Benchmark:
MOT15 |
Short name:
ALExTRAC
Detector:
Public
Description:
Appearance only tracking through the use of a self-supervised affinity model.
Reference:
A. Bewley, L. Ott, F. Ramos, B. Upcroft. ALExTRAC: Affinity Learning by Exploring Temporal Reinforcement within Association Chains. In International Conference on Robotics and Automation (ICRA), (to appear) 2016.
Last submitted:
September 12, 2015 (9 years ago)
Published:
February 16, 2016 at 04:03:23 CET
Submissions:
1
Project page / code:
Open source:
No
Hardware:
2.5 GHz, 4 cores
Runtime:
3.7 Hz
Benchmark performance:
Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
MOT15 | 17.0 | 17.3 | 0.0 | 28 (3.9) | 378 (52.4) | 9,233 | 39,933 | 35.0 | 70.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 1.6 | 1,859 (53.1) | 1,872 (53.5) |
Detailed performance:
Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
ADL-Rundle-1 | 5.1 | 13.5 | 0.0 | 5 | 7 | 3,503 | 5,010 | 46.2 | 55.1 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 7.0 | 321 | 306 |
ADL-Rundle-3 | 18.1 | 16.4 | 0.0 | 3 | 10 | 2,420 | 5,523 | 45.7 | 65.7 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 3.9 | 385 | 261 |
AVG-TownCentre | 13.3 | 21.3 | 0.0 | 3 | 138 | 442 | 5,637 | 21.1 | 77.4 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 1.0 | 118 | 152 |
ETH-Crossing | 19.6 | 23.1 | 0.0 | 2 | 17 | 13 | 783 | 21.9 | 94.4 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 0.1 | 10 | 10 |
ETH-Jelmoli | 32.9 | 33.0 | 0.0 | 6 | 13 | 283 | 1,334 | 47.4 | 81.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 0.6 | 86 | 98 |
ETH-Linthescher | 15.4 | 17.8 | 0.0 | 3 | 150 | 94 | 7,369 | 17.5 | 94.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 0.1 | 90 | 103 |
KITTI-16 | 13.9 | 12.8 | 0.0 | 0 | 4 | 105 | 1,279 | 24.8 | 80.1 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 0.5 | 80 | 73 |
KITTI-19 | 13.5 | 21.0 | 0.0 | 4 | 19 | 1,128 | 3,266 | 38.9 | 64.8 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 1.1 | 227 | 326 |
PETS09-S2L2 | 27.5 | 12.9 | 0.0 | 0 | 11 | 449 | 6,153 | 36.2 | 88.6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 1.0 | 385 | 359 |
TUD-Crossing | 51.2 | 41.0 | 0.0 | 2 | 2 | 39 | 459 | 58.3 | 94.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 0.2 | 40 | 50 |
Venice-1 | 12.5 | 12.2 | 0.0 | 0 | 7 | 757 | 3,120 | 31.6 | 65.6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 100.0 | 1.7 | 117 | 134 |
Raw data: