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Open Set Video Camera Model Verification
Conference proceeding

Open Set Video Camera Model Verification

Owen Mayer, Brian Hosler, Matthew C Stamm and IEEE
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), v 2020-, pp 2962-2966
May 2020

Abstract

Cameras Deep Learning Feature extraction Forensics Multimedia Forensics Open Set Signal processing Speech processing Streaming media Task analysis Verification Video Forensics
We introduce a new open set video forensics problem called video camera model verification. The video camera model verification task is to determine if two query videos were captured by the same camera model. Importantly, verification must be reliable on videos from camera models unknown to the investigator, referred to the as the open set scenario. While researchers have considered other open set problems for digital images, video forensics introduces unique challenges. In this work we propose a new, video-specific system for open set verification of camera models. To do this, we design a deep-learning based system that 1) uses a CNN to extract expressive deep features from video patches, 2) compares pairs of these features using a similarity network, and 3) fuses multiple comparisons to produce a video-level verification decision. We experimentally show that this technique accurately verifies the source camera model of videos in open set scenarios.

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27 citations in Scopus

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Web of Science research areas
Acoustics
Engineering, Electrical & Electronic
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