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1
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- Project 3 grades out today, write-ups online asap
- Project 4 extension: Thurs,
11:59pm
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2
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- Readings
- S. M. Seitz and C. R. Dyer, Photorealistic Scene Reconstruction by
Voxel Coloring, International Journal of Computer Vision, 35(2), 1999,
pp. 151-173.
- http://www.cs.washington.edu/homes/seitz/papers/ijcv99.pdf
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3
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- What’s the optimal baseline?
- Too small: large depth error
- Too large: difficult search
problem
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4
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5
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6
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7
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- Basic Approach
- Choose a reference view
- Use your favorite stereo algorithm BUT
- replace two-view SSD with SSD over all baselines
- Limitations
- Must choose a reference view (bad)
- Visibility!
- CMU’s 3D Room Video
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8
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9
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10
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11
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12
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- Theoretical Questions
- Identify class of all photo-consistent scenes
- Practical Questions
- How do we compute photo-consistent models?
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13
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14
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15
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- Reconstruction Contains the True Scene
- But is generally not the same
- In the limit (all views) get visual hull
- Complement of all lines that don’t intersect S
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16
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- Color voxel black if on silhouette in every image
- for M images, N3 voxels
- Don’t have to search 2N3 possible scenes!
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17
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- Pros
- Easy to implement, fast
- Accelerated via octrees [Szeliski 1993] or interval techniques [Matusik
2000]
- Cons
- No concavities
- Reconstruction is not photo-consistent
- Requires identification of silhouettes
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18
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19
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20
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21
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- Cameras oriented in many different directions
- Planar depth ordering does not apply
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22
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23
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24
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25
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26
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- Calibrated Turntable
- 360° rotation (21 images)
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27
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28
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- A view-independent depth order may not exist
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29
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30
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31
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- The Photo Hull is the UNION of all photo-consistent scenes in V
- It is a photo-consistent scene reconstruction
- Tightest possible bound on the true scene
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32
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- The Basic Algorithm is Unwieldy
- Alternative: Multi-Pass Plane
Sweep
- Efficient, can use texture-mapping hardware
- Converges quickly in practice
- Easy to implement
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33
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- Sweep plane in each of 6 principle directions
- Consider cameras on only one side of plane
- Repeat until convergence
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34
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- Sweep plane in each of 6 principle directions
- Consider cameras on only one side of plane
- Repeat until convergence
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35
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- Sweep plane in each of 6 principle directions
- Consider cameras on only one side of plane
- Repeat until convergence
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36
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- Sweep plane in each of 6 principle directions
- Consider cameras on only one side of plane
- Repeat until convergence
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37
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- Sweep plane in each of 6 principle directions
- Consider cameras on only one side of plane
- Repeat until convergence
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38
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- Sweep plane in each of 6 principle directions
- Consider cameras on only one side of plane
- Repeat until convergence
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39
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40
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41
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