OPTIMAL VANISHING POINT DETECTION AND ROTATION ESTIMATION OF SINGLE IMAGES FROM A LEGOLAND SCENE

摘要

The paper presents a method for automatically and optimally determining the vanishing points of a single image, and in case the interior orientation is given, the rotation of an image with respect to the intrinsic coordinate system of a lego land scene. We perform rigorous testing and estimation in order to be as independent on control parameters as possible. This refers to (1) estimating vanishing points from line segments and the rotation matrix, (2) to testing during RANSAC and during boosting lines and (3) to classifying the line segments w. r. t. their vanishing point. Spherically normalized homogeneous coordinates are used for line segments and especially for vanishing points to allow for points at infinity. We propose a minimal representation for the uncertainty of homogeneous coordinates of 2D points and 2D lines and rotations to avoid the use of singular covariance matrices of observed line segments. This at the same time allows to estimate the parameters with a minimal representation. The vanishing point detection method is experimentally validated on a set of 292 images.