[RHO] Initial commit of RHO algorithm for rapid homography estimation.

Implements the RHO algorithm as presented in

Paper: Bilaniuk, Olexa, Hamid Bazargani, and Robert Laganiere. "Fast
Target Recognition on Mobile Devices: Revisiting Gaussian Elimination
for the Estimation of Planar Homographies." In Computer Vision and
Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on, pp.
119-125. IEEE, 2014.

- Complete, heavily documented reference C implementation, as well as
temporarily disabled dirty SSE2 port.
- Enabled tests for RHO in test_homography; Currently these fail
presumably due to too-stringent accuracy requirements.
- Refinement and final refinement are not yet functional; Do not pass
their corresponding flags to RHO.

modules/calib3d/include/opencv2/calib3d.hpp

@@ -53,7 +53,8 @@ namespace cv
 
 //! type of the robust estimation algorithm
 enum { LMEDS  = 4, //!< least-median algorithm
-       RANSAC = 8  //!< RANSAC algorithm
+       RANSAC = 8, //!< RANSAC algorithm
+       RHO    = 16 //!< RHO algorithm
      };
 
 enum { SOLVEPNP_ITERATIVE = 0,

modules/calib3d/src/fundam.cpp

@@ -41,6 +41,10 @@
 //M*/
 
 #include "precomp.hpp"
+#include "rhorefc.h"
+#if CV_SSE2
+#include "rhosse2.h"
+#endif
 #include <iostream>
 
 namespace cv
@@ -273,6 +277,73 @@ public:
 }
 
 
+
+namespace cv{
+static bool createAndRunRHORegistrator(double confidence, int maxIters, double ransacReprojThreshold, int npoints, InputArray _src, InputArray _dst, OutputArray _H, OutputArray _tempMask){
+    Mat src = _src.getMat();
+    Mat dst = _dst.getMat();
+    Mat tempMask = _tempMask.getMat();
+    bool result;
+
+    /* Run RHO. Needs cleanup or separate function to invoke. */
+    Mat tmpH = Mat(3, 3, CV_32FC1);
+    tempMask = Mat(npoints, 1, CV_8U);
+    double beta = 0.35;/* 0.35 is a value that often works. */
+
+#if CV_SSE2 && 0
+    if(useOptimized()){
+        RHO_HEST_SSE2 p;
+        rhoSSE2Init(&p);
+        rhoSSE2EnsureCapacity(&p, npoints, beta);
+        result = !!rhoSSE2(&p,
+                          (const float*)src.data,
+                          (const float*)dst.data,
+                          (char*)       tempMask.data,
+                          npoints,
+                          ransacReprojThreshold,
+                          maxIters,
+                          maxIters,
+                          confidence,
+                          4,
+                          beta,
+                          RHO_FLAG_ENABLE_NR,
+                          NULL,
+                          (float*)tmpH.data);
+        rhoSSE2Fini(&p);
+    }else
+#endif
+    {
+        RHO_HEST_REFC p;
+        rhoRefCInit(&p);
+        rhoRefCEnsureCapacity(&p, npoints, beta);
+        result = !!rhoRefC(&p,
+                          (const float*)src.data,
+                          (const float*)dst.data,
+                          (char*)       tempMask.data,
+                          npoints,
+                          ransacReprojThreshold,
+                          maxIters,
+                          maxIters,
+                          confidence,
+                          4,
+                          beta,
+                          RHO_FLAG_ENABLE_NR,
+                          NULL,
+                          (float*)tmpH.data);
+        rhoRefCFini(&p);
+    }
+    tmpH.convertTo(_H, CV_64FC1);
+
+    /* Maps non-zero maks elems to 1, for the sake of the testcase. */
+    for(int k=0;k<npoints;k++){
+        tempMask.data[k] = !!tempMask.data[k];
+    }
+
+    return result;
+}
+}
+
+
 cv::Mat cv::findHomography( InputArray _points1, InputArray _points2,
                             int method, double ransacReprojThreshold, OutputArray _mask,
                             const int maxIters, const double confidence)
@@ -317,10 +388,12 @@ cv::Mat cv::findHomography( InputArray _points1, InputArray _points2,
         result = createRANSACPointSetRegistrator(cb, 4, ransacReprojThreshold, confidence, maxIters)->run(src, dst, H, tempMask);
     else if( method == LMEDS )
         result = createLMeDSPointSetRegistrator(cb, 4, confidence, maxIters)->run(src, dst, H, tempMask);
-    else
+    else if( method == RHO ){
+        result = createAndRunRHORegistrator(confidence, maxIters, ransacReprojThreshold, npoints, src, dst, H, tempMask);
+    }else
         CV_Error(Error::StsBadArg, "Unknown estimation method");
 
-    if( result && npoints > 4 )
+    if( result && npoints > 4 && method != RHO)
     {
         compressPoints( src.ptr<Point2f>(), tempMask.ptr<uchar>(), 1, npoints );
         npoints = compressPoints( dst.ptr<Point2f>(), tempMask.ptr<uchar>(), 1, npoints );

modules/calib3d/test/test_homography.cpp

@@ -62,10 +62,10 @@
 
 #define MAX_COUNT_OF_POINTS 303
 #define COUNT_NORM_TYPES 3
-#define METHODS_COUNT 3
+#define METHODS_COUNT 4
 
 int NORM_TYPE[COUNT_NORM_TYPES] = {cv::NORM_L1, cv::NORM_L2, cv::NORM_INF};
-int METHOD[METHODS_COUNT] = {0, cv::RANSAC, cv::LMEDS};
+int METHOD[METHODS_COUNT] = {0, cv::RANSAC, cv::LMEDS, cv::RHO};
 
 using namespace cv;
 using namespace std;
@@ -144,7 +144,7 @@ void CV_HomographyTest::print_information_1(int j, int N, int _method, const Mat
     cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else  cout << "vector <Point2f>";
     cout << "   Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl;
     cout << "Count of points: " << N << endl; cout << endl;
-    cout << "Method: "; if (_method == 0) cout << 0; else if (_method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl;
+    cout << "Method: "; if (_method == 0) cout << 0; else if (_method == 8) cout << "RANSAC"; else if (_method == cv::RHO) cout << "RHO"; else cout << "LMEDS"; cout << endl;
     cout << "Homography matrix:" << endl; cout << endl;
     cout << H << endl; cout << endl;
     cout << "Number of rows: " << H.rows << "   Number of cols: " << H.cols << endl; cout << endl;
@@ -156,7 +156,7 @@ void CV_HomographyTest::print_information_2(int j, int N, int _method, const Mat
     cout << "Type of srcPoints: "; if ((j>-1) && (j<2)) cout << "Mat of CV_32FC2"; else  cout << "vector <Point2f>";
     cout << "   Type of dstPoints: "; if (j % 2 == 0) cout << "Mat of CV_32FC2"; else cout << "vector <Point2f>"; cout << endl;
     cout << "Count of points: " << N << endl; cout << endl;
-    cout << "Method: "; if (_method == 0) cout << 0; else if (_method == 8) cout << "RANSAC"; else cout << "LMEDS"; cout << endl;
+    cout << "Method: "; if (_method == 0) cout << 0; else if (_method == 8) cout << "RANSAC"; else if (_method == cv::RHO) cout << "RHO"; else cout << "LMEDS"; cout << endl;
     cout << "Original matrix:" << endl; cout << endl;
     cout << H << endl; cout << endl;
     cout << "Found matrix:" << endl; cout << endl;
@@ -339,14 +339,15 @@ void CV_HomographyTest::run(int)
 
                     continue;
                 }
+            case cv::RHO:
             case RANSAC:
                 {
                     cv::Mat mask [4]; double diff;
 
-                    Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f, RANSAC, reproj_threshold, mask[0]),
-                                         cv::findHomography(src_mat_2f, dst_vec, RANSAC, reproj_threshold, mask[1]),
-                                         cv::findHomography(src_vec, dst_mat_2f, RANSAC, reproj_threshold, mask[2]),
-                                         cv::findHomography(src_vec, dst_vec, RANSAC, reproj_threshold, mask[3]) };
+                    Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f, method, reproj_threshold, mask[0]),
+                                         cv::findHomography(src_mat_2f, dst_vec, method, reproj_threshold, mask[1]),
+                                         cv::findHomography(src_vec, dst_mat_2f, method, reproj_threshold, mask[2]),
+                                         cv::findHomography(src_vec, dst_vec, method, reproj_threshold, mask[3]) };
 
                     for (int j = 0; j < 4; ++j)
                     {
@@ -466,14 +467,15 @@ void CV_HomographyTest::run(int)
 
                     continue;
                 }
+            case cv::RHO:
             case RANSAC:
                 {
                     cv::Mat mask_res [4];
 
-                    Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f, RANSAC, reproj_threshold, mask_res[0]),
-                                         cv::findHomography(src_mat_2f, dst_vec, RANSAC, reproj_threshold, mask_res[1]),
-                                         cv::findHomography(src_vec, dst_mat_2f, RANSAC, reproj_threshold, mask_res[2]),
-                                         cv::findHomography(src_vec, dst_vec, RANSAC, reproj_threshold, mask_res[3]) };
+                    Mat H_res_64 [4] = { cv::findHomography(src_mat_2f, dst_mat_2f, method, reproj_threshold, mask_res[0]),
+                                         cv::findHomography(src_mat_2f, dst_vec, method, reproj_threshold, mask_res[1]),
+                                         cv::findHomography(src_vec, dst_mat_2f, method, reproj_threshold, mask_res[2]),
+                                         cv::findHomography(src_vec, dst_vec, method, reproj_threshold, mask_res[3]) };
 
                     for (int j = 0; j < 4; ++j)
                     {