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.
|Title of host publication||Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018|
|Publisher||IEEE Computer Society|
|Number of pages||9|
|State||Published - 13 Dec 2018|
|Event||31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018 - Salt Lake City, United States|
Duration: 18 Jun 2018 → 22 Jun 2018
|Name||IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops|
|Conference||31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018|
|City||Salt Lake City|
|Period||18/06/18 → 22/06/18|
Bibliographical noteFunding Information:
This research was supported by grant no 1455/16 from the Israeli Science Foundation and by a grant from the Center for Cyber Law and Policy (CCLP), at the University of Haifa.
© 2018 IEEE.
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering