Simultaneous linear estimation of multiple view geometry and lens distortion

A bugbear of uncalibrated stereo reconstruction is that cameras which deviate from the pinhole model have to be pre-calibrated in order to correct for nonlinear lens distortion. If they are not, and point correspondence is attempted using the uncorrected images, the matching constraints provided by the fundamental matrix must be set so loose that point matching is significantly hampered. This paper shows how linear estimation of the fundamental matrix from two-view point correspondences may be augmented to include one term of radial lens distortion. This is achieved by (1) changing from the standard radiallens model to another which (as we show) has equivalent power, but which takes a simpler form in homogeneous coordinates, and (2) expressing fundamental matrix estimation as a Quadratic Eigenvalue Problem (QEP), for which efficient algorithms are well known. I derive the new estimator, and compare its performance against bundle-adjusted calibration-grid data. The new estimator is fas...

• Type: Conference
• Year: 2001
• Where: CVPR
• Authors: Andrew W. Fitzgibbon
• Keywords: Computer Vision, CVPR 2001, Fundamental Matrix Estimation, Nonlinear Lens Distortion, Point Matching, Radial Lens Distortion, RANSAC-based Matching Loop