University of Illinois Urbana-Champaign

Physically based geometry and reflectance recovery from images

Liu, Siying

Content Files
LIU-DISSERTATION-2016.pdf

Permalink

https://hdl.handle.net/2142/95307

Description

Title
Physically based geometry and reflectance recovery from images
Author(s)
Liu, Siying
Issue Date
2016-11-04
Director of Research (if dissertation) or Advisor (if thesis)
Do, Minh N.
Doctoral Committee Chair(s)
Do, Minh N.
Committee Member(s)
  • Kamalabadi, Farzad
  • Hasegawa-Johnson, Mark A.
  • Hart, John C.
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2017-03-01T15:46:19Z
Keyword(s)
  • texture
  • RGB-D
  • reflectance
  • image correspondence
  • color transfer
Abstract
An image is a projection of the three-dimensional world taken at an instance in space and time. Its formation involves a complex interplay between geometry, illumination and material properties of objects in the scene. Given image data and knowledge of some scene properties, the recovery of the remaining components can be cast as a set of physically based inverse problems. This thesis investigates three inverse problems on the recovery of scene properties and discusses how we can develop appropriate physical constraints and build them into effective algorithms. Firstly, we study the problem of geometry recovery from a single image with repeated texture. Our technique leverages the PatchMatch algorithm to detect and match repeated patterns undergoing geometric transformations. This allows effective enforcement of translational symmetry constraint in the recovery of texture lattice. Secondly, we study the problem of computational relighting using RGB-D data, where the depth data is acquired through a Kinect sensor and is often noisy. We show how the inclusion of noisy depth input helps to resolve ambiguities in the recovery of shape and reflectance in the inverse rendering problem. Our results show that the complementary nature of RGB and depth is highly beneficial for a practical relighting system. Lastly, in the third problem, we exploit the use of geometric constraints relating two views, to address a challenging problem in Internet image matching. Our solution is robust to geometric and photometric distortions over wide baselines. It also accommodates repeated structures that are commonly found in our modern environment. Building on the image correspondence, we also investigate the use of color transfer as an additional global constraint in relating Internet images. It shows promising results in obtaining more accurate and denser correspondence.
Graduation Semester
2016-12
Type of Resource
text
Permalink
http://hdl.handle.net/2142/95307
Copyright and License Information
Copyright 2016 Siying Liu

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Dissertations and Theses - Electrical and Computer Engineering
Dissertations and Theses in Electrical and Computer Engineering
Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois