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3D LOW-COST ACQUISITION FOR THE KNOWLEDGE OF CULTURAL HERITAGE:
THE CASE STUDY OF THE BUST OF SAN NICOLA DA TOLENTINO
Alessio Cardaci1*, Antonella Versaci2, Pietro Azzola1
1School of Engineering, University of Bergamo, Italy
2Faculty of Engineering and Architecture, University of Enna ‘Kore’, Italy
alessio.cardaci@unibg.it – antonella.versaci@unikore.it – pietro.azzola@unibg.it
Commission II
KEY WORDS: cultural heritage, virtual museum, videogrammetry, Sant’Agostino Church, Bergamo.
ABSTRACT:
The creation of three-dimensional models for the cataloguing and documentation of cultural heritage is today an emerging need in
the cultural sphere and, above all, for museums. The cultural heritage is still catalogued and documented based on descriptive les
assorted of photographic images which, however, fail to outline its spatial richness, possible only through the use of 3D artefacts. The
essay aims to propose a methodology of digitalization by low-cost and easy-to-use systems, to be employed even by non-expert survey
and photogrammetry’s operators. The case study of the statue of San Nicola da Tolentino, preserved at the Sant’Agostino complex in
Bergamo, oered the possibility of a comparison between 3D models acquired with dierent digitalization tools (professional/action/
amateur cameras and smartphone) and processed by several image-based 3D Reconstruction software and methods.
1. INTRODUCTION
The use of 3D digital platforms for the documentation, enhan-
cement and communication of cultural heritage is a very recent
practice and, perhaps, still not widely spread. Most of the pieces
of art in heritage collections are catalogued based on descriptive
sheets assorted of photographic images, which, nevertheless, fail
to outline their spatial richness, possible only by three-dimensio-
nal models. This is both due to the diculties in designing com-
plex interfaces for the use, sharing and dissemination of 3D data,
and in quickly creating virtual models, also accurate and faithful
in their geometries and colours.
The videogrammetry, if operated with the strict application of
a scientic method, even by using not particularly sophisticated
instrumentation, oers the possibility of producing in a short
time and in a simple way, three-dimensional documentation of
the cultural heritage in line with the Italian national standards
used for the cataloguing of the cultural patrimony (ICCD) and of
adequate quality for online broadcasting. Specically, low-cost
videogrammetry can be useful for the creation of 3D models of
those artworks that are often neglected and wrongly dened as
‘minor’ because considered of lower value, to which investments
for digitization are more rarely consecrated. It can also help in
highlighting the relationships with the historical context in which
this cultural heritage was produced and to which was related, as
well as those existing with the physical ‘container’ (a building,
an architectural complex or territorial space) where today it is
hosted and preserved.
This work intends to compare the results obtained through both
dierent acquisition systems (professional cameras, action came-
ras, amateur cameras and smartphones) and operating methods
employing several image-based 3D reconstruction software
(3DFlow Zephyr, Agisoft Metashape and Pix4D Mapper Pro).
The objective is to provide a solution that endures for the right
balance between a simplied practice and a quality sucient for
the determinations of the virtual museum.
2. THE BUST OF SAN NICOLA DA TOLENTINO
IN THE OLD CHURCH OF SANT’AGOSTINO
The Sant’Agostino complex in Bergamo is an ancient convent,
whose foundation dates back to the end of the 13th century, which
is today the seat of the local university. It sticks out on a plateau
close to the Venetian Walls, of which it has modied the layout,
near the homonymous door on the way to Venice. In the past,
this place had a strategic role in the defence of the city because
it ‘guarded’ the easternmost part of the Bergamo fortications,
which was also the weakest one as located at the bottom of the
hill and sloped down towards the plain (Cardaci & Versaci, 2016;
Cardaci et al, 2019).
The convent was suppressed in the 18th century following the
descent into Italy by Napoleon and the proclamation of the Ci-
salpine Republic. The patrimony of the Augustinian order was
conscated and the complex transformed into a barracks. The
assets of the church - paintings, sacred furnishings, altars - were
sold to noble and wealthy families, or donated to other churches
(Damiani et al, 2016).
The project of reconstruction of the decorative apparatus of the
former church (today, reused as the Aula Magna) on the occasion
of the celebrations for the 50 years of the university’s history, has
started a program of initiatives aimed at enhancing the ancient
monastic plexus (g. 1). In particular, the program gave life to
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/W17, 2019
6th International Workshop LowCost 3D – Sensors, Algorithms, Applications, 2–3 December 2019, Strasbourg, France
This contribution has been peer-reviewed.
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93
the setting up of the chapel dedicated to San Nicola da Tolentino,
with the relocation of the works of art removed after its desecra-
tion in 1798.
The chapel originally housed, in addition to the altars no longer
existing, some canvases, including the altarpiece by Gian Giaco-
mo Barbelli (1653) but, mainly, a large statue of the saint robed
in a cloth dress. This study has therefore focused on the only
sculpture enduring in the chapel (a prized piece of art by Gio-
vanni Antonio Sanz da Bergamo), although today only the bust
remains. It consists of a carved and painted wooden head, with
large eyes in the coloured glass paste, resting on a papier-mâché
bust supported by a wooden pedestal. In 1798, the sculpture was
transferred to the church of Sant’Andrea to be forgotten in the ba-
sement after the construction of the new temple. Rediscovered in
2016, it was restored at the behest of the University of Bergamo
and is today displayed in the old church of Sant’Agostino (g. 2).
The chapel of San Nicola da Tolentino was the occasion to expe-
riment a methodological practice aimed at the realization of vir-
tual artefacts to be used within an open and publicly accessible
database. A rst step for the construction of a virtual museum
destined to collect the contents of a systematic and multidiscipli-
nary study - partly already underway - on the former convent, the
fulcrum of the city’s cultural identity.
The use of today’s reality capture technologies for the digital re-
construction of pieces of art, the creation of interactive teaching
models, computerized lms and animations, as well as the use
of AR (augmented reality) to recreate objects in every place, are
tools that can allow to reach an ever wider public (Cardaci et al,
2018).
3. METHODOLOGICAL PRACTICE
The survey of the sculpture was preceded by the careful plan-
ning of the acquisition phases, performed with the use of active
and passive sensors. The bust was digitized employing 3D laser
scanning instruments, to create an accurate reference model for
the comparison of various photogrammetric artefacts - obtained
through pictures made both with professional and amateur ca-
meras - so reconstructing multiple 3D image-based virtual pro-
totypes having dierent complexity and precision (Bolognesi et
al, 2015; Brilakis et al., 2011). The survey project made it possi-
ble to nd solutions to the problems linked to the ‘measurement
site’, not a geomatic laboratory but the redone chapel of the an-
cient church. It has intact bound 3D laser scanning acquisitions,
given the impossibility to remove or move the statue from its
support, and complicated the photogrammetric sockets for the
multiple light conditions.
The activities carried out directly inside the new Aula Magna,
in the times and conditions dictated by the room use, therefore,
required a series of particular measures to conclude the measure-
ments quickly so to avoid problems in the experimentation due to
unforeseen circumstances.
It was possible to perform the survey in just a few hours only
thanks to the preparation of a dense network of markers for
geo-referencing all the scans into a single reference system. It
was decided to compare the models based on common points
with known coordinates, without delegating the registration of
Figure 1. The former church of Sant’Agostino in Bergamo, today the Aula Magna of the University of Bergamo
Figure 2. The chapel dedicated of San Nicola da Tolentino
and the bust of the saint in the complex of Sant’Agostino
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/W17, 2019
6th International Workshop LowCost 3D – Sensors, Algorithms, Applications, 2–3 December 2019, Strasbourg, France
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94
the acquisitions to ICP algorithms for shape registration. A digital
print was made on a rigid support and, in the laboratory, the coor-
dinates of the references were determined by direct, angular and
for redundancy polar-distance readings, from a base of known
length; this allowed to determine the coordinates of the points
with millimetric accuracy.
A subsequent response during the execution of the acquisitions
allowed assessing the loss of accuracy due to the inevitable de-
formations of the rigid transport support, the variation of the
hygrometric conditions, the weight of the statue. They were,
however negligible and contained in the order of instrumental
precision.
The markers, dierent in shape and layout so that they could be
automatically recognized by the dierent software, have made up
the GCP (Ground Control Point) and the GCC (Ground Control
Constraint) of the system. In particular, the GPCs, four univer-
sal collimated manually markers, have allowed both the correct
georeferencing and the verication of the error; the GCCs have
instead been used as ‘constraints’ of reference for the models wi-
thin the various photogrammetric software (g. 3).
The acquisition phases took place by vertically positioning the
bust of San Nicola and moving around with the various instru-
ments, avoiding altering the lighting conditions on the statue, ca-
sting shadows, hitting the object and changing its position.
3.1 Laser scanning data processing
The survey began with the acquisition of the San Nicola da To-
lentino bust with a TLS phase dierence instrument. Although
less ecient and accurate than structured-light laser scanners
- more appropriate to the survey of sculptures - it nevertheless
provided a model of sucient quality for the experimentation.
Specically, sixteen scans were performed by a Faro© laser
scanner, positioned at a distance of a few meters from the object.
Scans were done radially (8 + 8 scans) at double altitude, to maxi-
mize the coverage of the interested surface. The resolution of the
instrument, set in a value ½ (half of the maximum precision), en-
sured an average distance between the points of less than 1 mm;
the ‘x-control’ value was set to have a strong noise reduction.
The point cloud registration was performed after recording the
individual scans operated by using the proprietary software. A
rst scans’ approach was performed through a pre-registration
based on the targets to which the cloud cleaning followed.
In particular, all the points extraneous to the bust and pedestal ge-
ometry (portions of walls, pavement, ceiling, etc.) were elimina-
ted; the overlapping of areas common to several scans employing
ICP algorithms was improved.
This gave a cloud of over 400,000 points, which was transfor-
med into a continuous mesh model by the subsequent processing
in WRAP. A qualitative evaluation showed a noticeable noise of
the dark parts of the papier-mâché bust, not present on the co-
loured wooden face; this suggested applying a dedicated noise
reduction lter for these parts only (g. 4).The mesh gotten was
then subjected to the elimination of the spikes and the closure of
the gaps.
3.2 The photogrammetric and videogrammetric acquisition
The bust of San Nicola da Tolentino was, therefore, the subject of
a photographic campaign carried out rst with a Canon EOS 5D
Mark II professional camera (with Canon 24 mm xed lens - f
1.4), then with a GoPro Hero 4 action camera and, nally, with
an Apple I-Phone 7. In all cases, pictures were made by moving
the instruments on an ideal sphere of constant radius and by di-
recting the optic towards the centre of the statue.
The rst photographic survey campaign, made with professional
instrumentation, followed a rigorous practice to obtain a pho-
togrammetric 3D model of high metric and chromatic quality
(Verhoeven, 2016; Torresani & Remondino, 2019).
Photos were preceded by the calculation of both the depth of eld
and the hyperlocal distance, the control of the background noise
and the compensation of the colour temperature of the ambient
light by colour checker (g. 5).
The shots were taken in the AP (Aperture Priority) mode, setting
a closed aperture and obtaining - depending on the amount of
light measured by the camera’s exposure meter - the shutter rele-
ase time. The starbuster eects are the result of light diraction.
Diraction is the slightest bending of light into your room throu-
gh a small opening, i.e. a small opening at a low focal length, it
looks around the edges of the blades and creates the ‘star’ look.
Therefore, particular care was required in the choice of the
diaphragm, set at f/16 (and no longer closed as f/22 and f/32) to
reduce the ‘star’ eect (Liu, 2015) but with a limitation of the
depth of eld that has, in part, conditioned the sockets.
A set of 5 images was acquired with dierent exposure for the
production of HDR images. The ability of High Dynamic Ran-
ge (HDR) to record the full range of lighting in a scene has led
Figure 3. The statue and the markers used to georeference the model
Figure 4. 3D model (laser scanner and mesh)
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/W17, 2019
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95
to increasing interest in its use for the digital photogrammetry
(Suma et al., 2016; Santosi et al., 2019). The current methods are
not always eective in reconstructing objects under bad lighting
conditions.
The acquisitions with action camera and smartphone have been
very fast and carried out in automatic mode (the only one fore-
seen for these devices). As already mentioned, even in this case
photos were taken ‘freehand’ by moving the instruments around
the statue. At the same time, video footage was also taken both
in ‘direct connection’ and with the use of a DJI Osmo Mobile
triaxial gimbal stabilizer to create a smoother movie without the
vibrations caused by the operator (g. 6).
Both cameras have been set to the maximum resolution possible
(width 1920 pixels - height 1080 pixels) and a recording speed
of 30 frames per second. All the precautions have been taken in
order to maintain a stable and constant grip, an optimal framing
and focus (both of the subject and of the GCPs) and to respect as
much as possible, both the acquisition paths (made in a circular
manner) at dierent heights and the duration of the shot, chosen
for each video of around 100 seconds.
3.3 The photogrammetric data processing
The image-based 3D reconstruction technique, born from the
combination of computer research in the eld of computer vision
and traditional photogrammetry, has allowed extracting metric
information from the photographic images automatically, i.e. wi-
thout the need for the operator to collimate the points (Guidi et
al, 2015). The automatic photogrammetry processing (simplied
term to indicate the process, sometimes improperly called photo-
modeling) takes place through four successive phases:
• Structure-from-motion (SfM) and Multiview Stereo Recon-
struction (MVS): the geometry of the camera poses is recon-
structed and a rst scatter cloud of points is processed;
• Dense Point Cloud: the images are processed once again
with the SfM and MVS algorithms indicated above conside-
ring the position of the photographic sockets, to build a dense
point cloud, bigger and more accurate than the scattered cloud;
• Mesh reconstruction: from the dense point cloud a continuo-
us surface composed of polygons is reconstructed;
• Texture Mapping: the meshes are coloured by projecting
the photographic images on the sides of the polygons meshes.
However, the reconstruction of 3D models was made after the
development of .raw images, both in LDR and in HDR.
The LDR images were obtained in Adobe Camera Raw using
a single frame, the one correctly exposed, adjusting the colour
temperature, the lights and the shadows, increasing the sharpness
and colour saturation. The HDR images were instead ensured by
processing the sets of 5 frames with HDR Software Photoma-
tix because able to process the 12-bit .raw les of the camera
without reducing them in extension and transform them into .tif
formats, dierently from Adobe Camera Raw capable of work
only with 8-bit .tif images (g 7).
The photos acquired with the action camera and the smartphone
did not need any development, because they were provided by
the devices only in a compressed .jpg format (with a reduction in
the number of d and a limited colour range).
The reconstruction of the photogrammetric models, with the
workow shown at the beginning, was performed with three dif-
ferent software - 3DFlow Zephyr, Agisoft Metashape and Pix4D
Mapper Pro - to test the characteristics of each product in the
dierent conditions.
Figure 6. Gimbal and low-cost instruments for video acquisition
Figure 7. HDR photogrammetry model (Canon EOS5 Mark II
with 24 mm / f 1.4 and processing with 3DFlow Zephyr)
Figure 5. The calculation of the depth of eld, the hyperfocal distance
and the ground sampling distance (GSD),
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96
In particular, the models have been obtained from:
• HDR images, in .tif format, acquired with Canon EOS 5
Mark II camera - Canon 24 mm / f 1.4;
• LDR images, in .jpg format, acquired with Canon EOS 5
Mark II - Canon 24 mm / f 1.4;
• images, .jpg format, acquired with GoPro Hero 4;
• images, .jpg format, acquired with Apple I-Phone 7.
3.4 The key-frame extraction and selection from videos
The opportunity to easily extract frames from a video is now sup-
ported by the majority of photogrammetry software. In most ca-
ses, however, the process is performed automatically through the
choose of the number of images to be extracted in the unit of time
(Alsadik et al, 2015, Xu et al., 2016). This prevents to eliminate
similar or poor quality images, which add nothing to the creation
of the 3D model.
One of the opportunities oered by one of the three tested
software (3DFlow Zephyr) is to do this in an ‘intelligent’ way;
the algorithm rst extracts all the frames, then deletes a part of
them according to ltering based on similarity.
The algorithm was found to be much more eective than tem-
poral sampling as it was able to eliminate many frames when
the camera was stopped or was moving very slowly, in smaller
numbers when it moved faster.
A series of tests carried out on various 40-50 second duration l-
ms (consisting of about 1000 frames) showed how the algorithm
works by setting the similarity parameter with a value between
30 and 40. Below the value 25, no ltering occurs while, for va-
lues above 50, it preserves less than 10% of the frames. Particular
attention was paid to the quality of the images acquired (g. 8).
lity analysis of pictures, between the HDR image and the frame
video, showed other dierences:
• the video autofocus function changed focus distance, some-
times on the object and sometimes on the background;
• the white background plan interfered the exposure meter,
creating continuous brightness changes.
The processing was carried out by extracting the individual fra-
mes and repeating the procedure described in the previous para-
graph. Videogrammetric acquisitions have allowed the creation
of multiple models, both as dense point clouds and as textured
meshes, referenced in a single system.
The creation of the photogrammetric models was carried out, as
for the photographic catches, repeating the procedure described
in the previous paragraph. In particular, the following has been
developed:
• set of images from videos, in .jpg format, acquired ‘in direct
connection’ with GoPro Hero 4 action camera;
• set of video images, in .jpg format, acquired with gimbal
stabilizer and GoPro Hero 4 action camera;
• set of images from video images, in .jpg format, acquired
‘live’ with smartphone Apple I-Phone 7;
• set of images from video images, in .jpg format, acquired
with gimbal stabilizer and smartphone Apple I-Phone 7.
3.5 Comparison of point clouds
The CloudCompare software performed an evaluation of the ac-
curacy of the photogrammetric and videogrammetric models. For
this purpose, a direct comparison was made between each mesh
model and the laser-scanning reference model (g.10).
The models were generated using three dierent SFM software
starting from a common dataset made of six image sets. In parti-
cular, it consisted of two groups of static photogrammetric tradi-
tional images in .tif 24 bit format (with HDR technique and nor-
mal exposure) as well as four sets of .jpg 8 bit frames extracted
from videos (acquired with an action-cam and a smartphone, in
each case with both freehand and gimbal stabilizer). Each model
was created respecting the typical SFM workow: the coordina-
tes of the reference points identied in the frames were assigned
and, after optimizing the parameters and the camera’s alignment,
the dense point cloud was produced and exported. This procedure
was carried out by each of the three photogrammetric software
(3DFlow Zephyr, Agisoft Metashape, Pix4D Mapper Pro) and
the point clouds created were exported in .ply format.
The extraction of the frames from video precedes the photogram-
metric workow, for this reason, a poor input can inuence align-
ment results badly. The selection the photos ensures that blurred
and redundant frames, having probably a few key points between
each other, are discarded.
The image quality evaluation inuences the quality of frames ex-
tract. The test carried out with action camera and smartphone vi-
deos (with and without gimbal stabilizer) gave the results shown
in the following picture (g. 9). The points in the graph represent
the image quality value. It appears that the smartphone stabilized
acquisition produced the best results.
The test conrmed that the action camera made lower quali-
ty data (high noise value) than the smartphone, also with the
electronic stabilizer. Video images were of poorer quality than
images acquired with a professional instrumentation, however,
sucient for low-cost photogrammetric processing. Visive qua-
Figure 8. The trend of the similarity parameter
Figure 9. Image quality extimation graph
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97
The wrapping process was carried out using 3D Sistems Geoma-
gic Wrap software in standard conditions (no noise lter) for each
of the 18 models created, as well as for the laser-scanning one,
to avoid possible ltering and closing operations holes that SFM
software could have applied to point clouds. Each mesh was
exported in .ply format and was compared with the laser-scan-
ning reference model to assess their quality and highlight the
qualitative and quantitative trend of geometric dierences.
The maps created using the CloudCompare software show the
substantial dierences of the models, both when the acquisition
technique changes and when the software used to create them
varies (g. 12-13). In particular, we observed the remarkable va-
riability of the number of reconstructed points.
The comparison of histograms indicates averagely reliable resul-
ts in models with statically acquired images. The HDR technique
provided a fairly benet in terms of the number of points created
in processing with 3DFlow Zephyr, while it was quite irrelevant
in other cases. However, it was always favourable from the quali-
tative point of view of the texture, highlighting the details within
a wider chromatic range, globally supporting its comprehension.
The goodness of the videogrammetric results is much lower. In
particular, all the dierent techniques showed remarkable die-
rences that frequently exceeded 10 mm compared to the referen-
ce model, a considerable value in the eld of cultural heritage
valorisation.
From the tests carried out, it was possible to deduce that optical
stabilization using a low-cost triaxial gimbal in certain cases can
oer considerable advantages as it reduces the micro-moved ef-
fect of the frames, while it may be irrelevant or negative in other
cases, for example in the case of acquisition made with action-
cam. The Pix4D Mapper Pro software was not able to create the
dense point cloud of the three videogrammetric models with the
Figure 10. 3D laser scanning and photogrammetric model data
Figure 11. Comparison of the accuracy of
3D laser scanning data and photogrammetric models
Figure 12. Point cloud comparison between
photogrammetric model and 3D laser scanning reference
(processed by Agisoft Metashape, 3DFlow Zephyr, Pix4D Mapper Pro)
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98
lowest frame quality, while it proved to be valid in the case of
high-quality images.
An additional comparative test between the results of a complete
modelling with the examined software (from SFM to texturized
mesh) has nally shown that, although the creation of the point
cloud with Agisoft Metashape is generally very reliable and den-
se, the algorithm for creating the 3DFlow Zephyr mesh oers the
most reliable result (g. 14-15).
4. CONCLUSIONS
The quality of video captures, while providing a lower resolution,
guarantees a more uid overlap of frames and a quick acquisition
process, so making some data sets much easier to obtain. Howe-
ver, the qualitative level of the model based on the traditional
photogrammetric technique conducted in a rigorous way is not at
present obtainable. It was, thus, possible to deduce that the HDR
technique, if correctly applied, can oer signicant advantages in
the creation of 3D models.
The grade of accuracy clearly lower than in photogrammetric ca-
ses is surely inuenced by the particular low-cost characteristic
of the instrumentation used. The quality of the video frames is
not comparable to SLR images due to the quality of the equip-
ment but also to certain physical limits, for example, the sensor
size, the movement, the video noise produced by small sensors.
However, the video acquisition phase took few minutes, compa-
red to much hours of the SLR acquisition.
This aspect oers food for thought and opens up new possibili-
ties in a time to come in which technological development will
likely extend the market increasingly more ecient and compact
sensors at a lower cost, besides producing the possibility of being
able to detect assets so far found with less advanced techniques.
ACKNOWLEDGEMENTS
This work is part of a research promoted by the University of
Bergamo giving rise to a specic data sharing platform. The au-
thors are thankful to Don Giovanni Gusmini, rector of the Chur-
ch of Sant’Andrea Apostolo in via Porta Dipinta, expert in art
history and ‘discoverer’ of the statue of San Nicola da Tolentino.
REFERENCES
Alsadik, B., Gerke, M., & Vosselman, G. 2015. Ecient use
of video for 3D modelling of cultural heritage objects. ISPRS
- Annals of the Photogrammetry, Remote Sensing and Spatial
Information Sciences, II-3/W4, 1-8. doi.org/10.5194/isprsan-
nals-II-3-W4-1-2015.
Brilakis, I., Fathi, H., Rashidi, A. 2011. Progressive 3D recon-
struction of infrastructure with videogrammetry. Automation in
Construction, 20(7), 884-895.
Bolognesi, M., Furini, A., Russo, V., Pellegrinelli, A., & Russo,
P. 2015. Testing the low-cost potential in 3D Cultural Ceritage
Figure 13. Mesh comparison between photogrammetric model and
3D laser scanning reference (processed by Agisoft Metashape,
3DFlow Zephyr and Pix4D Mapper Pro)
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6th International Workshop LowCost 3D – Sensors, Algorithms, Applications, 2–3 December 2019, Strasbourg, France
This contribution has been peer-reviewed.
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99
reconstruction. ISPRS - International Archives of the Photogram-
metry, Remote Sensing & Spatial Information Sciences, XL-5/W4,
229-235. doi.org/10.5194/isprsarchives-XL-5-W4-229-2015.
Cardaci, A., Mirabella Roberti, G., Versaci, A. 2019. The Integra-
ted 3d Survey for Planned Conservation: the Former Church and
Convent of Sant’Agostino in Bergamo. ISPRS - International
Archives of the Photogrammetry, Remote Sensing and Spatial In-
formation Sciences, XLII-2/W9, 235-242. doi.org/10.5194/isprs-
archives-XLII-2-W9-235-2019.
Cardaci, A., Versaci, A. 2016. New technologies and methodo-
logies for the planned conservation of cultural heritage: a case
study applied to Venetian Walls and the former Convent of
Sant’Agostino in Bergamo. In Le Vie dei Mercanti: XIV Forum
Internazionale di Studi, 61, 1183-1192. La scuola di Pitagora edi-
trice, Napoli.
Cardaci, A., Versaci, A., Azzola, P. 2018. The Digital Platform
of the Gabinetto di Fisica of the Gymnasium School Paolo Sarpi
in Bergamo: A Case Study Between Research and Didactic. In
International and Interdisciplinary Conference on Digital Envi-
ronments for Education, Arts and Heritage, 202-211. Springer,
Cham.
Damiani, S., Lo Monaco, F., Maei, S. 2015. La cultura delle im-
magini: la chiesa di Sant’Agostino a Bergamo tra l’iconograa
sacra e la città. Aracne, Roma.
Guidi, G., Micoli, L. L., Gonizzi, S., Brennan, M., & Frischer,
B. 2015. Image-based 3D capture of cultural heritage artefacts
an experimental study about 3D data quality. In Digital Heritage
2, 321-324. IEEE.
Figure 14. Comparison of the point clouds obtained by two most
favourable survey technics (SLR HDR and stabilized smartphone)
Liu, D., Geng, H., & Klette, R. 2015. Star-Eect Simulation for
Photography Using Self-calibrated Stereo Vision. In Image and
Video Technology, 228-240. Springer, Cham.
Santosi, Z., Budak, I., Sokac, M., Hadzistevic, M., & Vukelic, D.
2019. Inuence of high dynamic range images on the accuracy
of the photogrammetric 3D digitization: A case study. Advances
in Production Engineering & Management, 14(3), 391-399. doi.
org/10.14743/apem2019.3.336.
Suma, R., Stavropoulou, G., Stathopoulou, E., van Gool, L., Ge-
orgopoulos, A., & Chalmers, A. 2016. Preliminary evaluation of
HDR tone mapping operators for cultural heritage. In 8th Interna-
tional congress on archaeology, computer graphics, cultural he-
ritage and innovation, 343-347. Editorial Universitat Politècnica
de València.
Torresani, A., Remondino, F. 2019, Videogrammetry VS Photo-
grammetry for Heritage 3d Reconstruction. ISPRS - Internatio-
nal Archives of the Photogrammetry, Remote Sensing and Spatial
Information Sciences, XLII-2/W15 1157-1162. doi.org/10.5194/
isprs-archives-XLII-2-W15-1157-2019.
Verhoeven, G. 2016. Basics of photography for cultural heritage
imaging. In 3D recording, documentation and management of
cultural heritage, 127-251. Whittles Publishing, Caithness.
Xu, Z., Wu, T. H., Shen, Y., & Wu, L. 2016. Three dimensional
reconstruction of large cultural heritage objects based on UAV
video and TLS data. ISPRS - The International Archives of Pho-
togrammetry, Remote Sensing and Spatial Information Sciences,
XLI-B5, 985-988. doi:10.5194/isprsarchives-XLI-B5-985-2016.
Figure 15. Comparison of the meshes obtained by two most
favourable survey technics (SLR HDR and stabilized smartphone)
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/W17, 2019
6th International Workshop LowCost 3D – Sensors, Algorithms, Applications, 2–3 December 2019, Strasbourg, France
This contribution has been peer-reviewed.
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