This paper presents a new approach to solve the classic perspective-three-point (P3P) problem. The basic conception behind is to determine the support plane, which is defined by the three control points. Computation of the plane normal is formulated as searching for the maximum likelihood on the Gaussian hemisphere by exploiting the geometric constraints of three known angles and length ratios from the control points. The distances of the control points are then computed from the normal and the calibration matrix by homography decomposition. The proposed algorithm has been tested with real image data. The computation errors for the plane normal and the distances are less than 0.35 degrees, and 0.8cm, respectively, within 1~2m camera-to-plane distances. The multiple solutions to P3P problem are also illustrated.
Paper
Full text
Perspective-Three-Point (P3P) by Determining the Support Plane
Semantic Scholar · Computer Science · 2011
Abstract
This paper presents a new approach to solve the classic perspective-three-point (P3P) problem. The basic conception behind is to determine the support plane, which is defined by the three control points. Computation of the plane normal is formulated as searching for the maximum likelihood on the Gaussian hemisphere by exploiting the geometric constraints of three known angles and length ratios from the control points. The distances of the control points are then computed from the normal and the calibration matrix by homography decomposition. The proposed algorithm has been tested with real image data. The computation errors for the plane normal and the distances are less than 0.35 degrees, and 0.8cm, respectively, within 1~2m camera-to-plane distances. The multiple solutions to P3P problem are also illustrated.