tld跟踪qt上opencv3运行例子

TLD === This is a C++ implementation of the Tracking-Learning-Detection (TLD) algorithm. using opencv2412 and visual studio 2012 in win7 x64 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**