Method

Near-Online Multi-target Tracking (HM baseline) [on] [NOMT-HM]


Submitted on 16 Oct. 2014 23:37 by
Wongun Choi (NEC Laboratories)

Running time:0.09 s
Environment:8 cores @ 2.5 Ghz (Matlab + C/C++)

Method Description:
The algorithm tracks targets using Hungarian
method equipped with the same match features used
in NOMT method. It makes the association in every
time frame in pure online fashion. More details on
the method will be updated as soon as possible.
Parameters:
Reference detections are used:
http://www.cvlibs.net/download.php?
file=data_tracking_det_2.zip
Latex Bibtex:
@article{Choi2015ICCV,
author = {Choi, Wongun},
title = {Near-Online Multi-target Tracking with
Aggregated Local Flow Descriptor
},
journal= {ICCV},
year={2015},
}

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 52.17 % 48.58 % 56.45 % 50.76 % 79.02 % 58.78 % 84.62 % 81.82 %
PEDESTRIAN 31.13 % 25.64 % 38.23 % 27.75 % 59.78 % 42.38 % 65.06 % 72.90 %

Benchmark TP FP FN
CAR 21579 12813 512
PEDESTRIAN 8589 14561 2155

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 60.68 % 79.00 % 61.26 % 199 47.50 %
PEDESTRIAN 26.86 % 67.66 % 27.79 % 217 14.86 %

Benchmark MT rate PT rate ML rate FRAG
CAR 34.15 % 38.00 % 27.85 % 224
PEDESTRIAN 15.12 % 34.02 % 50.86 % 763

Benchmark # Dets # Tracks
CAR 22091 715
PEDESTRIAN 10744 346

This table as LaTeX

This figure as: png pdf

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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