Embed Size (px)
Citation preview
Seeing through Obscure
Glass
Qi Shan, Brian Curless, and Todayoshi Kohno
University of Washington
What is obscure glass?
Obscure glass:
glass with texture relief
Refraction distorts and blurs
the background.
Examples of obscure glass
Examples of obscure glass
Examples of obscure glass
Examples of obscure glass
Camera
Camera
The goal of the project
* =
* = -1
Inverse
Digital approach
Optical approach
-1
. ( )
A linear form
I FL
. =
I F
Rewriting the formation process in a matrix-vector form
Lknown unknown unknown
= one pixel
.
Digital approach
Calibration
Reconstruction
. =
-1
. ( )
Recover from a
single input?
known unknown known
known unknown known
known unknown unknown
Calibration (obtaining F)
Assumption: have access to both sides of the glass.
Calibration process:
1. Place a set of known patterns at the back of the obscure glass;
2. Capture the images through the obscure glass
The number of calibration patterns
For 50x50 kernels, a naïve algorithms needs more than
2,500 image pairs
We assume sparseness of F combined with a multi-
scale optimization
The number of required patterns
◦ 2,500 -> ~100
Experimental procedure:
1) Position camera close to glass.
2) Capture calibration patterns through glass;
estimate F.
3) Remove, then approximately replace camera.
4) Take multiple shots from nearby viewpoints.
5) Compute a result image for each shot
6) Keep best image (nearest to original
viewpoint).
Results
Increase allowed size of kernels
Digital approach
Optical approach
-1
. ( )
Optical approach
Optical approach
Snell’s Law
sin
sin
in out
out in
n
n
in
in
out
out
Snell’s Law
sin,
sin
in outout in
out in
in out
nn n
n
in
out
in
out
Limitations
Digital approach requires:
◦ sparse-kernel glass;
◦ access to both sides for a period of time;
◦ ability to re-position camera reasonably well
Applied substance requires access to the textured
side(s)
Placing substance and/or camera on glass reveals
the observer
Digital approach
Optical approach
Backup slides
Natural image statistics
…
Natural image statistics
…
