Comparative Study of Two Automatic Registration Algorithms

Abstract

ABSTRACT:The Iterative Closest Point (ICP) algorithm is prevalent for the automatic fine registration of overlapping pairs of terrestrial laser scanning (TLS) data. This method along with its vast number of variants, obtains the least squares parameters that are necessary to align the TLS data by minimizing some distance metric between the scans. The ICP algorithm uses a "model-data" concept in which the scans obtain differential treatment in the registration process depending on whether they were assigned to be the "model" or "data". For each of the "data" points, corresponding points from the "model" are sought. Another concept of "symmetric correspondence" was proposed in the Point-to-Plane (P2P) algorithm, where both scans are treated equally in the registration process. The P2P method establishes correspondences on both scans and minimizes the point-to-plane distances between the scans by simultaneously considering the stochastic properties of both scans. This paper studies both the ICP and P2P algorithms in terms of their consistency in registration parameters for pairs of TLS data. The question being investigated in this paper is, should scan A be registered to scan B, will the parameters be the same if scan B were registered to scan A? Experiments were conducted with eight pairs of real TLS data which were registered by the two algorithms in the forward (scan A to scan B) and backward (scan B to scan A) modes and the results were compared. The P2P algorithm was found to be more consistent than the ICP algorithm. The differences in registration accuracy between the forward and backward modes were negligible when using the P2P algorithm (mean difference of 0.03mm). However, the ICP had a mean difference of 4.26mm. Each scan was also transformed by the forward and backward parameters of the two algorithms and the misclosure computed. The mean misclosure for the P2P algorithm was 0.80mm while that for the ICP algorithm was 5.39mm. The conclusion from this study is that the symmetric correspondence of the P2P algorithm provides more consistent registration results between a given pair of scans. The basis for this improvement is that symmetric correspondence better deals with the disparity between scans in terms of point density and point precision. BACKGROUNDThe registration of terrestrial laser scanning (TLS) data is an essential task in 3D modeling. The data of each scan are inherently referenced to a local coordinate system that is defined by the scanner's setup. Registration is thus needed to obtain a homogeneous dataset from the multiple disparate scans, prior to any 3D modeling and/or analysis.The development of automatic registration approaches is of interest to many research communities. Among the many automatic approaches that have been proposed, the Iterative Closest Point (ICP) method of Besl and McKay (1992) is one of the most popular methods used. The method is particularly prevalent for the fine registration of pairs of TLS data. Besl and McKay (1992) obtain the least squares parameters that are...

Review of mobile laser scanning target‐free registration methods for urban areas using improved error metrics

“…In contrast, in target‐based approaches the quality of the registration is evaluated based on the differences between the X , Y and Z coordinates of the corresponding target points after and before matching (Yang et al., ). The other error metric in target‐based evaluations calculates the changes in the estimated rotation angles and translation vectors with benchmarking values (Grant et al., ; Previtali et al., ; Yang et al., ).…”

“…() calculated the distances between target points before and after registration. Other researchers (Grant et al., ; Previtali et al., ; Yang et al., ) measured the registration quality based on differences between the estimated transformation parameters and benchmarking values. Another two error metrics were based on the root mean square (RMS) values of the residuals of the distances between corresponding pairs of points (Gressin et al., ; Takai et al., ) and the sum of the RMS of the residuals of the distances between points and their corresponding surfaces (Bae, ; Skaloud and Lichti, ; Rabbani et al., ; Chan et al., ).…”