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Daisuke Miyazaki Katsushi Ikeuchi The University of Tokyo
Virtual Heritage --- Photometric Aspect Polarization-based Shape Estimation of Transparent Objects for Digitizing Cultural Assets Daisuke Miyazaki Katsushi Ikeuchi The University of Tokyo
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Objective Estimate 3D shape of transparent object
Introduction(1/3) Polarization raytracing(7) Shape estimation(6) Experiment(5) Conclusion(2) Objective Estimate 3D shape of transparent object Analyze the polarization phenomena Polarization analysis Virtual transparent object Real transparent object
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Application fields Modeling cultural assets 3D catalog in web site
Introduction(2/3) Polarization raytracing(7) Shape estimation(6) Experiment(5) Conclusion(2) Application fields Modeling cultural assets 3D catalog in web site Manufacturing robot Object recognition to recycle
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Methods developed in this research
Introduction(3/3) Polarization raytracing(7) Shape estimation(6) Experiment(5) Conclusion(2) Methods developed in this research Saito et al. 1999 Miyazaki et al. 2004 Miyazaki et al. 2002 Today’s talk
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Polarization raytracing(1/7)
Introduction(3) Polarization raytracing(1/7) Shape estimation(6) Experiment(5) Conclusion(2) Polarization Light = wave oscillates Oscillates in certain direction polarization DOP = degree of polarization Partially polarized (DOP 0~1) Incident Reflected Air Object Transmitted Unpolarized (DOP 0) Light Perfectly polarized (DOP 1) Polarizer
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Reflection and transmission
Introduction(3) Polarization raytracing(2/7) Shape estimation(6) Experiment(5) Conclusion(2) Reflection and transmission Normal Depends upon Light Partially polarized Unpolarized Air Object Partially polarized
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Polarization raytracing(3/7)
Introduction(3) Polarization raytracing(3/7) Shape estimation(6) Experiment(5) Conclusion(2) Tracing the light rays Calculate reflection and transmission
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Polarization raytracing
Introduction(3) Polarization raytracing(4/7) Shape estimation(6) Experiment(5) Conclusion(2) Polarization raytracing Ray tracing Ray tracing Calculate intensity Calculate polarization Conventional raytracing Polarization raytracing
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Polarization raytracing(5/7)
Introduction(3) Polarization raytracing(5/7) Shape estimation(6) Experiment(5) Conclusion(2) Mueller calculus Conventional raytracing Intensity: Scalar Reflectivity&transmissivity: Scalar Polarization raytracing Polarization state: 4D vector Reflection&transmisstion matrix: 4x4 matrix
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Example of Mueller calculus
Introduction(3) Polarization raytracing(6/7) Shape estimation(6) Experiment(5) Conclusion(2) Example of Mueller calculus Conventional raytracing Reflected intensity reflectivity incident intensity Scalar Scalar Scalar Polarization raytracing Reflection vector reflection matrix incidence vector
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Polarization raytracing(7/7)
Introduction(3) Polarization raytracing(7/7) Shape estimation(6) Experiment(5) Conclusion(2) Example of matrices Reflection Transmission Rotation Phase shift
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Shape estimation Iterative computation with updating the shape
Introduction(3) Polarization raytracing(7) Shape estimation(1/6) Experiment(5) Conclusion(2) Shape estimation Iterative computation with updating the shape Initial shape Caculated DOP with polarization raytracing 2 min Input DOP (degree of polarization) Final shape
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Cost function Input Calculated Relationship between normal & height
Introduction(3) Polarization raytracing(7) Shape estimation(2/6) Experiment(5) Conclusion(2) Cost function Input Calculated Relationship between normal & height min dxdy Calculate height and normal
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Calculate normal from shape
Introduction(3) Polarization raytracing(7) Shape estimation(3/6) Experiment(5) Conclusion(2) Calculate normal from shape Set initial height H properly Calculate gradient p&q by differentiating height H
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Polarization raytracing(7)
Introduction(3) Polarization raytracing(7) Shape estimation(4/6) Experiment(5) Conclusion(2) Update normal Input DOP Light ray Object Calculated DOP Change normal Ray changes Error
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Calculate height from normal
Introduction(3) Polarization raytracing(7) Shape estimation(5/6) Experiment(5) Conclusion(2) Calculate height from normal Updated normal Relaxation method Calculated height
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Polarization raytracing(7)
Introduction(3) Polarization raytracing(7) Shape estimation(6/6) Experiment(5) Conclusion(2) Algorithm overview Initial height Normal from height Minimize 2 Input Calc. Update normal Output height is small enough 2 Input Calc. Stop when Height from normal
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Experimental setup Monochrome camera Camera adapter Computer
Introduction(3) Polarization raytracing(7) Shape estimation(6) Experiment(1/5) Conclusion(2) Experimental setup Camera adapter Computer Monochrome camera IR/UV cut-off filter Linear polarizer Geodesic dome Polarizer controller Transparent object inside 40W lamp Plastic sphere
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Simulational result Initial 25 loop Initial 20 loop
Introduction(3) Polarization raytracing(7) Shape estimation(6) Experiment(2/5) Conclusion(2) Simulational result Initial 25 loop Initial 20 loop Frontal shape(estimated) Refractive index 1.5 & Illumination (known) Frontal shape(truth) Rear shape(known)
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Polarization raytracing(7)
Introduction(3) Polarization raytracing(7) Shape estimation(6) Experiment(3/5) Conclusion(2) Experimental result Acrylic hemisphere Refractive index 1.5 Diameter 30mm Error(height):0.61mm Error(normal):7.0 Initial (previous method) 50 loop Error(height):2.8mm Error(normal):14 Initial (previous method) 10 loop 3000 50 25 1500 Error/loop
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Polarization raytracing(7)
Introduction(3) Polarization raytracing(7) Shape estimation(6) Experiment(4/5) Conclusion(2) Experimental result Initial 5 loop 50 loop Acrylic object Diameter(base)24mm Refractive index 1.5 Error(height) 0.24mm
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Experimental result Glass(refractive index 1.5) 10 loop
Introduction(3) Polarization raytracing(7) Shape estimation(6) Experiment(5/5) Conclusion(2) Experimental result Glass(refractive index 1.5) 10 loop Initial(previous method)
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Summary Polarization raytracing Iteration Initial shape
Introduction(3) Polarization raytracing(7) Shape estimation(6) Experiment(5) Conclusion(1/2) Summary Polarization raytracing Iteration Initial shape Calculated polarization data 2 min Input polarization data Object Shape
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Future work Realtime measurement Commercial product
Introduction(3) Polarization raytracing(7) Shape estimation(6) Experiment(5) Conclusion(2/2) Future work Commercial product Realtime measurement Estimating refractive index ? Modeling cultural assets
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Kamsa hamnida Supported by Ministry of Education, Culture, Sports, Science and Technology Special thanks to Robotics and Computer Vision Laboratory, Dept. of EECS, KAIST
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Daisuke Miyazaki 2005 Creative Commons Attribution 4
Daisuke Miyazaki 2005 Creative Commons Attribution 4.0 International License. Daisuke Miyazaki, Katsushi Ikeuchi, "Virtual Heritage - Photometric Aspect," in Proceedings of The 1st Joint Workshop of KAIST-RCV and U. Tokyo-Ikeuchi Lab. on Robust Vision Technology, Daejeon, Korea,
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