16.6.2.9.2 Tracking with LiDAR, Point Cloud Tracking

Chapter Contents (Back)
Target Tracking. LiDAR Tracking. Point Cloouds.
See also Obstacles, Objects on the Road Using Radar, Sonar, LiDAR, Active Vision.
See also Vehicle Tracking, Vehicle Motion Analysis.

Fortin, B., Lherbier, R., Noyer, J.,
A Model-Based Joint Detection and Tracking Approach for Multi-Vehicle Tracking With Lidar Sensor,
ITS(16), No. 4, August 2015, pp. 1883-1895.
IEEE DOI 1508
Equations BibRef

Cui, Y., Xu, H., Wu, J., Sun, Y., Zhao, J.,
Automatic Vehicle Tracking With Roadside LiDAR Data for the Connected-Vehicles System,
IEEE_Int_Sys(34), No. 3, May 2019, pp. 44-51.
IEEE DOI 1908
driver information systems, object detection, optical radar, road traffic, road vehicles, roads, automatic vehicle tracking, Radar tracking BibRef

Ma, Y.[Yuchi], Anderson, J.[John], Crouch, S.[Stephen], Shan, J.[Jie],
Moving Object Detection and Tracking with Doppler LiDAR,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Guo, Z.M.[Zi-Ming], Cai, B.G.[Bai-Gen], Jiang, W.[Wei], Wang, J.[Jian],
Feature-based detection and classification of moving objects using LiDAR sensor,
IET-ITS(13), No. 7, July 2019, pp. 1088-1096.
DOI Link 1906
BibRef

Vaquero, V.[Víctor], del Pino, I.[Iván], Moreno-Noguer, F.[Francesc], Solà, J.[Joan], Sanfeliu, A.[Alberto], Andrade-Cetto, J.[Juan],
Dual-Branch CNNs for Vehicle Detection and Tracking on LiDAR Data,
ITS(22), No. 11, November 2021, pp. 6942-6953.
IEEE DOI 2112
Laser radar, Vehicle detection, Sensors, Cameras, Convolutional neural networks, point cloud BibRef

Tian, S.J.[Sheng-Jing], Liu, X.P.[Xiu-Ping], Liu, M.[Meng], Bian, Y.H.[Yu-Hao], Gao, J.B.[Jun-Bin], Yin, B.C.[Bao-Cai],
Learning the Incremental Warp for 3D Vehicle Tracking in LiDAR Point Clouds,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Peng, X.Y.[Xiao-Yi], Shan, J.[Jie],
Detection and Tracking of Pedestrians Using Doppler LiDAR,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Cao, Y.[Yu], Su, X.Q.[Xiu-Qin], Qian, X.M.[Xue-Ming], Wang, H.T.[Hai-Tao], Hao, W.[Wei], Xie, M.[Meilin], Feng, X.B.[Xu-Bin], Han, J.F.[Jun-Feng], Chen, M.L.[Ming-Liang], Wang, C.L.[Cheng-Long],
A Tracking Imaging Control Method for Dual-FSM 3D GISC LiDAR,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
Target tracking in LiDAR BibRef

Cao, Y.[Yu], Xie, M.[Meilin], Wang, H.T.[Hai-Tao], Hao, W.[Wei], Guo, M.[Min], Jiang, K.[Kai], Wang, L.[Lei], Guo, S.[Shan], Wang, F.[Fan],
A Dual-FSM GI LiDAR Imaging Control Method Based on Two-Dimensional Flexible Turntable Composite Axis Tracking,
RS(16), No. 10, 2024, pp. 1679.
DOI Link 2405
BibRef

Zhang, Q.Y.[Qiu-Yu], Wang, L.P.[Li-Peng], Li, W.Y.[Wan-Yi], Meng, H.[Hao], Zhang, W.[Wen], Zhang, Z.[Zhi], Wang, P.[Peng],
OS-DS tracker: Orientation-variant Siamese 3D tracking with Detection based Sampling,
PRL(174), 2023, pp. 57-63.
Elsevier DOI 2310
LIDAR point clouds, Object tracking, Gaussian sampling, Candidate regions, Auto-encoder BibRef

Wang, L.[Li], Zhang, X.Y.[Xin-Yu], Qin, W.Y.[Wen-Yuan], Li, X.Y.[Xiao-Yu], Gao, J.H.[Jing-Han], Yang, L.[Lei], Li, Z.W.[Zhi-Wei], Li, J.[Jun], Zhu, L.[Lei], Wang, H.[Hong], Liu, H.P.[Hua-Ping],
CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking With Camera-LiDAR Fusion,
ITS(24), No. 11, November 2023, pp. 11981-11996.
IEEE DOI 2311
BibRef

Cho, M.H.[Min-Ho], Kim, E.T.[Eun-Tai],
3D LiDAR Multi-Object Tracking with Short-Term and Long-Term Multi-Level Associations,
RS(15), No. 23, 2023, pp. 5486.
DOI Link 2312
BibRef

Mei, J.B.[Jian-Biao], Yang, Y.[Yu], Wang, M.M.[Meng-Meng], Li, Z.Z.[Zi-Zhang], Ra, J.W.[Jong-Won], Liu, Y.[Yong],
LiDAR video object segmentation with dynamic kernel refinement,
PRL(178), 2024, pp. 21-27.
Elsevier DOI 2402
LiDAR segmentation, Video object segmentation, Dynamic kernel BibRef

Karki, S.[Shashank], Pingel, T.J.[Thomas J.], Baird, T.D.[Timothy D.], Flack, A.[Addison], Ogle, T.[Todd],
Enhancing Digital Twins with Human Movement Data: A Comparative Study of Lidar-Based Tracking Methods,
RS(16), No. 18, 2024, pp. 3453.
DOI Link 2410
BibRef

Sormoli, M.A.[Mohammadreza Alipour], Dianati, M.[Mehrdad], Mozaffari, S.[Sajjad], Woodman, R.[Roger],
Optical Flow Based Detection and Tracking of Moving Objects for Autonomous Vehicles,
ITS(25), No. 9, September 2024, pp. 12578-12590.
IEEE DOI 2409
Laser radar, Sensors, Point cloud compression, Estimation, Vectors, Filters, Target tracking, Autonomous vehicles, optical flow, LiDAR, state estimation BibRef

Fang, S.[Susu], Li, H.[Hao],
Multi-Vehicle Cooperative Simultaneous LiDAR SLAM and Object Tracking in Dynamic Environments,
ITS(25), No. 9, September 2024, pp. 11411-11421.
IEEE DOI 2409
Simultaneous localization and mapping, Vehicle dynamics, Pose estimation, Object tracking, Laser radar, Object detection, C-SLAMMODT BibRef

Guo, D.F.[Dong-Fang], Qu, Y.C.[Yan-Chen], Zhou, X.[Xin], Sun, J.F.[Jian-Feng], Yin, S.W.[Sheng-Wen], Lu, J.[Jie], Liu, F.[Feng],
Research on Cam-Kalm Automatic Tracking Technology of Low, Slow, and Small Target Based on Gm-APD LiDAR,
RS(17), No. 1, 2025, pp. 165.
DOI Link 2501
BibRef

Sun, J.T.[Jing-Tao], Wang, Y.[Yaonan], Feng, M.[Mingtao], Guo, X.F.[Xiao-Feng], Lu, H.M.[Hui-Min], Chen, X.[Xieyuanli],
Category-Level Multi-Object 9D State Tracking Using Object-Centric Multi-Scale Transformer in Point Cloud Stream,
MultMed(27), 2025, pp. 1072-1085.
IEEE DOI 2502
Transformers, Point cloud compression, 6-DOF, Solid modeling, State estimation, Shape, Pose estimation, Target tracking, Robots, point cloud processing BibRef

Zhao, X.T.[Xian-Tong], Han, Y.[Yinan], Tian, S.J.[Sheng-Jing], Liu, J.[Jian], Liu, X.P.[Xiu-Ping],
OST: Efficient One-Stream Network for 3D Single Object Tracking in Point Clouds,
MultMed(27), 2025, pp. 990-1002.
IEEE DOI 2502
Target tracking, Feature extraction, Transformers, Object tracking, Point cloud compression, Visualization, multi-scale BibRef


Cheong, B.[Brian], Zhou, J.C.[Jia-Chen], Waslander, S.[Steven],
JDT3D: Addressing the Gaps in Lidar-based Tracking-by-attention,
ECCV24(LXVI: 161-177).
Springer DOI 2412
BibRef

Kreutz, T.[Thomas], Mühlhäuser, M.[Max], Guinea, A.S.[Alejandro Sanchez],
Unsupervised 4D LiDAR Moving Object Segmentation in Stationary Settings with Multivariate Occupancy Time Series,
WACV23(1644-1653)
IEEE DOI 2302
Point cloud compression, Laser radar, Annotations, Time series analysis, Neural networks, Clustering algorithms BibRef

Yin, J., Shen, J., Guan, C., Zhou, D., Yang, R.,
LiDAR-Based Online 3D Video Object Detection With Graph-Based Message Passing and Spatiotemporal Transformer Attention,
CVPR20(11492-11501)
IEEE DOI 2008
Feature extraction, Spatiotemporal phenomena, Detectors, Object detection, Encoding, Message passing BibRef

Zhang, J., Xiao, W., Coifman, B., Mills, J.P.,
Image-based Vehicle Tracking From Roadside Lidar Data,
Laser19(1177-1183).
DOI Link 1912
BibRef

Yan, J.Z.[Ji-Zhou], Chen, D.D.[Dong-Dong], Myeong, H.[Heesoo], Shiratori, T.[Takaaki], Ma, Y.[Yi],
Automatic Extraction of Moving Objects from Image and LIDAR Sequences,
3DV14(673-680)
IEEE DOI 1503
Image color analysis BibRef

Natale, D.J.[Donald J.], Tutwiler, R.L.[Richard L.], Baran, M.S.[Matthew S.], Durkin, J.R.[John R.],
Using full motion 3D Flash LIDAR video for target detection, segmentation, and tracking,
Southwest10(21-24).
IEEE DOI 1005
Video rate LIDAR data. Tracking in 3-D, no need to derive 3-D. BibRef

Shackleton, J., van Voorst, B., Hesch, J.,
Tracking People with a 360-Degree Lidar,
AVSS10(420-426).
IEEE DOI 1009
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Mean-Shift Tracking Techniques .


Last update:Mar 17, 2025 at 20:02:03