AUTOMATIC RELATIVE ORIENTATION OF TERRESTRIAL LASER SCANS USING PLANAR STRUCTURES AND ANGLE CONSTRAINTS

Abstract

The relative orientation of independently acquired terrestrial laser scan point clouds is an important task. If good starting values are available, well-known iterative algorithms exist to determine the required transformation. In this paper, we describe a method to obtain such starting values fully automatically, which is applicable to scenes containing planar elements. Our method first extracts planar patches in each scan individually and then assigns patch triples across scans in order to compute the rotation and translation component of the relative orientation. We assess the performance of our approach using a set of 20 terrestrial scans acquired systematically at increasing distance. For each scan, we automatically extract the 50 largest planar patches. We show that, although there are 1.15 billion possible patch triple assignments, we are able to compute efficiently a ranked list of possible transformations where the correct transformation is usually within the first few positions. For our test data and three test runs, it has been among the first 53 positions, even for scans with little overlap. Thus, instead of 1.15 billion candidate solutions, the score function needs only to evaluate on the order of 100 candidate solutions, which is an improvement by a factor of 10 7. 1