A Novel Method for Intrinsic and Extrinsic Parameters Estimation by Solving Perspective-Three-Point Problem with Known Camera Position

The aim of the perspective-three-point (P3P) problem is to estimate extrinsic parameters of a camera from three 2D-3D point correspondences, including the orientation and position information. All the P3P solvers have a multi-solution phenomenon that is up to four solutions and needs a fully calibrated camera. In contrast, in this paper we propose a novel method for intrinsic and extrinsic parameter estimation based on three 2D-3D point correspondences with known camera position. Our core contribution is to build a new, virtual camera system whose frame and image plane are defined by the original 3D points, to build a new, intermediate world frame by the original image plane and the original 2D image points, and convert our problem to a P3P problem. Then, the intrinsic and extrinsic parameter estimation is to solve frame transformation and the P3P problem. Lastly, we solve the multi-solution problem by image resolution. Experimental results show its accuracy, numerical stability and uniqueness of the solution for intrinsic and extrinsic parameter estimation in synthetic data and real images.

Automated summary

A novel method for intrinsic and extrinsic parameter estimation based on three 2D-3D point correspondences with known camera position is proposed in this paper. By building a new virtual camera system and converting the problem to a P3P problem, the multi-solution problem is addressed successfully.