SIFT has proved to be the most robust local invariant feature descriptor in object recognition and matching.

目前，SIFT已经被证明鲁棒性最好的局部不变特征描述符。

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Our descriptor is inspired from earlier ones such as SIFT and GLOH but can be computed much faster for our purposes.

我们的描述符的灵感来自较早的如SIFT和GLOH，但我们的目的，可以更快的计算。

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A technique to construct an affine invariant descriptor for remote-sensing image registration based on the scale invariant features transform (SIFT) in a kernel space is proposed.

针对遥感图像配准，基于尺度不变特征变换(SIFT)提出了一种在核空间中构建仿射不变描述子的方法。

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