Computes an optimal affine transformation between two 3D point sets

M = cv.estimateAffine3D(src, dst)
[M, inliers] = cv.estimateAffine3D(...)
[...] = cv.estimateAffine3D(..., 'OptionName', optionValue, ...)

Input

• src First input 3D point set. Cell array of 3-element vectors {[x,y,z],...} or Nx3/Nx1x3/1xNx3 numeric array.
• dst Second input 3D point set. Same size and type as src.

Output

• M Output 3D affine transformation matrix 3x4
• inliers Output vector of same length as number of points, indicating which points are inliers.
• result success flag.

Options

• RansacThreshold Maximum reprojection error in the RANSAC algorithm to consider a point as an inlier. default 3.0.
• Confidence Confidence level, between 0 and 1, for the estimated transformation. Anything between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation. default 0.99.

The function estimates an optimal 3D affine transformation between two 3D point sets using the RANSAC algorithm.