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我正在尝试像全景视图一样在 android 中拼接图像。我正在尝试使用 surf 描述符来拼接图像。我正在使用 2.4.0 版本的 openCv，因为更高版本不包含用于 surf 描述符的非自由文件夹。我还包括

 #include "opencv2/nonfree/features2d.hpp"
 #include "opencv2/nonfree/nonfree.hpp"

在标题中，并 在包含所有.a文件的 GNU 路径中给出了路径..\jni\include和..\native\libs\armeabi-v7a 。 下面是我从 OpenCV 示例中获取的代码

 #include <stdio.h>
 #include <iostream>
 #include "opencv2/core/core.hpp"
 #include "opencv2/features2d/features2d.hpp"
 #include "opencv2/highgui/highgui.hpp"
 #include "opencv2/calib3d/calib3d.hpp"
 #include "opencv2/nonfree/features2d.hpp"
 #include "opencv2/nonfree/nonfree.hpp" 


 using namespace std;
 using namespace cv;

void readme();

 int main( int argc, char** argv )
{
 if( argc != 3 )
 { 
  readme(); return -1; 
 }

 Mat img_object = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
 Mat img_scene = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );

 if( !img_object.data || !img_scene.data )
 { std::cout<< " --(!) Error reading images " << std::endl; return -1; }

 //-- Step 1: Detect the keypoints using SURF Detector
 int minHessian = 400;

 SurfFeatureDetector detector(400); //error:undefined reference to cv::SURF::SURF(double, int, int, bool, bool)

 std::vector<KeyPoint> keypoints_object, keypoints_scene;

 detector.detect( img_object, keypoints_object );
 detector.detect( img_scene, keypoints_scene );

//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor; //error:undefined reference to cv::SURF::SURF()

Mat descriptors_object, descriptors_scene;

extractor.compute( img_object, keypoints_object, descriptors_object );
extractor.compute( img_scene, keypoints_scene, descriptors_scene );

//-- Step 3: Matching descriptor vectors using FLANN matcher
FlannBasedMatcher matcher;
std::vector< DMatch > matches;
matcher.match( descriptors_object, descriptors_scene, matches );

double max_dist = 0; double min_dist = 100;

//-- Quick calculation of max and min distances between keypoints

for( int i = 0; i < descriptors_object.rows; i++ )
{ double dist = matches[i].distance;
 if( dist < min_dist ) min_dist = dist;
  if( dist > max_dist ) max_dist = dist;}

printf("-- Max dist : %f \n", max_dist );
printf("-- Min dist : %f \n", min_dist );

 //-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
 std::vector< DMatch > good_matches;

 for( int i = 0; i < descriptors_object.rows; i++ )
 { if( matches[i].distance < 3*min_dist )
  { good_matches.push_back( matches[i]); }
  }

 Mat img_matches;
 drawMatches( img_object, keypoints_object, img_scene, keypoints_scene,
           good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
           vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );


  //-- Localize the object from img_1 in img_2
  std::vector<Point2f> obj;
  std::vector<Point2f> scene;

  for( size_t i = 0; i < good_matches.size(); i++ )
  {
  //-- Get the keypoints from the good matches
   obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );
   scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );
  }

 Mat H = findHomography( obj, scene, CV_RANSAC );

 //-- Get the corners from the image_1 ( the object to be "detected" )
  std::vector<Point2f> obj_corners(4);
  obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( img_object.cols, 0 );
  obj_corners[2] = cvPoint( img_object.cols, img_object.rows ); obj_corners[3] = cvPoint( 0, img_object.rows );
  std::vector<Point2f> scene_corners(4);

  perspectiveTransform( obj_corners, scene_corners, H);


 //-- Draw lines between the corners (the mapped object in the scene - image_2 )
 Point2f offset( (float)img_object.cols, 0);
 line( img_matches, scene_corners[0] + offset, scene_corners[1] + offset, Scalar(0, 255, 0), 4 );
 line( img_matches, scene_corners[1] + offset, scene_corners[2] + offset, Scalar( 0, 255, 0), 4 );
 line( img_matches, scene_corners[2] + offset, scene_corners[3] + offset, Scalar( 0, 255, 0), 4 );
 line( img_matches, scene_corners[3] + offset, scene_corners[0] + offset, Scalar( 0, 255, 0), 4 );

 //-- Show detected matches
 imshow( "Good Matches & Object detection", img_matches );

 waitKey(0);

 return 0;}

 /**
 * @function readme
 */
void readme()
{ std::cout << " Usage: ./SURF_Homography <img1> <img2>" << std::endl; }

我收到了 SurfFeatureDetector 和 SurfDescriptorExtractor 声明的错误。我在评论中写了错误。任何人对此有任何想法，然后请提出建议。我真的坚持这个问题。:(提前致谢。

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1 回答 1

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我知道我迟到了，但如果有人有同样的问题，这对我有用。在 Project Explorer 中选择您的项目。然后转到项目/属性。单击“C/C++ Build”选项左侧的箭头以显示其子列表。现在单击“设置”选项。它将显示在您的右侧“设置”面板。在此面板中，单击“工具设置”选项卡。在“设置”面板的左侧，您将看到另一个选项列表。单击“GCC C++ 链接器”箭头以显示/隐藏其子列表。在此子列表中单击“库”，面板将显示您的链接库（库（-l））和您的库搜索路径（库搜索路径（-L））。单击 (Libraries(-l)) 右上角带有加号的表示文档的按钮并写入 opencv_nonfree 。单击“确定”按钮，然后在“设置”面板中再次单击“确定”。祝你好运！

于 2014-11-28T14:13:00.333 回答