基于自适应重检测机制的多尺度相关滤波跟踪

2019 IEEE International Conference of Intelligent Applied Systems on Engineering (ICIASE) Pub Date : 2019-04-01 DOI:10.1109/ICIASE45644.2019.9074120

Ruoling Yang, Tingfa Xu, Yunru Bai, Axin Fan, Bo Yuan

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引用次数: 0

摘要

跟踪是人工智能领域的一个热门研究课题，但如何处理严重的遮挡和变形仍然是一个具有挑战性的问题。针对这一问题，我们提出了一种使用重检测模块的多尺度相关滤波跟踪器。具体来说，我们利用可靠置信度策略来估计初始结果的可靠性，并引入了一种新的模板匹配技术来解决目标重新定位问题。实验结果表明，该方法优于几种经典跟踪器。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multi-scale Correlation Filter Tracking with Adaptive Re-detection Mechanism

Tracking is a popular research topic in artificial intelligence, but how to handle the severe occlusion and deformation remains a challenging problem. Focusing on this issue, we propose a multi-scale correlation filter tracker using a re-detection module. Specifically, we utilize a reliable confidence strategy to estimate the reliability of initial results, and introduce a novel template matching technique to solve the target relocation problem. Experiment results demonstrate that our method can outperform several classic trackers.

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来源期刊

2019 IEEE International Conference of Intelligent Applied Systems on Engineering (ICIASE)

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