对于尺度不变的特征提取，SURF 和 SIFT 是否有任何快速的替代方案? [英] Are there any fast alternatives to SURF and SIFT for scale-invariant feature extraction?

问题描述

SURF 已获得专利，SIFT 也是如此.ORB 和 Brief 没有专利，但它们的特性不是尺度不变的，严重限制了它们在复杂场景中的实用性.

SURF is patented, as is SIFT. ORB and BRIEF are not patented, but their features are not scale-invariant, seriously limiting their usefulness in complex scenarios.

是否有任何特征提取器可以像 SURF 一样快地提取尺度不变特征，并且没有像 SURF 和 SIFT 那样严格的专利?

Are there any feature extractors that can extract scale-invariant features as fast as SURF and are not so strictly patented as SURF and SIFT?

推荐答案

虽然您已经选择了 BRISK，但您可能会发现 FREAK 很有趣.作者声称比 BRISK 和 ORB 有更好的结果.我还应该补充一点，ORB 是 尺度不变的，但在该领域存在一些问题.所以我还是会推荐给别人试试.

Although you already choose BRISK, you might find FREAK interesting. Author claims to have better results than BRISK and ORB. I should also add that ORB is scale-invariant but has some problems in that area. So I would still recommend it for someone to try it.

FREAK 源代码 与 OpenCV 兼容(合并它们有​​多容易我不知道知道)并且作者正在努力将其提交给 OpenCV 项目.

The FREAK source code is compatible with OpenCV (how easy it is to merge them I do not know) and the author is working on submitting it to the OpenCV project.

FREAK 现在是 opencv 特征检测器/描述符的一部分.

您可以在这里阅读更多关于几种特征检测器/提取器之间的差异，以及一系列基准测试 其中包括 FREAK 和其他流行的.

You can read here more about the differences between several feature detectors/extractors, and also a series of benchmarks which includes FREAK and other popular ones.

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