CS_MOT: A Cost Matrix Optimization Method Based on Spatial Constraints under Hungarian Algorithm
MOT16-01
Short name:
CS_MOT
Detector:
Public
Description:
Reference:
A Cost Matrix Optimization Method Based on Spatial Constraints under Hungarian Algorithm
Last submitted:
July 13, 2020 (1 year ago)
Published:
July 18, 2020 at 08:26:19 CET
Submissions:
1
Project page / code:
n/a
Open source:
No
Hardware:
Tesla P100
Runtime:
1.2 Hz
Benchmark performance:
| Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
| MOT16 | 46.7 | 51.5 | 37.6 | 76 (10.0) | 332 (43.7) | 5,941 | 90,566 | 50.3 | 93.9 | 39.0 | 36.7 | 41.6 | 72.9 | 38.6 | 72.1 | 77.9 | 1.0 | 619 (12.3) | 2,981 (59.2) |
Detailed performance:
| Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
| MOT16-01 | 30.1 | 27.7 | 22.9 | 2 | 11 | 150 | 4,284 | 33.0 | 93.4 | 22.2 | 23.7 | 25.0 | 60.4 | 24.6 | 69.6 | 76.5 | 0.3 | 36 | 145 |
| MOT16-03 | 56.7 | 59.2 | 42.3 | 34 | 26 | 2,689 | 42,454 | 59.4 | 95.8 | 41.6 | 43.2 | 44.0 | 74.4 | 45.5 | 73.4 | 78.2 | 1.8 | 157 | 1,485 |
| MOT16-06 | 36.2 | 42.0 | 31.1 | 10 | 118 | 381 | 6,909 | 40.1 | 92.4 | 33.6 | 29.0 | 39.6 | 65.3 | 30.4 | 70.0 | 76.8 | 0.3 | 77 | 271 |
| MOT16-07 | 41.4 | 41.2 | 31.2 | 6 | 18 | 926 | 8,509 | 47.9 | 89.4 | 28.8 | 34.2 | 30.8 | 69.0 | 36.3 | 67.8 | 75.7 | 1.9 | 133 | 407 |
| MOT16-08 | 37.7 | 44.7 | 34.2 | 11 | 22 | 523 | 9,826 | 41.3 | 93.0 | 37.4 | 31.4 | 40.5 | 73.2 | 33.0 | 74.3 | 80.0 | 0.8 | 86 | 268 |
| MOT16-12 | 39.7 | 53.8 | 40.6 | 9 | 40 | 425 | 4,545 | 45.2 | 89.8 | 48.6 | 33.9 | 51.8 | 74.8 | 36.3 | 72.1 | 80.4 | 0.5 | 29 | 90 |
| MOT16-14 | 18.9 | 28.5 | 20.3 | 4 | 97 | 847 | 14,039 | 24.0 | 84.0 | 24.2 | 17.3 | 26.1 | 63.9 | 18.1 | 63.2 | 74.7 | 1.1 | 101 | 315 |
Raw data:
