Benchmark:
MOT16 |
Short name:
PHD_GSDL16
Detector:
Public
Description:
n/a
Reference:
Z. Fu, P. Feng, F. Angelini, J. Chambers, S. Naqvi. Particle PHD Filter based Multiple Human Tracking using Online Group-Structured Dictionary Learning. In IEEE Access, 2018.
Last submitted:
January 24, 2019 (5 years ago)
Published:
February 07, 2019 at 12:11:28 CET
Submissions:
1
Project page / code:
n/a
Open source:
No
Hardware:
3.5GHz, 1 Core
Runtime:
8.3 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 | 41.0 | 43.1 | 33.1 | 86 (11.3) | 315 (41.5) | 6,498 | 99,257 | 45.6 | 92.7 | 32.6 | 33.8 | 35.6 | 69.4 | 35.7 | 72.7 | 79.1 | 1.1 | 1,810 (39.7) | 3,650 (80.1) |
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 | 28.6 | 37.8 | 28.3 | 2 | 9 | 246 | 4,255 | 33.5 | 89.7 | 33.7 | 23.8 | 36.7 | 67.1 | 25.1 | 67.4 | 76.9 | 0.5 | 63 | 149 |
| MOT16-03 | 48.2 | 45.2 | 34.6 | 23 | 34 | 2,456 | 51,186 | 51.0 | 95.6 | 31.6 | 38.2 | 33.9 | 67.8 | 40.0 | 74.8 | 79.3 | 1.6 | 559 | 1,896 |
| MOT16-06 | 44.8 | 52.4 | 38.6 | 28 | 95 | 429 | 5,700 | 50.6 | 93.2 | 41.3 | 36.4 | 51.7 | 65.1 | 38.5 | 70.9 | 77.5 | 0.4 | 235 | 314 |
| MOT16-07 | 35.5 | 41.9 | 30.9 | 5 | 18 | 819 | 9,467 | 42.0 | 89.3 | 31.6 | 30.6 | 33.4 | 74.5 | 32.5 | 69.2 | 77.5 | 1.6 | 248 | 477 |
| MOT16-08 | 29.4 | 34.3 | 29.3 | 6 | 27 | 450 | 11,203 | 33.1 | 92.5 | 32.6 | 26.3 | 34.7 | 77.3 | 27.4 | 76.7 | 82.4 | 0.7 | 168 | 231 |
| MOT16-12 | 34.9 | 48.1 | 38.3 | 14 | 37 | 997 | 4,329 | 47.8 | 79.9 | 43.7 | 33.6 | 49.2 | 69.5 | 38.2 | 63.9 | 79.7 | 1.1 | 78 | 117 |
| MOT16-14 | 20.6 | 31.8 | 23.3 | 8 | 95 | 1,101 | 13,117 | 29.0 | 83.0 | 25.5 | 21.5 | 27.2 | 72.0 | 22.9 | 65.4 | 77.6 | 1.5 | 459 | 466 |
Raw data: