Overview of 3D Scanners - PowerPoint PPT Presentation

About This Presentation
Title:

Overview of 3D Scanners

Description:

Bad around silhouettes. Confused by non-diffuse surfaces ... problems in areas of low texture, in non-diffuse regions, and around silhouettes ... – PowerPoint PPT presentation

Number of Views:38
Avg rating:3.0/5.0
Slides: 48
Provided by: Szymo8
Category:

less

Transcript and Presenter's Notes

Title: Overview of 3D Scanners


1
Overview of 3D Scanners

Acknowledgement some content and figures by
Brian Curless
2
3D Data Types
  • Point Data
  • Volumetric Data
  • Surface Data

3
3D Data Types Point Data
  • Point clouds
  • Advantage simplest data type
  • Disadvantage no information onadjacency /
    connectivity

4
3D Data Types Volumetric Data
  • Regularly-spaced grid in (x,y,z) voxels
  • For each grid cell, store
  • Occupancy (binary occupied / empty)
  • Density
  • Other properties
  • Popular in medical imaging
  • CAT scans
  • MRI

5
3D Data Types Volumetric Data
  • Advantages
  • Can see inside an object
  • Uniform sampling simpler algorithms
  • Disadvantages
  • Lots of data
  • Wastes space if only storing a surface
  • Most vision sensors / algorithms returnpoint
    or surface data

6
3D Data Types Surface Data
  • Polyhedral
  • Piecewise planar
  • Polygons connected together
  • Most popular triangle meshes
  • Smooth
  • Higher-order (quadratic, cubic, etc.) curves
  • Bézier patches, splines, NURBS, subdivision
    surfaces, etc.

7
3D Data Types Surface Data
  • Advantages
  • Usually corresponds to what we see
  • Usually returned by vision sensors / algorithms
  • Disadvantages
  • How to find surface for translucent objects?
  • Parameterization often non-uniform
  • Non-topology-preserving algorithms difficult

8
3D Data Types Surface Data
  • Implicit surfaces (cf. parametric)
  • Zero set of a 3D function
  • Usually regularly sampled (voxel grid)
  • Advantage easy to write algorithms that change
    topology
  • Disadvantage wasted space, time

9
2½-D Data
  • Image stores an intensity / color alongeach of
    a set of regularly-spaced rays in space
  • Range image stores a depth alongeach of a set
    of regularly-spaced rays in space
  • Not a complete 3D description does notstore
    objects occluded (from some viewpoint)
  • View-dependent scene description

10
2½-D Data
  • This is what most sensors / algorithmsreally
    return
  • Advantages
  • Uniform parameterization
  • Adjacency / connectivity information
  • Disadvantages
  • Does not represent entire object
  • View dependent

11
2½-D Data
  • Range images
  • Range surfaces
  • Depth images
  • Depth maps
  • Height fields
  • 2½-D images
  • Surface profiles
  • xyz maps

12
Related Fields
  • Computer Vision
  • Passive range sensing
  • Rarely construct complete, accurate models
  • Application recognition
  • Metrology
  • Main goal absolute accuracy
  • High precision, provable errors more important
    than scanning speed, complete coverage
  • Applications industrial inspection, quality
    control, as-built models

13
Related Fields
  • Computer Graphics
  • Often want complete model
  • Low noise, geometrically consistent model more
    important than absolute accuracy
  • Application animated CG characters

14
Terminology
  • Range acquisition, shape acquisition,
    rangefinding, range scanning, 3D scanning
  • Alignment, registration
  • Surface reconstruction, 3D scan merging, scan
    integration, surface extraction
  • 3D model acquisition

15
Range Acquisition Taxonomy
Mechanical (CMM, jointed arm)
Inertial (gyroscope, accelerometer)
Contact
Ultrasonic trackers
Magnetic trackers
Industrial CT
Rangeacquisition
Transmissive
Ultrasound
MRI
Radar
Non-optical
Sonar
Reflective
Optical
16
Range Acquisition Taxonomy
Shape from X stereo motion shading texture f
ocus defocus
Passive
Opticalmethods
Active variants of passive methods Stereo w.
projected texture Active depth from
defocus Photometric stereo
Active
Time of flight
Triangulation
17
Touch Probes
  • Jointed arms with angular encoders
  • Return position, orientation of tip

Faro Arm Faro Technologies, Inc.
18
Optical Range Acquisition Methods
  • Advantages
  • Non-contact
  • Safe
  • Usually inexpensive
  • Usually fast
  • Disadvantages
  • Sensitive to transparency
  • Confused by specularity and interreflection
  • Texture (helps some methods, hurts others)

19
Stereo
  • Find feature in one image, search along epipolar
    line in other image for correspondence

20
Stereo
  • Advantages
  • Passive
  • Cheap hardware (2 cameras)
  • Easy to accommodate motion
  • Intuitive analogue to human vision
  • Disadvantages
  • Only acquire good data at features
  • Sparse, relatively noisy data (correspondence is
    hard)
  • Bad around silhouettes
  • Confused by non-diffuse surfaces
  • Variant multibaseline stereo to reduce ambiguity

21
Why More Than 2 Views?
  • Baseline
  • Too short low accuracy
  • Too long matching becomes hard

22
Why More Than 2 Views?
  • Ambiguity with 2 views

23
Multibaseline Stereo
Okutami Kanade
24
Shape from Motion
  • Limiting case of multibaseline stereo
  • Track a feature in a video sequence
  • For n frames and f features, have2?n?f knowns,
    6?n3?f unknowns

25
Shape from Motion
  • Advantages
  • Feature tracking easier than correspondence in
    far-away views
  • Mathematically more stable (large baseline)
  • Disadvantages
  • Does not accommodate object motion
  • Still problems in areas of low texture, in
    non-diffuse regions, and around silhouettes

26
Shape from Shading
  • Given image of surface with known, constant
    reflectance under known point light
  • Estimate normals, integrate to find surface
  • Problem ambiguity

27
Shape from Shading
  • Advantages
  • Single image
  • No correspondences
  • Analogue in human vision
  • Disadvantages
  • Mathematically unstable
  • Cant have texture
  • Photometric stereo (active method) more
    practical than passive version

28
Shape from Texture
  • Mathematically similar to shape from shading, but
    uses stretch and shrink of a (regular) texture

29
Shape from Texture
  • Analogue to human vision
  • Same disadvantages as shape from shading

30
Shape from Focus and Defocus
  • Shape from focus at which focus setting is a
    given image region sharpest?
  • Shape from defocus how out-of-focus is each
    image region?
  • Passive versions rarely used
  • Active depth from defocus can bemade practical

31
Active Optical Methods
  • Advantages
  • Usually can get dense data
  • Usually much more robust and accurate than
    passive techniques
  • Disadvantages
  • Introduces light into scene (distracting, etc.)
  • Not motivated by human vision

32
Active Variants of Passive Techniques
  • Regular stereo with projected texture
  • Provides features for correspondence
  • Active depth from defocus
  • Known pattern helps to estimate defocus
  • Photometric stereo
  • Shape from shading with multiple known lights

33
Pulsed Time of Flight
  • Basic idea send out pulse of light (usually
    laser), time how long it takes to return

34
Pulsed Time of Flight
  • Advantages
  • Large working volume (up to 100 m.)
  • Disadvantages
  • Not-so-great accuracy (at best 5 mm.)
  • Requires getting timing to 30 picoseconds
  • Does not scale with working volume
  • Often used for scanning buildings, rooms,
    archeological sites, etc.

35
AM Modulation Time of Flight
  • Modulate a laser at frequency?m , it returns with
    a phase shift ??
  • Note the ambiguity in the measured phase!? Range
    ambiguity of 1/2?mn

36
AM Modulation Time of Flight
  • Accuracy / working volume tradeoff(e.g., noise
    1/500 working volume)
  • In practice, often used for room-sized
    environments (cheaper, more accurate than pulsed
    time of flight)

37
Triangulation
38
Triangulation Moving theCamera and Illumination
  • Moving independently leads to problems with
    focus, resolution
  • Most scanners mount camera and light source
    rigidly, move them as a unit

39
Triangulation Moving theCamera and Illumination
40
Triangulation Moving theCamera and Illumination
41
Triangulation Extending to 3D
  • Possibility 1 add another mirror (flying spot)
  • Possibility 2 project a stripe, not a dot

Object
42
Triangulation Scanner Issues
  • Accuracy proportional to working volume(typical
    is 10001)
  • Scales down to small working volume(e.g. 5 cm.
    working volume, 50 ?m. accuracy)
  • Does not scale up (baseline too large)
  • Two-line-of-sight problem (shadowing from either
    camera or laser)
  • Triangulation angle non-uniform resolution if
    too small, shadowing if too big (useful range
    15?-30?)

43
Triangulation Scanner Issues
  • Material properties (dark, specular)
  • Subsurface scattering
  • Laser speckle
  • Edge curl
  • Texture embossing

44
Multi-Stripe Triangulation
  • To go faster, project multiple stripes
  • But which stripe is which?
  • Answer 1 assume surface continuity

45
Multi-Stripe Triangulation
  • To go faster, project multiple stripes
  • But which stripe is which?
  • Answer 2 colored stripes (or dots)

46
Multi-Stripe Triangulation
  • To go faster, project multiple stripes
  • But which stripe is which?
  • Answer 3 time-coded stripes

47
Time-Coded Light Patterns
  • Assign each stripe a unique illumination
    codeover time Posdamer 82

Time
Space
Write a Comment
User Comments (0)
About PowerShow.com