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 |
74.39 % |
75.27 % |
74.16 % |
78.77 % |
86.42 % |
76.24 % |
91.05 % |
87.17 % |
PEDESTRIAN |
39.38 % |
40.60 % |
38.72 % |
43.43 % |
61.49 % |
40.98 % |
68.33 % |
71.25 % |
Benchmark |
TP |
FP |
FN |
CAR |
30895 |
3497 |
454 |
PEDESTRIAN |
14191 |
8959 |
2161 |
Benchmark |
MOTA |
MOTP |
MODA |
IDSW |
sMOTA |
CAR |
87.82 % |
85.69 % |
88.51 % |
239 |
74.97 % |
PEDESTRIAN |
49.82 % |
64.42 % |
51.97 % |
496 |
28.01 % |
Benchmark |
MT rate |
PT rate |
ML rate |
FRAG |
CAR |
76.15 % |
21.39 % |
2.46 % |
390 |
PEDESTRIAN |
27.49 % |
48.45 % |
24.05 % |
1410 |
Benchmark |
# Dets |
# Tracks |
CAR |
31349 |
922 |
PEDESTRIAN |
16352 |
724 |
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.