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Efficient and robust color consistency for community photo collections

Cited 32 time in Web of Science Cited 49 time in Scopus
Authors

Park, Jaesik; Tai, Yu-Wing; Sinha, Sudipta N.; Kweon, In So

Issue Date
2016
Publisher
IEEE
Citation
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol.2016-December, pp.430-438
Abstract
We present an efficient technique to optimize color consistency of a collection of images depicting a common scene. Our method first recovers sparse pixel correspondences in the input images and stacks them into a matrix with many missing entries. We show that this matrix satisfies a rank two constraint under a simple color correction model. These parameters can be viewed as pseudo white balance and gamma correction parameters for each input image. We present a robust low-rank matrix factorization method to estimate the unknown parameters of this model. Using them, we improve color consistency of the input images or perform color transfer with any input image as the source. Our approach is insensitive to outliers in the pixel correspondences thereby precluding the need for complex pre-processing steps. We demonstrate high quality color consistency results on large photo collections of popular tourist landmarks and personal photo collections containing images of people.
ISSN
1063-6919
URI
https://hdl.handle.net/10371/201322
DOI
https://doi.org/10.1109/CVPR.2016.53
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  • College of Engineering
  • Dept. of Computer Science and Engineering
Research Area Computer Graphics, Computer Vision, Machine Learning, Robotics

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