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 |
83.04 % |
79.87 % |
87.15 % |
85.17 % |
85.65 % |
89.91 % |
91.74 % |
87.99 % |
PEDESTRIAN |
46.82 % |
41.26 % |
53.40 % |
45.69 % |
58.80 % |
57.45 % |
65.12 % |
71.29 % |
Benchmark |
TP |
FP |
FN |
CAR |
33032 |
1360 |
1168 |
PEDESTRIAN |
14733 |
8417 |
3256 |
Benchmark |
MOTA |
MOTP |
MODA |
IDSW |
sMOTA |
CAR |
92.62 % |
86.70 % |
92.65 % |
10 |
79.85 % |
PEDESTRIAN |
49.16 % |
64.52 % |
49.58 % |
96 |
26.58 % |
Benchmark |
MT rate |
PT rate |
ML rate |
FRAG |
CAR |
87.85 % |
8.46 % |
3.69 % |
52 |
PEDESTRIAN |
30.58 % |
35.05 % |
34.36 % |
984 |
Benchmark |
# Dets |
# Tracks |
CAR |
34200 |
669 |
PEDESTRIAN |
17989 |
231 |
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.