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Symmetric Photography: Exploiting Datasparseness in Reflectance Fields
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Symmetric Photography: Dealing with 8D Reflectance Fields. Relighting ... Symmetric Photography. Transport equation: T is symmetric (Helmholtz reciprocity) ... – PowerPoint PPT presentation
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Title: Symmetric Photography: Exploiting Datasparseness in Reflectance Fields
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Symmetric PhotographyExploiting Data-sparseness
in Reflectance Fields
- Gaurav Garg
Eino-Ville
Hendrik P. A. Lensch
Marc Levoy
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Symmetric PhotographyDealing with 8D
Reflectance Fields
Example Capture
- Relighting
Ground Truth
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Overview
- Full 8D Reflectance field!
- Changing View (4D) Changing Light (4D)
- Eg. For Each 4D, 3x3 images at 100x100 res
results in 1010 4D table - How do we deal with data explosion?
- Exploit Symmetry between light/view
- Helmholtz reciprocity
- Exploit Data Sparseness
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Symmetric Photography
Transport equation
- T is symmetric (Helmholtz reciprocity)
- T is not sparse
- But sub-blocks of T are data sparse
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Visualizing Symmetry andData-sparsity
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Outline
- Data Acquisition Setup
- Exploiting Symmetry and Data Sparsity in the
Transport Matrix - Results
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Symmetric Setup
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Acquisition
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Outline
- Data Acquisition Setup
- Exploiting Symmetry and Data Sparsity in the
Transport Matrix - Results
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Exploiting Symmetry Data Sparsity
- Symmetry Data Sparsity used for a hierarchical
acquisition scheme which simultaneously acquires
and compresses the data.
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Hierarchical Tensors Parallel Acquisition
- If M0, U1 and U2 are radiometrically isolated.
- If M!0, but is known, we can subtract it out to
isolate U1 and U2 - This allows us to illuminate projector pixels in
U1 and U2 in parallel.
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Hierarchical Tensors Rank-1 Approximation
- An image captured by the camera is the sum of
the columns corresponding to the pixels lit by
the projector. The image is also the sum of the
corresponding rows - Use two projector patterns (Pr and Pc) s.t.
- and
- The rank-1 approximation of M is
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Hierarchical Acquisition
- Already have a rank-1 approximation
- For root node, use flood lit image for first
approximation - Divide node by 16 and move to next level
- 4 projector blocks X 4 camera blocks
- Use 4 projector patterns and capture 4 images (8
images total) - Evaluate previous levels rank-1 approx against
these images - If good enough, finish
- If the size of the projector block is down to a
pixel, finish - Else, use these images to create 16 rank-1
approximations, and goto 1.) for each of them - Note I have heavily glossed over the selection
of projector patterns
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Outline
- Data Acquisition Setup
- Exploiting Symmetry and Data Sparsity in the
Transport Matrix - Results
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Changing Light
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Changing View
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Symmetric vs. Dual Photography
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Artifacts Due to Non-Symmetry
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Hierarchy Levels
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Table
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