Deep Tracking: Visual Tracking Using Deep Convolutional Networks
نویسندگان
چکیده
In this paper, we study discriminatively trained deep convolutional networks for the task of visual tracking. Our tracker utilizes both motion and appearance features extracted from a pre-trained dual stream deep convolution network. By using optical flow and deep networks to implement a dual appearance and motion stream to inform tracking, our tracker outperforms current state of the art tracking methods on recent tracking benchmark data.
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عنوان ژورنال:
- CoRR
دوره abs/1512.03993 شماره
صفحات -
تاریخ انتشار 2015