Rework RLOF by using HAL universal instructions

modules/optflow/include/opencv2/optflow/rlofflow.hpp

@@ -66,12 +66,12 @@ class CV_EXPORTS_W RLOFOpticalFlowParameter{
     RLOFOpticalFlowParameter()
         :solverType(ST_BILINEAR)
         ,supportRegionType(SR_CROSS)
-        ,normSigma0(3.2f)
-        ,normSigma1(7.f)
+        ,normSigma0(std::numeric_limits<float>::max())
+        ,normSigma1(std::numeric_limits<float>::max())
         ,smallWinSize(9)
         ,largeWinSize(21)
         ,crossSegmentationThreshold(25)
-        ,maxLevel(5)
+        ,maxLevel(4)
         ,useInitialFlow(false)
         ,useIlluminationModel(true)
         ,useGlobalMotionPrior(true)
@@ -90,13 +90,13 @@ class CV_EXPORTS_W RLOFOpticalFlowParameter{
     */
 
     float normSigma0;
-    /**< &sigma paramter of the shrinked Hampel norm introduced in @cite Senst2012. If
+    /**< &sigma parameter of the shrinked Hampel norm introduced in @cite Senst2012. If
      * &sigma = std::numeric_limist<float>::max() the least-square estimator will be used
      * instead of the M-estimator. Althoug M-estimator is more robust against outlier in the support
      * region the least-square can be fast in computation.
     */
     float normSigma1;
-    /**< &sigma paramter of the shrinked Hampel norm introduced in @cite Senst2012. If
+    /**< &sigma parameter of the shrinked Hampel norm introduced in @cite Senst2012. If
      * &sigma = std::numeric_limist<float>::max() the least-square estimator will be used
      * instead of the M-estimator. Althoug M-estimator is more robust against outlier in the support
      * region the least-square can be fast in computation.
@@ -151,6 +151,14 @@ class CV_EXPORTS_W RLOFOpticalFlowParameter{
      *   See @cite Senst2016 for more details.
     */
 
+    //! @brief Enable M-estimator or disable and use least-square estimator.
+    /** Enables M-estimator by setting sigma parameters to (3.2, 7.0). Disabling M-estimator can reduce
+     *  runtime, while enabling can improve the accuracy.
+     *  @param val If true M-estimator is used. If false least-square estimator is used.
+     *    @see setNormSigma0, setNormSigma1
+    */
+    CV_WRAP void setUseMEstimator(bool val);
+
     CV_WRAP void setSolverType(SolverType val);
     CV_WRAP SolverType getSolverType() const;
 
@@ -216,9 +224,8 @@ class CV_EXPORTS_W RLOFOpticalFlowParameter{
  * For the RLOF configuration see optflow::RLOFOpticalFlowParameter for further details.
  * Parameters have been described in @cite Senst2012 @cite Senst2013 @cite Senst2014 and @cite Senst2016.
  *
- * @note SIMD parallelization is only available when compiling with SSE4.1. If the grid size is set to (1,1) and the
- * forward backward threshold <= 0 that the dense optical flow field is purely.
- * computed with the RLOF.
+ * @note If the grid size is set to (1,1) and the forward backward threshold <= 0 than pixelwise dense optical flow field is
+ * computed by RLOF without using interpolation.
  *
  * @see optflow::calcOpticalFlowDenseRLOF(), optflow::RLOFOpticalFlowParameter
 */

modules/optflow/perf/perf_rlof.cpp

@@ -47,7 +47,7 @@ typedef tuple<std::string, int> INTERP_GRID_Dense_t;
 typedef TestBaseWithParam<INTERP_GRID_Dense_t> INTERP_GRID_Dense;
 PERF_TEST_P(INTERP_GRID_Dense, OpticalFlow_DenseRLOF,
     testing::Combine(
-        testing::Values<std::string>("INTERP_EPIC", "INTERP_GEO"),
+        testing::Values<std::string>("INTERP_EPIC", "INTERP_GEO", "INTERP_RIC"),
         testing::Values<int>(4,10))
 )
 {
@@ -63,6 +63,8 @@ PERF_TEST_P(INTERP_GRID_Dense, OpticalFlow_DenseRLOF,
         interp_type = INTERP_EPIC;
     if (get<0>(GetParam()) == "INTERP_GEO")
         interp_type = INTERP_GEO;
+    if (get<0>(GetParam()) == "INTERP_RIC")
+        interp_type = INTERP_RIC;
     PERF_SAMPLE_BEGIN()
         calcOpticalFlowDenseRLOF(frame1, frame2,flow, param, 1.0f, Size(get<1>(GetParam()), get<1>(GetParam())), interp_type);
     PERF_SAMPLE_END()