AB3DMOT
A real-time baseline 3D multi-object tracking system using LiDAR point clouds, combining 3D Kalman filter and Hungarian algorithm.
What is AB3DMOT?
AB3DMOT is a baseline system for 3D multi-object tracking that uses LiDAR point clouds to track objects in real-time for applications like autonomous driving. It combines a 3D Kalman filter with the Hungarian algorithm for state estimation and data association, achieving high accuracy and speed. The project also introduces new evaluation metrics to better assess 3D MOT performance.
Researchers and engineers working on autonomous vehicles, robotics, or computer vision who need efficient and accurate 3D object tracking solutions. It's particularly useful for those benchmarking or developing real-time perception systems.
Developers choose AB3DMOT because it provides a simple, high-performance baseline that is both state-of-the-art in accuracy and extremely fast, running at 214.7 FPS. Its modular design and support for major datasets like KITTI and nuScenes make it a practical and reliable choice for 3D MOT tasks.
Overview
(IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"
Use Cases
Best For
- Real-time 3D object tracking in autonomous driving systems
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