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Deep Tracking: Visual Tracking Using Deep Convolutional Networks

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 نشر من قبل Meera Hahn
 تاريخ النشر 2015
  مجال البحث الهندسة المعلوماتية
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In this paper, we study a discriminatively trained deep convolutional network for the task of visual tracking. Our tracker utilizes both motion and appearance features that are extracted from a pre-trained dual stream deep convolution network. We show that the features extracted from our dual-stream network can provide rich information about the target and this leads to competitive performance against state of the art tracking methods on a visual tracking benchmark.



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