Error analysis of camera parameter estimation based on collinear features

Abstract

Feature points for camera parameter estimation are detected in noisy images. Therefore, the feature points and also the camera parameters can only be estimated with limited accuracy. In case of collinear feature points, it is possible to benefit from this geometrical regularity which results in an increased accuracy of the camera parameters. In this paper, a complete theoretical covariance propagation starting from the error of the feature points up to the error of the estimated camera parameters is performed. Additionally, by determining the Fisher information matrix the Cramer-Rao bounds for the covariance of the corrected feature point positions are determined. To demonstrate the impact of collinearity on the accuracy of the camera parameters, a covariance propagation is performed with varying feature point error covariances.