Ioannis Gkioulekas1 Anat Levin2,3 Todd Zickler1

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Presentation transcript:

An evaluation of computational imaging techniques for inverse scattering Ioannis Gkioulekas1 Anat Levin2,3 Todd Zickler1 Thanks for the introduction. 1Harvard SEAS 2Weizmann Institute 3Technion

Looking inside stuff making sense of this source sensor visible X-ray EM spectrum visible X-ray making sense of this 2: To tease you about scattering, I made this collage to show you that scattering materials are everywhere. Our skin and most biological tissues have scattering. And so do jewels and natural minerals. Leaves, fruits and vegetables, and most of the stuff we eat are made of scattering materials We see scattering in chemicals ranging from soap and wax, to cosmetics, to industrial coating powers. And material scientists are continually developing structures that exhibit new and useful forms of scattering behavior. Because of the ubiquitity of these materials, several sciences have been studying scattering for several decades, from physics biology, and chemistry, to computer graphics and vision.

New imaging capabilities selecting which photons to measure conventional imaging structured light transient imaging short long combinations 2: To tease you about scattering, I made this collage to show you that scattering materials are everywhere. Our skin and most biological tissues have scattering. And so do jewels and natural minerals. Leaves, fruits and vegetables, and most of the stuff we eat are made of scattering materials We see scattering in chemicals ranging from soap and wax, to cosmetics, to industrial coating powers. And material scientists are continually developing structures that exhibit new and useful forms of scattering behavior. Because of the ubiquitity of these materials, several sciences have been studying scattering for several decades, from physics biology, and chemistry, to computer graphics and vision.

Problem statement and contributions heterogeneous inverse scattering by appearance matching sensor source material m(x) min ǁ - image(m) ǁ2 m(x) optimization problem Are there ambiguities between the unknowns? 2: To tease you about scattering, I made this collage to show you that scattering materials are everywhere. Our skin and most biological tissues have scattering. And so do jewels and natural minerals. Leaves, fruits and vegetables, and most of the stuff we eat are made of scattering materials We see scattering in chemicals ranging from soap and wax, to cosmetics, to industrial coating powers. And material scientists are continually developing structures that exhibit new and useful forms of scattering behavior. Because of the ubiquitity of these materials, several sciences have been studying scattering for several decades, from physics biology, and chemistry, to computer graphics and vision. How do we solve this optimization problem?

Ambiguities between unknowns? transient video t = 10 fs t = 20 fs t = 30 fs t = 40 fs t = 50 fs … source + sensor uniquely determines deepest layer 2: To tease you about scattering, I made this collage to show you that scattering materials are everywhere. Our skin and most biological tissues have scattering. And so do jewels and natural minerals. Leaves, fruits and vegetables, and most of the stuff we eat are made of scattering materials We see scattering in chemicals ranging from soap and wax, to cosmetics, to industrial coating powers. And material scientists are continually developing structures that exhibit new and useful forms of scattering behavior. Because of the ubiquitity of these materials, several sciences have been studying scattering for several decades, from physics biology, and chemistry, to computer graphics and vision. recursion: uniquely determines entire volume deepest layer reached after t = 40 fs travel time

Problem statement and contributions heterogeneous inverse scattering by appearance matching source sensor min ǁ - image(m) ǁ2 optimization problem m(x) material m(x) Are there ambiguities between the unknowns? 2: To tease you about scattering, I made this collage to show you that scattering materials are everywhere. Our skin and most biological tissues have scattering. And so do jewels and natural minerals. Leaves, fruits and vegetables, and most of the stuff we eat are made of scattering materials We see scattering in chemicals ranging from soap and wax, to cosmetics, to industrial coating powers. And material scientists are continually developing structures that exhibit new and useful forms of scattering behavior. Because of the ubiquitity of these materials, several sciences have been studying scattering for several decades, from physics biology, and chemistry, to computer graphics and vision. provable uniqueness for certain imaging types How do we solve this optimization problem?

How do we do optimization? density albedo phase function smoke volume large-scale simulation: 20 thousand cores 1 million measurements 10 thousand unknowns 104 unknowns source sensor min ǁ - image(m) ǁ2 m(x) optimization problem material m(x) very non-linear material m+∂m ∂image(m) ∂m ~ 2: To tease you about scattering, I made this collage to show you that scattering materials are everywhere. Our skin and most biological tissues have scattering. And so do jewels and natural minerals. Leaves, fruits and vegetables, and most of the stuff we eat are made of scattering materials We see scattering in chemicals ranging from soap and wax, to cosmetics, to industrial coating powers. And material scientists are continually developing structures that exhibit new and useful forms of scattering behavior. Because of the ubiquitity of these materials, several sciences have been studying scattering for several decades, from physics biology, and chemistry, to computer graphics and vision. while (not converged) update m using ∂loss(m) ∂m ~ stochastic gradient descent scattering albedo σ (x) a (x) fs (θ,x) phase function volumetric density material m (x) θ σ a fs(θ) Monte Carlo rendering

Problem statement and contributions heterogeneous inverse scattering by appearance matching source sensor min ǁ - image(m) ǁ2 optimization problem m(x) material m(x) http://tinyurl.com/InvTransient Are there ambiguities between the unknowns? 2: To tease you about scattering, I made this collage to show you that scattering materials are everywhere. Our skin and most biological tissues have scattering. And so do jewels and natural minerals. Leaves, fruits and vegetables, and most of the stuff we eat are made of scattering materials We see scattering in chemicals ranging from soap and wax, to cosmetics, to industrial coating powers. And material scientists are continually developing structures that exhibit new and useful forms of scattering behavior. Because of the ubiquitity of these materials, several sciences have been studying scattering for several decades, from physics biology, and chemistry, to computer graphics and vision. provable uniqueness for certain imaging types How do we solve this optimization problem? scalable, general, physically-accurate algorithm empirical evaluation of imaging configurations