#include <EigenSVDPointAlign.hpp>
template<typename T, typename PointT = float>
class lvr2::EigenSVDPointAlign< T, PointT >
Definition at line 46 of file EigenSVDPointAlign.hpp.
◆ Mat3
template<typename T , typename PointT  = float> 
      
 
 
◆ Mat4
template<typename T , typename PointT  = float> 
      
 
 
◆ Point3
template<typename T , typename PointT  = float> 
      
 
 
◆ PointPairVector
template<typename T , typename PointT  = float> 
      
 
 
◆ Vec3
template<typename T , typename PointT  = float> 
      
 
 
◆ EigenSVDPointAlign()
template<typename T , typename PointT  = float> 
 
 
◆ alignPoints() [1/2]
template<typename T , typename PointT  = float> 
      
 
Calculates the estimated Transformation to match a Data Pointcloud to a Model Pointcloud. 
Apply the resulting Transform to the Data Pointcloud.
- Parameters
- 
  
    | points | A vector of pairs with (model, data) Points |  | centroid_m | The center of the Model Pointcloud |  | centroid_d | The center of the Data Pointcloud |  | align | Will be set to the Transformation |  
 
- Returns
- The average Point-to-Point error of the Scans 
 
 
◆ alignPoints() [2/2]
template<typename T , typename PointT  = float> 
      
 
Calculates the estimated Transformation to match a Data Pointcloud to a Model Pointcloud. 
Apply the resulting Transform to the Data Pointcloud.
- Parameters
- 
  
    | scan | The Data Pointcloud |  | neighbors | An array containing a Pointer to a neighbor in the Model Pointcloud for each Point in scan, or nullptr if there is no neighbor for a Point |  | centroid_m | The center of the Model Pointcloud |  | centroid_d | The center of the Data Pointcloud |  | align | Will be set to the Transformation |  
 
- Returns
- The average Point-to-Point error of the Scans 
 
 
The documentation for this class was generated from the following file: