如何在opencv中使用SIFT [英] how to use SIFT in opencv

问题描述

我现在正在学习C ++和OpenCV。给定图像，我想提取其SIFT特征。从的示例

  #include< opencv2 / core / core.hpp> 
 #include< opencv2 / highgui / highgui.hpp> 
 #include< opencv2 / nonfree / features2d.hpp> //感谢Alessandro 
 
 int main（int argc，const char * argv []）
 {
 const cv :: Mat input = cv :: imread（input。 jpg，0）; // Load as grayscale 
 
 cv :: SiftFeatureDetector检测器; 
 std :: vector< cv :: KeyPoint>关键点; 
 detector.detect（input，keypoints）; 
 
 //将结果添加到图像并保存。 
 cv :: Mat output; 
 cv :: drawKeypoints（input，keypoints，output）; 
 cv :: imwrite（sift_result.jpg，output）; 
 
 return 0; 
} 
  

在OpenCV 2.4.8上测试

I am learning C++ and OpenCV these days. Given an image, I want to extract its SIFT features. From http://docs.opencv.org/modules/nonfree/doc/feature_detection.html, we can know that OpenCV 2.4.8 has the SIFT module. See here:

But I do not know how to use it. Currently, to use SIFT, I need to first call the class SIFT to get a SIFT instance. Then, I need to use SIFT::operator()() to do SIFT.

But what is OutputArray , InputArray, KeyPoint? Could anyone give a demo to show how to use SIFT class to do SIFT?

解决方案

See the example from Sift implementation with OpenCV 2.2

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/nonfree/features2d.hpp> //Thanks to Alessandro

int main(int argc, const char* argv[])
{
    const cv::Mat input = cv::imread("input.jpg", 0); //Load as grayscale

    cv::SiftFeatureDetector detector;
    std::vector<cv::KeyPoint> keypoints;
    detector.detect(input, keypoints);

    // Add results to image and save.
    cv::Mat output;
    cv::drawKeypoints(input, keypoints, output);
    cv::imwrite("sift_result.jpg", output);

    return 0;
}

Tested on OpenCV 2.4.8

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