This paper presents a method to automatically and efficiently detect face tampering in videos, and particularly focuses on two recent techniques used to generate hyper-realistic forged videos: Deepfake and Face2Face. Traditional image forensics techniques are usually not well suited to videos due to the compression that strongly degrades the data. Thus, this paper follows a deep learning approach and presents two networks, both with a low number of layers to focus on the mesoscopic properties of images. We evaluate those fast networks on both an existing dataset and a dataset we have constituted from online videos. The tests demonstrate a very successful detection rate with more than 98% for Deepfake and 95% for Face2Face.

https://hal-upec-upem.archives-ouvertes.fr/hal-01867298/document

MesoNet: a Compact Facial Video Forgery Detection Network

MesoNet: a Compact Facial Video Forgery Detection Network.

Validating a given multimedia content is nowadays quite a hard task because of the huge amount of possible alterations that could have been operated on it. In order to face this problem, image and video experts have proposed a wide set of solutions to reconstruct the processing history of a given multimedia signal. These strategies rely on the fact that non-reversible operations applied to a signal leave some traces ("footprints") that can be identified and classified in order to reconstruct the possible alterations that have been operated on the original source. These solutions permit also to identify which source generated a specific image or video content given some device-related peculiarities. The paper aims at providing an overview of the existing video processing techniques, considering all the possible alterations that can be operated on a single signal and also the possibility of identifying the traces that could reveal important information about its origin and use.

/pdf/an-overview-on-video-forensics-20693kkcsx.pdf

An overview on video forensics

The illegal distribution of a digital movie is a common and significant threat to the film industry. With the advent of high-speed broadband Internet access, a pirated copy of a digital video can now be easily distributed to a global audience. A possible means of limiting this type of digital theft is digital video watermarking whereby additional information, called a watermark, is embedded in the host video. This watermark can be extracted at the decoder and used to determine whether the video content is watermarked. This paper presents a review of the digital video watermarking techniques in which their applications, challenges, and important properties are discussed, and categorizes them based on the domain in which they embed the watermark. It then provides an overview of a few emerging innovative solutions using watermarks. Protecting a 3D video by watermarking is an emerging area of research. The relevant 3D video watermarking techniques in the literature are classified based on the image-based representations of a 3D video in stereoscopic, depth-image-based rendering, and multi-view video watermarking. We discuss each technique, and then present a survey of the literature. Finally, we provide a summary of this paper and propose some future research directions.

An Overview of Digital Video Watermarking

Ternary radial harmonic Fourier moments based robust stereo image zero-watermarking algorithm

The popularity of 3D content is on the rise since it provides an immersive experience to viewers. In this situation, depth-image-based rendering (DIBR) has taken on an important role in 3D technology due to its low bandwidth cost and ease of depth configuration. Noting that the viewer could record provided center view or synthesized views for illegal distribution, it is clear that copyright protection must be taken into account for the DIBR 3D content, including the possibility that one single view could be illegally distributed as 2D content. In this paper, we propose a robust watermarking scheme for DIBR 3D images by quantization on dual-tree complex wavelet transform (DT-CWT) coefficients with consideration of imperceptibility. To make the proposed scheme robust to DIBR process, two characteristics of DT-CWT are employed: approximate shift invariance and directional selectivity. We select certain coefficient sub-blocks and group the coefficient rows based on the properties of DIBR. On the extraction side, the threshold is carefully chosen with a low false positive rate. The simulation results show that the embedded watermark is stably extracted from the center view and the synthesized left and right views. In addition, even if the synthesized left and right views are distorted by general attacks, the watermark is successfully extracted. Furthermore, the proposed scheme is robust to pre-processing of the depth image and baseline adjusting, which are common processing on the DIBR system for better quality of 3D views.

Robust DT-CWT Watermarking for DIBR 3D Images

A wearable electrical impedance tomography (EIT) system is proposed for the portable real-time 3-D lung ventilation monitoring. It consists of two types of SoCs, active electrode (AE)-SoC and Hub-SoC, mounted on wearable belts. The 48-channel AE-SoCs are integrated on flexible printed circuit board belt, and Hub-SoC is integrated in the hub module which performs data gathering and wireless communication between an external imaging device. To get high accuracy under the variation of conductivity, the dual-mode current stimulator provides the optimal frequency for time difference-EIT and frequency difference-EIT with simultaneous 4 k–128 kHz impedance sensing. A wide dynamic range instruments amplifier is proposed to provide 94 dB of wide dynamic range impedance sensing. In addition, the 48-channel AE system with the dedicated communication and calibration is implemented to achieve 1.4- $\text{m}\Omega $ sensitivity of impedance difference in the in vivo environment. The AE-/Hub-SoCs occupy 3.2 and 1.3 mm2 in 65-nm CMOS technology and consume $124~\mu \text{W}$ and 1.1 mW with 1.2 V supply, respectively. As a result, EIT images are reconstructed with 90% of accuracy, and up to 10 frames/s real-time 3-D lung images are successfully displayed.

A 1.4-m $\Omega$ -Sensitivity 94-dB Dynamic-Range Electrical Impedance Tomography SoC and 48-Channel Hub-SoC for 3-D Lung Ventilation Monitoring System

Three dimensional (3D) video technologies have made noticeable progress and become common. The 3D videos using depth image based rendering (DIBR) technique are getting the spotlight due to its visual reality, however, they are exposed to illegal distribution. To protect 3D video contents from copyright infringement, a 3D video watermarking scheme can be employed. Since 3D display itself may give rise to unnatural artifacts and arouse visual fatigue to audiences, the imperceptibility is considered as the most significant factor. In this paper, a 3D video watermarking which focuses on perceptual embedding is introduced. The proposed scheme exploits visual characteristics, motion on z-axis and pixels to be hidden by rendering, from depth information. For evaluating the proposed scheme, a stereoscopic display environment is set and the mean opinion score (MOS) is measured as a subjective quality measure for the watermarked 3D videos. Experimental results prove that our proposed scheme has less affect on the perceptibility when watching 3D videos. Also, the proposed method is robust against lossy compression and adding Gaussian noise.

https://hklee.kaist.ac.kr/publications/2011%20IIH-MSP(with%20Min-Jeong%20Lee).pdf

Perceptual Watermarking for 3D Stereoscopic Video Using Depth Information

A small form-factor, lightweight wireless capsule endoscope (WCE) system with body channel communication (BCC) transceiver ICs is proposed for VGA-resolution image transferring and capsule localization. The transceiver ICs are composed of capsule chip and receiver chip, implemented in a 65-nm CMOS process. In the capsule side, the proposed system provides 360° image capturing through four-camera integration to reduce the miss rate. Also, a dual-band pulse-shaping BCC transmitter is proposed to enable low-power (<1 mW), high-speed (80 Mb/s) image transmission. In the receiver side, contact attenuation compensated-received signal strength indicator (CAC-RSSI) is proposed to increase the capsule localization accuracy. The external system is composed of eight-receiver nodes that allow signal demodulation and localization of the capsule. To reduce transceiver payload and system power consumption, image encoder is implemented in the capsule. The transceiver IC is integrated into the capsule system and verified with body mimicking phantom. The proposed system satisfies compatibility with medical grade diagnosis by operating longer than 8 h with 4 fps and 12 h with 2 fps with conventional two silver oxide 55-mA · h coin batteries. The tested localization accuracy shows less than sub-centimeter range.

A Four-Camera VGA-Resolution Capsule Endoscope System With 80-Mb/s Body Channel Communication Transceiver and Sub-Centimeter Range Capsule Localization

Jiwon Lee

Papers

Robust DT-CWT Watermarking for DIBR 3D Images

A 1.4-m $\Omega$ -Sensitivity 94-dB Dynamic-Range Electrical Impedance Tomography SoC and 48-Channel Hub-SoC for 3-D Lung Ventilation Monitoring System

Perceptual Watermarking for 3D Stereoscopic Video Using Depth Information

A Four-Camera VGA-Resolution Capsule Endoscope System With 80-Mb/s Body Channel Communication Transceiver and Sub-Centimeter Range Capsule Localization

Region-based tampering detection and recovery using homogeneity analysis in quality-sensitive imaging