Personalization of Image Enhancement

Sing Bing Kang, Ashish Kapoor, Dani Lischinski

CVPR 2010 pp. 1799-1806

doi:10.1109/CVPR.2010.5539850 /cvpr/2010/kang2010cvpr-personalization/

Abstract

We address the problem of incorporating user preference in automatic image enhancement. Unlike generic tools for automatically enhancing images, we seek to develop methods that can first observe user preferences on a training set, and then learn a model of these preferences to personalize enhancement of unseen images. The challenge of designing such system lies at intersection of computer vision, learning, and usability; we use techniques such as active sensor selection and distance metric learning in order to solve the problem. The experimental evaluation based on user studies indicates that different users do have different preferences in image enhancement, which suggests that personalization can further help improve the subjective quality of generic image enhancements.

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Cite

Text

Kang et al. "Personalization of Image Enhancement." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010. doi:10.1109/CVPR.2010.5539850

Markdown

[Kang et al. "Personalization of Image Enhancement." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010.](https://mlanthology.org/cvpr/2010/kang2010cvpr-personalization/) doi:10.1109/CVPR.2010.5539850

BibTeX

@inproceedings{kang2010cvpr-personalization,
  title     = {{Personalization of Image Enhancement}},
  author    = {Kang, Sing Bing and Kapoor, Ashish and Lischinski, Dani},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2010},
  pages     = {1799-1806},
  doi       = {10.1109/CVPR.2010.5539850},
  url       = {https://mlanthology.org/cvpr/2010/kang2010cvpr-personalization/}
}