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问题描述

我想开始使用(C ++)OpenCv进行sift特征提取。我需要使用SIFT提取特征,在原始图像(例如书)和场景之间进行匹配,然后计算相机姿态。

I'm trying to get started working with sift feature extraction using (C++) OpenCv. I need to extract features using SIFT, match them between the original image (e.g. a book) and a scene, and after that calculate the camera pose.

到目前为止,使用SURF找到。有没有人知道一个基本代码,从我可以开始,或者可能是一个方法来转换从SURF到SIFT的链接?

So far I have found this algorithm using SURF. Does anyone know a base code from which I can get started, or maybe a way to convert the algorithm in the link from SURF to SIFT?

提前感谢。

编辑:
好​​,我为筛选问题制定了解决方案。现在我试图计算相机的姿势。我试图使用:solvePnP,任何人都可以帮助我一个例子?

Ok, I worked out a solution for the sift problem. Now I'm trying to figure the camera pose. I'm trying to use: solvePnP, can anyone help me with an example?

推荐答案

查看。
有以下代码的教程:

Check out the feature2d tutorial section of the new OpenCV docs website.There tutorials with code showing:


  1. SURF



  1. Feature detection with e.g. SURF
  2. Feature Description
  3. Feature Matching

这篇关于筛选提取 - opencv的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!

08-04 22:36
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