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 |
76.59 % |
76.27 % |
77.47 % |
79.59 % |
86.30 % |
80.95 % |
87.70 % |
86.97 % |
PEDESTRIAN |
50.73 % |
50.78 % |
50.94 % |
54.80 % |
72.28 % |
58.02 % |
65.85 % |
78.39 % |
Benchmark |
TP |
FP |
FN |
CAR |
31253 |
3139 |
468 |
PEDESTRIAN |
16482 |
6668 |
1070 |
Benchmark |
MOTA |
MOTP |
MODA |
IDSW |
sMOTA |
CAR |
89.03 % |
85.56 % |
89.51 % |
164 |
75.92 % |
PEDESTRIAN |
65.65 % |
74.59 % |
66.58 % |
214 |
47.56 % |
Benchmark |
MT rate |
PT rate |
ML rate |
FRAG |
CAR |
78.31 % |
18.92 % |
2.77 % |
159 |
PEDESTRIAN |
41.24 % |
35.74 % |
23.02 % |
566 |
Benchmark |
# Dets |
# Tracks |
CAR |
31721 |
682 |
PEDESTRIAN |
17552 |
281 |
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.