Short name:
GMPHD_DAL
Benchmark:
Description:
n/a
Hardware:
3 GHZ, 1 Core
Detector:
Public
Processing:
Online
Last submitted:
March 17, 2019 (8 months ago)
Published:
March 18, 2019 at 00:02:01 CET
Submissions:
3
Open source:
No
Project page / code:
n/a
Reference:
N. Baisa. Online Multi-object Visual Tracking using a GM-PHD Filter with Deep Appearance Learning. In 22nd International Conference on Information Fusion, 2019.
Benchmark performance:
MOTA | MOTP | FAF | MT | ML | FP | FN | ID Sw. | Frag | Specifications | Detector |
44.4 | 77.4 | 1.1 | 14.9 % | 39.4 % | 19,170 | 283,380 | 11,137 | 13,900 | 3 GHZ, 1 Core | Public |
IDF1 | ID Precision | ID Recall |
36.2 | 52.2 | 27.7 |
Detailed performance:
Sequence | MOTA | IDF1 | MOTP | FAF | GT | MT | ML | FP | FN | ID Sw | Frag |
MOT17-01-DPM | 21.8 | 19.5 | 73.6 | 0.1 | 24 | 8.3 % | 58.3 % | 63 | 4,873 | 107 | 170 |
MOT17-03-DPM | 40.9 | 27.4 | 76.9 | 0.7 | 148 | 8.1 % | 29.7 % | 1,000 | 58,458 | 2,395 | 3,122 |
MOT17-06-DPM | 39.4 | 36.1 | 74.3 | 0.1 | 222 | 8.1 % | 52.3 % | 122 | 6,700 | 314 | 372 |
MOT17-07-DPM | 28.5 | 23.2 | 75.0 | 0.7 | 60 | 6.7 % | 53.3 % | 325 | 11,274 | 472 | 641 |
MOT17-08-DPM | 23.0 | 21.4 | 80.3 | 0.3 | 76 | 6.6 % | 55.3 % | 199 | 15,847 | 229 | 310 |
MOT17-12-DPM | 35.8 | 34.2 | 77.7 | 0.2 | 91 | 8.8 % | 52.7 % | 201 | 5,202 | 157 | 232 |
MOT17-14-DPM | 14.2 | 15.6 | 75.6 | 0.4 | 164 | 2.4 % | 74.4 % | 271 | 15,213 | 378 | 498 |
MOT17-01-FRCNN | 25.6 | 32.5 | 76.7 | 3.3 | 24 | 25.0 % | 33.3 % | 1,470 | 3,267 | 63 | 79 |
MOT17-03-FRCNN | 56.5 | 46.2 | 78.0 | 1.1 | 148 | 23.0 % | 18.2 % | 1,697 | 43,147 | 699 | 1,094 |
MOT17-06-FRCNN | 51.0 | 41.1 | 77.8 | 0.5 | 222 | 21.6 % | 27.0 % | 610 | 4,758 | 406 | 340 |
MOT17-07-FRCNN | 31.2 | 30.0 | 74.8 | 3.1 | 60 | 10.0 % | 25.0 % | 1,526 | 9,624 | 473 | 531 |
MOT17-08-FRCNN | 22.0 | 27.5 | 80.1 | 1.4 | 76 | 9.2 % | 51.3 % | 863 | 15,466 | 150 | 200 |
MOT17-12-FRCNN | 35.1 | 46.2 | 78.4 | 0.8 | 91 | 13.2 % | 47.3 % | 717 | 4,817 | 94 | 160 |
MOT17-14-FRCNN | 15.3 | 25.4 | 71.5 | 4.0 | 164 | 6.1 % | 46.3 % | 2,965 | 11,987 | 708 | 740 |
MOT17-01-SDP | 37.0 | 27.7 | 74.7 | 2.4 | 24 | 29.2 % | 20.8 % | 1,066 | 2,765 | 234 | 249 |
MOT17-03-SDP | 70.4 | 48.0 | 78.6 | 0.8 | 148 | 43.9 % | 10.8 % | 1,145 | 28,044 | 1,773 | 2,503 |
MOT17-06-SDP | 53.7 | 44.7 | 76.4 | 0.5 | 222 | 25.2 % | 30.2 % | 615 | 4,465 | 377 | 328 |
MOT17-07-SDP | 42.8 | 29.7 | 76.4 | 1.9 | 60 | 18.3 % | 28.3 % | 948 | 8,141 | 581 | 626 |
MOT17-08-SDP | 27.3 | 25.1 | 79.5 | 1.0 | 76 | 10.5 % | 44.7 % | 600 | 14,326 | 433 | 535 |
MOT17-12-SDP | 38.0 | 39.5 | 79.4 | 0.9 | 91 | 18.7 % | 44.0 % | 765 | 4,407 | 203 | 286 |
MOT17-14-SDP | 27.0 | 27.1 | 73.2 | 2.7 | 164 | 6.1 % | 37.8 % | 2,002 | 10,599 | 891 | 884 |
Raw data:
n/a