CIPA 2003 XIX th International Symposium, 30 September - 04 October, 2003, Antalya, Turkey
Algorithms for automated or semi-automated feature
extraction from 3D point clouds, combined with appropriate
point cloud thinning methods overcome or reduce this
shortcoming of the laser scanner.
photogrammetric point position accuracy is typically highqr
for targeted natural points at short distances (5m to 15 m).
At larger distances the accuracies of photogrammetry and
laser scanning become similar and at distances approaching
100 m laser scanning appears to provide slightly higher
accuracies.
cameras are significantly lighter, easier to transport and
mechanically more robust than laser scanners,
photogrammetrically acquired photography provides
permanent records, allowing originally unplanned
measurements of detail at a later stage
for highly textured surfaces, point clouds can be generated
at higher densities than laser scans. In laser scanning this
disadvantage can be overcome by repeat scans with slightly
modified orientations.
at present, photogrammetric equipment is significantly less
expensive than laser scanning equipment,
photogrammetric procedures are designed to provide
redundancy (Barber et al., 2001), while the laser might
tempt the operator to accept data from a single scan. For the
Kilwa documentation redundancy was achieved for the
principal surfaces by repeat scanning of the same surface
from a different station.
No difficulties were experienced with poor surface reflection.
This can be attributed to the homogeneous surface structure of
the Kilwa buildings, which consist of well reflecting light coral
stones, partly covered with a highly reflecting lime plaster.
At present, the integration of photogrammetry and laser
scanning can be seen as a reliable and accurate method of
documentation. One can, however, anticipate that the above
listed advantages of close range photogrammetry will be
equalled by scanners in the near future. One can expect laser
scanners to be equipped with fully integrated, stable, high
resolution digital cameras, in a configuration which can be
calibrated to create a common geometry for the integrated
system. One can, indeed, venture to predict that laser scanning
will have the same impact on close-range photogrammetry as
GPS had on conventional surveying.
3. DATA PROCESSING
The Kilwa documentation has the dual objective of recording
the structures in Kilwa as well as the development of an
appropriate methodology suitable for documentation of African
heritage sites in general, bearing in mind restrictions in
technical and funding resources and limitations due to difficult
environments. Three approaches were chosen for processing the
acquired imagery and laser scans. 1
1. Sequential processing -photogrammetry employing a
combination of in-house and off-the-shelf software.
2. Integrated processing -photogrammetry employing a stand
alone integrated software programme.
3. Hybrid processing- combination of laser scanning and
photogrammetry.
3.1 Sequential Processing
The photogrammetric processing follows standard procedures
of photogrammetric triangulation (using Australis software),
line drawing (AutoCAD), image matching (in-house software,)
ortho-image generation (in-house software) and 3D modelling,
as for example described in Riither et a, 2001).
3.1.1 Data structure for automated photogrammetry-CAD
transfer. A new model for the data acquisition with Australis
software was developed with a view to an automated transfer of
photogrammetrically digitised feature points into a CAD
system. The following workflow was adopted:
An approximate CAD model was created using tape
measurements of the Gereza’s ground plan (Figure 5).
Figure 5. A bird’s eye view of Gereza’s preliminary
solid model designed for planning purposes
The working model was used to label (code) each point
according to its location within the structure, the feature
type and the location on the feature, according to a pre
designed data structure; for instance, EG1-1 (Figure 6)
refers the first point on the left side of the gate in the East
wall, or EWPW1_1 refers to vertex 1 of window 1 on
Figure 6. East wall and detail of entrance gate
showing an example of the labelling system for
automated point identification in CAD
