3D Multi-Object Tracking using Random Finite Set-based Multiple Measurement Models Filtering (RFS-M3) for Autonomous Vehicles-Reference-Cited by-同舟云学术

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3D Multi-Object Tracking using Random Finite Set-based Multiple Measurement Models Filtering (RFS-M3) for Autonomous Vehicles

Published:2021-05-30 Issue: Volume: Page:
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Container-title:2021 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Pang Su,Morris Daniel,Radha Hayder

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9560720/9560666/09561852.pdf?arnumber=9561852

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A reliable unmanned aerial vehicle multi-target tracking system with global motion compensation for monitoring Procapra przewalskii;Ecological Informatics;2024-07

2. Which Framework is Suitable for Online 3D Multi-Object Tracking for Autonomous Driving with Automotive 4D Imaging Radar?;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

3. Neural Enhanced Belief Propagation for Multiobject Tracking;IEEE Transactions on Signal Processing;2024

4. DB-Tracker: Multi-Object Tracking for Drone Aerial Video Based on Box-MeMBer and MB-OSNet;Drones;2023-09-27

5. PMBM Filter for Multiple Extended Targets With Unknown Clutter Rate and Detection Probability;IEEE Sensors Journal;2023-08-01

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