ML Anthology

Depth-Stretch: Enhancing Depth Perception Without Depth

Hagit Hel-Or, Yacov Hel-Or, Renato Keshet
CVPRW 2017 pp. 1006-1014
doi:10.1109/CVPRW.2017.137 /cvprw/2017/helor2017cvprw-depthstretch/

Abstract

A simple and efficient method is presented to enhance the depth perception of an image. The approach termed Depth-Stretch (D-stretch) is a tone mapping operation that is applied to the shading component of the given image. Although re-rendering a scene under geometric transformations typically requires extracting the 3D model of the scene, we show that under very simple assumptions D-stretch can be implemented without 3D reconstruction, while still providing a convincing effect of depth enhancement.

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Cite

Text

Hel-Or et al. "Depth-Stretch: Enhancing Depth Perception Without Depth." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017. doi:10.1109/CVPRW.2017.137

Markdown

[Hel-Or et al. "Depth-Stretch: Enhancing Depth Perception Without Depth." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017.](https://mlanthology.org/cvprw/2017/helor2017cvprw-depthstretch/) doi:10.1109/CVPRW.2017.137

BibTeX

@inproceedings{helor2017cvprw-depthstretch,
  title     = {{Depth-Stretch: Enhancing Depth Perception Without Depth}},
  author    = {Hel-Or, Hagit and Hel-Or, Yacov and Keshet, Renato},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2017},
  pages     = {1006-1014},
  doi       = {10.1109/CVPRW.2017.137},
  url       = {https://mlanthology.org/cvprw/2017/helor2017cvprw-depthstretch/}
}