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 |
82.08 % |
78.78 % |
86.21 % |
84.83 % |
83.98 % |
90.00 % |
89.84 % |
87.14 % |
| PEDESTRIAN |
57.15 % |
55.38 % |
59.67 % |
60.38 % |
70.63 % |
65.71 % |
71.80 % |
77.42 % |
| Benchmark |
TP |
FP |
FN |
| CAR |
33326 |
1066 |
1414 |
| PEDESTRIAN |
18377 |
4773 |
1413 |
| Benchmark |
MOTA |
MOTP |
MODA |
IDSW |
sMOTA |
| CAR |
92.75 % |
85.61 % |
92.79 % |
12 |
78.81 % |
| PEDESTRIAN |
72.20 % |
72.98 % |
73.28 % |
250 |
50.75 % |
| Benchmark |
MT rate |
PT rate |
ML rate |
FRAG |
| CAR |
90.15 % |
4.46 % |
5.38 % |
64 |
| PEDESTRIAN |
52.58 % |
36.77 % |
10.65 % |
593 |
| Benchmark |
# Dets |
# Tracks |
| CAR |
34740 |
649 |
| PEDESTRIAN |
19790 |
329 |
This table as LaTeX
|
[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.
