1 / 5

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

kylar
Télécharger la présentation

Week 8

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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.

More Related