Method

BiTrack [BiTrack]


Submitted on 22 Sep. 2024 15:04 by
Kemiao Huang (Southern University of Science and Technology)

Running time:0.01 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
Bidirectional MOT optimization with 2D-3D fusion.
Parameters:
Please check the paper.
Latex Bibtex:
@misc{huang2024bitrackbidirectionaloffline3d,
title={BiTrack: Bidirectional Offline 3D
Multi-Object Tracking Using Camera-LiDAR Data},
author={Kemiao Huang and Meiying Zhang and
YinQi Chen and
Qi Hao},
year={2024},
eprint={2406.18414},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2406.18414},
}

Detailed Results

From all 29 test sequences, our benchmark computes the HOTA tracking metrics (HOTA, DetA, AssA, DetRe, DetPr, AssRe, AssPr, LocA) [1] as well as the CLEARMOT, MT/PT/ML, identity switches, and fragmentation [2,3] metrics. The tables below show all of these metrics.


Benchmark HOTA DetA AssA DetRe DetPr AssRe AssPr LocA
CAR 82.70 % 80.04 % 86.17 % 84.53 % 87.19 % 89.11 % 92.16 % 88.68 %

Benchmark TP FP FN
CAR 32422 1970 922

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 91.55 % 87.56 % 91.59 % 14 79.83 %

Benchmark MT rate PT rate ML rate FRAG
CAR 85.69 % 7.23 % 7.08 % 277

Benchmark # Dets # Tracks
CAR 33344 652

This table as LaTeX

This figure as: png pdf

[1] J. Luiten, A. Os̆ep, P. Dendorfer, P. Torr, A. Geiger, L. Leal-Taixé, B. Leibe: HOTA: A Higher Order Metric for Evaluating Multi-object Tracking. IJCV 2020.
[2] K. Bernardin, R. Stiefelhagen: Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics. JIVP 2008.
[3] Y. Li, C. Huang, R. Nevatia: Learning to associate: HybridBoosted multi-target tracker for crowded scene. CVPR 2009.


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