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 |
71.09 % |
73.19 % |
69.63 % |
75.81 % |
86.95 % |
71.73 % |
90.06 % |
87.13 % |
PEDESTRIAN |
41.44 % |
43.54 % |
39.88 % |
47.98 % |
68.95 % |
43.47 % |
73.29 % |
78.27 % |
Benchmark |
TP |
FP |
FN |
CAR |
29751 |
4641 |
234 |
PEDESTRIAN |
14272 |
8878 |
1839 |
Benchmark |
MOTA |
MOTP |
MODA |
IDSW |
sMOTA |
CAR |
84.75 % |
85.77 % |
85.83 % |
369 |
72.44 % |
PEDESTRIAN |
51.43 % |
74.46 % |
53.71 % |
527 |
35.68 % |
Benchmark |
MT rate |
PT rate |
ML rate |
FRAG |
CAR |
66.61 % |
27.69 % |
5.69 % |
326 |
PEDESTRIAN |
32.30 % |
40.89 % |
26.80 % |
693 |
Benchmark |
# Dets |
# Tracks |
CAR |
29985 |
987 |
PEDESTRIAN |
16111 |
877 |
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.