Laser Journal, Volume. 45, Issue 1, 191(2024)

3D Multi-object tracking algorithm based on improved data association

ZHANG Huaxu1, LIU Zheng1、*, LEI Zufang2, and XIE Rong1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    References(7)

    [8] [8] Weng X, Wang J, Held D, et al. Ab3dmot: A baseline for 3d multi-object tracking and new evaluation metrics[J].arXiv preprint arXiv:2008. 08063, 2020.

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    [10] [10] Zhang Y, Guo Y, Niu H, et al. Directed Data Association for Single Object Tracking in Point Clouds[C] / /2022 IEEE 18th International Conference on Automation Science and Engineering (CASE). IEEE, 2022: 1157-1162.

    [11] [11] Wu H, Han W, Wen C, et al. 3d multi-object tracking in point clouds based on prediction confidence-guided data association[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 23(6): 5668-5677.

    [13] [13] Burnett K, Samavi S, Waslander S, et al. autotrack: A lightweight object detection and tracking system for the sae autodrive challenge[C] / /2019 16th Conference on Computer and Robot Vision (CRV). IEEE, 2019: 209-216.

    [14] [14] Milan A, Leal-Taixé L, Reid I, et al. MOT16: A benchmark for multi-object tracking[J]. arXiv preprint arXiv:1603. 00831, 2016.

    [15] [15] Chen J, Xu H, Wu J, et al. Deer crossing road detection with roadside LiDAR sensor[J]. IEEE Access, 2019, 7:65944-65954.

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    ZHANG Huaxu, LIU Zheng, LEI Zufang, XIE Rong. 3D Multi-object tracking algorithm based on improved data association[J]. Laser Journal, 2024, 45(1): 191

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    Paper Information

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    Received: Aug. 25, 2023

    Accepted: --

    Published Online: Aug. 6, 2024

    The Author Email: Zheng LIU (lz@xidian.edu.cn)

    DOI:10.14016/j.cnki.jgzz.2024.1.191

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