尺度插值Hessian-Laplace和Haar描述子在特征匹配中的性能评价

Akshay Bhatia, R. Laganière, G. Roth
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引用次数: 4

摘要

本文研究了各种尺度不变检测器在特征匹配中的性能。特别地,我们提出了一种我们称之为尺度插值的黑森-拉普拉斯算子的实现。本研究还提出了利用Haar小波变换得到的Haar描述子。与其他描述符相比,它的优点是计算成本低,尺寸更小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Evaluation of Scale-Interpolated Hessian-Laplace and Haar Descriptors for Feature Matching
This paper studies the performance of various scale- invariant detectors in the context of feature matching. In particular, we propose an implementation of the Hessian-Laplace operator that we called scale-interpolated Hessian-Laplace. This research also proposes to use Haar descriptors which are derived from the Haar wavelet transform. It offers the advantage of being computationally inexpensive and smaller in size when compared to other descriptors.
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