Depth Map Fingerprinting and Splicing Detection

Matern F, Riess C, Stamminger M (2020)


Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2020

Publisher: IEEE

Pages Range: 2782-2786

Conference Proceedings Title: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Event location: Barcelona ES

ISBN: 978-1-5090-6631-5

DOI: 10.1109/ICASSP40776.2020.9052979

Abstract

With the ubiquity of social networks, images have become crucial in todays exchange of information. Most of these images are taken by smartphones. For forensic approaches relying on fixed image formation pipelines, the capabilities of smartphones using computational photography pose new challenges. But these new capabilities also offer opportunities for forensic analysis. A growing amount of commodity devices are able to capture 3-D information using various technologies such as stereo imaging or structured light. Modern smartphones commonly save such 3-D information as depth maps alongside regular images.In this work, we propose to use characteristic artifacts of depth reconstruction algorithms as trace for forensic analysis. The proposed method is able to infer the source algorithm of stereo reconstructions with an accuracy of up to 97%. We further demonstrate the applicability of the method to collected smartphone data. It is able to discriminate patches from different sources with an AUC of up to 0.88 and can be used for splicing localization in depth maps.

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How to cite

APA:

Matern, F., Riess, C., & Stamminger, M. (2020). Depth Map Fingerprinting and Splicing Detection. In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 2782-2786). Barcelona, ES: IEEE.

MLA:

Matern, Falko, Christian Riess, and Marc Stamminger. "Depth Map Fingerprinting and Splicing Detection." Proceedings of the ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona IEEE, 2020. 2782-2786.

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