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Week 7: Deep Tracking
Students: Si Chen & Meera HahnMentor: Afshin Deghan
F Score Comparisons
Video Names
Autoencoder + SVM
Fully Connected Network
Offline CAFFE Deep
TrackerSTRUCK
Bike 46.09 76.52 96.52 89.47
David 79.13 98.26 98.26 84.52
Deer 98.59 9.86 85.92 97.14
Ironman 18.26 9.57 3.48 3.61
Shaking 70.43 75.65 76.52 37.53
Skiing 49.38 46.91 49.38 6.17
Subway 92.17 26.09 81.74 78.86
Tiger 48.70 18.26 84.35 80.23
Average 62.84 45.14 72.02 59.69
Offline Caffe Deep Tracking
Ran offline code on all 50 sequences
Fixed code:Problem with LibSVMProcessing greyscale images
Next steps: calculate fscores
CAFFE
• Trained models into tracker
• Changed python paths
• How well does the tracker preform in comparison to using pre-trained weights?
Next steps• Fine tuning Caffe
• Learning additional attributes of videos:• Motion: provide temporal data to the
network so it can learn the motion• Scale change