Fig. 4.

In R1PPnP, the selection of control point o is related to the convergence rate. (a) An example to illustrate this behavior with 2D space and 1D camera imaging plane. According to the R and µ updating methods in Eqs.(15) and (16). ∠ (p − o₁, q − o₁) > ∠ (p − o₂, q − o₂) and $\Vert {\mathbf{x}}_i-{\mathbf{x}}_{o1}\Vert /\Vert {\mathbf{v}}_i-{\mathbf{x}}_{o1}\Vert >\Vert {\mathbf{x}}_i-{\mathbf{x}}_{o2}\Vert /\Vert {\mathbf{v}}_i-{\mathbf{x}}_{o2}\Vert$ suggest that the iteration process is more likely to have larger R and µ updating rate when o is closer to p. (b) A real-world example to illustrate this behavior, the radius of a circle represents the required number of iterations when using this feature point as the control point o.