International Archives of the Photogrammetry, Remote Sensing 
and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
  
5. APPLICATIONS 
Cultural heritage and space exploration applications are 
presented in this section. Both information augmentation and 
uncertainty management examples are covered. 
5.1 Information augmentation 
The Abbey of Pomposa is one of the most appealing Italian 
churches of the Romanesque period. It is a complex made of 
several architecturally simple buildings with mostly planar 
surfaces. There are also three arches decorated with brick and 
stonework. The main façade is ornamented with several bas- 
relief works of art. Except for those, all the structures have been 
completely modeled using a 4 mega-pixel digital camera. Seven 
different sets of images were acquired including one from low 
altitude airplane and one inside the entrance hall of the church 
(in 2002). The resulting seven models are shown in Figure 9a. 
Details like the left wheel and the peacock carvings (Figure 9b) 
were scanned with our Biris 3D sensor in 1998. The level of 
details of the scanned sections, which was acquired at 0.5 mm 
resolution, is much higher than the other regions. It is more 
convincing when viewing these sections up close while 
navigating through the model. We import points from the 
detailed model (wheel, peacock) along the perimeter of 
common surfaces into the less-detailed model. Then we adjust 
the latter's mesh with the new added points to create a hole into 
which we insert the detailed model without overlaps. Finally, 
points from adjacent models on the borders of the gap are used 
to re-triangulate it so that we have realistic surfaces rather than 
perfect planes in the filled gap (El-Hakim et al., 2003). 
  
a) b) 
Figure 9. Elements used to build the 3D model of the Abbey. 
The goal of this project is to show different methods available 
to model a site for visualization, documentation, preservation 
and remote fruition. Snap shots, one shaded and one textured, 
from the complete model are shown in Figure 10. 
    
Figure 10. Complete site, a) shaded view of 3D model, b) texture 
mapped model. 
5.2 Uncertainty management 
5.2.1 Case 1: Cultural Heritage 
In spite of the detailed information produced by 3D optical 
technologies, in some cases, the method for generating a digital 
model from multiple 3D acquisitions involves the propagation 
of errors. These errors limit the overall metric accuracy 
attainable with such procedure (Jokinen et al., 1998; Okatani et 
al.. 2002). The uncertainty in the alignment of 3D images (pose 
estimation) depends among other things on the range 
uncertainty, the size of the overlapping region between 3D 
images and the curvature of the object surface (Laboureux et 
al.. 2001). For instance, propagation of errors occur when a 3D 
scanner can only produce the targeted spatial resolution and 
range uncertainty within a relatively small field of view (single 
3D image) compared to the overall size of the object or site 
being surveyed. The other troublesome situation presents itself 
when the single 3D image has the required specifications within 
a large field of view but the object or site contains unacceptable 
3D (and texture) features that don’t allow proper locking of the 
3D images between themselves (flat walls, object can’t be 
closed, presence of range artefacts, etc.). A procedure by which 
the metric reliability of the 3D model can be assessed and 
guaranteed to an acceptable level is necessary. Some 
commercial systems are available on the market, which 
combine a 3D scanner and a photogrammetric solution (Colet, 
2003). Unfortunately, very little information in the literature is 
available to a wider public interested in knowing the details of 
the procedure (Scaioni et al., 1996). Guidi et al., 2004 present a 
method aimed at the verification and correction of the accuracy 
of a 3D model of a wooden sculpture obtained through iterative 
alignments of about 170 single 3D images. Though 3D data was 
acquired with a fringe projection system, the same method can 
be used with a laser scanner. Figure 11 shows schematically the 
process where non-impeding optical targets were specifically 
designed for placement around an object like a sculpture. These 
targets are measured using a close range digital 
photogrammetry technique and a 3D scanner. From these 
measurements, transformation matrices are calculated. Each 
matrix allows for the pose calculation of the key 3D images 
from the local coordinate system of the range camera to an 
accurate global coordinate system determined by the digital 
photogrammetric procedure. These key 3D images are locked in 
place and the alignment of the other 3D images proceeds 
normally. For that sculpture (overall dimension of some 180 
cm), the results show a maximum vertical deviation of below 
0.5 mm. Close to an order of magnitude improvement was 
achieved. A metric camera was also used for comparison. 
Digital 
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Figure 11. Example of processing steps and data flow for the 
integration of photogrammetry and 3D scanning systems 
(adapted from Guidi et al., 2004). 
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