supported by radiometric information in the overlapping area 
and that reliability and robustness of results is increased and 
validated by an independent control. 
Approaches for the fusion of independent clouds of points have 
been given e.g. by (Besl & Mc Kay, 1992), (Neugebauer, 1997) 
and others. Data fusion there is in general a two step procedure 
consisting of registration and integration of point clouds, with 
registration being the determination of transformation 
parameters which merge separate point clouds into a common 
co-ordinate system. Registration of 3D point clouds has been 
described in detail by (Besl & Mc Kay, 1992) where the root 
means square error of distances is used to determine the 
unknown transformation parameters. The integration of 
overlapping point clouds is the next step which assures, that a 
part of a surface is described by separate points unequivocally. 
(Turk & Levoy, 1994) show the integration of a surface net by 
intersection, (Neugebauer, 1997) proposes to describe object 
space by volume elements (voxels) and to sculpture a surface 
from a solid volume. Here, no support of radiometric 
information has been used for registration or integration up to 
now. However, there are first approaches in this direction. 
(Gühring, 2001) presents how data can be acquired and 
processed considering adequate co-variances in the processing 
step and (Sequeira, 1999) besides geometric reconstruction uses 
radiometric information for visualisation purposes. 
  
Figure 1. Rendered test surface 
2. EXPERIMENT 
In order to validate a controlled process of data fusion trough 
numerical experiments, two surfaces from close range 
measurement applications are used. Both objects represent free 
form surfaces of different type which appear in measurement 
tasks frequently. 
The objects have been acquired by a stripe projecting device 
and also by a digital camera. The digital images have been 
plotted by means of stereo-photogrammetry and also by means 
of a multiple-image approach separately. 
The results of a common adjustment of 3D points and intensity 
images using different weights for the observations are 
presented and interpreted considering improvements of the 
procedure and insight into correct weighting of measurements. 
2.1 Surfaces 
The first object has especially been prepared for control 
purposes, cf. figure 1, the size is 100 x 100 mm? and the 
material is aluminium. It has a surface precisely defined by 
discrete points which were used for the production of the object 
in a milling machine. The precision of the production can be 
considered superior to the measurement devices used but as 
systematic effects will be described later, no assumptions will 
be introduced beforehand. 
Furthermore the surface is continuous and opaque but isotropic 
and is not textured. In order to prepare the surface for 
photogrammetric acquisition, a chalk spray has been utilised 
and texture has been applied by a projecting device. 
The second object is a gravelled tile of concrete and, thus, has a 
much more rough and structured surface than the first object, cf. 
figure 2. The plotted size of the object is 125 x 125 mm? An 
ideal geometric model of this surface should be a real 3D 
description, but here only a 2 1/2 D model has been used. From 
this, deficiencies of the result are expected. Furthermore, the 
texture of the surface has not been improved by projection. 
  
Figure 2. Rendered concrete surface 
2.2 Instrumentation 
Both surfaces have been measured with the stripe projecting 
device ATOS HR of Gesellschaft fiir Optische Messtechnik 
mbH (GOM), the digital images were taken with a consumer 
camera Fuji Finepix S1 Pro. 
The stripe projector is designed for digitisation of free form 
surfaces and uses an analogue projector and two CCD-cameras. 
Depending on the size of the object to be measured, different 
lenses with varying focal length can be used. From this, 
distances between points in object space vary from 0.06 to 0.6 
mm having an accuracy of 0.005 to 0.05 mm, (GOM, 2002). 
The greatest influence on the accuracy of the system is due to 
the instability of the projecting device caused by temperature 
effects. An object is now measured by projecting unequivocal 
patterns on the surface and plotting the reflected patterns which 
have been registered by the cameras. 
The photogrammetric registration with Fuji Finepix S1 Pro 
yielded 8 bit images with 2304 x 1536 picture elements. The 
lens had a focal length of 28 mm and was calibrated 
simultaneously. 
—106— 
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