Semiautomatic Methods for Recovering Radial Distortion Parameters from A Single Image

In this technical report, we address the problem of recovering the camera radial distortion coefficients from one image. In particular, we present three interactive methods where the user indicate lines in the single image. The first method is the most direct: the manually chosen points are used to compute the radial distortion parameters. The second and third methods allow the user to draw snakes on the image, with each approximately corresponding to a projected straight line in space. These snakes are drawn to strong edges subject to regularization. The difference between these two methods is the behavior of the snakes. In one of the last two methods, they behave like independent, conventional snakes. In the other method, their behavior are globally connected via a consistent model of image radial distortion. We call such snakes radial distortion snakes. Experiments show that among the three methods, radial distortion snakes are the most robust and accurate. This is attributed to the direct link of edge fitting to the radial distortion parameters, in comparison to the other methods in which the process of locating edges is independent of radial distortion parameter estimation. c Digital Equipment Corporation, 1997 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of the Cambridge Research Laboratory of Digital Equipment Corporation in Cambridge, Massachusetts; an acknowledgment of the authors and individual contributors to the work; and all applicable portions of the copyright notice. Copying, reproducing, or republishing for any other purpose shall require a license with payment of fee to the Cambridge Research Laboratory. All rights reserved. CRL Technical reports are available on the CRL’s web page at http://www.crl.research.digital.com. Digital Equipment Corporation Cambridge Research Laboratory One Kendall Square, Building 700 Cambridge, Massachusetts 02139 CONTENTS i