使用estimateRigidTransform而不是findHomography [英] Using estimateRigidTransform instead of findHomography

问题描述

下面的链接中的示例是使用 findHomography 获得两组点之间的变换。我想限制转换中使用的自由度，因此要用 estimateRigidTransform 替换 findHomography 。

http： //docs.opencv.org/doc/tutorials/features2d/feature_homography/feature_homography.html#featurehography

下面我使用 estimateRigidTransform 以获得对象和场景点之间的变换。 objPoints 和 scePoints 表示为 vector< Point2f> 。

  Mat H = estimateRigidTransform（objPoints，scePoints，false）;按照上面的教程中使用的方法，我想使用转换<$的方式转换角点值。
  

c $ c> H 。本教程使用 findHomography 返回的3x3矩阵使用 perspectiveTransform 。使用刚体变换只返回一个2x3矩阵，所以这个方法不能使用。

我如何变换角的值，表示为 vector2< Point2f> 。我只是希望执行与教程相同的功能，但具有较少的自由度的变换。我已经看过其他方法，如 warpAffine 和 getPerspectiveTransform 以及，但到目前为止没有找到解决方案。 p>

编辑：

我试过David Nilosek的建议。下面我向矩阵添加额外的行。

  Mat row =（Mat_< double>（1,3） < 0,0,1）; 
 H.push_back（row）; 
  

但是，当使用透视变换时会出现此错误。

  OpenCV Error：Assertion failed（mtype == type0 ||（CV_MAT_CN（mtype）== CV_MAT_CN（type0）&&（（1<< type0）& fixedDepthMask）！= 0））in create，file /Users/cgray/Downloads/opencv-2.4.6/modules/core/src/matrix.cpp，第1486行
 libc ++ abi.dylib：以uncaught结束异常类型cv ::异常：/Users/cgray/Downloads/opencv-2.4.6/modules/core/src/matrix.cpp:1486：error：（-215）mtype == type0 ||在函数中创建（CV_MAT_CN（mtype）== CV_MAT_CN（type0）&&（（1<< type0）& fixedDepthMask）！= 0）
  

ChronoTrigger建议使用 warpAffine 。我在下面调用 warpAffine 方法，1 x 5的大小是 objCorners 和 sceCorners 。

  warpAffine（objCorners，sceCorners，H，Size（1,4））; 
  

这会产生下面的错误，这表明类型错误。 objCorners 和 sceCorners 是向量< Point2f> 4个角。我认为 warpAffine 会接受 Mat 图片，可能会解释错误。

  OpenCV错误：断言失败（（M0.type（）== CV_32F || M0.type（）== CV_64F）&& M0.rows == 2& ;& M0.cols == 3）in warpAffine，file /Users/cgray/Downloads/opencv-2.4.6/modules/imgproc/src/imgwarp.cpp，line 3280 
  
 
 
解决方案
过去这样做：
  cv :: Mat R = cv :: estimateRigidTransform（p1，p2，false）; 
 
 if（R.cols == 0）
 {
 continue; 
} 
 
 cv :: Mat H = cv :: Mat（3,3，R.type（））; 
 H.at< double>（0,0）= R.at double（0,0）; 
 H.at< double>（0,1）= R.at double（0,1）; 
 H.at< double>（0,2）= R.at double（0,2）; 
 
 H.at< double>（1,0）= R.at double（1,0）; 
 H.at< double>（1,1）= R.at double（1,1）; 
 H.at< double>（1,2）= R.at double（1,2）; 
 
 H.at< double>（2,0）= 0.0; 
 H.at< double>（2,1）= 0.0; 
 H.at&Double;（2,2）= 1.0; 
 
 
 cv :: Mat warped; 
 cv :: warpPerspective（img1，warped，H，img1.size（））; 
  
与David Nilosek建议的相同：在矩阵的末尾添加一个0 0 1行
 
 
 
此代码通过刚性变换扭曲IMAGES。
 
 
 
我想要扭曲/您必须使用具有3x3矩阵的 perspectiveTransform 函数（ http://docs.opencv.org/modules/core/doc/operations_on_arrays.html?highlight=perspectivetransform#perspectivetransform ）
 
 
 
教程：
 
 
 
  http://docs.opencv.org/doc/tutorials/features2d/feature_homography/feature_homography.html  
 
 
 
或您可以它通过循环您的向量和
手动。
  cv :: Point2f result; 
 result.x = point.x * R.at double（0,0）+ point.y * R.at double（0,1）+ R.at double（0,2） ）; 
 result.y = point.x * R.at< double>（1,0）+ point.y * R.at double（1,1）+ R.at double ）; 
  
希望有所帮助。
 
 
 
没有测试手工代码，而是应该工作。 
 
 
 
编辑：这是完整的（测试过的）代码：
  // points 
 std :: vector< cv :: Point2f> p1; 
 p1.push_back（cv :: Point2f（0,0））; 
 p1.push_back（cv :: Point2f（1,0））; 
 p1.push_back（cv :: Point2f（0,1））; 
 
 //从p1进行简单转换以进行测试：
 std :: vector< cv :: Point2f> p2; 
 p2.push_back（cv :: Point2f（1,1））; 
 p2.push_back（cv :: Point2f（2,1））; 
 p2.push_back（cv :: Point2f（1,2））; 
 
 cv :: Mat R = cv :: estimateRigidTransform（p1，p2，false）; 
 
 //扩展刚性变换以使用透视变换：
 cv :: Mat H = cv :: Mat（3,3，R.type（））; 
 H.at< double>（0,0）= R.at double（0,0） 
 H.at< double>（0,1）= R.at double（0,1）; 
 H.at< double>（0,2）= R.at double（0,2） 
 
 H.at< double>（1,0）= R.at double（1,0）; 
 H.at< double>（1,1）= R.at double（1,1）; 
 H.at< double>（1,2）= R.at double（1,2）; 
 
 H.at< double>（2,0）= 0.0; 
 H.at< double>（2,1）= 0.0; 
 H.at< double>（2,2）= 1.0; 
 
 //在p1上计算透视变换
 std :: vector< cv :: Point2f>结果; 
 cv :: perspectiveTransform（p1，result，H）; 
 
 for（unsigned int i = 0; i< result.size（）; ++ i）
 std :: cout< result [i]<< std :: endl; 
  
可输出符合预期：
  [1,1] 
 [2,1] 
 [1,2] 
  
 
The example in the link below is using findHomography to get the transformation between two sets of points. I want to limit the degrees of freedom used in the transformation so want to replace findHomography with estimateRigidTransform.

http://docs.opencv.org/doc/tutorials/features2d/feature_homography/feature_homography.html#feature-homography 

Below I use estimateRigidTransform to get the transformation between the object and scene points. objPoints and scePoints are represented by vector <Point2f>. 
Mat H = estimateRigidTransform(objPoints, scePoints, false);
Following the method used in the tutorial above, I want to transform the corner values using the transformation H. The tutorial uses perspectiveTransform with the 3x3 matrix returned by findHomography. With the rigid transform it only returns a 2x3 Matrix so this method cannot be used.

How would I transform the values of the corners, represented as vector <Point2f> with this 2x3 Matrix. I am just looking to perform the same functions as the tutorial but with less degrees of freedom for the transformation. I have looked at other methods such as warpAffine and getPerspectiveTransform as well, but so far not found a solution.

EDIT:

I have tried the suggestion from David Nilosek. Below I am adding the extra row to the matrix.
Mat row = (Mat_<double>(1,3) << 0, 0, 1);
H.push_back(row);
However this gives this error when using perspectiveTransform.
OpenCV Error: Assertion failed (mtype == type0 || (CV_MAT_CN(mtype) == CV_MAT_CN(type0) && ((1 << type0) & fixedDepthMask) != 0)) in create, file /Users/cgray/Downloads/opencv-2.4.6/modules/core/src/matrix.cpp, line 1486
libc++abi.dylib: terminating with uncaught exception of type cv::Exception: /Users/cgray/Downloads/opencv-2.4.6/modules/core/src/matrix.cpp:1486: error: (-215) mtype == type0 || (CV_MAT_CN(mtype) == CV_MAT_CN(type0) && ((1 << type0) & fixedDepthMask) != 0) in function create
ChronoTrigger suggested using warpAffine. I am calling the warpAffine method below, the size of 1 x 5 is the size of objCorners and sceCorners. 
warpAffine(objCorners, sceCorners, H, Size(1,4));
This gives the error below, which suggests the wrong type. objCorners and sceCorners are vector <Point2f> representing the 4 corners. I thought warpAffine would accept Mat images which may explain the error.
OpenCV Error: Assertion failed ((M0.type() == CV_32F || M0.type() == CV_64F) && M0.rows == 2 && M0.cols == 3) in warpAffine, file /Users/cgray/Downloads/opencv-2.4.6/modules/imgproc/src/imgwarp.cpp, line 3280

解决方案
I've done it this way in the past:
cv::Mat R = cv::estimateRigidTransform(p1,p2,false);

    if(R.cols == 0)
    {
        continue;
    }

    cv::Mat H = cv::Mat(3,3,R.type());
    H.at<double>(0,0) = R.at<double>(0,0);
    H.at<double>(0,1) = R.at<double>(0,1);
    H.at<double>(0,2) = R.at<double>(0,2);

    H.at<double>(1,0) = R.at<double>(1,0);
    H.at<double>(1,1) = R.at<double>(1,1);
    H.at<double>(1,2) = R.at<double>(1,2);

    H.at<double>(2,0) = 0.0;
    H.at<double>(2,1) = 0.0;
    H.at<double>(2,2) = 1.0;


    cv::Mat warped;
    cv::warpPerspective(img1,warped,H,img1.size());
which is the same as David Nilosek suggested: add a 0 0 1 row at the end of the matrix

this code warps the IMAGES with a rigid transformation.

I you want to warp/transform the points, you must  use perspectiveTransform function with a 3x3 matrix ( http://docs.opencv.org/modules/core/doc/operations_on_arrays.html?highlight=perspectivetransform#perspectivetransform )

tutorial here:

http://docs.opencv.org/doc/tutorials/features2d/feature_homography/feature_homography.html

or you can do it manually by looping over your vector and
cv::Point2f result;
result.x = point.x * R.at<double>(0,0) + point.y * R.at<double>(0,1) + R.at<double>(0,2);
result.y = point.x * R.at<double>(1,0) + point.y * R.at<double>(1,1) + R.at<double>(1,2);
hope that helps.

remark: didn't test the manual code, but should work. No PerspectiveTransform conversion needed there!

edit: this is the full (tested) code:
// points
std::vector<cv::Point2f> p1;
p1.push_back(cv::Point2f(0,0));
p1.push_back(cv::Point2f(1,0));
p1.push_back(cv::Point2f(0,1));

// simple translation from p1 for testing:
std::vector<cv::Point2f> p2;
p2.push_back(cv::Point2f(1,1));
p2.push_back(cv::Point2f(2,1));
p2.push_back(cv::Point2f(1,2));

cv::Mat R = cv::estimateRigidTransform(p1,p2,false);

// extend rigid transformation to use perspectiveTransform:
cv::Mat H = cv::Mat(3,3,R.type());
H.at<double>(0,0) = R.at<double>(0,0);
H.at<double>(0,1) = R.at<double>(0,1);
H.at<double>(0,2) = R.at<double>(0,2);

H.at<double>(1,0) = R.at<double>(1,0);
H.at<double>(1,1) = R.at<double>(1,1);
H.at<double>(1,2) = R.at<double>(1,2);

H.at<double>(2,0) = 0.0;
H.at<double>(2,1) = 0.0;
H.at<double>(2,2) = 1.0;

// compute perspectiveTransform on p1
std::vector<cv::Point2f> result;
cv::perspectiveTransform(p1,result,H);

for(unsigned int i=0; i<result.size(); ++i)
    std::cout << result[i] << std::endl;
which gives output as expected: 
[1, 1]
[2, 1]
[1, 2]


                        
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