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Lighting transfer across multiple views through local color transforms

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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.

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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.

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Correspondence to Qian Zhang.

Additional information

This article is published with open access at Springerlink.com

Qian Zhang is a research assistant at Nanyang Technological University, Singapore. Her research interests include image processing, computational photography, and image-based rendering. Qian Zhang has her B.S. degree in electronics and information engineering from Huazhong University of Science and Technology, China.

Pierre-Yves Laffont is the CEO and co-founder of Lemnis Technologies. During this research, he was a postdoctoral researcher at ETH Zurich and a visiting researcher at Nanyang Technological University. His research interests include intrinsic image decomposition, example-based appearance transfer, and image-based rendering and relighting. He has his Ph.D. degree in computer science from Inria Sophia-Antipolis.

Terence Sim is an associate professor at the School of Computing, National University of Singapore. He is also an assistant dean of corporate relations at the School. For research, Dr. Sim works primarily in the areas of facial image analysis, biometrics, and computational photography. He is also interested in computer vision problems in general, such as shapefrom- shading, photometric stereo, and object recognition. From 2014 to 2016, Dr. Sim served as president of the Pattern Recognition and Machine Intelligence Association (PREMIA), a national professional body for pattern recognition, affiliated with the International Association for Pattern Recognition (IAPR).

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Zhang, Q., Laffont, P. & Sim, T. Lighting transfer across multiple views through local color transforms. Comp. Visual Media 3, 315–324 (2017) doi:10.1007/s41095-017-0085-5

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Keywords

  • Relighting
  • Photo Collection
  • Time-Lapse
  • Image Editing