1. Triangulation Scanner Design Options

2. Triangulation System Options
Single-stripe systems most robust, but slowest
To go faster, project multiple stripes
But which stripe is which?
In limit, project 2D pattern, determine projector/camera correspondence

3. Time-Coded Light Patterns
Assign each stripe a unique illumination code over time [Posdamer 82]
Time
Just as an example, here’s a very simple code based on binary numbers. If you look at a single position in space (i.e., a single pixel), you see a certain on/off pattern over these four frames. This conveys a code that tells you which stripe you are looking at, which gives you a plane in space with which you can then triangulate to find depths.
Space

4. Gray-Code Patterns
To minimize effects of quantization error: each point may be a boundary only once
Time
Space

5. Accounting for Reflectance
Because of surface reflectance and ambient light, distinguishing between black and white not always easy
Solution: project all-white (and sometimes all-black) frame
Permits multiple shades of gray

6. Multiple Shades of Gray

7. Multiple Shades of Gray

8. Intensity Wedges
Limiting case: intensity wedges

9. Temporal vs. Spatial Continuity
Structured-light systems make certain assumptions about the scene:
Temporal continuity assumption:
Assume scene is static
Assign stripes a code over time
Spatial continuity assumption:
Assume scene is one object
Project a grid, pattern of dots, etc.

10. Grid Methods Assume exactly one continuous surface
Count dots or grid lines
Occlusions cause problems
Some methods use dynamic programming
[Maas]

11. Codes Assuming Local Spatial Continuity
Codeword

12. Codes Assuming Local Spatial Continuity
[Zhang]
[Ozturk]

13. Spatio-Temporal Continuity
Another possible assumption:
Object may move
Velocity low enough to permit tracking
“Spatio-temporal” continuity

14. Designing a Code for Moving Scenes
Projector
Camera

15. Designing a Code for Moving Scenest

16. Designing a Code for Moving Scenes
Codeword t

17. Codes for Moving Scenes
Assign time codes to stripe boundaries
Perform frame-to-frame tracking of corresponding boundaries
Propagate illumination history
[Hall-Holt & Rusinkiewicz, ICCV 2001]
In our system, though, the objects are moving from frame to frame, so if you just used the simple algorithm you might get half of one code and half of another, and come up with the wrong code. So, we need to do some tracking from frame to frame. In fact, we do this based on looking at the boundaries between stripes. The stripes are tracked from frame to frame, and at the end of the day the illumination on both sides of the boundary is what conveys the code.
Illumination history = (WB),(BW),(WB)
Code

18. Designing a Code
Want many “features” to track: lots of black/white edges at each frame
Try to minimize ghosts – WW or BB “boundaries” that can’t be seen directly
There’s an extra little wrinkle, though. If you’re looking for the boundaries between stripes, sometimes you have a “boundary” between two stripes of the same color, which we’ll call a ghost. So, some stripes are easy to track, because you can see them in both frames, but in some cases you have to infer the presence of a stripe you can’t see directly. In order to make this at all feasible, we have to design a code that tries to minimize these ghosts and ensures, for example, that a ghost in one frame becomes visible in the next.

19. Designing a Code Design a code to make tracking possible:
Do not allow two spatially adjacent ghosts
Do not allow two temporally adjacent ghosts t

20. Designing a Code Graph (for 4 frames): Nodes: stripes (over time)
0011
1110
1011
0110
0100
1001
0001
1100
0000
1101
1010
0111
1000
0101
1111
0010
Edges: boundaries (over time)
Nodes: stripes (over time)
Space
Time

21. Designing a Code
Graph (for 4 frames):
0011
1110
1011
0110
0100
1001
0001
1100
0000
1101
1010
0111
1000
0101
1111
0010
Nodes: stripes (over time)
Boundary visible at even times
Boundary visible at odd times
Edges: boundaries (over time)
Path with alternating colors: 55 edges in graph  maximal-length traversal has 110 boundaries (111 stripes)

22. Designing a Code
Many solutions to the graph problem as stated, so we can add more constraints
Maximize effect of errors
No static boundaries
Even distribution of stripes of width 1 and 2

23. Implementation Pipeline: DLP projector illuminates scene @ 60 Hz.
Synchronized NTSC camera captures video
Pipeline returns range 60 Hz.
Project
Code
Capture
Images
Find
Boundaries
Match
Boundaries
Decode
Compute
Range
So here’s how the range scanner looks. We project stripes at 60 Hz., capture video frames at the same rate, and process them to get range images at 60 Hz.

24. Results
Video
frames
Stripe
boundaries
unknown
known
ghosts

25. More Options: Shadow Scanning
Variant of single-stripe triangulation
Use a simple lamp, stick to create a shadow
[Bouguet]

26. More Options: Active Stereo
Benefit: only camera/camera calibration, not camera/projector
Projection possibilities:
Random texture
Single stripe
Others (space-time codes?)
[Davis]