Method

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


Submitted on 10 Nov. 2014 01:56 by
Wongun Choi (NEC Laboratories)

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

Method Description:
* use Regionlet detetions available at:
http://www.xiaoyumu.com/s/data/kitti-tracking.zip
Parameters:
n/a
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 59.08 % 61.27 % 57.45 % 65.14 % 79.29 % 60.25 % 83.46 % 82.63 %
PEDESTRIAN 34.76 % 33.96 % 35.81 % 37.64 % 62.76 % 39.23 % 66.66 % 75.36 %

Benchmark TP FP FN
CAR 27099 7293 1156
PEDESTRIAN 11606 11544 2279

Benchmark MOTA MOTP MODA IDSW sMOTA
CAR 74.66 % 80.39 % 75.43 % 266 59.21 %
PEDESTRIAN 38.60 % 70.85 % 40.29 % 391 23.99 %

Benchmark MT rate PT rate ML rate FRAG
CAR 50.77 % 34.92 % 14.31 % 254
PEDESTRIAN 21.65 % 35.74 % 42.61 % 689

Benchmark # Dets # Tracks
CAR 28255 835
PEDESTRIAN 13885 462

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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