Expose maxIters in findFundamentalMat

Lets the user choose the maximum number of iterations the robust
estimator runs for, similary to findHomography. This can significantly
improve performance (at a computational cost).

modules/calib3d/include/opencv2/calib3d.hpp

@@ -1905,6 +1905,7 @@ point localization, image resolution, and the image noise.
 @param confidence Parameter used for the RANSAC and LMedS methods only. It specifies a desirable level
 of confidence (probability) that the estimated matrix is correct.
 @param mask
+@param maxIters The maximum number of robust method iterations.
 
 The epipolar geometry is described by the following equation:
 
@@ -1938,6 +1939,11 @@ stereoRectifyUncalibrated to compute the rectification transformation. :
      findFundamentalMat(points1, points2, FM_RANSAC, 3, 0.99);
 @endcode
  */
+CV_EXPORTS_W Mat findFundamentalMat( InputArray points1, InputArray points2,
+                                     int method, double ransacReprojThreshold, double confidence,
+                                     int maxIters, OutputArray mask = noArray() );
+
+/** @overload */
 CV_EXPORTS_W Mat findFundamentalMat( InputArray points1, InputArray points2,
                                      int method = FM_RANSAC,
                                      double ransacReprojThreshold = 3., double confidence = 0.99,

modules/calib3d/src/fundam.cpp

@@ -809,7 +809,7 @@ public:
 
 cv::Mat cv::findFundamentalMat( InputArray _points1, InputArray _points2,
                                 int method, double ransacReprojThreshold, double confidence,
-                                OutputArray _mask )
+                                int maxIters, OutputArray _mask )
 {
     CV_INSTRUMENT_REGION();
 
@@ -861,7 +861,7 @@ cv::Mat cv::findFundamentalMat( InputArray _points1, InputArray _points2,
             confidence = 0.99;
 
         if( (method & ~3) == FM_RANSAC && npoints >= 15 )
-            result = createRANSACPointSetRegistrator(cb, 7, ransacReprojThreshold, confidence)->run(m1, m2, F, _mask);
+            result = createRANSACPointSetRegistrator(cb, 7, ransacReprojThreshold, confidence, maxIters)->run(m1, m2, F, _mask);
         else
             result = createLMeDSPointSetRegistrator(cb, 7, confidence)->run(m1, m2, F, _mask);
     }
@@ -872,11 +872,17 @@ cv::Mat cv::findFundamentalMat( InputArray _points1, InputArray _points2,
     return F;
 }
 
-cv::Mat cv::findFundamentalMat( InputArray _points1, InputArray _points2,
-                               OutputArray _mask, int method,
-                               double ransacReprojThreshold , double confidence)
+cv::Mat cv::findFundamentalMat( cv::InputArray points1, cv::InputArray points2,
+                                     int method, double ransacReprojThreshold, double confidence,
+                                     cv::OutputArray mask )
+{
+    return cv::findFundamentalMat(points1, points2, method, ransacReprojThreshold, confidence, 1000, mask);
+}
+
+cv::Mat cv::findFundamentalMat( cv::InputArray points1, cv::InputArray points2, cv::OutputArray mask,
+                                int method, double ransacReprojThreshold, double confidence )
 {
-    return cv::findFundamentalMat(_points1, _points2, method, ransacReprojThreshold, confidence, _mask);
+    return cv::findFundamentalMat(points1, points2, method, ransacReprojThreshold, confidence, 1000, mask);
 }