Method

CyberTrack [CyberTrack]


Submitted on 3 Jul. 2022 11:36 by
Xiaoliang Wang (SJTU)

Running time:0.5 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
None
Parameters:
None
Latex Bibtex:

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 78.25 % 77.51 % 79.88 % 82.95 % 84.99 % 82.45 % 91.69 % 87.62 %

Benchmark TP FP FN
CAR 32318 2074 1249

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 90.14 % 86.25 % 90.34 % 69 77.22 %

Benchmark MT rate PT rate ML rate FRAG
CAR 85.85 % 7.23 % 6.92 % 177

Benchmark # Dets # Tracks
CAR 33567 689

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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