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Unwrapping Highly-Detailed 3D Meshes of Rotationally Symmetric Man-Made Objects

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Rotationally symmetric objects commonly occur at archæological finds. Instead of creating 2D images for documentation purposes by manual drawing or photographic methods, we propose a method based on digitally colored surface models that are acquired by 3D scanners, thereby including color information. We then transform these highly-detailed meshes using simple geometrical objects such as cones and spheres and unwrap the objects onto a plane. Our method can handle curved vessel profiles by dividing the surface into multiple segments and approximating each segment with a cone frustum that serves as an auxiliary surface. In order to minimize distortions, we introduce a simple quality measure based on distances of points to a fitted cone. We then extend our method to approximately spherical objects by fitting a sphere on the surface of the object and applying a map projection, namely the equirectangular projection known from cartography. Our implementation generates true-to-scale images from triangular meshes. Exemplary results demonstrate our methods on real objects, ranging from small and medium-sized objects such as clay cones from the Ancient Orient and figural friezes of Greek vessels to extremely large objects such as the remains of a cylindrical tower of Heidelberg Castle.
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UNWRAPPING HIGHLY-DETAILED 3D MESHES OF
ROTATIONALLY SYMMETRIC MAN-MADE OBJECTS
Bastian Rieck, Hubert Mara, and Susanne Kr¨
omker
Interdisciplinary Center for Scientific Computing, Heidelberg University, Germany
{bastian.rieck, hubert.mara, kroemker}@iwr.uni-heidelberg.de
KEY WORDS: Archæology, Cultural Heritage, Geometry, High resolution, Rendering, Visualization, Colour
ABSTRACT:
Rotationally symmetric objects commonly occur at archæological finds. Instead of creating 2D images for documentation purposes
by manual drawing or photographic methods, we propose a method based on digitally colored surface models that are acquired by 3D
scanners, thereby including color information. We then transform these highly-detailed meshes using simple geometrical objects such
as cones and spheres and unwrap the objects onto a plane. Our method can handle curved vessel profiles by dividing the surface into
multiple segments and approximating each segment with a cone frustum that serves as an auxiliary surface. In order to minimize distor-
tions, we introduce a simple quality measure based on distances of points to a fitted cone. We then extend our method to approximately
spherical objects by fitting a sphere on the surface of the object and applying a map projection, namely the equirectangular projection
known from cartography. Our implementation generates true-to-scale images from triangular meshes. Exemplary results demonstrate
our methods on real objects, ranging from small and medium-sized objects such as clay cones from the Ancient Orient and figural
friezes of Greek vessels to extremely large objects such as the remains of a cylindrical tower of Heidelberg Castle.
1 INTRODUCTION
Due to the demand by archæologists for a fast and accurate docu-
mentation as well as analysis of small ancient objects, close-range
3D scanners are increasingly used within museums and on exca-
vation sites (Sablatnig and Menard, 1992). These man-made ob-
jects are manufactured from various materials, and they are often
rotationally symmetric. Furthermore, many of them depict lots
of details, such as iconographic imagery, ornamental paintings
or inscriptions. While parallel projections and cross-sections are
used to show the general shape of an object (Orton et al., 1993),
the details along the surface have to be unwrapped. Tradition-
ally, unwrapping an object is a time-consuming task requiring
either a highly skilled draftsperson or special equipment for roll-
out photography (Lynch-Johnt and Perkins, 2008). Fig. 1 shows
an example of unwrapped conical friezes of an ancient vessel.
1.1 Related work
Previous research in photogrammetry used cylinder fitting for un-
wrapping 3D surfaces with known analytical expressions (Karras
et al., 1996). Likewise, cartographic projections have already
been proved useful for obtaining raster images of paintings on
arches and spherical surfaces (Karras et al., 1997). More recent
works uses triangle strips that are adjusted to the surface of arbi-
trary objects in order to unfold them (Massarwi et al., 2007). A
detailed body of methods for unwrapping spherical objects can be
found in cartography (Grafarend and Krumm, 2006). Our method
enables experts of cultural heritage to rapidly compute planar rep-
resentations of cultural heritage objects for important tasks such
as iconographic analysis. These planar representations cannot be
substituted by 3D models e.g. via the Internet, because tasks such
as historic interpretations require all parts of an object to be visi-
ble.
The simplest geometric primitive for an unwrapping transforma-
tion is the cylinder. It has already been used for 3D models of
ancient cylinder seals (Pitzalis et al., 2008). Since the cylinder is
a degenerate cone, we focus on unwrapping approximately coni-
cal objects in the next section. However, as there is a vast number
of objects with a spherical shape, we also show how to unwrap a
sphere.
1.2 Data format
In the following, we assume that the user is working with 3D
representations of cultural heritage objects, such as ceramic ves-
sels or cuneiform tablets. We require an object to be specified as
atriangular mesh, e.g. in Stanford Triangle Format (PLY). This
mesh is composed of vertices, i.e. points in R3, and faces, i.e.
triangles consisting of three distinct vertices. The edges of the
faces are described implicitly by this representation. Triangular
meshes are commonly used and generated by most of commer-
cial 3D scanners: Three non-collinear vertices always define a
plane and allow for the simple calculation of normals and other
properties of the faces.
Figure 1: Unwrapping both figural friezes of a vessel (KHM Inv.-
No. 3618 ) by fitting two different cones (Bechtold et al., 2010).
2 DEVELOPABLE SURFACES
In this part of the paper, we will focus on developable surfaces
that can be unwrapped without any distortions. The unwrapping
transformation is bijective, i.e. it can be reversed without loss of
accuracy. For simplicity, we only talk about finite cones and cone
frusta, i.e. truncated cones. We will later generalize these tech-
niques to unwrap cylinders, as well.
2.1 Fitting a cone frustum
Many ceramic vessels can be described by conical shapes. Typi-
cally, the objects are at least approximately rotationally symmet-
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W1, 2013
XXIV International CIPA Symposium, 2 – 6 September 2013, Strasbourg, France
This contribution has been peer-reviewed. The double-blind peer-review was conducted on the basis of the full paper.
259
ric due to their manufacturing process, which uses a rotational
plate. In most cases, one can think of vessels as being comprised
of several cone frusta. Usually, two or three frusta are sufficient
for unwrapping these vessels—see Fig. 1 for a typical example.
For fitting a cone frustum, we let the user interactively specify an
axis of the cone as well as two points on the surface of an object.
We then calculate the height of the truncated cone by projecting
the selected points to the cone axis. The upper and lower radius of
the cone are then determined by the position of the points selected
by the user. Furthermore, by employing cone frusta, the user can
exclude regions of the vessel that are removed upon unwrapping
the object. This is useful when the user is interested in a depiction
around the middle of the vessel, but does not want to include han-
dles or the base of the vessel. From an algorithmic point of view,
this approach of cone fitting offers additional possibilities: (i) The
process of determining a rotational axis may be automated. In re-
cent publications (Mumford and Cao, 2002, Mara and Sablatnig,
2006), methods for automatically finding the best rotational axis
have been introduced. (ii) If an axis has been determined, numer-
ical fitting methods can be applied in order to find the optimum
radii of the cone frustum with respect to some quality measure,
such as minimized squared distances (Strutz, 2010).
2.2 Cone distance calculation
When unwrapping an arbitrary object that is not a perfect cone,
we want to minimize any distortions occurring due to the trans-
formation. To this end, we need to define a quality measure. In
the case of a complete cone, we use the distance of each point of
an object to the fitted cone as a simple quality measure. When
fitting a cone frustum, this method has the advantage of deter-
mining whether a point is located above or below the planes of
the cone frustum such that distance calculations are not neces-
sary. In these cases, the corresponding vertices are skipped and
will not be processed any further. This greatly improves the speed
of the unwrapping transformation.
For calculating the cone distance, we assume that the cone is sit-
uated in the origin of the coordinate system and opens towards
the positive y-axis. The main idea is to use the angle γ=βα
between the position vector of the vertex and the vector along the
surface of the cone. With Fig. 2 depicting the required angles, we
obtain
dist(p) = sin(γ)· kpk=d, (1)
where kpkis the Euclidean norm of the vector connecting the
apex of the cone and p. If the angle βbecomes larger than π/2,
we set dist(p):=kpk.
When fitting a cone frustum, we use the same distance calculation
as defined above. In addition, we check whether the orthogonal
projection of a query point onto the y-axis is outside the frustum.
If so, we assign the point a semi-transparent colour. Points whose
distances are defined, on the other hand, will be drawn using a
heat map colour ramp. This enables the user to see the quality of
the fitted cone frustum in one glance—see Fig. 3.
2.3 Unwrapping a cone
Before unwrapping a cone, we first transform the object and the
cone into a local coordinate system with the axis of the fitted cone
being the y-axis of the coordinate system. This transformation
simplifies later calculations. See Fig. 4 for the current setting.
We describe the required formulæ and refer to (Bechtold et al.,
2010) for a more detailed derivation. For simplicity, we express
the coordinates of the vertices in a conical coordinate system, i.e.
one that employs an angle ϕiand a height hito uniquely describe
the position of a point pion the surface of the cone.
β
α
γ
p
d
y
x
Figure 2: Angles used for calculating the distance to a cone.
Figure 3: Heat map visualization of the distance to a fitted cone.
Due to the high curvature of the vessel (KHM Inv.-No. 3601)
larger distances at the middle part of the frustum are visible.
Unwrapping a cone is of the points of the object. Since the maxi-
mum height of a point in the conical coordinate system is given as
h, whereas the unwrapped cone has a maximum polar radius of
s, we require some sort of scaling. The same applies to the vertex
angles: In the conical coordinate system, they span the half-open
interval of [0,2π), whereas they are limited by an angle θin the
plane of the unwrapped cone. From Fig. 4, we obtain the ratio
2πr
θ=2πs
2πθ= 2πr
s.(2)
Consequently, the angle scale factor λis given as
λ=r
s= sin(α).(3)
For the height scale factor µ, we observe that a point at height h
will be transformed to height swhen being unwrapped. Hence,
µis given as
µ=s
h=1
cos(α).(4)
We thus arrive at the following transformation for vertices:
Tc(ϕi, hi) = (λϕi, µhi)(5)
This handles the unwrapping of a cone that is centered along the
y-axis of the coordinate system.
2.4 Unwrapping a cone frustum
In the case of a cone frustum, care must be taken only to apply this
transformation to vertices that are contained between the upper
and lower plane of the cone frustum. To describe a cone frustum,
we require an axis, which is again supposed to be the y-axis of
the coordinate system, and two limiting planes perpendicular to
the y-axis. We determine these limiting planes by specifying an
upper position yuand a lower position yl, with yl< yu. The two
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W1, 2013
XXIV International CIPA Symposium, 2 – 6 September 2013, Strasbourg, France
This contribution has been peer-reviewed. The double-blind peer-review was conducted on the basis of the full paper.
260
s
h
r
αT
2πr
θ
s
y
x
y
x
Figure 4: Depiction of the unwrapping process of a cone. Note
how angles and heights of the points on the cone are changed.
positions then yield a simple and criterion for the transformation
function Tfof a cone frustum:
Tf(ϕi, hi) = ((λϕi, µhi)hi[yl, yu]
undefined else (6)
In practice, we let the user interactively select two points on the
surface of a digital object. From these two points, we obtain an
upper radius ruand a lower radius rl, with rl< rubecause
we require the apex of the complete cone to be the origin of the
coordinate system. We then calculate the respective y-positions
required for Eq. (6):
yu=ru
tan(α), yl=rl
tan(α)(7)
In this section, we exploited the fact that the cone axis is the y-
axis of the coordinate system.
In many cases, the user wants to center the projection of the cone
on a certain angle, be it to highlight a certain figurative element
on a vessel or to push handles to the side where the cone is split.
Following usage in cartography, we call this process selecting
a prime meridian. In mathematical terms, this is accomplished
by applying a fixed offset σ[π, π)to the projected vertex
coordinates, i.e. θi:=θiσ, and then normalizing the vertex
angle θito a range of [π, π). Likewise, we have a splitting
meridian, i.e. the angle opposite to the prime meridian. This is
where the cone will be ‘split’ when being unwrapped to the plane.
2.5 Unwrapping a 3D mesh
So far, we have only discussed the unwrapping of a perfectly con-
ical object. In practice, objects are approximately conical at best
and may consist of multiple layers. In order to apply the trans-
formation described in Eq. (6), we perform the following steps
for each vertex pi= (xi, yi, zi)T: (i) Determine coordinates
ϕi= arctan (zi/xi),hi=yiof vertex within the conical co-
ordinate system. (ii) Obtain radial distance ri=px2
i+z2
iof
vertex with respect to cone axis. (iii) Set new coordinates of ver-
tex to be (x
i, y
i, z
i):= (Tf(ϕi, hi), ri).
The second step solves the depth-sorting problem (Foley et al.,
1997, pp. 673–686): Digital objects acquired with a structured
light scanner do not have an infinitely thin surface. Instead, each
object is composed of an inner and outer shell. The transforma-
tion described in Eq. (6) is 2D, which means that points of all
layers would be projected on top of each other. By using a radial
distance, we obtain a 3D object with the correct depth order—see
Fig. 5 for an example.
The mesh consists of discrete data points in R3. Therefore, re-
moving all points whose distances are undefined results in trun-
cated triangles and rough edges along the upper and lower part
Figure 5: An unwrapped version of an approximately conical ves-
sel, UMJ Inv.-No. 4611 (Karl et al., 2009), that has been rotated
to convey the depth information. The highlighted contour is the
cross-section at the splitting meridian. This line is identical to the
profile line as drawn by archæologists (Orton et al., 1993).
of the fitted cone. Truncated triangles, in turn, appear as jagged
edges in the resulting object. As a remedy, we implemented an
algorithm employing splitting planes. The main idea is to define
a plane in Hesse normal form, and intersect it with the object. The
intersection will create points that are situated on the plane, along
the edge of a triangle. By re-triangulating the existing points, the
object may be split seamlessly along the plane.
3 NON-DEVELOPABLE SURFACES
In the following, we will handle spheres and the equirectangular
projection only. However, the methods presented in this section
can be generalized to use any cartographic projection or transfor-
mation operation.
3.1 Fitting a sphere through four points
If a vessel has spherical characteristics, unwrapping the object by
using a sphere instead of a cone yields better results. We let the
user choose four points {(xi, yi, zi)T|i= 1 . . . 4}on the surface
of the object. By solving a determinant equation,
det
x2+y2+z2x y z 1
x2
1+y2
1+z2
1x1y1z11
x2
2+y2
2+z2
2x2y2z21
x2
3+y2
3+z2
3x3y3z31
x2
4+y2
4+z2
4x4y4z41
= 0,(8)
we obtain a general equation for the sphere; see (Osgood and
Graustein, 1921), pp. 524526, for a detailed derivation. Ex-
panding the determinant by minors M1i, we get
(x2+y2+z2)M11 xM12 +yM13 zM14 +M15 = 0.
The implicit equation of a sphere of radius rcentered at a point
(x0, y0, z0)Tis given by (xx0)2+(yy0)2+ (zz0)2=r2.
Equating the terms of the last two equations yields both radius
and center of the sphere:
x0=1
2·M12
M11
, y0=1
2·M13
M11
, z0=1
2·M14
M11
r2=x2
0+y2
0+z2
0M15
M11
(9)
In Eq. (9), M11 is required to be nonzero. If this is not the case,
we may assume that the points are either coplanar or three of the
points are collinear. Consequently, fitting a sphere through these
points is impossible.
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W1, 2013
XXIV International CIPA Symposium, 2 – 6 September 2013, Strasbourg, France
This contribution has been peer-reviewed. The double-blind peer-review was conducted on the basis of the full paper.
261
pi
θi
ϕi
Ts
θ
ϕ
2π
π
2
π
2
p
i= (ϕi, θi)
Figure 6: The equirectangular projection of a unit sphere.
Figure 7: An aryballos, UMJ Inv.-No. 8738 (Karl et al., 2009), a
vessel with a spherical shape that is well-suited for the equirect-
angular projection. Note that the sphere does not envelop the
object. This signifies that the object is not perfectly spherical.
3.2 Equirectangular projection of spherical meshes
We assume that points of a perfectly spherical object are given
and that the center of the sphere is the origin of the coordinate
system. Having described the sphere on which they are situ-
ated, we are now able to perform an equirectangular projection,
thereby unwrapping the sphere to the plane. To accomplish this,
we convert the Euclidean coordinates of the points of the object
into spherical coordinates: Let a point in R3be described by
pi= (xi, yi, zi)T. Then the corresponding spherical coordi-
nates are given by
ri=qx2
i+y2
i+z2
i
ϕi= arctan zi
xi, θi= arcsin yi
ri(10)
and we obtain the following projection function:
Ts(ri, ϕi, θi) = (ϕi, θi)(11)
Fig. 6 depicts the relation between spherical coordinates and the
resulting equirectangular projection. Note that a variant of the
equirectangular projections scales all points by the radius rof the
sphere. This ensures that the projection is true to scale.
3.3 Equirectangular projection of arbitrary meshes
Eq. (11) is insufficient for arbitrary meshes: Not all vertices of the
object may be situated on the outside of the same sphere. Since
we lose all depth information, different vertices would overlap—
this is essentially the same problem that occurs when unwrap-
ping arbitrary 3D meshes using cone frusta. We hence again use
the radius of the spherical coordinates in order to add depth in-
formation. This yields the following procedure for each point
pi= (xi, yi, zi)T: (i) Fit a sphere to the object and make the
center of the sphere the new origin of the coordinate system.
(ii) Determine spherical coordinates ri,ϕi,θifor piby using
Eq. (10). (iii) Set new coordinates of point to be (x
i, y
i, z
i)T:=
(a) Manual drawing
(b) Equirectangular projection
(c) Distances to the fitted sphere
Figure 8: A comparison of a manual drawing (courtesy of S. Karl)
and the equirectangular projection for the aryballos in Fig. 7.
(Ts(ϕ, θ), ri). This transformation ensures that the outside of
the original object remains the outside of the projected object.
Hence, we again obtain a 3D projection, which may be used for
further post-processing, such as detecting curvature, inscriptions,
and other surface details. Fig. 7 depicts a vessel that is well-
suited for an equirectangular projection along with a fitted sphere.
The result of the projection operation for this object is shown by
Fig. 8.
4 RESULTS
As this work was originally motivated by the Austrian Corpus
Vasorum Antiquorum (CVA) project, we provided 25 unwrapped
vessels for CVA volume Austria 5 (Kratzm ¨
uller, 2014). All the
final images are orthographic projections and hence true to scale.
Our implementation can create high-resolution raster images of
the transformed objects by using OpenGL-based tiled rendering
techniques. Examples are shown in the previous sections. Fig. 1
depicts the usage of multiple cones for one vessel, while Fig. 10
shows the difference between unwrapping transformations using
a cone and a sphere.
Cuneiform tablets from the Ancient Orient have their details rep-
resented within geometry. These ancient hand-writings become
only visible when properly illuminated e.g. by bright sunlight.
While virtual illumination is a global operation, we used local
filters based on Multi-Scale Integral Invariants (MSII) (Mara et
al., 2010) to compute a false colour texture map that highlights
curvature-related features. An example of cuneiform inscription
and such texture maps on a clay cone are shown in Fig. 9.
Finally, we demonstrate the independence of scale and acquisi-
tion device by applying the unwrapping transformation to one of
the towers of Heidelberg Castle, namely the famous ruins known
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W1, 2013
XXIV International CIPA Symposium, 2 – 6 September 2013, Strasbourg, France
This contribution has been peer-reviewed. The double-blind peer-review was conducted on the basis of the full paper.
262
as the Pulverturm (powder tower). Together with the Institute of
Geography, Heidelberg University, we documented the present
conditions of this part of the castle using Terrestrial Laser Scan-
ning (Siart et al., 2012) with a Riegl VZ-400. Fig. 11 shows the
tower and its 3D model.
For the model of the Pulverturm, we extended the techniques
from Section 2.5 to unwrap cylinders, as well: A cylinder is a
degenerate cone whose upper and lower radius are equal. This
equality yields a cone angle of α= 0, but, following Section 2.4,
we can still use an angle ϕiand a height hito uniquely describe
the position of a point pion the surface of the cylinder. With the
notation of Section 2.3, Eq. (3) evaluates to λ= 0, while Eq. (4)
evaluates to µ= 1. Since λ= 0, the transformation function
from Eq. (5) maps all angles ϕito 0, which is incorrect. We han-
dle this by setting Tcyl(ϕi, hi) = (i, hi), where rdenotes the
radius of the fitted cylinder. Scaling the angle ϕiwith rensures
that the transformation is true to scale. Using the previous equa-
tion, we then proceed as described in Sec. 2.5. The result of the
transformation is shown in Fig. 11.
5 CONCLUSIONS AND FUTURE WORK
The work shown in this article demonstrates the use of elemen-
tary geometry to unwrap high-resolution 3D meshes of highly
detailed objects of cultural heritage. The presented algorithms
were successfully tested on a large number of real-world 3D data
from archæological projects. Due to this interdisciplinary work,
we can suggest several improvements: (i) For some types of ob-
jects, it may be advantageous to use standard cartographic projec-
tions. There are many projections available offering a variety of
different results: Some preserve angles, while others preserve ar-
eas. For further discussion regarding several cartographic meth-
ods, we refer to (Grafarend and Krumm, 2006). (ii) Future ad-
ditions to our framework will be the usage of primitives such as
ellipsoids or parameterizable surfaces. (iii) To improve the color
representation, flashlights can be added to cancel shadows dur-
ing acquisition of the texture-map of the 3D model as described
by (Dellepiane et al., 2010).
ACKNOWLEDGMENTS
We would like to thank Dir. Dr. Alfred Bernhard-Walcher and Dr.
Bettina Kratzm¨
uller of the collection of antiquities of the Kun-
sthistorisches Museum, Vienna, as well as Stephan Karl from
Graz University for kindly authorizing us to present images of
items from the respective collections. For the collaborative work
on cuneiform tablets we thank the Assyriology Group, Heidel-
berg University, and the Assur Forschungsstelle of the Heidelberg
Academy of Sciences and Humanities.
For data acquisition and post-processing of the terrestrial laser
scan data, we thank Markus Forbriger and Larissa M¨
uller of the
Institute of Geography, Heidelberg University. Access to the Pul-
verturm was kindly granted by Heidelberg Castle administration
and plans were provided by Dr. Claudia Mohn.
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Strutz, T., 2010. Data Fitting and Uncertainty: A Practical In-
troduction to Weighted Least Squares and Beyond. Vieweg and
Teubner.
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W1, 2013
XXIV International CIPA Symposium, 2 – 6 September 2013, Strasbourg, France
This contribution has been peer-reviewed. The double-blind peer-review was conducted on the basis of the full paper.
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(a) Illuminated 3D model
(b) Distances between the cone and the 3D model, unwrapped model, and color ramp.
(c) MSII filter responses, unwrapped model without virtual illumination, and grayscale ramp.
Figure 9: 3D model of a building inscription with cuneiform characters on a Tonnagel (clay cone), ca. 22002000 B.C., Sammlung des
Seminars f¨
ur Sprachen und Kulturen des Vorderen Orients, Assyriologie, Universit¨
at Heidelberg. For information about the inscription
and its known 451 ancient duplicates see (Steible, 1991, Text Ur-Baba 7).
Figure 10: Oinochoe, UMJ Inv.-No. 4181 (Karl et al., 2009). From left to right: A scanned version of the object, an unwrapped variant
using a cone, and the result of the equirectangular projection. Unpainted parts of the vessel have been discarded.
Figure 11: Pulverturm of Heidelberg Castle. Left: Photograph of the tower and the Riegl VZ-400 Terrestrial Laser Scanner. Middle:
Orthographic, true-to-scale, isometric view of the 3D model with the realigned wall fragment. The cylinder for the unwrapping
transformation has a radius of 12m and is shown in red color. Right: Perspective front view of the unwrapped 3D model.
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W1, 2013
XXIV International CIPA Symposium, 2 – 6 September 2013, Strasbourg, France
This contribution has been peer-reviewed. The double-blind peer-review was conducted on the basis of the full paper.
264
... Generating rollouts of rotation-symmetric objects represent an important computational tool for enhancing perception. It was applied on cylindrical seals [Pitzalis et al. 2008;Dahl et al. 2018] or on pottery with curved vessel profiles using frustum-shaped cones or clipped off spheres as proxy geometry [Bechtold et al. 2010;Mara and Portl 2013;Rieck et al. 2013]. The lastmentioned methods are implemented in the open access GigaMesh software framework 1 , freely available with video tutorials 2 . ...
... The equirectangular projection is shown in Figure 5 and has proven most suitable for painted pottery among the rollouts using cones and cylinders as well as their combinations [Bechtold et al. 2010;Rieck et al. 2013]. It has no distortions along the longitudinal lines. ...
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Unwrappings are crucial in archaeological pottery studies. Within the study of Greek pottery, unwrappings of painted surfaces have a long tradition and their significance is still well-deserved. They show the depiction without photographic distortions or partitioning in multiple photographs, enabling archaeologists to analyse and interpret the image as a whole. This is especially true in the case of Corinthian pottery, where the poor preservation of the painting tending to flake off often results in unclear photographs. Nevertheless, traces of flaked off painting layers are still visible on the surface under specific illumination. Creating unwrappings manually is time-consuming. Manual acquisition with tactile tools like tracing paper is often not allowed due to the fragile nature of the surfaces. To facilitate this task for pottery archaeologists, a combination of 3D data derived by "Structure-from-Motion" (SfM) and "computed tomography" (CT) is proposed, where each technique can also be on its own. The fusion of these data sources to exploit their specific strengths is a new approach in the field of "Cultural Heritage" (CH): SfM with a high resolution in texture and CT with a high accuracy in geometry. The SfM and CT data are combined by transferring colour information to the vertices of the CT model. Afterwards, the GigaMesh Software Framework was used for enhancing geometric features in the surface data, in this study case, the fine incisions of the black-figure painting. With this approach, accurate and sufficiently detailed unwrappings aligned to the needs of pottery specialists can be created in minimum time.
... Developable surfaces can be "unfolded" on a plane without any deformation. This operation is bijective and can be reversed with no loss of accuracy [7]. ...
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... Today, various 3D mesh processing and visualisation tools, like the GigaMesh Software Framework (Mara et al. 2021) or CloudCompare (Girardeau-Montaut et al. 2021), allow to perform such unwrappings directly on a virtual 3D model of a vessel (Rieck et al. 2013;Karl et al. 2019). They utilise proxy geometries that exhibit a simple surface of revolution (cylinder, cone, sphere) that best approximates the vessel shape. ...
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This paper focuses on digitally-supported research methods for an important group of cultural heritage objects, the Greek pottery, especially with figured decoration. The design, development and application of new digital methods for searching, comparing, and visually exploring these vases need an interdisciplinary approach to effectively analyse the various features of the vases, like shape, decoration, and manufacturing techniques, and relationships between the vases. We motivate the need and opportunities by a multimodal representation of the objects, including 3D shape, material, and painting. We then illustrate a range of innovative methods for these representations, including quantified surface and capacity comparison, material analysis, image flattening from 3D objects, retrieval and comparison of shapes and paintings, and multidimensional data visualization. We also discuss challenges and future work in this area.
... Figure 1 displays the schematic diagram of the proposed algorithm, which consists of three steps. First, the CT surface data of the patient's head are transformed into a 2D image using spherical unwrapping, since the head's surface data are similar to a sphere [28]. Similarly, the surface measurement data obtained with the sensor are also converted to a 2D image using spherical unwrapping and the mean radius computed from the CT surface data. ...
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... Hence, more sophisticated techniques create a planar projection of the 3D surface as a whole. This can be achieved by projecting the surface texture onto a shape primitive, e. g. cylinder, cone or sphere, fitted to the given geometry, which is then unwrapped virtually [17,18]. The projective distortions introduced with this method can then be reduced with an elastic relaxation [19]. ...
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A complex of enclosed karst depressions near Kritsa-Latô (Dikti Mountains, Eastern Crete) was analysed with regard to its surface and subsurface topography using a new multi-method approach. Based on a combination of terrestrial laser scanning, electrical resistivity tomography and geographic information systems, crucial geophysical and morphometrical parametres were derived and correlated with sedimentological results in order to provide first-time insights into the formation, size and archive function of dolines. High-resolution digital elevation models (0.25 m, 2 m) allowed conducting topographical analyses with special respect to micro-relief attributes and traces of former land use, as well as placing all findings into a 3D context for enhanced interpretation. As shown by the results, both limestone dissolution and local tectonics led to the development of an extensive sediment trap, whose subsurface is characterised by a distinct three-part segmentation. Above the bedrock, a highly fractured epikarst zone exhibits features typical of buried karst systems, such as subterraneous sinkholes and pinnacles. In contrast, the near-surface section completely consists of fine-grained, loamy substrates. Despite thicknesses of up to 25 m, the loose infilling entirely lacks stratification and therefore indicates permanent low energetic colluviation processes under rather stable geomorphodynamic conditions during the Quaternary. In respect to the local human impact, several geophysical anomalies suggest the existence of an ancient water harvesting system, which quite likely dates back to Minoan or Dorian times. As water supply must be considered essential for agricultural purposes in the karstified mountains of Crete, the Kritsa dolines must have served as favourable locations for settlement and land use purposes. With the the help of the multi-technique approach, both the geomorphological and the geoarchaeological characteristics of the study area could be captured. The findings help improve the understanding of the landscape evolution and the associated man-environment interactions in Eastern Crete. Combining terrestrial laser scanning and tomographical mapping proves to be particularly suitable for integral surface and subsurface prospecting and therefore promises substantial potential for future studies.