Method

AnonymousK [Anonymous ]
[Anonymous Submission]

Submitted on 3 Jul. 2022 21:27 by
[Anonymous Submission]

Running time:0.00 s
Environment:8 cores @ 3.5 Ghz (C/C++)

Method Description:
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Parameters:
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Latex Bibtex:
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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 73.06 % 74.34 % 72.34 % 77.95 % 85.80 % 75.10 % 88.26 % 87.07 %

Benchmark TP FP FN
CAR 30611 3781 635

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 86.26 % 85.71 % 87.16 % 311 73.54 %

Benchmark MT rate PT rate ML rate FRAG
CAR 73.69 % 23.69 % 2.62 % 597

Benchmark # Dets # Tracks
CAR 31246 963

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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