TLD
TLD copied to clipboard
Published
20 hours ago •
y-x-c
y-x-c
C++ implementation of the Tracking-Learning-Detection (TLD) algorithm by Yuxin Chen
TLD
This is a C++ implementation of the Tracking-Learning-Detection (TLD) algorithm.
The code is functional right now, but not stable, i.e. little changes of parameters will lead the result turning worse.
Following is the performance evaluation on TLD dataset measured by Precision / Recall / F-measure.
| Sequence | Frames | OpenTLD(MatLab) | My implementation(404dd93302) |
|---|---|---|---|
| 1.David | 761 | 1.00 / 1.00 / 1.00 | 0.968379 / 0.968379 / 0.968379 |
| 2.Jumping | 313 | 1.00 / 1.00 / 1.00 | 1.000000 / 0.990385 / 0.995169 |
| 3.Pedestrian 1 | 140 | 1.00 / 1.00 / 1.00 | 1.000000 / 0.992806 / 0.996390 |
| 4.Pedestrian 2 | 338 | 0.89 / 0.92 / 0.91 | 0.842857 / 0.445283 / 0.582716 |
| 5.Pedestrian 3 | 184 | 0.99 / 1.00 / 0.99 | 0.987097 / 1.000000 / 0.993506 |
| 6.Car | 945 | 0.92 / 0.97 / 0.94 | 0.928339 / 0.996503 / 0.961214 |
| 7.Motocross | 2665 | 0.89 / 0.77 / 0.83 | 0.821918 / 0.849858 / 0.835655 |
| 8.Volkswagen | 8576 | 0.80 / 0.96 / 0.87 | 0.834528 / 0.997275 / 0.908672 |
| 9.Carchase | 9928 | 0.86 / 0.70 / 0.77 | 0.798744 / 0.646189 / 0.714413 |
| 10.Panda | 3000 | 0.58 / 0.63 / 0.60 | 0.630420 / 0.692561 / 0.660031 |
y-x-c