3d scanning techniques

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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

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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)

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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

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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)


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 …

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Stripe-based scanning


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

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Output: range map


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

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Scanning example


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

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Acquisition accuracy

o … on the surface shape nearby the sampled point

o … and on surface reflectance [see Curless Levoy “…Space Time Analysis”, ’95]


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]

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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]


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

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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


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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)



Questions?

o  Contact:

Visual Computing Lab. of ISTI - CNR

http://vcg.isti.cnr.it

[email protected]

3d scanning techniques

Technology