Inverse problems in time-of-flight imaging : theory, algorithms and applications
Name
904051579-MIT.pdf
Description
Full printable version
Size
15.05 MB
Format
Adobe PDF
Checksum (MD5)
55f33b50b4800c39cd9281c6f114886a
Author(s)
Bhandari, Ayush
Advisor(s)
Ramesh Raskar.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
Time-of-Fight (ToF) cameras utilize a combination of phase and amplitude information to return real-time, three dimensional information of a scene in form of depth images. Such cameras have a number of scientific and consumer oriented applications. In this work, we formalize a mathematical framework that leads to unifying perspective on tackling inverse problems that arise in the ToF imaging context. Starting from first principles, we discuss the implications of time and frequency domain sensing of a scene. From a linear systems perspective, this amounts to an operator sampling problem where the operator depends on the physical parameters of a scene or the bio-sample being investigated. Having presented some examples of inverse problems, we discuss detailed solutions that benefit from scene based priors such sparsity and rank constraints. Our theory is corroborated by experiments performed using ToF/Kinect cameras. Applications of this work include multi-bounce light decomposition, ultrafast imaging and fluorophore lifetime estimation.
Description
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 100-108).
Subjects
Architecture. Program in Media Arts and Sciences.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Persistent DSpace Link
