TREAT: Terse Rapid Edge-Anchored Tracklets

Rémi Trichet, N. O’Connor
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Abstract

Fast computation, efficient memory storage, and performance on par with standard state-of-the-art descriptors make binary descriptors a convenient tool for many computer vision applications. However their development is mostly tailored for static images. To respond to this limitation, we introduce TREAT (Terse Rapid Edge-Anchored Tracklets), a new binary detector and descriptor, based on tracklets. It harnesses moving edge maps to perform efficient feature detection, tracking, and description at low computational cost. Experimental results on 3 different public datasets demonstrate improved performance over other popular binary features. These experiments also provide a basis for benchmarking the performance of binary descriptors in video-based applications.
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治疗:简洁快速边缘锚定轨迹
快速的计算、高效的内存存储以及与最先进的标准描述符相当的性能使二进制描述符成为许多计算机视觉应用程序的方便工具。然而,它们的开发主要针对静态图像。为了应对这一限制,我们引入了一种新的基于Tracklets的二进制检测器和描述符TREAT(简捷快速边缘锚边Tracklets)。它利用移动边缘映射以低计算成本执行有效的特征检测、跟踪和描述。在3个不同的公共数据集上的实验结果表明,与其他流行的二进制特征相比,性能有所提高。这些实验也为在基于视频的应用中对二进制描述符的性能进行基准测试提供了基础。
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