Method

[on] Online MOTS using Simple Affinity Fusion [GMPHD_SAF]


Submitted on 29 May. 2020 22:08 by
Young-min Song (Gwanju Institute of Science and Technology)

Running time:0.08 s
Environment:4 cores @ 4.2 Ghz (C/C++)

Method Description:
TBD
Parameters:
TBD
Latex Bibtex:
@article{gmphdsaf,
title={Online Multi-Object Tracking and Segmentation
with GMPHD Filter and Simple Affinity Fusion},
author={Young-min Song and Moongu Jeon},
journal={arXiv preprint arXiv:2009.00100},
year={2020}
}

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 55.14 % 77.01 % 39.76 % 81.57 % 87.29 % 69.22 % 49.42 % 88.72 %
PEDESTRIAN 49.33 % 65.45 % 38.32 % 69.62 % 80.98 % 57.88 % 49.77 % 83.82 %

Benchmark TP FP FN
CAR 33391 3369 960
PEDESTRIAN 17226 3471 567

Benchmark MOTSA MOTSP MODSA IDSW sMOTSA
CAR 86.73 % 87.52 % 88.22 % 549 75.39 %
PEDESTRIAN 78.20 % 81.58 % 80.49 % 474 62.87 %

Benchmark MT rate PT rate ML rate FRAG
CAR 82.13 % 17.27 % 0.60 % 734
PEDESTRIAN 59.26 % 35.93 % 4.81 % 620

Benchmark # Dets # Tracks
CAR 34351 426
PEDESTRIAN 17793 275

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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