific and Instance-Specific Cues,
ACCV10(II: 67-81).
Springer DOI 1011
BibRef

Yuan, X.T.[Xiao-Tong], Li, S.Z.,
Learning Feature Extraction and Classification for Tracking Multiple Objects: A Unified Framework,
AVSBS06(22-22).
IEEE DOI 0611
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Online Tracking, Real Time Tracking Multiple Objects .


Last update:May 6, 2024 at 15:50:14