Finds an object pose from 3 3D-2D point correspondences

[rvecs, tvecs, solutions] = cv.solveP3P(objectPoints, imagePoints, cameraMatrix)
[...] = cv.solveP3P(..., 'OptionName', optionValue, ...)

Input

• objectPoints Array of object points in the object coordinate space, 1xNx3/Nx1x3 or Nx3 array, where N=3 is the number of points, or cell array of length N=3 of 3-element vectors can be also passed here {[x1,y1,z1], [x2,y2,z2], [x3,y3,z3]}.
• imagePoints Array of corresponding image points, 1xNx2/Nx1x2 or Nx2 array, where N=3 is the number of points, or cell array of length N=3 of 2-element vectors can be also passed here {[x1,y1], [x2,y2], [x3,y3]}.
• cameraMatrix Input camera matrix A = [fx 0 cx; 0 fy cy; 0 0 1].

Output

• rvecs Output rotation vectors (see cv.Rodrigues) that, together with tvecs, brings points from the model coordinate system to the camera coordinate system. A P3P problem has up to 4 solutions.
• tvecs Output translation vectors.
• solutions number of solutions.

Options

• DistCoeffs Input vector of distortion coefficients [k1,k2,p1,p2,k3,k4,k5,k6,s1,s2,s3,s4,taux,tauy] of 4, 5, 8, 12 or 14 elements. If the vector is empty, the zero distortion coefficients are assumed. default empty.
• Method Method for solving the P3P problem. One of the following:
  • P3P (default) Method is based on the paper [gao2003complete].
  • AP3P Method is based on the paper [Ke17].

The function estimates the object pose given 3 object points, their corresponding image projections, as well as the camera matrix and the distortion coefficients.

References

[gao2003complete]:

X.S. Gao, X.R. Hou, J. Tang, H.F. Chang; "Complete Solution Classification for the Perspective-Three-Point Problem", IEEE Trans. on PAMI, vol. 25, No. 8, p. 930-943, August 2003.

[Ke17]:

T. Ke, S. Roumeliotis; "An Efficient Algebraic Solution to the Perspective-Three-Point Problem", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 PDF