3D Scanning

1
3D Scanning

Acknowledgement some content and figures by
Brian Curless
2
Data Types

• Volumetric Data
• Voxel grids
• Occupancy
• Density
• Surface Data
• Point clouds
• Range images (range maps)

3
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

4
Related Fields

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

5
Terminology

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

6
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
7
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
8
Optical Range Scanning Methods

• Advantages
• Non-contact
• Safe
• Usually inexpensive
• Usually fast
• Disadvantages
• Sensitive to transparency
• Confused by specularity and interreflection
• Texture (helps some methods, hurts others)

9
Stereo

• Find feature in one image, search along epipole
  in other image for correspondence

10
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

11
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

12
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

13
Shape from Shading

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

14
Shape from Shading

• Advantages
• Single image
• No correspondences
• Analogue in human vision
• Disadvantages
• Mathematically unstable
• Cant have texture
• Not really practical
• But see photometric stereo

15
Shape from Texture

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

16
Shape from Texture

• Analogue to human vision
• Same disadvantages as shape from shading

17
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

18
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

19
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

20
Pulsed Time of Flight

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

21
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.

22
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

23
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)

24
Triangulation
25
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

26
Triangulation Moving theCamera and Illumination
27
Triangulation Moving theCamera and Illumination
28
Triangulation Extending to 3D

• Possibility 1 add another mirror (flying spot)
• Possibility 2 project a stripe, not a dot

Object
29
Triangulation Scanner Issues

• Accuracy proportional to working volume (typical
  is 10001)
• Scales down to small working vol. (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?)

30
Triangulation Scanner Issues

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

31
Multi-Stripe Triangulation

• To go faster, project multiple stripes
• But which stripe is which?
• Answer 1 assume surface continuity

32
Multi-Stripe Triangulation

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

33
Multi-Stripe Triangulation

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

34
Time-Coded Light Patterns

• Assign each stripe a unique illumination
  codeover time Posdamer 82

Time
Space
35
Gray-Code Patterns

• To minimize effects of quantization erroreach
  point may be a boundary only once

Time
Space