Method

EnLife-MOT [EnLife-MOT]


Submitted on 17 Apr. 2025 16:14 by
kai li (xxx)

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

Method Description:
N/A
Parameters:
N/A
Latex Bibtex:
N/A

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 81.69 % 79.12 % 84.94 % 82.60 % 87.50 % 88.03 % 91.13 % 88.11 %

Benchmark TP FP FN
CAR 31947 2445 516

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 91.34 % 86.91 % 91.39 % 18 79.18 %

Benchmark MT rate PT rate ML rate FRAG
CAR 86.77 % 5.08 % 8.15 % 60

Benchmark # Dets # Tracks
CAR 32463 635

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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