Method

MOTC* [MOTC*]
[Anonymous Submission]

Submitted on 2 Aug. 2022 13:48 by
[Anonymous Submission]

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

Method Description:
This Mot system performs online joint object
detection and tracking with high data association
performance.
Parameters:
See the code for details.
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 70.69 % 73.72 % 68.46 % 78.67 % 84.35 % 71.54 % 88.29 % 86.96 %

Benchmark TP FP FN
CAR 30938 3454 1141

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 85.61 % 85.41 % 86.64 % 353 72.49 %

Benchmark MT rate PT rate ML rate FRAG
CAR 76.46 % 20.61 % 2.92 % 726

Benchmark # Dets # Tracks
CAR 32079 1180

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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