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1
Introduction to 3D
digitization
technologies
Roberto Scopigno
Visual Computing Lab.
CNR-ISTI
Pisa, Italy
R. Scopigno, 3D Digitization - HW 1
Overview
o  Digitization for visual presentation: 3D
vs. enhanced 2D media
o  3D digitization technologies
2
2
Acquiring Visually Rich 3D Models
Goal:
Build accurate digital models to
clone the reality (shape +
surface reflection properties)
Acquisition methodologies:
n  Image-based Rendering
o  Panoramic images (2D)
o  RTI images (2D)
n  Standard CAD modeling
(manual process)
n  Approaches based on
Sampling
o  3D scanning (active)
o  3D from images (passive)
3
Modelling vs. Sampling
o  Modelling
n  Manual process
[“redraw”]
n  Accuracy is unknown
n  3D model is usually
complete
o  Sampling/scanning
n  Semi-automatic process
[“photography”]
n  Accuracy is known
n  3D model is usually
uncomplete (many
unsampled regions)
R. Scopigno, 3D Digitization - HW
3
R. Scopigno, 3D Digitization - HW 4
3D scanning devices
Many different technologies, just two
examples:
o  Laser or structured light,
Triangulation
n  Small/medium scale artifacts (statues)
n  Small/medium workspace 20x20 ->
100x100 cm, distance from artifact ~1 m
n  High accuracy (>0.05 mm)
n  High sampling density (0.2 mm)
n  Fast (1 shot in ~1-2 sec)
o  Laser, Time of flight
n  Large scale (architectures)
n  Wide workspace (many meters)
n  Medium accuracy (~4-10 mm)
n  Medium sampling density (10 mm)
n  Slow (1 shot in ~20 min)
R. Scopigno, 3D Digitization - HW 5
Active Optical Technologies
o  Using light is much faster than using
a physical probe
o  Allows also scanning of soft or fragile
objects which would be threatened by
probing
o  Three types of optical sensing:
n  Point, similar to a physical
probe
o slow approach, lots of physical
movement by the sensor.
n  Stripe
o  faster: a band of many points
passes over the object at once
n Other patterns …
4
R. Scopigno, 3D Digitization - HW 6
Stripe-based scanning
R. Scopigno, 3D Digitization - HW 7
Optical Technologies - Triangulation
How do we compute the 3D
coordinates of each sampled
point?
o  By triangulation, known:
n  emitting point of the
light source + direction
(illuminant or
emitter)
n  the focus point of the
acquisition camera
(sensor)
n  the center of the
imaged reflection on the
acquisition sensor plane
( P(a) )
Triangulation is an old, simple approach (Thales-Talete)
Issues: precision and price of the system
5
R. Scopigno, 3D Digitization - HW 8
Output: range map
R. Scopigno, 3D Digitization - HW 9
Triangulation-based systems
An inherent limitation of the
triangulation approach:
non-visible regions
o  Some surface regions can be
visible to the emitter and
not-visible to the receiver,
and vice-versa
o  In all these regions we miss
sampled points è
integration of multiple scans
6
R. Scopigno, 3D Digitization - HW 10
Scanning example
R. Scopigno, 3D Digitization - HW 11
Acquisition accuracy
o  Depends on sweeping
approach …
o  … on surface curvature
w.r.t. light direction …
o  Laser syst.: the
reflected intensity can
be used as an estimate of
the accuracy of the
measure
7
R. Scopigno, 3D Digitization - HW 12
Acquisition accuracy
o  … on the surface shape nearby the sampled point
o  … and on surface reflectance
[see Curless Levoy “…Space Time Analysis”, ’95]
R. Scopigno, 3D Digitization - HW 13
Optical Tech. – Time of Flight
Measure the time a light impulse needs to travel from the emitter to the
target point (and back)
n  Source: emits a light pulse and starts a nanosecond watch
n  Sensor: detects the reflected light, stops the watch
(roundtrip time)
n  Distance = ½ time * lightspeed [e.g. 6.67 ns è 1 m ]
o  Advantages: no triangulation, source and receiver can be on the
same axis è smaller footprint (wide distance measures), no shadow
effects
[Image by R. Lange et al, SPIE v.3823]
8
R. Scopigno, 3D Digitization - HW 14
Optical– Time of Flight
o  Optical signal:
n  Pulsed light: easier to be detected, more complex to be
generated at high frequency (short pulses, fast rise and fall
times)
n  Modulated light (sine waves, intensity): phase difference
between sent and received signal è distance (modulo
wavelenght)
n  A combination of the previous (pulsed sine)
o  Scanning:
n  single spot measure
n  range map, by rotating mirrors
or motorized 2 DOF head
[Image by Brian Curless,
Sig2000 CourseNotes]
R. Scopigno, 3D Digitization - HW 15
3D scanning – raw output data
For the user, same type of output data :
n  Range map: 2D map of sampled 3D points
(640x480 -> 2M - 5M points)
n  Can be managed as a point cloud or a
triangulated surface chunk
9
R. Scopigno, 3D Digitization - HW 16
Why processing raw scanned data?
The acquisition of a single shot
(range map) is only a single step
in the 3D scanning process, since
it returns a partial & incomplete
representation
dal parziale
al totale
We need algorithms and software
tools for transforming redundandt
sampled data into a complete and
optimal 3D model

3D Scanning Pipeline
R. Scopigno, 3D Digitization - HW 17
10
Note:
New approaches appeared that use many
redundant & overlapping images to
produce results similar to those produced
with active scanning devices
è
3D from images (passive methods)
R. Scopigno, 3D Digitization - HW 18
R. Scopigno, 3D Digitization - HW 19
Questions?
o  Contact:
Visual Computing Lab.
of ISTI - CNR
http://vcg.isti.cnr.it
r.scopigno@isti.cnr.it

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3d scanning techniques

  • 1. 1 Introduction to 3D digitization technologies Roberto Scopigno Visual Computing Lab. CNR-ISTI Pisa, Italy R. Scopigno, 3D Digitization - HW 1 Overview o  Digitization for visual presentation: 3D vs. enhanced 2D media o  3D digitization technologies
  • 2. 2 2 Acquiring Visually Rich 3D Models Goal: Build accurate digital models to clone the reality (shape + surface reflection properties) Acquisition methodologies: n  Image-based Rendering o  Panoramic images (2D) o  RTI images (2D) n  Standard CAD modeling (manual process) n  Approaches based on Sampling o  3D scanning (active) o  3D from images (passive) 3 Modelling vs. Sampling o  Modelling n  Manual process [“redraw”] n  Accuracy is unknown n  3D model is usually complete o  Sampling/scanning n  Semi-automatic process [“photography”] n  Accuracy is known n  3D model is usually uncomplete (many unsampled regions) R. Scopigno, 3D Digitization - HW
  • 3. 3 R. Scopigno, 3D Digitization - HW 4 3D scanning devices Many different technologies, just two examples: o  Laser or structured light, Triangulation n  Small/medium scale artifacts (statues) n  Small/medium workspace 20x20 -> 100x100 cm, distance from artifact ~1 m n  High accuracy (>0.05 mm) n  High sampling density (0.2 mm) n  Fast (1 shot in ~1-2 sec) o  Laser, Time of flight n  Large scale (architectures) n  Wide workspace (many meters) n  Medium accuracy (~4-10 mm) n  Medium sampling density (10 mm) n  Slow (1 shot in ~20 min) R. Scopigno, 3D Digitization - HW 5 Active Optical Technologies o  Using light is much faster than using a physical probe o  Allows also scanning of soft or fragile objects which would be threatened by probing o  Three types of optical sensing: n  Point, similar to a physical probe o slow approach, lots of physical movement by the sensor. n  Stripe o  faster: a band of many points passes over the object at once n Other patterns …
  • 4. 4 R. Scopigno, 3D Digitization - HW 6 Stripe-based scanning R. Scopigno, 3D Digitization - HW 7 Optical Technologies - Triangulation How do we compute the 3D coordinates of each sampled point? o  By triangulation, known: n  emitting point of the light source + direction (illuminant or emitter) n  the focus point of the acquisition camera (sensor) n  the center of the imaged reflection on the acquisition sensor plane ( P(a) ) Triangulation is an old, simple approach (Thales-Talete) Issues: precision and price of the system
  • 5. 5 R. Scopigno, 3D Digitization - HW 8 Output: range map R. Scopigno, 3D Digitization - HW 9 Triangulation-based systems An inherent limitation of the triangulation approach: non-visible regions o  Some surface regions can be visible to the emitter and not-visible to the receiver, and vice-versa o  In all these regions we miss sampled points è integration of multiple scans
  • 6. 6 R. Scopigno, 3D Digitization - HW 10 Scanning example R. Scopigno, 3D Digitization - HW 11 Acquisition accuracy o  Depends on sweeping approach … o  … on surface curvature w.r.t. light direction … o  Laser syst.: the reflected intensity can be used as an estimate of the accuracy of the measure
  • 7. 7 R. Scopigno, 3D Digitization - HW 12 Acquisition accuracy o  … on the surface shape nearby the sampled point o  … and on surface reflectance [see Curless Levoy “…Space Time Analysis”, ’95] R. Scopigno, 3D Digitization - HW 13 Optical Tech. – Time of Flight Measure the time a light impulse needs to travel from the emitter to the target point (and back) n  Source: emits a light pulse and starts a nanosecond watch n  Sensor: detects the reflected light, stops the watch (roundtrip time) n  Distance = ½ time * lightspeed [e.g. 6.67 ns è 1 m ] o  Advantages: no triangulation, source and receiver can be on the same axis è smaller footprint (wide distance measures), no shadow effects [Image by R. Lange et al, SPIE v.3823]
  • 8. 8 R. Scopigno, 3D Digitization - HW 14 Optical– Time of Flight o  Optical signal: n  Pulsed light: easier to be detected, more complex to be generated at high frequency (short pulses, fast rise and fall times) n  Modulated light (sine waves, intensity): phase difference between sent and received signal è distance (modulo wavelenght) n  A combination of the previous (pulsed sine) o  Scanning: n  single spot measure n  range map, by rotating mirrors or motorized 2 DOF head [Image by Brian Curless, Sig2000 CourseNotes] R. Scopigno, 3D Digitization - HW 15 3D scanning – raw output data For the user, same type of output data : n  Range map: 2D map of sampled 3D points (640x480 -> 2M - 5M points) n  Can be managed as a point cloud or a triangulated surface chunk
  • 9. 9 R. Scopigno, 3D Digitization - HW 16 Why processing raw scanned data? The acquisition of a single shot (range map) is only a single step in the 3D scanning process, since it returns a partial & incomplete representation dal parziale al totale We need algorithms and software tools for transforming redundandt sampled data into a complete and optimal 3D model  3D Scanning Pipeline R. Scopigno, 3D Digitization - HW 17
  • 10. 10 Note: New approaches appeared that use many redundant & overlapping images to produce results similar to those produced with active scanning devices è 3D from images (passive methods) R. Scopigno, 3D Digitization - HW 18 R. Scopigno, 3D Digitization - HW 19 Questions? o  Contact: Visual Computing Lab. of ISTI - CNR http://vcg.isti.cnr.it r.scopigno@isti.cnr.it