Polarization-based Shape Estimation of Transparent Objects by Using Raytracing and PLZT Camera...
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Transcript of Polarization-based Shape Estimation of Transparent Objects by Using Raytracing and PLZT Camera...
Polarization-based Shape Estimation of Transparent Objects by Using Raytracing a
nd PLZT CameraDaisuke Miyazaki The University of TokyoNoriyuki Takashima Furuuchi Chemical CorporationAkira Yoshida Furuuchi Chemical CorporationEiki Harashima Furuuchi Chemical CorporationKatsushi Ikeuchi The University of Tokyo
The 1st part of this talk
• PLZT polarization camera• Measures the polarization state (Stokes
vector) of the light• Is controllable from the computer
Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(11)Introduction(1/2)
The 2nd part of this talk
• Inverse polarization raytracing• Estimates the 3D shape of transparent obj
ects• Solves the inverse problem of the polarizati
on raytracing
Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(11)Introduction(2/2)
PLZT polarization camera
Mueller calculusLight: 4D vector (Stokes vector)Material: 4x4 matrix (Mueller matrix)
3
2
1
0
ssss Intensity
Power of 0 linear polarized lightPower of 45 linear polarized lightPower of right circular polarized light
DOP(degree of polarization)
2 2 21 2 3
0
s s ss
Introduction(2) Conclusion(2)
Algorithm(6) Experiment(4)
Inverse polarization raytracing(11)PLZT polarization camera(1/12)
Intro(1/2)
Mueller matrixND (neutral density) filter
1000010000100001
NWN
WN: alpha value (0~1)
Retardation1 0 0 00 1 0 0
( )0 0 cos sin0 0 sin cos
D
δ: retardation value
Horizontal linear polarizer
1000010000110011
LWL
WL: 0~0.5 (ideally 0.5)
Rotation1 0 0 00 cos 2 sin 2 0
( )0 sin 2 cos 2 00 0 0 1
C
Introduction(2) Conclusion(2)
Algorithm(6) Experiment(4)
Inverse polarization raytracing(11)PLZT polarization camera(2/12)
Intro(2/2)
PLZT
• Lanthanum-modified lead zirconate titanate• Made from 4 kinds of metal compound
Pb: leadLa: lanthanumZr: zirconiumTi: titanium
• Transparent ceramics• Birefringent media depending on the voltage
3x/4lylyxx-l O)Ti(ZrLaPb
Introduction(2) Conclusion(2)
Experiment(4)
Inverse polarization raytracing(11)PLZT polarization camera(3/12)
Algorithm(1/6)Intro(2)
PLZT and ND filter
Camera Target scene(Light, object, ...)
PLZTNDfilter
x
y
z
+90
Opticalaxis
Introduction(2) Conclusion(2)
Experiment(4)
Inverse polarization raytracing(11)PLZT polarization camera(4/12)
Algorithm(2/6)Intro(2)
Mueller matrix of the system
: Amount of the phase shift of PLZT(depends on the voltage)
cossin00sincos0000100001
)(ˆ)( NND WDNMSystem
NND filter
ˆ ( ) ( 90 ) ( ) ( 90 ) D C D CPLZT rotated 90
( )CRotation( )DRetardation
Introduction(2) Conclusion(2)
Experiment(4)
Inverse polarization raytracing(11)PLZT polarization camera(5/12)
Algorithm(3/6)Intro(2)
PLZT and linear polarizer
Camera Target scene(Light, object, ...)
PLZTLinearpolarizer
+22.5x
y
z
+90
Opticalaxis
Opticalaxis
Introduction(2) Conclusion(2)
Experiment(4)
Inverse polarization raytracing(11)PLZT polarization camera(6/12)
Algorithm(4/6)Intro(2)
Mueller matrix of the system
ˆ ( )DPLZT rotated 90
( )CRotation
: Amount of the phase shift of PLZT(depends on the voltage)
System
0000
sin21cos
21
21
22
sin21cos
21
21
22
sin22cos
22
221
)(ˆˆ)(
LPL WDLM
Linear polarizer rotated 22.5ˆ ( 22.5 ) ( 22.5 ) L C LC
Horizontal linear polarizer L
Introduction(2) Conclusion(2)
Experiment(4)
Inverse polarization raytracing(11)PLZT polarization camera(7/12)
Algorithm(5/6)Intro(2)
Computing Stokes vectorPLZT with ND filterPLZT with linear polarizer [ retarder]PLZT with linear polarizer [1/4 waveplate]PLZT with linear polarizer [1/2 waveplate]
NDM
( )PL M
( 2)PL M
( )PL M
3
2
1
0
2/1,,0
4/1,,0
,,0
,0
022
22
220
22
sin22cos
22
22
000
ssss
WWW
WWW
WWWW
W
ssss
LLL
LLL
LLLL
N
PL
PL
PL
ND
Inversematrix
Stokes vectorfrom 4 images
Introduction(2) Conclusion(2)
Experiment(4)
Inverse polarization raytracing(11)PLZT polarization camera(8/12)
Algorithm(6/6)Intro(2)
Experiment setup
CameraSlider
ND filterLinear polarizer
PLZT unitBand-pass filter
UV-cut filterIR-cut filter
+x
-x+y
-y
Introduction(2) Conclusion(2)Inverse polarization raytracing(11)PLZT polarization camera(9/12)
Intro(2) Algorithm(6) Experiment(1/4)
Experiment result
s0 s1 s2 s3
DOP
Introduction(2) Conclusion(2)Inverse polarization raytracing(11)PLZT polarization camera(10/12)
Intro(2) Algorithm(6) Experiment(2/4)
Evaluation
• DOP of linear polarizer• True value = 1.0• Measurement result
= 0.72
• s3/s0 of left circular polarizer• True value = -1.0• Measurement result
= -0.25
Introduction(2) Conclusion(2)Inverse polarization raytracing(11)PLZT polarization camera(11/12)
Intro(2) Algorithm(6) Experiment(3/4)
Related work
• Liquid crystal polarization camera• Wolff, Mancini, Pouli
qen, Andreou (1997)• Fujikake, Takizawa,
Aida, Kikuchi, Fujii, Kawakita (1998)
• Harnett, Craighead (2002)
• Our PLZT polarization camera• Obtain whole Stokes
parameters• PLZT has higher
response time than LC
Introduction(2) Conclusion(2)Inverse polarization raytracing(11)PLZT polarization camera(12/12)
Intro(2) Algorithm(6) Experiment(4/4)
Inverse polarization raytracing
Reflection and transmissionNormal
Unpolarized
AirObject
Partially polarized
Partially polarized
LightDepends
upon
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(1/11)
Intro(1/4) Algorithm(3) Experiment(4)
Interreflection
[Miyazaki 2004]Reflection only
[This method]Reflection & transmission
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(2/11)
Intro(2/4) Algorithm(3) Experiment(4)
Polarization raytracing
• Raytracing with polarization• Gondek et al. 1994, Wolff & Kurlander 199
0, Tannenbaum et al. 1994, Guy & Soler 2004, Chipman 1995, Wilkie 2001
• Commercial software
• We use: raytracing + Mueller calculus
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(3/11)
Intro(3/4) Algorithm(3) Experiment(4)
Reflection/Transmission matrix
Transmission
|| ||
|| ||
||
||
2 2 0 0
2 2 0 0
0 0 0
0 0 0
T T T T
T T T T
TT
TT
T
Reflection
RRRR
RRRRRRRR
||
||
||||
||||
00000000220022
R
Fresnel coefficients: ||R R ||T T
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(4/11)
Intro(4/4) Algorithm(3) Experiment(4)
Cost function
min
Calculate height and normal
dxdy
dxdyqHpHII yxRE222min
Input Calculated
RE II
Relationshipbetween
normal & heightxHp yHq
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(5/11)
Experiment(4)Intro(4) Algorithm(1/3)
Update normal
Light ray
Object
Ray changes
Ray changes
Changenormal
Input DOPCalculated DOP
Error
1p p E 2RE IIE 2q q E
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(6/11)
Experiment(4)Intro(4) Algorithm(2/3)
Algorithm overviewInitial height
Output height
Normal fromheight
Height fromnormal
is small
2
Input Calc.
Stop when
Minimize
Update normal
2
Input Calc.
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(7/11)
Experiment(4)Intro(4) Algorithm(3/3)
Monochromecamera IR/UV cut-off
filter
Linearpolarizer
Transparent object inside
40Wlamp
Plasticsphere
Experimental setupIntroduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(8/11)
Intro(4) Algorithm(3) Experiment(1/4)
Experimental result
Acrylic hemisphere (r=15mm) 10 loop
Initial (Miyazaki 2004) 50 loop
Error(height)2.8mm 0.61mm
Error(normal)147.0
Frontal shape(estimated)Frontal shape(truth)Rear shape(known)
Refractive index 1.5& Illumination (known)
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(9/11)
Intro(4) Algorithm(3) Experiment(2/4)
Experimental result
Initial (Miyazaki 2004)
10 loop
Glass (n=1.5)
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(10/11)
Intro(4) Algorithm(3) Experiment(3/4)
Related work
• Shape estimation of transparent object• Murase 1992, Hata et al.
1996, Ohara et al. 2003, Ben-Ezra & Nayar 2003, Kutulakos 2005, Saito et al. 1999, Miyazaki et al. 2002, Miyazaki et al. 2004
• Shape from polarization• Koshikawa & Shirai 198
7, Wolff & Boult 1991, Rahmann 1999, Rahmann 2000, Rahmann & Canterakis 2001, Rahmann 2003, Drbohlav & Sara 2001, Miyazaki et al. 2003
Target is transparentEstimate arbitrary shape[Our method]
Introduction(2) Conclusion(2)PLZT polarization camera(12) Inverse polarization raytracing(11/11)
Intro(4) Algorithm(3) Experiment(4/4)
Conclusion
Summary[Inverse polarization raytracing][PLZT polarization camera]
PLZTND/LP filter
0 1 2 3Ts s s s
Stokes vector
Voltage
Shape
Iteration
min2
Input Calc.
Introduction(2) PLZT polarization camera(12) Inverse polarization raytracing(11) Conclusion(1/2)
Future work[Inverse polarization raytracing][PLZT polarization camera]
Estimating refractive index
?
Realtime measurement
Improve the accuracy
Introduction(2) PLZT polarization camera(12) Inverse polarization raytracing(11) Conclusion(2/2)
© Daisuke Miyazaki 2005All rights reserved.
http://www.cvl.iis.u-tokyo.ac.jp/Daisuke Miyazaki, Noriyuki Takashima, Akira Yoshida, Eiki Harashima, Katsushi Ikeuchi, "Polarization-based Shape Estimation of Transparent Objects by Using Raytracing and PLZT Camera," in Proceedings of SPIE (Polarization Science and Remote Sensing II, Part of SPIE's International Symposium on Optics and Photonics 2005), Vol. 58
88, pp. 1-14, San Diego, CA USA, 2005.8