Update doCornerRefinement() parameter to cornerRefinementMethod().

modules/aruco/samples/detector_params.yml

@@ -12,7 +12,7 @@ minCornerDistance: 10.0
 minDistanceToBorder: 3
 minMarkerDistance: 10.0
 minMarkerDistanceRate: 0.05
-doCornerRefinement: false
+cornerRefinementMethod: 0
 cornerRefinementWinSize: 5
 cornerRefinementMaxIterations: 30
 cornerRefinementMinAccuracy: 0.1

modules/aruco/tutorials/aruco_detection/aruco_detection.markdown

@@ -702,23 +702,23 @@ Default value: 0.6
 #### Corner Refinement
 
 After markers have been detected and identified, the last step is performing subpixel refinement
-in the corner positions (see OpenCV ```cornerSubPix()```)
+in the corner positions (see OpenCV ```cornerSubPix()``` and ```cv::aruco::CornerRefineMethod```)
 
 Note that this step is optional and it only makes sense if the position of the marker corners have to
 be accurate, for instance for pose estimation. It is usually a time consuming step and it is disabled by default.
 
-- ```bool doCornerRefinement```
+- ```int cornerRefinementMethod```
 
 This parameter determines if the corner subpixel process is performed or not. It can be disabled
 if accurate corners are not necessary.
 
-Default value: false.
+Default value: ```CORNER_REFINE_NONE```.
 
  - ```int cornerRefinementWinSize```
 
 This parameter determines the window size of the subpixel refinement process.
 
-High values can produce that close image corners are included in the window region, so that the
+High values can produce the effect that close image corners are included in the window region, so that the
 marker corner moves to a different and wrong location during the process. Furthermore
 it can affect to performance.
 

modules/aruco/tutorials/charuco_detection/charuco_detection.markdown

@@ -142,7 +142,7 @@ are optional. A similar example without these parameters would be:
     std::vector<int> markerIds;
     std::vector<std::vector<cv::Point2f>> markerCorners;
     cv::Ptr<cv::aruco::DetectorParameters> params;
-    params->doCornerRefinement = false;
+    params->cornerRefinementMethod = cv::aruco::CORNER_REFINE_NONE;
     cv::aruco::detectMarkers(inputImage, board.dictionary, markerCorners, markerIds, params);
 
     // if at least one marker detected
@@ -207,7 +207,7 @@ Finally, this is a full example of ChArUco detection (without using calibration
     cv::Ptr<cv::aruco::CharucoBoard> board = cv::aruco::CharucoBoard::create(5, 7, 0.04, 0.02, dictionary);
 
     cv::Ptr<cv::aruco::DetectorParameters> params;
-    params->doCornerRefinement = false;
+    params->cornerRefinementMethod = cv::aruco::CORNER_REFINE_NONE;
 
     while (inputVideo.grab()) {
         cv::Mat image, imageCopy;