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