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Computational Visual Media

, Volume 3, Issue 4, pp 315–324 | Cite as

Lighting transfer across multiple views through local color transforms

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Research Article
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Abstract

We present a method for transferring lighting between photographs of a static scene. Our method takes as input a photo collection depicting a scene with varying viewpoints and lighting conditions. We cast lighting transfer as an edit propagation problem, where the transfer of local illumination across images is guided by sparse correspondences obtained through multi-view stereo. Instead of directly propagating color, we learn local color transforms from corresponding patches in pairs of images and propagate these transforms in an edge-aware manner to regions with no correspondences. Our color transforms model the large variability of appearance changes in local regions of the scene, and are robust to missing or inaccurate correspondences. The method is fully automatic and can transfer strong shadows between images. We show applications of our image relighting method for enhancing photographs, browsing photo collections with harmonized lighting, and generating synthetic time-lapse sequences.

Keywords

Relighting Photo Collection Time-Lapse Image Editing 

Notes

Acknowledgements

We would like to thank all reviewers for their comments and suggestions. The first author carried out the earlier phase of the research at the National University of Singapore with support from the School of Computing. This research is supported by the BeingThere Centre, a collaboration between Nanyang Technological University Singapore, Eidgenössische Technische Hochschule Zörich, and the University of North Carolina at Chapel Hill. The BeingThere Centre is supported by the Singapore National Research Foundation under its International Research Centre @ Singapore Funding Initiative and is administered by the Interactive Digital Media Programme Office.

Supplementary material

41095_2017_85_MOESM1_ESM.pdf (1.9 mb)
Lighting transfer across multiple views through local color transforms

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© The Author(s) 2017

Open Access The articles published in this journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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Authors and Affiliations

  1. 1.Nanyang Technological UniversitySingaporeSingapore
  2. 2.ETH ZurichZurichSwitzerland
  3. 3.National University of SingaporeSingaporeSingapore

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