An Approach for Self-Calibration by a Quartered Circle

Abstract

The camera calibration is a key step for converting a projective reconstruction into a metric one, which is equivalent to recovering the unknown intrinsic parameters with each image. A circle is a common geometric primitive for the camera self-calibration. To avoid the limit of circle center to the camera self-calibration in a planar template, a method how to solve out the vanishing line is proposed. Then using the property of vanishing line, the camera intrinsic parameters are figured out and the camera self-calibration is achieved. The template contains a quartered circle in the study. Firstly, the camera is used to take photographs of the template from three or more direction. Secondly, using the ellipse and two mutually perpendicular diameters which are extracted from the image, according to the polarity principle and making use of the invariant property of cross-ratio of four lines which are intersected in one same point, the vanishing line can be solved out. In the end, the circular points can be figured out by the intersection between vanishing line and the circle. And using the property of the circular points, the selfcalibration is realized.

Accurate Self-calibration of Camera with Variable Intrinsic Parameters from Unknown 3D Scene

“…To make a comparison, we chose three methods in literature, the first is a well-known method [6], the second is a robust self-calibration method [32] and the third is a camera self-calibration method characterized by varying intrinsic parameters [24]. The comparison is carried out by studying the relative errors on the focal length, the principal point, the scale factor, the skew factor and the execution time and this according to the added noise and the number of used images.…”

“…In this third part of our simulation we tested the influence of the number of images on the focal length, the principal point, the scale factor and the skew factor while making a comparison with the methods [6,24,32].…”