Globally-optimal greedy algorithms for tracking a variable number of objects

The Hungarian method for the assignment problem

Kuhn, H. W. (1955) · Naval Research Logistics Quarterly · doi:10.1002/nav.3800020109 · Cited by 13,120

Network Flows: Theory, Algorithms, and Applications.

Smith, D. K., Ahuja, R. K., Magnanti, T. L., & Orlin, J. B. (1994) · Journal of the Operational Research Society · doi:10.2307/2583863 · Cited by 8,121

Fast approximate energy minimization via graph cuts

Boykov, Y., Veksler, O., & Zabih, R. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.969114 · Cited by 6,988

A discriminatively trained, multiscale, deformable part model

Felzenszwalb, P. F., McAllester, D., & Ramanan, D. (2008) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2008.4587597 · Cited by 2,972

Sonar tracking of multiple targets using joint probabilistic data association

Fortmann, T. E., Bar‐Shalom, Y., & Scheffe, M. M. (1983) · IEEE Journal of Oceanic Engineering · doi:10.1109/joe.1983.1145560 · Cited by 1,474

Pedestrian detection: A benchmark

Dollár, P., Wojek, C., Schiele, B., & Perona, P. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2009.5206631 · Cited by 1,351

Multiple Object Tracking Using K-Shortest Paths Optimization

Berclaz, J., Fleuret, F., Turetken, E., & Fua, P. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.21 · Cited by 1,015

Global data association for multi-object tracking using network flows

Zhang, L., Li, Y., & Nevatia, R. (2008) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2008.4587584 · Cited by 945

BraMBLe: a Bayesian multiple-blob tracker

Isard, M., & MacCormick, J. (2002) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2001.937594 · Cited by 633

Depth and Appearance for Mobile Scene Analysis

Ess, A., Leibe, B., & Van Gool, L. (2007) · 2007 IEEE 11th International Conference on Computer Vision · doi:10.1109/iccv.2007.4409092 · Cited by 540

Multiple pedestrian tracking by combining particle filter and network flow model

Cui, Y., Zhang, J., He, Z., & Hu, J. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.03.077 · Cited by 14

Online Learned Siamese Network with Auto-Encoding Constraints for Robust Multi-Object Tracking

Liu, P., Li, X., Liu, H., & Fu, Z. (2019) · Electronics · doi:10.3390/electronics8060595 · Cited by 14

Revisiting Jump-Diffusion Process for Visual Tracking: A Reinforcement Learning Approach

Liu, X., Xu, Q., Chau, T., Mu, Y., Zhu, L., & Yan, S. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2018.2862891 · Cited by 14

A novel multi-target multi-camera tracking approach based on feature grouping

Xu, J., Bo, C., & Wang, D. (2021) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2021.107153 · Cited by 14

Efficient Single-Shot Multi-Object Tracking for Vehicles in Traffic Scenarios

Lee, Y., Lee, S.-H., Yoo, J., & Kwon, S. (2021) · Sensors · doi:10.3390/s21196358 · Cited by 17

FAANet: feature-aligned attention network for real-time multiple object tracking in UAV videos

Liang, Z., Wang, J., Xiao, G., & Zeng, L. (2022) · Chinese Optics Letters · doi:10.3788/col202220.081101 · Cited by 14

Semantic Object Segmentation in Tagged Videos via Detection

Zhang, Y., Chen, X., Li, J., Wang, C., Xia, C., & Li, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2727049 · Cited by 14

Scene-Centric Joint Parsing of Cross-View Videos

Qi, H., Xu, Y., Yuan, T., Wu, T., & Zhu, S. C. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.12256 · Cited by 14

GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature LearningPreprint

Weng, X., Wang, Y., Man, Y., & Kitani, K. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.07327 · Cited by 14

High-Performance Detection-Based Tracker for Multiple Object Tracking in UAVs

Li, X., Zhu, R., Yu, X., Cong, Y., & Wang, X. (2023) · Drones · doi:10.3390/drones7110681 · Cited by 13

Online Multi-Target Tracking With Unified Handling of Complex Scenarios

Jiang, H., Wang, J., Gong, Y., Rong, N., Chai, Z., & Zheng, N. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2446331 · Cited by 13

Long-Term Multi-Cue Tracking of Hands in Vehicles

Rangesh, A., Ohn-Bar, E., & Trivedi, M. M. (2016) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2015.2508722 · Cited by 13

The detection, tracking, and temporal action localisation of swimmers for automated analysis

Hall, A., Victor, B., He, Z., Langer, M., Elipot, M., Nibali, A., & Morgan, S. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-05485-3 · Cited by 13

Enhancing Online UAV Multi-Object Tracking with Temporal Context and Spatial Topological Relationships

Xiao, C., Cao, Q., Zhong, Y., Lan, L., Zhang, X., Cai, H., & Luo, Z. (2023) · Drones · doi:10.3390/drones7060389 · Cited by 13

Multi-object tracking via discriminative appearance modeling

Huang, S., Jiang, S., & Zhu, X. (2016) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2016.06.003 · Cited by 13

Part-aware trajectories association across non-overlapping uncalibrated cameras

Cheng, D., Gong, Y., Wang, J., Hou, Q., & Zheng, N. (2016) · Neurocomputing · doi:10.1016/j.neucom.2016.11.038 · Cited by 13

Skeleton model based behavior recognition for pedestrians and cyclists from vehicle sce ne camera

Deng, Q., Tian, R., Chen, Y., & Li, K. (2018) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2018.8500359 · Cited by 13

Online multiple object tracking using confidence score‐based appearance model learning and hierarchical data association

Liu, M., Jin, C., Yang, B., Cui, X., & Kim, H. (2018) · IET Computer Vision · doi:10.1049/iet-cvi.2018.5499 · Cited by 13

Target-Specific Action Classification for Automated Assessment of Human Motor Behavior from Video

Rezaei, B., Christakis, Y., Ho, B. K., Thomas, K. C., Erb, K., Ostadabbas, S., & Patel, S. (2019) · Sensors · doi:10.3390/s19194266 · Cited by 13

Moving Camera-Based Object Tracking Using Adaptive Ground Plane Estimation and Constrained Multiple Kernels

Liu, T., & Liu, Y. (2021) · Journal of Advanced Transportation · doi:10.1155/2021/8153474 · Cited by 13

Deformable multiple-kernel based human tracking using a moving camera

Hou, L., Wan, W., Lee, K.-H., Hwang, J., Okopal, G., & Pitton, J. W. (2015) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2015.7178371 · Cited by 13

Improving Global Multi-target Tracking with Local Updates

Milan, A., Gade, R., Dick, A., Moeslund, T. B., & Reid, I. D. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-16199-0_13 · Cited by 13

Multi-target tracking by non-linear motion patterns based on hierarchical network flows

Lu, W., Zhou, Z., Zhang, L., & Zheng, G. (2019) · Multimedia Systems · doi:10.1007/s00530-019-00614-y · Cited by 13

Online, Real-Time Tracking Using a Category-to-Individual Detector

Hall, D. C., & Perona, P. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10590-1_24 · Cited by 12

From Coarse to Fine: Two-Stage Indoor Localization with Multisensor Fusion

Zhang, L., Bao, J., Xu, Y., Wang, Q., Xu, J., & Li, D. (2022) · Tsinghua Science & Technology · doi:10.26599/tst.2022.9010029 · Cited by 12

Robust Human Tracking Based on DPM Constrained Multiple-Kernel from a Moving Camera

Hou, L., Wan, W., Lee, K.-H., Hwang, J., Okopal, G., & Pitton, J. W. (2015) · Journal of Signal Processing Systems · doi:10.1007/s11265-015-1097-y · Cited by 12

Multi-object tracking through learning relational appearance features and motion patterns

Gwak, J. (2017) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2017.05.010 · Cited by 12

Efficient Global MOT Under Minimum-Cost Circulation Framework

Wang, C., Wang, Y., & Yu, G. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3026257 · Cited by 12

Critical Overview of Visual Tracking with Kernel Correlation Filter

Yadav, S., & Payandeh, S. (2021) · Technologies · doi:10.3390/technologies9040093 · Cited by 13

Multi-human tracking using part-based appearance modelling and grouping-based tracklet association for visual surveillance applications

Yang, E., Gwak, J., & Jeon, M. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-015-3219-8 · Cited by 12

Pedestrian Detection in Binocular Stereo Sequence Based on Appearance Consistency

Zhang, Z., & Tao, W. (2015) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2015.2475855 · Cited by 12

A Unified Video Text Detection Method with Network Flow

Yang, X., He, W., Yin, F., & Liu, C. (2017) · IAPR International Conference on Document Analysis and Recognition (ICDAR) · doi:10.1109/icdar.2017.62 · Cited by 12

Identity Retention of Multiple Objects under Extreme Occlusion Scenarios using Feature Descriptors

Israni, D., & Mewada, H. K. (2018) · Journal of Communications Software and Systems · doi:10.24138/jcomss.v14i4.541 · Cited by 12

Dual L1-Normalized Context Aware Tensor Power Iteration and Its Applications to Multi-object Tracking and Multi-graph Matching

Hu, W., Shi, X., Zhou, Z., Xing, J., Ling, H., & Maybank, S. J. (2019) · International Journal of Computer Vision · doi:10.1007/s11263-019-01231-y · Cited by 12

Multi-view Tracking of Multiple Targets with Dynamic Cameras

Kroeger, T., Dragon, R., & Gool, L. V. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11752-2_54 · Cited by 12

A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets

Haubold, C., Aleš, J., Wolf, S., & Hamprecht, F. A. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46478-7_35 · Cited by 12

A Greedy Data Association Technique for Multiple Object Tracking

Singh, G., Rajan, S., & Majumdar, S. (2017) · IEEE International Conference on Multimedia Big Data · doi:10.1109/bigmm.2017.53 · Cited by 12

ArTIST: Autoregressive Trajectory Inpainting and Scoring for TrackingPreprint

Saleh, F. S., Aliakbarian, S., Salzmann, M., & Gould, S. J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.07482 · Cited by 12

Vehicular/Non-Vehicular Multi-Class Multi-Object Tracking in Drone-Based Aerial Scenes

Bisio, I., Garibotto, C., Haleem, H., Lavagetto, F., & Sciarrone, A. (2023) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2023.3332132 · Cited by 11

Based on improved joint detection and tracking of UAV for multi-target detection of livestock

Shen, P., Wang, F., Luo, W., Zhao, Y., Li, L., Zhang, G., & Zhu, Y. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e38316 · Cited by 11

Combined segmentation, reconstruction, and tracking of multiple targets in multi-view video sequences

Babaee, M., You, Y., & Rigoll, G. (2016) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2016.08.006 · Cited by 11

Tracking Millions of Humans in Crowded Spaces

Alahi, A., Ramanathan, V., & Fei-Fei, L. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809276-7.00007-2 · Cited by 11

Accelerating Dynamic Programs via Nested Benders Decomposition with Application to Multi-Person Pose Estimation

Wang, S., Ihler, A., Kording, K. P., & Yarkony, J. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01264-9_40 · Cited by 11

Re-identification for Improved People Tracking

Fleuret, F., Shitrit, H. B., & Fua, P. (2014) · Advances in computer vision and pattern recognition · doi:10.1007/978-1-4471-6296-4_15 · Cited by 11

Multi-pose multi-target tracking for activity understanding

Izadinia, H., Ramakrishna, V., Kitani, K., & Huber, D. (2013) · Proceedings · doi:10.1109/wacv.2013.6475044 · Cited by 11

Human detection and tracking over camera networks: A review

Hou, L., Wan, W., Han, K., Muhammad, R., & Yang, M. (2016) · International Conference on Audio, Language and Image Processing · doi:10.1109/icalip.2016.7846643 · Cited by 11

Identifying motion pathways in highly crowded scenes: A non-parametric tracklet clustering approach

Hassanein, A. S., Hussein, M. E., Gomaa, W. E., Makihara, Y., & Yagi, Y. (2018) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2018.08.004 · Cited by 11

Multiple object tracking by reliable tracklets

Liang, Y., Lu, X., He, Z., & Zheng, Y. (2019) · Signal Image and Video Processing · doi:10.1007/s11760-019-01418-3 · Cited by 11

3D Pedestrian tracking using local structure constraints

Nguyen, U., & Heipke, C. (2020) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2020.05.002 · Cited by 11

Online Multiple Athlete Tracking with Pose-Based Long-Term Temporal Dependencies

Kong, L., Zhu, M., Ran, N., Liu, Q., & He, R. (2020) · Sensors · doi:10.3390/s21010197 · Cited by 11

LAMAR: LiDAR based Multi-inhabitant Activity Recognition

Alam, M. A. U., Mazzoni, F., Rahman, M. M., & Widberg, J. Q. (2020) · EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous) · doi:10.1145/3448891.3450334 · Cited by 11

Fast Simultaneous People Detection and Re-identification in a Single Shot Network

Ranst, W. V., Smedt, F. D., Berte, J., & Goedemé, T. (2018) · IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) · doi:10.1109/avss.2018.8639489 · Cited by 11

Data Association for Multi-Object Visual Tracking

Betke, M., & Wu, Z. (2016) · Synthesis lectures on computer vision · doi:10.2200/s00726ed1v01y201608cov009 · Cited by 11

Tracking Objects with Higher Order Interactions using Delayed Column GenerationPreprint

Wang, S., Wolf, S., Fowlkes, C. C., & Yarkony, J. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1512.02413 · Cited by 11

Unsupervised Multiple Person Tracking using AutoEncoder-Based Lifted MulticutsPreprint

Ho, K., Keuper, J., & Keuper, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2002.01192 · Cited by 11

Dynamic mutation enhanced greedy strategy for wavefront shaping

Zhang, C., Yao, Z., Liu, T., Sui, X., Chen, Q., Xie, Z., & Liu, G. (2023) · Optics & Laser Technology · doi:10.1016/j.optlastec.2023.110018 · Cited by 10

An Asymmetric Feature Enhancement Network for Multiple Object Tracking of Unmanned Aerial Vehicle

Ma, J., Liu, D., Qin, S., Ge, J., Zhang, J., & Xu, Z. (2023) · Remote Sensing · doi:10.3390/rs16010070 · Cited by 10

Multiway histogram intersection for multi-target tracking

Pang, Y., Shi, X., Jia, B., Blasch, E., Sheaff, C., Pham, K. D., Chen, G., & Ling, H. (2015) · Cited by 10

Online Video Text Detection with Markov Decision Process

Yang, X., Yin, F., & Liu, C. (2018) · IAPR International Workshop on Document Analysis Systems (DAS) · doi:10.1109/das.2018.20 · Cited by 10

Variational Inference for 3-D Localization and Tracking of Multiple Targets Using Multiple Cameras

Byeon, M., Lee, M., Kim, K., & Choi, J. Y. (2019) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2890526 · Cited by 10

Probability hypothesis density filter using determinantal point processes for multi object tracking

Jorquera, F., Hernández, S., & Vergara, D. (2019) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2019.04.001 · Cited by 10

Prototype-guided Instance matching for multiple pedestrian tracking

Wang, Q., Zhang, W., Yang, W., Xu, C., & Cui, Z. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.03.068 · Cited by 10

Learnable Graph Matching: A Practical Paradigm for Data Association

He, J., Huang, Z., Wang, N., & Zhang, Z. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3362401 · Cited by 10

Leveraging single for multi-target tracking using a novel trajectory overlap affinity measure

Manén, S., Timofte, R., Dai, D., & Gool, L. V. (2016) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2016.7477566 · Cited by 10

Online Multi-object Tracking Based on Hierarchical Association Framework

Ju, J., Kim, D., Ku, B., Ko, H., & Han, D. K. (2016) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2016.161 · Cited by 10

Globality–Locality-Based Consistent Discriminant Feature Ensemble for Multicamera Tracking

Nithin, K., & Brémond, F. (2016) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2016.2615538 · Cited by 10

Tracking Solar Phenomena from the SDO

Kempton, D., Schuh, M. A., & Angryk, R. A. (2018) · The Astrophysical Journal · doi:10.3847/1538-4357/aae9e9 · Cited by 10

Self-balance Motion and Appearance Model for Multi-object Tracking in UAV

Yu, H., Li, G., Zhang, W., Yao, H., & Huang, Q. (2019) · ACM International Conference on Multimedia in Asia (MMAsia) · doi:10.1145/3338533.3366561 · Cited by 10

Multiple Object Tracking for Dense Pedestrians by Markov Random Field Model with Improvement on Potentials

Liu, P., Li, X., Wang, Y., & Fu, Z. (2020) · Sensors · doi:10.3390/s20030628 · Cited by 10

Deep Learning Technique Based Surveillance Video Analysis for the Store

Xu, Q., Zheng, W., Liu, X., & Jing, P. (2020) · Applied Artificial Intelligence · doi:10.1080/08839514.2020.1784611 · Cited by 10

A Viewport Prediction Framework for Panoramic Videos

Tang, J., Huo, Y., Yang, S., & Jiang, J. (2020) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn48605.2020.9207562 · Cited by 10

A Graphical Social Topology Model for RGB-D Multi-Person Tracking

Gao, S., Ye, Q., Liu, L., Kuijper, A., & Ji, X. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3049397 · Cited by 10

Deep Learning-Based Multi-class Multiple Object Tracking in UAV Video

Micheal, A. A., & Vani, K. S. (2022) · Journal of the Indian Society of Remote Sensing · doi:10.1007/s12524-022-01615-7 · Cited by 10

Carried Object Detection and Tracking Using Geometric Shape Models and Spatio-temporal Consistency

Tavanai, A., Sridhar, M., Gu, F., Cohn, A. G., & Hogg, D. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39402-7_23 · Cited by 10

Vehicle Tracking in Wide Area Motion Imagery via Stochastic Progressive Association Across Multiple Frames

Elliethy, A. S., & Gaurav Sharma, A. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2818443 · Cited by 10

A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos

Chen, T., Pennisi, A., Li, Z., Zhang, Y., & Hichem Sahli, B. (2018) · Remote Sensing · doi:10.3390/rs10091347 · Cited by 10

AIC2018 Report: Traffic Surveillance Research

Mao, T., Zhang, W., He, H., Lin, Y., Kale, V. U., Stein, A., & Kostić, Z. (2018) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2018.00019 · Cited by 10

Transfer learning‐based online multiperson tracking with Gaussian process regression

Zhang, B., Li, S., Huang, Z., Rahi, B. H., Wang, Q., & Li, M. (2018) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.4917 · Cited by 10

Vehicle Detection and Tracking from Surveillance Cameras in Urban Scenes

Messoussi, O., de Magalhães, F. G., Lamarre, F., Perreault, F., Sogoba, I., Bilodeau, G.-A., & Nicolescu, G. (2021) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-90436-4_15 · Cited by 9

SuperMOT: Decoupling Motion and Fusing Temporal Pyramid Features for UAV Multiobject Tracking

Ren, L., Yin, W., Diao, W., Fu, K., & Sun, X. (2025) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2025.3563060 · Cited by 9

How AI-based computer vision algorithms are impacting the sports industry: a survey

Rossi, L. F., Sanna, A., Manuri, F., & Bianco, M. D. (2025) · Discover Artificial Intelligence · doi:10.1007/s44163-025-00586-1 · Cited by 9

HM-Net: A Regression Network for Object Center Detection and Tracking on Wide Area Motion Imagery

Motorcu, H., Ates, H. F., Uğurdağ, H. F., & Gunturk, B. K. (2021) · IEEE Access · doi:10.1109/access.2021.3138980 · Cited by 9

Multi-Target Tracking Based on High-Order Appearance Feature Fusion

Han, G., Gao, Y., & Sun, N. (2019) · IEEE Access · doi:10.1109/access.2019.2955809 · Cited by 9

A Two-Stage Minimum Cost Multicut Approach to Self-supervised Multiple Person Tracking

Ho, K., Kardoost, A., Pfreundt, F., Keuper, J., & Keuper, M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-69532-3_33 · Cited by 9

Graph-Based Data Association in Multiple Object Tracking: A Survey

Τούσκα, Δ., Gkountakos, K., Tsikrika, T., Ioannidis, K., Vrochidis, S., & Kompatsiaris, I. Y. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-27818-1_32 · Cited by 9

A Sheaf Theoretical Approach to Uncertainty Quantification of Heterogeneous Geolocation Information

Joslyn, C., Charles, L., Deperno, C. S., Gould, N. P., Nowak, K., Praggastis, B., Purvine, E., Robinson, M., Strules, J., & Whitney, P. (2020) · Sensors · doi:10.3390/s20123418 · Cited by 9

SQE: a Self Quality Evaluation Metric for Parameters Optimization in Multi-Object Tracking

Huang, Y., Zhu, F., Zeng, Z., Qiu, X., Shen, Y., & Wu, J. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00833 · Cited by 9

Assignment-Space-based Multi-Object Tracking and Segmentation

Choudhuri, A., Chowdhary, G. V., & Schwing, A. G. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01334 · Cited by 9

Object Tracking by Detection with Visual and Motion CuesPreprint

Salscheider, N. O. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2101.07549 · Cited by 12

Parameter estimation and contextual adaptation for a multi-object tracking CRF model

Heili, A., & Odobez, J. (2013) · IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS) · doi:10.1109/pets.2013.6523790 · Cited by 8

Globally optimal target tracking in real time using max-flow network

Choe, T. E., Rasheed, Z., Taylor, G., & Haering, N. (2011) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2011.6130474 · Cited by 8

RGB-D Railway Platform Monitoring and Scene Understanding for Enhanced Passenger Safety

Wallner, M., Steininger, D., Widhalm, V., Schörghuber, M., & Beleznai, C. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-68787-8_47 · Cited by 8

Tracking with a mixed continuous-discrete Conditional Random Field

Pellegrini, S., & Gool, L. V. (2012) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2012.09.005 · Cited by 8

Effective evaluation of privacy protection techniques in visible and thermal imagery

Nawaz, T. H., Berg, A., Ferryman, J. M., Ahlberg, J., & Felsberg, M. (2017) · Journal of Electronic Imaging · doi:10.1117/1.jei.26.5.051408 · Cited by 8

Unified optimization framework for localization and tracking of multiple targets with multiple cameras

Byeon, M., Yoo, H., Kim, K., Oh, S., & Choi, J. Y. (2017) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2017.10.009 · Cited by 8

Kooperativ interagierende Automobile

Stiller, C., Burgard, W., Deml, B., Eckstein, L., & Flemisch, F. O. (2018) · at - Automatisierungstechnik · doi:10.1515/auto-2017-0129 · Cited by 8

Single Object Tracking Applied to an Aircraft

Ellouze, A., Ksantini, M., Delmotte, F., & Karray, M. (2018) · International Multi-Conference on Systems, Signals & Devices (SSD) · doi:10.1109/ssd.2018.8570663 · Cited by 8

Information Fusion for Industrial Mobile Platform Safety via Track-Before-Detect Labeled Multi-Bernoulli Filter

Rathnayake, T., Tennakoon, R., Gostar, A. K., Bab‐Hadiashar, A., & Hoseinnezhad, R. (2019) · Sensors · doi:10.3390/s19092016 · Cited by 8

Multiple Object Tracking: Case of Aircraft Detection and Tracking

Ellouze, A., Ksantini, M., Delmotte, F., & Karray, M. (2019) · International Multi-Conference on Systems, Signals & Devices (SSD) · doi:10.1109/ssd.2019.8893202 · Cited by 8

Learning sequence-to-sequence affinity metric for near-online multi-object tracking

Feng, W., Lan, L., Zhang, X., & Luo, Z. (2020) · Knowledge and Information Systems · doi:10.1007/s10115-020-01488-7 · Cited by 8

C.: Globally-Optimal Greedy Algorithms for Tracking a Variable Number of Objects

Pirsiavash, H., Ramanan, D., & Fowlkes, C. C. (2011)

Greedy algorithm for real-time multi-object tracking

Kim, T., Lee, C., & Yoo, C. D. (2014) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2014.7025079 · Cited by 5

GraphTrack: Fast and globally optimal tracking in videos

Amberg, B., & Vetter, T. R. (2011) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2011.5995341 · Cited by 6

A probabilistic multimodal algorithm for trackingg multiple and dynamic objects

Marron, Sotelo, & García (2004) · World Automation Congress (WAC) · doi:10.1109/wac.2004.185269

One global optimization method in network flow model for multiple object tracking

He, Z., Cui, Y., Wang, H., You, X., & Chen, C. L. P. (2015) · Knowledge-Based Systems · doi:10.1016/j.knosys.2015.04.018 · Cited by 26