中心仿射几何中的特征匹配与热流

arXiv: Differential Geometry Pub Date : 2020-03-30 DOI:10.3842/SIGMA.2020.093

P. Olver, C. Qu, Yun Yang

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引用次数: 4

摘要

本文研究了中心仿射几何中的微分不变量和不变量热流，证明了后者等价于无粘Burgers方程。此外，我们应用中心仿射不变量开发了一种不变量算法来匹配图像中出现的物体的特征。结果表明，该算法优于广泛应用的尺度不变特征变换(SIFT)、加速鲁棒特征变换(SURF)和仿射特征变换(ASIFT)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。

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Feature Matching and Heat Flow in Centro-Affine Geometry

In this paper, we study the differential invariants and the invariant heat flow in centro-affine geometry, proving that the latter is equivalent to the inviscid Burgers' equation. Furthermore, we apply the centro-affine invariants to develop an invariant algorithm to match features of objects appearing in images. We show that the resulting algorithm compares favorably with the widely applied Scale-Invariant Feature Transform (SIFT), Speeded Up Robust Features (SURF), and Affine-SIFT (ASIFT) methods.

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arXiv: Differential Geometry

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