In visual object tracking, robust and accurate scale estimation of a target is a challenging task. Despite the associated computational expense, existing tracking methods cannot accommodate large scale variations. Here, we propose a scale searching scheme that obtains robust and accurate scale estimation by incorporating a novel and robust criterion, the average peak-to-correlation energy, into a multi-resolution translation filter framework. To address the problem of computational expense, we introduce an expeditious search strategy. The resulting system is named FAST: Fast and Accurate Scale estimation for Tracking. Comprehensive evaluation using the publicly available tracking benchmark datasets demonstrates that the proposed scale searching framework can accommodate large scale variation while also yielding computational efficiency.

中文翻译：

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FAST：用于跟踪的快速准确的尺度估计

在视觉对象跟踪中，目标的稳健且准确的尺度估计是一项具有挑战性的任务。尽管相关的计算费用，现有的跟踪方法不能适应大规模变化。在这里，我们提出了一种尺度搜索方案，该方案通过将一种新颖且稳健的标准（平均峰值相关能量）纳入多分辨率平移滤波器框架中，从而获得稳健而准确的尺度估计。为了解决计算开销的问题，我们引入了快速搜索策略。由此产生的系统被命名为 FAST：用于跟踪的快速和准确的尺度估计。使用公开可用的跟踪基准数据集进行的综合评估表明，所提出的尺度搜索框架可以适应大规模变化，同时也产生计算效率。