基于补丁的尺度计算视觉跟踪

Yulong Xu, Yafei Zhang, Jiabao Wang, Yang Li, Hang Li
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引用次数: 0

摘要

鲁棒尺度计算是视觉目标跟踪中一个具有挑战性的问题。大多数最先进的跟踪器无法处理复杂图像序列中的大规模变化。提出了一种检测跟踪框架下鲁棒尺度计算的新方法。该方法将目标分割为4个小块,通过核化相关滤波器找到每个小块的最大响应位置,从而计算尺度因子。在最近的基准评价中,对20个尺度变化的序列进行了实验。结果表明,我们的方法在实时操作时优于最先进的跟踪方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Patch-based scale calculation for visual tracking
Robust scale calculation is a challenging problem in visual object tracking. Most state-of-the-art trackers fail to handle large scale variations in complex image sequences. This paper propose a novel approach for robust scale calculation in a tracking-by-detection framework. The proposed approach divides the target into four patches and computes the scale factor by finding the maximum response position of each patch via kernelized correlation filter. Experiments are performed on 20 sequences with scale variations in the recent benchmark evaluation. And the results show that our method outperforms state-of-the-art tracking methods while operating in real-time.
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