Function normal_estimate_def 

pub fn normal_estimate_def(
    normals: &mut impl ToOutputArray,
    curvatures: &mut impl ToOutputArray,
    input_pts: &impl ToInputArray,
    nn_idx: &impl ToInputArray,
) -> Result<()>

Estimate the normal and curvature of each point in point cloud from NN results.

Normal estimation by PCA:

• Input: Nearest neighbor points of a specific point:
• Step:
  1. Calculate the of ;
  2. A 3x3 covariance matrix is obtained by ;
  3. Calculate the eigenvalues() and corresponding eigenvectors() of ;
  4. is the normal of the specific point, is the curvature of the specific point;
• Output: Normal and curvature of the specific point.

Parameters

• normals:[out] Normal of each point, support vector and Mat of size Nx3.
• curvatures:[out] Curvature of each point, support vector and Mat.
• input_pts: Original point cloud, support vector and Mat of size Nx3/3xN.
• nn_idx: Index information of nearest neighbors of all points. The first nearest neighbor of each point is itself. Support vector<vector>, vector and Mat of size NxK. If the information in a row is [0, 2, 1, -5, -1, 4, 7 … negative number], it will use only non-negative indexes until it meets a negative number or bound of this row i.e. [0, 2, 1].
• max_neighbor_num: The maximum number of neighbors want to use including itself. Setting to a non-positive number or default will use the information from nn_idx.

Note

This alternative version of normal_estimate function uses the following default values for its arguments:

• max_neighbor_num: 0