Fixed some existing doxygen comments

modules/surface_matching/include/opencv2/surface_matching/icp.hpp

@@ -101,14 +101,18 @@ public:
 
   /**
      *  \brief ICP constructor with default arguments.
+     *  @param [in] iterations
      *  @param [in] tolerence Controls the accuracy of registration at each iteration of ICP.
-     *  @param [in] rejectionScale Robust outlier rejection is applied for robustness. This value actually corresponds to the standard deviation coefficient. Points with rejectionScale * \sigma are ignored during registration.
-     *  @param [in] numLevels Number of pyramid levels to proceed. Deep pyramids increase speed but decrease accuracy. Too coarse pyramids might have computational overhead on top of the inaccurate registrtaion. This parameter should be chosen to optimize a balance. Typical values range from 4 to 10.
-     *  @param [in] sampleType Currently this parameter is ignored and only uniform sampling is applied. Leave it as 0.
+     *  @param [in] rejectionScale Robust outlier rejection is applied for robustness. This value
+            actually corresponds to the standard deviation coefficient. Points with
+            rejectionScale * &sigma are ignored during registration.
+     *  @param [in] numLevels Number of pyramid levels to proceed. Deep pyramids increase speed but
+            decrease accuracy. Too coarse pyramids might have computational overhead on top of the
+            inaccurate registrtaion. This parameter should be chosen to optimize a balance. Typical
+            values range from 4 to 10.
+     *  @param [in] sampleType Currently this parameter is ignored and only uniform sampling is
+            applied. Leave it as 0.
      *  @param [in] numMaxCorr Currently this parameter is ignored and only PickyICP is applied. Leave it as 1.
-     *  \return
-     *
-     *  \details Constructor
      */
   ICP(const int iterations, const float tolerence=0.05, const float rejectionScale=2.5, const int numLevels=6, const ICP_SAMPLING_TYPE sampleType = ICP_SAMPLING_TYPE_UNIFORM, const int numMaxCorr=1)
   {

modules/surface_matching/include/opencv2/surface_matching/pose_3d.hpp

@@ -96,13 +96,11 @@ public:
 
   /**
    *  \brief Updates the pose with the new one
-   *  \param [in] NewPose New pose to overwrite
    */
   void updatePose(double NewR[9], double NewT[3]);
 
   /**
    *  \brief Updates the pose with the new one, but this time using quaternions to represent rotation
-   *  \param [in] NewPose New pose to overwrite
    */
   void updatePoseQuat(double Q[4], double NewT[3]);
 

modules/surface_matching/include/opencv2/surface_matching/ppf_helpers.hpp

@@ -49,18 +49,18 @@ namespace ppf_match_3d
 {
 
 /**
- *  \brief Load a PLY file
- *
- *  \param [in] fileName The PLY model to read
- *  \param [in] withNormals Flag wheather the input PLY contains normal information, 
+ *  @brief Load a PLY file
+ *  @param [in] fileName The PLY model to read
+ *  @param [in] withNormals Flag wheather the input PLY contains normal information,
  *  and whether it should be loaded or not
- *  \return Returns the matrix on successfull load
+ *  @return Returns the matrix on successfull load
  */
 CV_EXPORTS Mat loadPLYSimple(const char* fileName, int withNormals);
 
 /**
- *  \brief Write a point cloud to PLY file
- *  \param [in] fileName The PLY model file to write
+ *  @brief Write a point cloud to PLY file
+ *  @param [in] PC Input point cloud
+ *  @param [in] fileName The PLY model file to write
 */
 CV_EXPORTS void writePLY(Mat PC, const char* fileName);
 
@@ -69,6 +69,7 @@ Mat samplePCUniformInd(Mat PC, int sampleStep, std::vector<int>& indices);
 
 /**
  *  Sample a point cloud using uniform steps
+ *  @param [in] pc Input point cloud
  *  @param [in] xrange X components (min and max) of the bounding box of the model
  *  @param [in] yrange Y components (min and max) of the bounding box of the model
  *  @param [in] zrange Z components (min and max) of the bounding box of the model
@@ -77,7 +78,7 @@ Mat samplePCUniformInd(Mat PC, int sampleStep, std::vector<int>& indices);
  *  the parameter sample_step_relative. 
  *  @param [in] weightByCenter The contribution of the quantized data points can be weighted
  *  by the distance to the origin. This parameter enables/disables the use of weighting.
- *  \return Sampled point cloud
+ *  @return Sampled point cloud
 */
 CV_EXPORTS Mat samplePCByQuantization(Mat pc, float xrange[2], float yrange[2], float zrange[2], float sample_step_relative, int weightByCenter=0);
 
@@ -94,7 +95,7 @@ void queryPCFlann(void* flannIndex, Mat& pc, Mat& indices, Mat& distances);
  *  @param [in] pc Input point cloud (CV_32F family). Point clouds with 3 or 6 elements per
  *  row are expected.
  *  @param [in] scale The scale after normalization. Default to 1.
- *  \return Normalized point cloud
+ *  @return Normalized point cloud
 */
 CV_EXPORTS Mat normalize_pc(Mat pc, float scale);
 
@@ -107,7 +108,7 @@ Mat transPCCoeff(Mat pc, float scale, float Cx, float Cy, float Cz, float MinVal
  *  row are expected. In the case where the normals are provided, they are also rotated to be
  *  compatible with the entire transformation
  *  @param [in] Pose 4x4 pose matrix, but linearized in row-major form.
- *  \return Transformed point cloud
+ *  @return Transformed point cloud
 */
 CV_EXPORTS Mat transformPCPose(Mat pc, double Pose[16]);
 
@@ -120,25 +121,23 @@ CV_EXPORTS void getRandomPose(double Pose[16]);
 /**
  *  Adds a uniform noise in the given scale to the input point cloud
  *  @param [in] pc Input point cloud (CV_32F family). 
- *  @param [in] scale Input scale of the noise. The larger the scale, the more
- *  noisy the output
+ *  @param [in] scale Input scale of the noise. The larger the scale, the more noisy the output
 */
 CV_EXPORTS Mat addNoisePC(Mat pc, double scale);
 
 /**
- *  \brief Compute the normals of an arbitrary point cloud
- *
- *  @param [in] PC Input point cloud to compute the normals for.
- *  @param [in] PCNormals Output point cloud
- *  @param [in] NumNeighbors Number of neighbors to take into account in a local region
- *  @param [in] FlipViewpoint Should normals be flipped to a viewing direction?
- *  \return Returns 0 on success
- *
- *  \details computeNormalsPC3d uses a plane fitting approach to smoothly compute
+ *  @brief Compute the normals of an arbitrary point cloud
+ *  computeNormalsPC3d uses a plane fitting approach to smoothly compute
  *  local normals. Normals are obtained through the eigenvector of the covariance
  *  matrix, corresponding to the smallest eigen value.
  *  If PCNormals is provided to be an Nx6 matrix, then no new allocation
  *  is made, instead the existing memory is overwritten.
+ *  @param [in] PC Input point cloud to compute the normals for.
+ *  @param [in] PCNormals Output point cloud
+ *  @param [in] NumNeighbors Number of neighbors to take into account in a local region
+ *  @param [in] FlipViewpoint Should normals be flipped to a viewing direction?
+ *  @param [in] viewpoint
+ *  @return Returns 0 on success
  */
 CV_EXPORTS int computeNormalsPC3d(const Mat& PC, Mat& PCNormals, const int NumNeighbors, const bool FlipViewpoint, const double viewpoint[3]);
 } // namespace ppf_match_3d