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 |
71.75 % |
73.16 % |
71.01 % |
75.78 % |
86.84 % |
73.04 % |
90.39 % |
86.97 % |
PEDESTRIAN |
41.42 % |
44.41 % |
39.03 % |
47.84 % |
71.82 % |
42.77 % |
72.94 % |
78.69 % |
Benchmark |
TP |
FP |
FN |
CAR |
29772 |
4620 |
239 |
PEDESTRIAN |
14217 |
8933 |
1202 |
Benchmark |
MOTA |
MOTP |
MODA |
IDSW |
sMOTA |
CAR |
84.86 % |
85.56 % |
85.87 % |
347 |
72.36 % |
PEDESTRIAN |
54.09 % |
74.81 % |
56.22 % |
493 |
38.62 % |
Benchmark |
MT rate |
PT rate |
ML rate |
FRAG |
CAR |
66.15 % |
27.54 % |
6.31 % |
317 |
PEDESTRIAN |
31.61 % |
40.55 % |
27.84 % |
681 |
Benchmark |
# Dets |
# Tracks |
CAR |
30011 |
963 |
PEDESTRIAN |
15419 |
761 |
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.