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Week 8

Week 8. Students: Meera Hahn and Si Chen Mentor: Afshin Deghan. Cifar Network. 3 convolutional layer network Trained Caffe classifier using this network and our training images from the first frames of the video sequence

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Week 8

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  1. Week 8 Students: Meera Hahn and Si Chen Mentor: AfshinDeghan

  2. Cifar Network • 3 convolutional layer network • Trained Caffe classifier using this network and our training images from the first frames of the video sequence • Experimented with parameters such as number of training iterations, learning rate and number of training images

  3. Imagenet Network • 5 convolutional layers • This is the network we ran to train the offline Caffe tracker with Caffe’s given pre-trained weights which gave very high results • Trained Caffe classifier using this network and our training images from the first frames of the video sequence

  4. F Score Comparisons 45.14 77.01 75.57 62.84 61.24 56.28 • Running Offline Caffe Deep Tracking code on all 50 sequences • Fixed: processing greyscale images • Calculated STRUCK results from benchmark results

  5. Online Object Tracking: A Benchmark 1 Spatial Robustness Evaluation (SRE) Temporal Robustness Evaluation (TRE) Frames evaluated based on bounding box location • 8 spatial shifts of the ground truth = 12 total shifts Precision Plot Success Plot • Error in center location • Overlap in bounding boxes • Ratio of successful tracking 1 Yi Wu, Jongwoo Lim, and Ming-Hsuan Yang, “Online Object Tracking: A Benchmark,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.

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