Computational light transport using space, time, and polarization

Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 261-273). === Understanding how light travels through macroscopic scenes can...

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Main Author: Kadambi, Achuta
Other Authors: Ramesh Raskar.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2018
Subjects:
Online Access:http://hdl.handle.net/1721.1/115742
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-1157422019-05-02T16:02:32Z Computational light transport using space, time, and polarization Kadambi, Achuta Ramesh Raskar. Program in Media Arts and Sciences (Massachusetts Institute of Technology) Program in Media Arts and Sciences (Massachusetts Institute of Technology) Program in Media Arts and Sciences () Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 261-273). Understanding how light travels through macroscopic scenes can transform autonomous driving, medical imaging and consumer photography. Unfortunately, this understanding is difficult to achieve: trillions of light paths are measured by millions of pixels. The framework of computational light transport was introduced to model this complex interaction between light and matter in a tractable space. In this thesis, we study new methods to invoke space, time, and polarization into a computational light transport framework. First, we study how probing the time dimension enables cameras to separate bounces from multiple light paths. Our solutions are inspired by prior work on multipath in wireless and telecommunications. We then invoke both time and space to provide the first provable bound on resolution for seeing around corners or through scattering media. Finally, we jointly invoke space, time, and polarization to propose an ultra-high quality form of 3D imaging. This thesis contributes a few analytical theories, including: (1) provable bounds on multipath separation; (2) provable bounds on seeing around corners; and (3) proof of shape reconstruction from polarimetric measurements. The thesis also contributes new applications that span: (a) micron-scale 3D cameras; (b) real-time object tracking around corners; and (c) single-shot computational relighting of images. Future applications encompass equipping self-driving cars the ability to see through fog, or enabling doctors to see deeper inside the body using light. by Achuta Kadambi. Ph. D. 2018-05-23T16:32:47Z 2018-05-23T16:32:47Z 2018 2018 Thesis http://hdl.handle.net/1721.1/115742 1036986780 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 273 pages application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Program in Media Arts and Sciences ()
spellingShingle Program in Media Arts and Sciences ()
Kadambi, Achuta
Computational light transport using space, time, and polarization
description Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 261-273). === Understanding how light travels through macroscopic scenes can transform autonomous driving, medical imaging and consumer photography. Unfortunately, this understanding is difficult to achieve: trillions of light paths are measured by millions of pixels. The framework of computational light transport was introduced to model this complex interaction between light and matter in a tractable space. In this thesis, we study new methods to invoke space, time, and polarization into a computational light transport framework. First, we study how probing the time dimension enables cameras to separate bounces from multiple light paths. Our solutions are inspired by prior work on multipath in wireless and telecommunications. We then invoke both time and space to provide the first provable bound on resolution for seeing around corners or through scattering media. Finally, we jointly invoke space, time, and polarization to propose an ultra-high quality form of 3D imaging. This thesis contributes a few analytical theories, including: (1) provable bounds on multipath separation; (2) provable bounds on seeing around corners; and (3) proof of shape reconstruction from polarimetric measurements. The thesis also contributes new applications that span: (a) micron-scale 3D cameras; (b) real-time object tracking around corners; and (c) single-shot computational relighting of images. Future applications encompass equipping self-driving cars the ability to see through fog, or enabling doctors to see deeper inside the body using light. === by Achuta Kadambi. === Ph. D.
author2 Ramesh Raskar.
author_facet Ramesh Raskar.
Kadambi, Achuta
author Kadambi, Achuta
author_sort Kadambi, Achuta
title Computational light transport using space, time, and polarization
title_short Computational light transport using space, time, and polarization
title_full Computational light transport using space, time, and polarization
title_fullStr Computational light transport using space, time, and polarization
title_full_unstemmed Computational light transport using space, time, and polarization
title_sort computational light transport using space, time, and polarization
publisher Massachusetts Institute of Technology
publishDate 2018
url http://hdl.handle.net/1721.1/115742
work_keys_str_mv AT kadambiachuta computationallighttransportusingspacetimeandpolarization
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