AUTOMATIC ORIENTATION AND MERGING OF LASER SCANNER ACQUISITIONS
THROUGH VOLUMETRIC TARGETS: PROCEDURE DESCRIPTION AND TEST
RESULTS
G.Artese *, V.Achilli °, G.Salemi 5, A.Trecroci *
* Dept. of Land Planning, University of Calabria, Cosenza - Italy — g.artese@unical.it
^ Dept. of Architecture, Land Planning and Surveying, University of Padua, Via Marzolo, Padua —
vladimiro.achilli@unipd.it
Commission V, WG V/2
KEY WORDS: Laser scanning, Orientation, Mosaic, Automation, Acquisition, Targets, Radiometric
ABSTRACT:
The use of volumetric targets for the automatic merging and orientation of laser scanner acquisitions has been experimented. The
used procedure is fully automatic.
The targets can also be used for the orientation of photogrammetric acquisitions, and allow to have a synergic coupling of different
kinds of surveying. If a calibration grid is used, the absolute coordinates of the cone vertices are known; for larger objects
(architecture), the vertices coordinates can be obtained by a topographic survey.
The procedure described in the article, performs the automatic recognition of the targets, and allows to obtain the coordinates of the
target vertices in the reference system of the laser scanner. The merging and the orientation of the laser scanner acquisitions can be
easily obtained.
The scans of a building facade have been used to perform a test. The coordinates of the target vertices, obtained through the
described procedure, have been comparated with the coordinates obtained by a topographic survey. The distances among the vertices,
obtained using the acquisitions and the topographic survey data, have been compared. The differences are about one millimeter.
1. INTRODUCTION
To build 3Dmodels using laser scanner data, two critical
problems are should be solved:
- Pairwise alignment of the 3D images;
- Global alignment.
To solve this problem, several methods can be followed. For the
mosaicking, some methods use tie points (generally 4 or more)
in two 3D images which are to be merged. One of the most
popular methods is the iterative closest point (ICP) algorithm
developed by Besl and McKay (1992), Chen and Medioni
(1992), and Zhang (1994). An automatic method has been pro-
posed by Akca (2003).
Other procedures use retro-reflecting or volumetric (conical,
cylindrical, spherical) targets. In this case it is possible to
calculate the position and orientation data of the sensor during
acquisition of the 3D images.
If volumetric conical targets are used, the vertices coordinates
have to be determined. In the point cloud acquired by the laser
scanner, the very vertices of the targets are generally not
present. In this case, the interpolation of the point cloud with
the known target surface should be performed.
The interpolation can be obtained by the diagonalization of the
cloud inertia tensor; in this way, the eigenvectors and the
eigenvalues are found, and the coordinates of the vertices are
computed. The biggest problem is due to the unhomogeneous
distribution of the clouds, so it is necessary to assign a weight
to the points. In this case, the procedure is not fully automatic.
In our work, a technique based on the least square method and a
peculiar kind of target is proposed.
2. THE TARGET
The proposed target (Figure 1) is both radiometric and
volumetric. It is constituted by a circular plane base, with a
diameter of 10 centimeters, and a cone, with an aperture of 90?
and a base diameter of 7 centimeters. The top surface of the
base is painted with a white reflecting coating, whilest the
surface of the cone, and the lateral surface of the base have a
not reflecting coating. Different colours can be used. The
targets have been realized with plaster casts using a silicone
rubber mould.
For the test, 9 targets have been positioned using biadhesive
tape.
Figure 1. The conical target
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