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 |
74.09 % |
75.86 % |
72.99 % |
78.59 % |
87.36 % |
75.20 % |
90.90 % |
87.44 % |
PEDESTRIAN |
42.38 % |
46.82 % |
38.73 % |
51.16 % |
71.41 % |
42.30 % |
72.91 % |
79.26 % |
Benchmark |
TP |
FP |
FN |
CAR |
30683 |
3709 |
254 |
PEDESTRIAN |
15116 |
8034 |
1468 |
Benchmark |
MOTA |
MOTP |
MODA |
IDSW |
sMOTA |
CAR |
87.44 % |
86.08 % |
88.48 % |
357 |
75.02 % |
PEDESTRIAN |
56.55 % |
75.48 % |
58.95 % |
557 |
40.54 % |
Benchmark |
MT rate |
PT rate |
ML rate |
FRAG |
CAR |
75.69 % |
20.46 % |
3.85 % |
335 |
PEDESTRIAN |
36.77 % |
42.27 % |
20.96 % |
724 |
Benchmark |
# Dets |
# Tracks |
CAR |
30937 |
991 |
PEDESTRIAN |
16584 |
818 |
This table as LaTeX
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[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.