3 D A C Q U I S I T I O N A N D M O D E L I N G I N C U LT U R A L H E R I TA G E : E V O L U T I O N A N D P E R S P E C T I V E S

G A B R I E L E G U I D I , P H D D E P T. O F M E C H A N I C A L E N G I N E E R I N G P O L I T E C N I C O D I M I L A N O , I TA LY

Indiana University, Bloomington (IN) USA - Nov. 21, 2014

3 D F O R C U LT U R A L H E R I TA G E R E S E A R C H G R O U P

Gabriele Guidi

CoordinatorElectronic Engineer

Michele RussoTemporary Researcher

Architect

Laura Micoli Post Doc Architect

Davide Angheleddu

Phd Student Architect

Sara Gonizzi Phd Student Archaeologist

+ 1 to 3 intern students and 1 to 3 thesis students depending on the period

R E S E A R C H A C T I V I T I E S

• Integration of Passive/Active technologies

• Characterization of 3D acquisition technologies

• 3D post processing

• Applications of 3D acquisition and modeling to:

• Cultural Heritage (reality based & reconstruction)

• Industrial applications

A B I T O F M Y / O U R S T O R Y

1988!•!GG: Master degree in Electronic Engineering, Univ. Florence!•!Thesis on real-time signal processing of Doppler signals!

1992!•!GG: PhD in Bioengineering, Univ. Bologna!•!Thesis on measurement of blood speed in 3D!

1998!•!Marc Levoy scans the David by Michelangelo!

1999!•!Parnaso project!•!First experiments with 3D scanning of CH at Univ. Florence!

2000!•!First large 3D scanning project at the Univ. of Florence!•!Maddalena by Donatello!

• Sculpted in 1455 approx.

• Height 180 cm

• Width 40 cm

• Complex shape involving shades and fragmented range maps

• Wooden statue originally gold coated: currently dark with reflective spots (optically non cooperative)

M A D D A L E N A B Y D O N AT E L L O

Golden decorations (high reflectance)

Areas with no decoration (high absorption)

E Q U I P M E N T U S E D

• Generates 3D images (range maps) • Working principle: triangulation • Pattern projection of vertical strips

M E A S U R I N G R A N G E 0 . 5 - 1 . 2 M

M E A S U R E M E N T U N C E R T A I N T Y 0 . 0 5 - 0 . 2 M M

S E N S O R S I Z E ( P I X E L ) 7 6 8 X 5 7 6

M E A S U R E M E N T R E S O L U T I O N 0 . 5 - 0 . 1 M M

P R O J E C T P L A N N I N G

•! First stage: model skeleton!–! Required resolution: 0.4 mm!–! Framed field (focal plane): 30x23 cm!–! Uncertainty along z: 0.125 mm!–! Volume divided in 11 stripes 23 cm tall,

vertically overlapped (29%)!–! Each stripe divided in 8-10 images (range

maps) horizontally overlapped (~30%)!–! Supplemental images for hands, legs and

arms!

•! Second stage: Hi-res model!–! Final required resolution: 0.25 mm!–! Framed area: 19x14 cm!–! Uncertainty along z : 0.070 mm!

E X P E R I M E N TA L S E T- U P

Range device

Range device control unit

Pre-alignment work-station

S TA N D A R D P O S T- P R O C E S S I N G

Alignment of the acquired range maps!

Merge in a single mesh! Editing!

Head !Resolution: 250 µm!!z: 70 µm!

Face detail !Resolution: 100 µm!!z: 21 µm!

Hands !Resolution: 250 µm!!z: 70 µm!

Right foot !Resolution: 100 µm!!z: 21 µm!

A D D I T I O N A L S U B - M O D E L S

HandsResolution: 250 Resolution: 250 !z: 70 µµ

S U M M A R Y

2.64!Total data

(Gbyte) !

19.65!30.89!115.3!Size (Mbyte) !

724 k!1.2M!4.6 M!Triangles!

23!13!374!Number of range maps !

21 "m!21 "m!70-125 "m!Uncertainty !

Foot !Face !Full model !

Phase 1!!200 range maps, 170 used!!155 work hours!

Phase 2 !205 additional range maps!160 man-hours!

Q U A L I T Y C H E C K

• At this stage an acquisition work was usually considered completed

• In our project a quality control was arranged in order to check the metric reliability of the whole model

• A complementary method was used in order to achieve such purpose: photogrammetry

Negative deviations worst case : -4.2 mm (1.66 %) !

d9 – d11 !

Positive deviations worst case: 4.3 mm (0.25 %)!

d6 – d8 !

Agreement between 3D and photogrammetry!

d1 – d5 !d2 !d1 !

d3 !

d4 ! d5 !

d9 !

d11 !d10 !

d7 !d6 !

d8 !

2001!•!Visiting Researcher at NRC Canada with Angelo J. Beraldin!•! Integration of photogrammetry and 3D scanning!

TA R G E T E X T R A C T I O N M I X I N G 2 D A N D 3 D I N F O R M AT I O N

Geometry!Texture!

xt, yt!3D

plane!

Geometry

Projection! x,y,z!

3D model !

Alignment and merging !

A!

B ! C!

D!

Photogrammetric X Y Z coordinates !

A!

B !

C!

D !

Roto-translation matrices !

3D images in the photogrammetric coordinate system !

Quaternion !

A!

B! C!

D !

F I N A L C H E C K

• Mesurements on the new model were coherent with photogrammetry: the new model grown in height of few millimeters

• By comparing the two models other lateral unexpected distortions became evident

L E S S O N L E A R N E D

• the usual approach for creating 3D models from small range images may involve a loss of metric accuracy even when the single images are highly accurate

• A sensor fusion between the two methods allowed to overcome the alignment problems

• As a general criteria 3D scanning should always be coupled to a complementary measurement method at least for checking global accuracy

Grey coded pattern projection

range camera!

“ A D O R A Z I O N E D E I M A G I ” B Y L E O N A R D O D A V I N C I“ A D O R A Z I O N E D E I M A G I ” B Y L E O N A R D O D A V I N C I

2002!•!First 3D acquisition and modeling of a wooden painting!

3 D M O D E L O F T H E PA I N T I N G

393 range maps, H&V res= 0.3 mm! 222 range maps, H&V res=0.4!

D E V I AT I O N F R O M P L A N A R I T Y

Front side Rear side

L E S S O N L E A R N E D

• High resolution dimensional monitoring appears to be extremely useful for applications in wood restoration, specially when it is the support of a delicate painting

• However, due to the natural deformations of wood, the possibility of repeating the same monitoring in different times seems a key feature for gaining the information needed by restorators

2003!•!First 3D scan with a Laser Radar in the CH field!

Pietà (Michelangelo) 1997, IBM

Pattern projection (triangulation)

Madonna col Bambino (G. Pisano) 1997, Univ. Padova / NRC Canada

Laser scanning (triangulation)

David (Michelangelo) 1999, Stanford University

Laser scanning (triangulation)

Maddalena (Donatello) 2001, Univ. Firenze, NRC Canada, Optonet Srl

Pattern projection (triangulation)

T O F V S . T R I A N G U L AT I O N ( M E T R O L O G Y )

Measurement uncertainty

Triangulation range device

0.1 mm

Time-of-flight range device

4-8 mm

L A S E R R A D A R W O R K I N G P R I N C I P L E

M E T R O L O G Y I M P R O V E M E N T

Measurement uncertainty

Triangulation range device

0.1 mm

Time-of-flight range device

4-8 mm

Frequency modulated Laser Radar 0.1 mm

3 D D ATA A L I G N M E N T

Triangulation based camera

• Mostly local to the camera

• Range maps have to be aligned by means of semi-automatic procedures (ICP)

• Range maps have to be redundant in order to make ICP work

FM laser radar

• All 3D data are directly re-oriented in a global reference system thanks to special targets over the scene (metallic spheres)

M O D E L G E N E R AT I O N P I P E L I N E

Triangulation sensor !

3D scanning !

ICP!method!

Camera referenced !Range maps !

Aligned range maps (referenced to a single

coordinate system) !Merge! Polygonal

model !

FM Laser Radar !3D scanning!

Range maps !Referenced to a !

single coordinate system !Merge! Polygonal

model !

D AV I D B Y D O N AT E L L O

• Height 160 cm

• Located over a 1m basement

Critical points

• Non cooperative material

• Hidden surfaces

Lateral resolution needed

• 1mm on low curvature surfaces

• 0.5mm on compex surfaces

• System capable to work through a Front Surface Mirror (FSM)

• From the same point of view front and rear points can be captured

• 80 hours for acquisition

• 20 hours for merge & preliminary editing (much less than in previous project!)

6 M P O LY G O N S F I N A L M O D E L

L E S S O N L E A R N E D

• Acquisitions from a single point of view dramatically enhance the amount of surface captured in a single acquisition

• The possibility to use mirrors further increases this feature, solving also problems of data alignment in objects with small thickness

• Metallic rectified sphere added on the scene allow automatic 3D data orientation

2003-6!•! 3D acquisition of a large and detailed object:“Plastico di Roma Antica”!•!CAD remodeling on the scanned data: “Rome Reborn”!

M O T I VAT I O N S

• Digital Roman Forum project (Frischer et al. 1999-2003)

• Rome Reborn project (Frischer et al. 2004-2008): extend this virtual model of ancient Rome up to the exterior walls

• Idea: reverse engineering Gismondi’s “plastico” for creating a good starting point

• Updated with the most recent archaeological discoveries

3 D D I G I T I Z AT I O N C O N S T R A I N T S

17.4 m

16.0 m

• No measurement machinery flying over the “plastico”

• Long range (7-24 m)

• Wide area (about 200 sq. m)

• Small buildings (2-20 cm) Low uncertainty (<0.5 mm)

• Balcony pavement at 2.7 meters respect to the model

• Balustrade 1.2m high

20 cm

5 cm! 3mm

Plaster plane

Balcony plane

Plaster plane

Balcony Balcony plane

2.7 m

1.2 m

24 7

Observation point

Plaster plane

Balcony plane

M E T R I S L A S E R R A D A R

• Known: same equipment used for the David’s work

• Range = up to 24 m

• Uncertainty (1σ): 300 µm (metrology mode)

• Framed area: 360° H x 90° V (from -45° to +45°)

• Beam spot size = 400 µm with automatic refocusing (metrology mode)

• Stacking mode: reduce uncertainty averaging repeated measures (metrology mode)

➜ Metrologically Ok

… B U T, W H AT A B O U T S P E E D ?

• Triangulation range device: >150 000 points/s

• TOF range device: > 20 000 points/s

• Laser radar in metrology mode: 1 point/s (!)

➜ time for one complete scan: 40 days (nights included). Not feasible!!

S Y S T E M C U S T O M I Z AT I O N

The most time consuming activity in metrology mode is refocusing ☟

• Scanning on circular scanlines

• Focusing only once (at the beginning of each scan line)

• Stacking level optimized for the best tradeoff

F E AT U R E S O P T I M I Z AT I O N

(mm)

No averaging

Average on 2

Average on 5

Average on 10

• Several averaging test were made using planar targets

• Best tradeoff: average on 4 values

• !=0.3 mm

• Speed: 170 points/s

S Y S T E M S E T T I N G S

• 2 mm resolution

• 0.3 mm uncertainty

• 200 m2 per scan

• 50 millions of points per scan

• Registration with external targets, no need for redundancy

➜ Time for a complete scan of the “plastico”: 4 days (nights included). Not fast but feasible

T Y P I C A L S C A N N I N G S E S S I O N

1. Locate the scanner in place

2. Measure targets for determining scanner position

3. Measure the plaster perimeter from that particular location

4. Off-line calculation intersections between circular scan-lines and the perimeter ➭ pass them as input of the custom control software ➭ start scanning

T Y P I C A L S C A N N I N G S E S S I O N

1. Locate the scanner in place

2. Measure targets for determining scanner position

3. Measure the plaster perimeter from that particular location

4. Off-line calculation intersections between circular scan-lines and the perimeter ➭ pass them as input of the custom control software ➭ start scanning

T Y P I C A L S C A N N I N G S E S S I O N

1. Locate the scanner in place

2. Measure targets for determining scanner position

3. Measure the plaster perimeter from that particular location

4. Off-line calculation intersections between circular scan-lines and the perimeter ➭ pass them as input of the custom control software ➭ start scanning

T Y P I C A L S C A N N I N G S E S S I O N

1. Locate the scanner in place

2. Measure targets for determining scanner position

3. Measure the plaster perimeter from that particular location

4. Off-line calculation intersections between circular scan-lines and the perimeter ➭ pass them as input of the custom control software ➭ start scanning

P L A N N I N G

First stage

• Acquisition from 3 locations on the balcony for a first massive data capture

Second stage

• Searching several optimal locations for small data integrations

• Actual acquisition

• Data merge

• Editing

F I R S T S TA G E

• Laser radar only

• 3 locations on the balcony

• Blind areas below 45° (to be integrated)

• 12 days total scanning time

Blind areas

D ATA S U B D I V I S I O N A N D M E S H I N G

• Each scan 50 MPoints

• huge data set, not manageable at that time (2004-5)

• sets 2m x 2m blocks generated with a 3D grid

• aligment made globally, integration and meshing singularly on each block

S E C O N D S TA G E ( 1 )

• Laser radar for integrations of the central area

• 1 more locations from the balcony (4)

• 6 locations at ground level (5-10)

S E C O N D S TA G E ( 2 )

• Minolta Vivid 900 sensor

• Range maps all around the Aurelian Walls

• Integrated with LR data through ICP alignment

A T T H E E N D O F S U C H P R O C E S S T H E W H O L E M E S H W A S C O M P L E T E D

R E A L V S . D I G I T I Z E D

• resolution and uncertainty chosen resulted sufficient to detect all the details

• the result was significant considering the technical and logistic difficulties

• however…

D R A W B A C K S

• a lot of occlusions " these nice meshes required a considerable amount of editing work

• a mesh is still a mesh (e.g. e static representation of a 3D geometry)

• LOD might be implemented up to acquisition resolution, while in a VR application closeups might be needed

! remodeling over the mesh

Edited mesh

Simplified unedited mesh

R E M O D E L I N G T H E M E S H

• different approaches are possible

• very different in terms of time-consumption and visual result

• the squared area has been processed differently in the next slides

J U S T T H E E D I T E D M E S H

T H E D E TA I L E D R E M O D E L I N G O F T H E B U I L D I N G ( S E V E R A L D A Y S )

A S I M P L I F I E D R E M O D E L I N G O F T H E B U I L D I N G ( F E W H O U R S )

J U S T T H E E D I T E D M E S H

T H E D E TA I L E D R E M O D E L I N G O F T H E B U I L D I N G ( S E V E R A L D A Y S )

T H E D E TA I L E D R E M O D E L I N G O F T H E B U I L D I N G ( S E V E R A L D A Y S )

A S I M P L I F I E D R E M O D E L I N G O F T H E B U I L D I N G ( F E W H O U R S )

R E M O D E L I N G C H O I C E S

• remodeling all at the maximum level of details would have required 1 week x about 7000 buildings: not feasible

• a simplified approach could have been acceptable for the simpler structures, not for the monumental buildings, hoverer still time-consuming!

T W O C A T E G O R I E S O F B U I L D I N G S W E R E I D E N T I F I E D

Urban fabric

Monumental buildings

U R B A N FA B R I C H A S T O B E M O D U L A R …

• The extension of the model and the relatively short time needed for sure an optimized assembly line

• Monumental buildings developed singularly

• Urban fabric developed with archetypes

O T H E R C L U E S

• Gismondi left few documents

• however some preparatory drawings have been found

• they shows domus types studies

– J A N E Z D O N N O , M A S T E R T H E S I S ( 2 0 0 6 )

Approach #1: search of recurring elements and Maya modelling of a limited set of modules

(library)

R E C U R R I N G E L E M E N T S I N R O O F S

A B A C U S O F R O O F S

• Pattern analysis on horizontal and vertical sections of the mesh

• Classification of similarities

R E C U R R I N G E L E M E N T S I N B U I L D I N G S

R E S U LT S

• About 20 types of elementary building archetypes employed for 90% of the physical model

• Used in the “Plastico” with variation of scale and in different combination hiding geometric repetitions

P R E L I M I N A R Y E X P E R I M E N T W I T H M O D U L A R I Z E D G E O M E T R I E S

– I G N A Z I O L U C E N T I , M A S T E R T H E S I S ( 2 0 0 7 )

Approach #2: search of recurring elements and procedural modeling of a class of buildings

(object oriented)

P R O C E D U R A L M O D E L I N G

• Sofware used: Side Effects Houdini

• General purpose procedural modeling package

• Every item is considered as a flow of data and can be manipulated through a network of operators

• Users can make their own custom operators and custom “prototypes” (called digital assets)

H O U D I N I S C R E E N S H O T

B E N E F I T S O F T H I S A P P R O A C H

• Models are made up of reusable parametric modules (e.g. a column asset can be used in every object that contains a column)

• Updating the model became very easy because only the asset needs to be modified and all the instances are updated accordingly

• For example, to update the temple models, add a texture or a new parameter, user needs to modify the prototype only and the changes will be reflected in every existing temple

• It is possible to have different versions of the model, switching them automatically (e.g. different levels of detail based on camera distance)

• Object parameters can be controlled manually, by algorithms, by data sources (database) or even by image maps

W O R K F L O W

• Definition of the object parameters (analysis)

• Making a parametric model of the object

• Turning it into a Digital Asset (prototype) with its own custom interface

• Placing instances of the prototype on the 3D model of the “plastico” (manually or driven by a rule)

T E M P L E S C L A S S I F I C AT I O N

Tholos Prostyle Peristyle

Pseudo Pseudo sine postico Sine Postico

PA R A M E R I C E L E M E N T S

Column • Diameter • Height • Base height

Roof • Entablature height • Roof slope • Frame taper

Podium • Typology • Size (x,y,z) • Steps width • Step height

P R O C E D U R A L M O D E L O F T H E T E M P L E S

B U I L D I N G M O D E L E D P R O C E D U R A L LY

• Temples

• Bridges

• Exterior city walls

D T M F R O M T H E P L A S T I C O M E S H

• All the buildings in the 3D scan have been deleted

• All the consequent holes filled

• The resulting mesh have been sliced in order to separate river, land, and paved roads (for assigning them different shaders)

M E R G E I N S I N G L E D I G I TA L M O D E LM E R G E I N S I N G L E D I G I TA L M O D E LM E R G E I N S I N G L E D I G I TA L M O D E L

Included: • DTM (original mesh) • vernacular buildings (library) • Temples (procedural) • Bridges (procedural) • Walls (procedural)

Such 3D model, once integrated by Bernard Frischer’s group with the various high-detail models of monumental

buildings (Forum, Coliseum, Circus Maximum, etc.), became the model known as Rome Reborn 1.0

It was also the starting point of the following fully procedural versions of RR, based on CityEngine:

http://romereborn.frischerconsulting.com

L E S S O N L E A R N E D

• Laser Radar technology can solve the difficult task of acquiring large artifacts with small details

• The acquired data is always valuable but sometimes it is visually not sufficient for virtual reality

• In that case the right post-processing approach may change dramatically the time needed for completing the model

Large area:

• 150 m maximum length

• 80 m maximum width

• 8 large structures included

• 377 small finds spread all over the area

2007-8!

•! 3D survey of the Pompeii Forum (Scuola Normale di Pisa)!•! POLIMI coordination, 3D scanning and modeling, integration, rendering!•! FBK Trento contributing with photogrammetry!

N

150 m

80 m

• Level of detail ranging from the geographical scale to the object scale • For each scale the more suitable survey technology was adopted • The consequent resolution varied from 25 cm to 0.2 mm

L O W - R E S O L U T I O N ( G E O G R A P H I C A L A R E A F R A M I N G )

Digital surface model (DSM) of about 1 square km around the forum: • existing aerial Images for geometry

capture • 1:3500 photogram scale • geometric resolution: 25 cm

Acquisition of single points for image registration • GPS • Standard topographic approach

Texture mapping from above • Pictometry images • 15 cm texture resolution

M E D I U M - R E S O L U T I O N ( L A R G E S T R U C T U R E S )

Leica HDS 3000 laser scanner for long-range acquisitions (3D framing of the forum) Resolution 5-20 mm

Leica HDS 6000 for fast and massive acquisitions (3D acquisition of areas with many occlusions) Resolution 5-10 mm

Close range photogrammetry digital reflex cameras with manual processing Resolution: dynamically changing

H I G H - R E S O L U T I O N ( D E TA I L S )

Close range photogrammetry with digital reflex cameras and automatic matching (ETH multi-photo matcher) Resolution: up to 0.5 mm

C ATA L O G U I N G T H E R U I N S

• Each geometrical entity was identified, catalogued, photographed and coded

• All the following work has been referred to such IDs for image storing and models management

L A S E R S C A N N I N G• 10 days of scanning in two stages • 1.2 G points acquired • 100 M points used for modeling (1:10 ratio) • Heavy hand cleaning for deleting artifacts (visitors, spurious data) • ICP alignment • Sorting and subdivision with two outputs:

• General reference for the whole model • Single sets of data for each structure

D I G I TA L P H O T O G R A M E T R Y

• 3200 images acquired with precalibrated cameras • Photogrammetric models metrically generated in their own reference • Aligned with the 3D scanned reference in the final integration stage

F I N A L I N T E G R AT I O N

I N T E G R AT I O N P R O C E S S

2011!

•!3D survey and modeling of Temples in My Son (Vietnam)!•!Virtual reconstruction with strong integration between actual

3D data and other sources!

3D scanning with Faro Focus 3D

Image based 3D and textures

F LY I N G O V E R T H E S I T E

S C I E N T I F I C R E C O N S T R U C T I O N

3 D R E C O N S T R U C T I O N P I P E L I N E

3 D R E C O N S T R U C T I O N

2012!

•! 3D survey and modeling of Certosa di Pavia (Italy)!•! Virtual reconstruction of several historical phases based on integration

between real 3D and historical sources!

2012-15!

•!EU project 3D-ICONS: 3000+ models for EUROPEANA!•!POLIMI: massive digitization of 527 items!•!Wide use of automatic photogrammetry based on SFM!

5 3 1 M O D E L S C O M P L E T E D

2007-!•!Metrologic analysis of 3D devices and methods!

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• In “modern” metrology uncertainty incorporates both concepts

• Useful in standards for acceptance tests

• Not for separately analyzing systematic and random error components

T E S T O B J E C T S F O R 3 D

NRC, Canada

NPL, UK

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POLIMI, small volumes

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M E T R O L O G Y F O R C H M O D E L I N G

Laser scanned reference Ref. vs. Photogrammetric model - Agisoft Photoscan SW - Nikon D90 - Mean error = 1.18 mm - Std. dev. = 3.38 mm

Ref. vs. Photogrammetric model - Autodesk Recap Web service - Nikon D600 - Mean error = 0.34 mm - Std. dev. = 1.80 mm

Gabriele GUIDI, Bernard FRISCHER, Photomodeling vs. traditional 3D data capture of cultural heritage artifacts, Conference on Cultural Heritage and New Technologies, November 3-5 2014, Vienna, Austria

C O N C L U D I N G R E M A R K S

• In order to solve complex problems you have to go deeply into them. Many of the CH models shown could not be feasible if electronic engineering, informatics, archaeology, statistics, architecture, geomatics, computer graphics and metrology would not have interacted positively. The keyword is interdisciplinarity intended as action giving a result larger than the sum of the single disciplinar contributions

• The 3D model is important but often it is not enough. In many case it is just a (fundamental) starting point for a documentation activity that necessarily involves an enrichment of such models, both geometric (3D semantics), visual (computer graphics) and informative (metadata & ontologies)

• Similarly the 3D model can be used for communication purposes where the main issues are related with both local and remote 3D visualization (including virtual reality and augmented reality)

C O N C L U D I N G R E M A R K S ( 2 )

• The technologies seen show that many of those models required months to be created. Although any experimentation is important it is clear that the future of 3D documentation can’t be that. It has to be quick! Only in this way it will be possible to handle problems of massive 3D digitization. Image based modeling integrated with laser scanning and smart 3D post processing techniques seems nowadays the most promising way

• The quality of what your 3D data indicates what you can do with them. The traceability of the whole 3D acquisition pipeline (sensor, process, 3D model) is fundamental for a scientific use of 3D

• The same concept can be extended to any 3D modeling activity in CH, including reconstructive modeling of something not anymore existing (philological traceability), obtained through a wise use of metadata documenting the process and the sources for generating the 3D model

C R E D I T S

• Carlo Atzeni (Emeritus, retired from University of Florence, Italy)

• Jean-Angelo Beraldin (National Research Council, Ottawa, Canada)

• Bernard Frischer (University of Indiana, Bloomington, USA)

• Fabio Remondino (FBK, Trento, Italy)

• Alessandro Spinetti (Florence Engineering, Florence, Italy)

• Tommaso Grasso (3dHPM, Rome, Italy)

• Sara Lazzari (formerly Optonet, Brescia, Italy)

• Grazia Tucci (University of Florence, Italy)

• Monica De Simone (Director of Museo Archeologico di Rieti, Italy)

• Claudia Angelelli (Università degli Studi di Padova,Italy)

• Salvatore Barba (University of Salerno, Italy)

• Carlo Bianchini (University of Rome “La Sapienza”, Italy)

• Maurizio Seracini (UC, San Diego, USA)

• Federico Uccelli (Leica Geosystems, Lodi, Italy)

• Achim Lupus (Leica GEOSYSTEMS AG, Switzerland)

• Patrizia Zolese (Fondazione Lerici, Rome, Italy)

• Mara Landoni (Politecnico di Milano, Italy)

• Sebastiano Ercoli (Politecnico di Milano, Italy)

thanks for your attention gabriele.guidi@polimi.it