Structured light and active ranging techniques Class 8 - PowerPoint PPT Presentation

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Structured light and active ranging techniques Class 8

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Structured light and active ranging techniques Class 8 Plane-sweep multi-view matching Simple algorithm for multiple cameras No rectification necessary, but also no ... – PowerPoint PPT presentation

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Title: Structured light and active ranging techniques Class 8


1
Structured light and active ranging
techniquesClass 8
2
last Wednesday stereo
per-pixel optimization
per-scanline optimization
full image optimization
3
original image pair
planar rectification
polar rectification
4
Plane-sweep multi-view matching
  • Simple algorithm for multiple cameras
  • No rectification necessary, but also no gain
  • Doesnt deal with occlusions

Collins96 Roy and Cox98 (GC) Yang et
al.02/03 (GPU)
5
3D photography course schedule(tentative)
Lecture Exercise
Sept 26 Introduction -
Oct. 3 Geometry Camera model Camera calibration
Oct. 10 Single View Metrology Measuring in images
Oct. 17 Feature Tracking/matching (Friedrich Fraundorfer) Correspondence computation
Oct. 24 Epipolar Geometry F-matrix computation
Oct. 31 Shape-from-Silhouettes (Li Guan) Visual-hull computation
Nov. 7 Stereo matching Project proposals
Nov. 14 Structured light and active range sensing Papers
Nov. 21 Structure from motion Papers
Nov. 28 Multi-view geometry and self-calibration Papers
Dec. 5 Shape-from-X Papers
Dec. 12 3D modeling and registration Papers
Dec. 19 Appearance modeling and image-based rendering Final project presentations
6
Todays class
  • unstructured light
  • structured light
  • time-of-flight

(some slides from Szymon Rusinkiewicz, Brian
Curless)
7
A Taxonomy
8
A taxonomy
9
Unstructured light
  • project texture to
  • disambiguate stereo

10
Space-time stereo
Davis, Ramamoothi, Rusinkiewicz, CVPR03
11
Space-time stereo
Davis, Ramamoothi, Rusinkiewicz, CVPR03
12
Space-time stereo
Zhang, Curless and Seitz, CVPR03
13
Space-time stereo
Zhang, Curless and Seitz, CVPR03
  • results

14
Light Transport Constancy
Davis, Yang, Wang, ICCV05
15
Triangulation
16
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

17
Triangulation Moving theCamera and Illumination
18
Triangulation Moving theCamera and Illumination
(Rioux et al. 87)
19
Triangulation Extending to 3D
  • Possibility 1 add another mirror (flying spot)
  • Possibility 2 project a stripe, not a dot

Object
20
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?)

21
Triangulation Scanner Issues
  • Material properties (dark, specular)
  • Subsurface scattering
  • Laser speckle
  • Edge curl
  • Texture embossing

22
(No Transcript)
23
Space-time analysis
Curless 95
24
Space-time analysis
Curless 95
25
Projector as camera
26
Multi-Stripe Triangulation
  • To go faster, project multiple stripes
  • But which stripe is which?
  • Answer 1 assume surface continuity

e.g. Eyetronics ShapeCam
27
Real-time system
Koninckx and Van Gool
28
Multi-Stripe Triangulation
  • To go faster, project multiple stripes
  • But which stripe is which?
  • Answer 2 colored stripes (or dots)

29
Multi-Stripe Triangulation
  • To go faster, project multiple stripes
  • But which stripe is which?
  • Answer 3 time-coded stripes

30
Time-Coded Light Patterns
  • Assign each stripe a unique illumination
    codeover time Posdamer 82

Time
Space
31
Better codes
  • Gray code
  • Neighbors only differ one bit

32
Poor mans scanner
Bouget and Perona, ICCV98
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
Depth cameras
  • 2D array of
  • time-of-flight sensors
  • e.g. Canestas CMOS 3D sensor
  • jitter too big on single measurement,
  • but averages out on many
  • (10,000 measurements?100x improvement)

36
Depth cameras
                                                                                                                                       
                                                                                                                                       
                                                                                                                                       
                                                                                                                                       
                                                                                                                                       
3DVs Z-cam
  • Superfast shutter standard CCD
  • cut light off while pulse is coming back, then
    IZ
  • but Ialbedo (use unshuttered reference view)

37
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

38
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)

39
Shadow Moire
40
Depth from focus/defocus
Nayar95
41
Next class structure from motion
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