Abstract: A method for creating a plane panorama from point cloud data using Hough transformations is disclosed. The method involves converting the three-dimensional point cloud into a two-dimensional histogram with bins grouping neighboring points, and performing a Hough transformation on the histogram. The resulting transformed data is segmented and the method searches the segments iteratively for a major line, followed by lines that are orthogonal, diagonal, or parallel to the major line, and discards outlying data in each bin as lines are identified. The detected lines are connected to form planes, and the planes are assembled into a hole- and gap-filled panorama. The method may also use an algorithm such as a Random Sample Consensus (RANSAC) algorithm to detect a ground plane.

Abstract: Correction of the locations of panoramas and associated physical locations in a region are disclosed. The task of correcting the locations of the panoramas is divided into XY location correction followed by Z location correction. The panorama set is filtered to remove extraneous planes. In XY-plane correction, neighboring panoramas are identified using a neighbor graph, and the locations of sets of neighboring planes are constrained to be within a specified distance of one another, and a system of linear equations is constructed to represent the locations of the panoramas. A weighted absolute sum of the constraints is minimized across the entire system using a convex quadratic program solver to derive new locations for the planes. The location of ground planes is similarly corrected using a minimization of errors technique.