Abstract In the DCF framework, a crucial component except DCF trackers is the adopted feature map, especially when we need the tracker to be applied in practical. The powerful feature map from CNN achieves an outstanding performance when compared to the handcrafted feature (HOG, Color-Name), however, it makes the tracker slower and could not meet the need in the real-time scene. In this paper, we visualize the respective feature maps, filter, and location score from CNN, HOG and ColorName, to make a comparison. We also dig into the detail of the target label, for balance the accuracy and robustness of the tracker. Experiments on OTB-2015 show the performance loss from handcrafted feature is acceptable for the real-time application.

中文翻译：

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DCF 对象跟踪器中的 CNN 功能或手工制作的功能？

摘要 在 DCF 框架中，除了 DCF 跟踪器之外的一个关键组件是采用的特征图，特别是当我们需要将跟踪器应用于实际时。CNN 强大的特征图与手工制作的特征（HOG，Color-Name）相比，表现出众，但跟踪速度较慢，无法满足实时场景的需要。在本文中，我们将来自 CNN、HOG 和 ColorName 的各自特征图、过滤器和位置分数可视化，以进行比较。我们还深入研究了目标标签的细节，以平衡跟踪器的准确性和鲁棒性。OTB-2015 上的实验表明，实时应用程序可以接受手工特征的性能损失。