General Linear Cameras with Finite Aperture Andrew Adams and Marc Levoy Stanford University.
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Transcript of General Linear Cameras with Finite Aperture Andrew Adams and Marc Levoy Stanford University.
Slices of Ray Space
• Pushbroom
• Cross Slit
• General Linear Cameras
Yu and McMillan ‘04
Román et al. ‘04
Projections of Ray Space
• Plenoptic Cameras
• Camera Arrays
• Regular Cameras
Ng et al. ‘04
Wilburn et al. ‘05Leica Apo-Summicron-M
What is this paper?
• An intuitive reformulation of general linear cameras in terms of eigenvectors
• An analogous description of focus
What is this paper?
• An intuitive reformulation of general linear cameras in terms of eigenvectors
• An analogous description of focus
• A theoretical framework for understanding and characterizing linear slices and integral projections of ray space
Slices of Ray Space
• Image(x, y) = L(x, y, P(x, y))
• P determines perspective
• Let’s assume P is linear
Slices of Ray Space
• Rays meet when:
((1-z)P + zI) is low rank
• Substitute b = z/(z-1):
((1-z)P + zI) = (1-z)(P – bI)
• Rays meet when:
(P – bI) is low rank
Slices of Ray Space
Real Eigenvalues
Complex Conjugate Eigenvalues
Equal Eigenvalues
Equal Eigenvalues,
2D Eigenspace
Slices of Ray Space
Real Eigenvalues
Complex Conjugate Eigenvalues
Equal Eigenvalues
One slit at infinity
Equal Eigenvalues,
2D Eigenspace
Projections of Ray Space
• Rays meet when:
((1-z)I + zF) is low rank
• Substitute b = (z-1)/z:
((1-z)I + zF) = z(F – bI)
• Rays meet when:
(F – bI) is low rank
Slices of Ray Space
Real Eigenvalues
Complex Conjugate Eigenvalues
Equal Eigenvalues
Equal Eigenvalues,
2D Eigenspace
Slices of Ray Space
Real Eigenvalues
Complex Conjugate Eigenvalues
Equal Eigenvalues
One focal slit at infinity
Equal Eigenvalues,
2D Eigenspace
Projections of Ray Space
• Factor Q as:
• M warps lightfield in (x, y)– warps final image
A
M
IP
FI
APM
FAMQ
0
0
Projections of Ray Space
• Factor Q as:
• M warps lightfield in (x, y)– warps final image
• A warps lightfield in (u, v)– shapes domain of integration (bokeh, aperture size)
A
M
IP
FI
APM
FAMQ
0
0
Conclusion
• General Linear Cameras can be characterized by the eigenvalues of a 2x2 matrix.
• Focus can be described in the same fashion.
Conclusion
• General Linear Cameras can be characterized by the eigenvalues of a 2x2 matrix.
• Focus can be described in the same fashion.
• These matrices are a good way to analyze and specify linear integral projections of ray space.