Precision Of Camera Calibration Research Articles

Two Vanishing Points Error Estimation Based on Line Clustering and Condition Adjustment with Parameters

In close-range digital photogrammetry and computer vision, a major challenge is the automation of 3D reconstruction from 2D-images. And single image calibration is a fundamental task in these areas for research. It is known that camera parameters can be recovered by the vanishing points of three orthogonal directions. However, three reliable and well-distributed vanishing points are not always available. Therefore, how to estimate the error of two vanishing points is very significant for us to analyze the precision of camera calibration. New methods for vanishing point detection and error estimation are presented, which can be illustrated as follows. Firstly, the line clustering, which parallel to object lines and correspond to the vanishing points, are detected based on RANSAC (Random Sample Consensus). Secondly, "condition adjustment with parameters" is utilized to estimate a nonlinear error equation. Thirdly, the error of vanishing point is expressed by error ellipse that is derived by co-factor matrix according to adjustment principle. Finally, experimental results of vanishing points coordinates and their errors are shown and analyzed.

A Technique for Binocular Stereo Vision System Calibration by the Nonlinear Optimization and Calibration Points with Accurate Coordinates

With the increasing need for higher accuracy measurement in computer vision, the precision of camera calibration is a more important factor. The objective of stereo camera calibration is to estimate the intrinsic and extrinsic parameters of each camera. We presented a high-accurate technique to calibrate binocular stereo vision system having been mounted the locations and attitudes, which was realized by combining nonlinear optimization method with accurate calibration points. The calibration points with accurate coordinates, were formed by an infrared LED moved with three-dimensional coordinate measurement machine, which can ensure indeterminacy of measurement is 1/30000. By using bilinear interpolation square-gray weighted centroid location algorithm, the imaging centers of the calibration points can be accurately determined. The accuracy of the calibration is measured in terms of the accuracy in the reconstructing calibration points through triangulation, the mean distance between reconstructing point and given calibration point is 0.039mm. The technique can satisfy the goals of measurement and camera accurate calibration.