Geometry-Based Camera Calibration Using Five-Point Correspondences From a Single Image

Abstract

As an essential step in many computer vision tasks, camera calibration has been studied extensively. In this paper, we propose a novel calibration technique that, based on geometric analysis, camera parameters can be estimated effectively and accurately from just one view of only five corresponding points. Our core contribution is the geometric analysis for deriving the basic equations to realize camera calibration from four coplanar corresponding points and a fifth noncoplanar one. The position, orientation, and focal length of a zooming camera can be directly estimated with unique solution. The estimated parameters are further optimized by the bundle adjustment technique. The proposed calibration method is examined and evaluated on both computer simulated data and real images. The experimental results confirm the validity of the proposed method that camera parameters can be estimated with sufficient accuracy using just five-point correspondences from a single image, even in the presence of image noise.