Forgery Detection in 3D-Sensor Images

Noa Privman-Horesh, Azmi Haider, Hagit Hel-Or

CVPRW 2018 pp. 1561-1569

doi:10.1109/CVPRW.2018.00206 /cvprw/2018/privmanhoresh2018cvprw-forgery/

Abstract

The field of Image Forensic, and with it the notion of image forgery and its detection, is widely studied in 2D images and videos. Since 3D cameras (cameras with depth sensors) are becoming increasingly commonplace, it is of importance to introduce the notion of forgery detection in depth-images. In this paper, we present an introductory study of forgery detection in depth-images. Specifically, we show that noise statistics in depth-images can be exploited for camera source identification, image forgery detection and even depth reconstruction from noise.

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Cite

Text

Privman-Horesh et al. "Forgery Detection in 3D-Sensor Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018. doi:10.1109/CVPRW.2018.00206

Markdown

[Privman-Horesh et al. "Forgery Detection in 3D-Sensor Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018.](https://mlanthology.org/cvprw/2018/privmanhoresh2018cvprw-forgery/) doi:10.1109/CVPRW.2018.00206

BibTeX

@inproceedings{privmanhoresh2018cvprw-forgery,
  title     = {{Forgery Detection in 3D-Sensor Images}},
  author    = {Privman-Horesh, Noa and Haider, Azmi and Hel-Or, Hagit},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2018},
  pages     = {1561-1569},
  doi       = {10.1109/CVPRW.2018.00206},
  url       = {https://mlanthology.org/cvprw/2018/privmanhoresh2018cvprw-forgery/}
}