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Title
New perspectives to save cultural heritage
Author
Altan, M. Orhan

CIPA 2003 XIX"' International Symposium, 30 September-04 October, 2003, Antalya, Turkey
vision algorithms, which process images taken of a calibration
object. The adopted Tsai camera model (Tsai, 1987) uses 5
parameters (focal length, centre of project, pixel aspect ratio and
1st degree radial distortion). Range information was used to
estimate the external parameters (the translation and rotation of
the camera relative to the global reference frame).
Finally per scan triangulation, based on the 2D grid provided by
the scanner (Turk, 92), was created. The main problem with per
scan triangulation is that the meshes from different scans need
to be merged after triangulation, which can be a difficult task.
nThe final result of laser data processing was a textured 3D
model which can be measured and compare with model.
7.2 Photogrammetric data
The photogrammetric process, described in section 4, provides a
set of geometrical data on the lacked geometry coming from
laser scanner measurement. The lacked geometry has two
different origins: the object is broken (a part of the lips is
destroyed) and a artificial hole was simulates in the belly part to
represent a physical obstacle during the laser scanning phase.
The photogrammetry gave us the photograph orientation, in the
same reference system, a textured mesh obtain with an
automatic measurement process and data to generate theoretical
model.
8. MEASURING OBJECT WITH A THEOTERICAL
MODEL
8.1 Elaboration of a Specific Body
The measurement process proposed in this work is relying upon
the hypothesis of the existence a theoretical model of the
architectural objects studied. We can suggest a theoretical
model for the amphora founded in the Etruscan wreck.
All of these amphorae are of Etruscan origin and have the same
shape as amphorae individualized by A. Py in 1974 (type Py 4)
in a study of the imports to Vaunage and Villevielle (Gard).
Eleven years later, Gras and Slaska completed this initial
classification by proposing a typology of amphora from
Southern Etruria. The type Py 4 and its variants have been
included in the EMD group (for detail see [Py M. et F., 1974]
and the work of Sourisseau, 1997). This regularity in the
production of the amphora allows us to use a modelling
approach and to formalize this knowledge into a hierarchy of
objects sharing the same properties and structured according to
the Object paradigm. The amphorae from the wreck, for the
time being, have been grouped into four sub-classes of the Py 4
type amphorae according to morphological considerations.
8.2 The use of an expert system
The objects heterogeneity handled by the archaeologist and the
geometric complexity of their surfaces led us to search for
stable morphological characteristics of the objects where
diagnostic measurements could be taken. These diagnostic
characteristics are also described in the model.
A series of simple geometric primitives are used to approximate
these morphological characteristics and are used as an interface
between the photogrammetric measurement and the underlying
model. The measurement can have two purposes: object
orientation and position and determine their intrinsic
characteristics.
Fig. 4. The Expert System general schema. Fig.5. Ideal amphora model: from archaeologist design to digital model
The photogrammetric measurement is supported by some
strategic points on the amphora (Fig. 4, on the right side). Five
areas are used to redundantly define the amphora coordinate
system definition parameters. If measurements to certain parts
of the amphora are impossible, the coordinate system
determination mechanism uses relationships between amphorae
(if existent) or default values. The inference problem of values
relying upon incomplete data or data that needs to be re
evaluated is frequent in archaeology.
Obtaining an amphora 3D representation requires a merge of
photogrammetric measurements (S2) and theoretical model
(SI). The technique that we use consists in supplementing
photogrammetric measurements by the theoretical model. These
two data sources give information on the remarkable zones of
the amphorae, defined by an archaeologist (lip, belly, handles,
back, see Fig. 4). It is obvious that the difficulty of the source
merge consists in finding at which time to use a source or the
other. The solution used by our system is the recourse to
propositional logic to formalize the knowledge contained in the
two sources and how to use it. The merging method is provided
by an inference on the logic formalization of the sources which
generates actions to be achieved. Finally the merge is carried
out according to the actions. [Drap, Seinturier, Long, 2003].