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 |
71.61 % |
78.32 % |
65.98 % |
83.51 % |
87.42 % |
68.03 % |
92.61 % |
89.33 % |
PEDESTRIAN |
58.81 % |
67.96 % |
52.38 % |
71.86 % |
82.22 % |
54.40 % |
88.23 % |
84.18 % |
Benchmark |
TP |
FP |
FN |
CAR |
33858 |
2902 |
1255 |
PEDESTRIAN |
17657 |
3040 |
432 |
Benchmark |
MOTSA |
MOTSP |
MODSA |
IDSW |
sMOTSA |
CAR |
86.74 % |
88.25 % |
88.69 % |
716 |
75.92 % |
PEDESTRIAN |
81.33 % |
82.00 % |
83.22 % |
392 |
65.97 % |
Benchmark |
MT rate |
PT rate |
ML rate |
FRAG |
CAR |
84.53 % |
14.87 % |
0.60 % |
713 |
PEDESTRIAN |
62.59 % |
31.85 % |
5.56 % |
567 |
Benchmark |
# Dets |
# Tracks |
CAR |
35113 |
1804 |
PEDESTRIAN |
18089 |
743 |
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.