Coherent intrinsic images from photo collections
Name
Laffont_12_Coherent_Intrinsic_Images.pdf
Description
Accepted version
Size
4.52 MB
Format
Adobe PDF
Checksum (MD5)
77b913683f5abce69d02f4ffb3309a26
Author(s)
Laffont, Pierre-Yves
Bousseau, Adrien
Paris, Sylvain
Durand, Frederic
Drettakis, George
Date Issued
November 2012
Journal
ACM Transactions on Graphics
Publisher
Association for Computing Machinery (ACM)
Citation
Laffont, Pierre-Yves et al. "Coherent intrinsic images from photo collections." ACM Transactions on Graphics 31, 6 (November 2012): 202. © 2012 ACM
Version
Author's final manuscript
Abstract
An intrinsic image is a decomposition of a photo into an illumination layer and a reflectance layer, which enables powerful editing such as the alteration of an object's material independently of its illumination. However, decomposing a single photo is highly under-constrained and existing methods require user assistance or handle only simple scenes. In this paper, we compute intrinsic decompositions using several images of the same scene under different viewpoints and lighting conditions. We use multi-view stereo to automatically reconstruct 3D points and normals from which we derive relationships between reflectance values at different locations, across multiple views and consequently different lighting conditions. We use robust estimation to reliably identify reflectance ratios between pairs of points. From these, we infer constraints for our optimization and enforce a coherent solution across multiple views and illuminations. Our results demonstrate that this constrained optimization yields high-quality and coherent intrinsic decompositions of complex scenes. We illustrate how these decompositions can be used for image-based illumination transfer and transitions between views with consistent lighting.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/2366145.2366221
