Flicker Forensics for Camcorder Piracy

Hajj-Ahmad, Adi; Baudry, Séverine; Chupeau, Bertrand; Doerr, Gwenaël; Wu, Min

doi:10.1109/tifs.2016.2603603

Cited by 18 publications

(8 citation statements)

References 28 publications

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“…Additionally, the flicker effect causes the luminance to vary periodically along the video and brings scrolling stripes. Therefore, Baudry et al modeled this effect in an effort to remove the distortions [24].…”

Section: Related Workmentioning

confidence: 99%

Camcording-Resistant Forensic Watermarking Fallback System Using Secondary Watermark Signal

Mareen

Courteaux

Praeter

et al. 2021

IEEE Trans. Circuits Syst. Video Technol.

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Forensic watermarking is used to track down digital pirates after they illegally redistribute video content. Although existing algorithms often resist common signal processing attacks, they are not always robust against camcording attacks. As a solution in the state of the art, registration methods are used to align the attacked video to the original one. However, watermark detection still fails when the quality is sufficiently decreased or when exposed to targeted attacks. Therefore, this paper proposes a novel fallback system that aims to detect the watermark when traditional methods fail. More concretely, we demonstrate that a primary watermark embedded by a traditional scheme indirectly creates a secondary watermark signal during video encoding. This secondary watermark consists of compression artifacts and is detected by the fallback system. Additionally, the proposed system incorporates video registration to cope with camcording attacks. The experimental results indicate that the fallback system has a striking increase in robustness compared to the existing methods. For example, the observed false-negative rate for targeted attacks improves from 100% to 0%. Moreover, the fallback is camcording resistant even when the traditional method combined with registration is not. In conclusion, the proposed system can be used as a fallback when traditional detection fails.

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Section: Related Workmentioning

confidence: 99%

Camcording-Resistant Forensic Watermarking Fallback System Using Secondary Watermark Signal

Mareen

Courteaux

Praeter

et al. 2021

IEEE Trans. Circuits Syst. Video Technol.

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“…• Resistance against hand vibrations • Resistance against perspective drifts • Resistance against obstacles such as people's heads or people walking between the handheld camera and the screen • Resistance against zoom changes One point to note here is that the distortion factors studied in Table 1 are not the only factors that make it complex to recover the projection time watermark from pirate copies. For example, it was shown in [60] that the lamination flickers, induced by the interplay between an LCD and a camcorder can cause some difficulties in the recovery of the watermark. In addition to temporal luminance variations studied in [60], spatial luminance variations induced by camcorder recording have been studied in [61].…”

Section: Figurementioning

confidence: 99%

“…For example, it was shown in [60] that the lamination flickers, induced by the interplay between an LCD and a camcorder can cause some difficulties in the recovery of the watermark. In addition to temporal luminance variations studied in [60], spatial luminance variations induced by camcorder recording have been studied in [61].…”

Section: Figurementioning

confidence: 99%

A Survey on Piracy Protection Techniques in Digital Cinema Watermarking Schemes

Zolfaghari¹,

Mitra²

2020

Recent Trends in Communication Networks

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Watermarking is used in several areas such as CDNs (Content Delivery Networks), as part of the rights management system for counterfeit prevention. Watermarking schemes need some additional features in order to be used in digital cinema. In fact, extra watermarks are added to movies by cinema projectors in projection time, which help identify the cinema hall in which the illegal copy has been recorded. But distortions caused by hand vibrations and the point of view angle make it difficult to recover the watermark. This makes it necessary to be distortionresistant for the watermarking schemes used in digital cinema. On the other hand, theatre owners would like to locate the camcorder that has recorded the pirate copy. This requires watermarking schemes to be able to estimate the distance and angle using the distributed pirate copy. In this chapter, we present a review on watermarking techniques specifically designed to attack the aforementioned problems.

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“…In order to solve this problem, forensic researchers put a huge effort toward the development of video forensic solutions in the last few years [1]. In particular, several tasks of interest were identified and addressed, such as video device identification [2,3], local tampering detection and localization [4,5,6,7], physical inconsistencies detection [8], computer-generated video identification [8], video recapture understanding [9,10], frame addition and removal analysis [11], detection of temporal interpolation [12], fake bitrate detection [13], video codec identification [14], and multiple compression detection [15].…”

Section: Introductionmentioning

confidence: 99%

Video Codec Forensics Based on Convolutional Neural Networks

Verde

Bondi

Bestagini

et al. 2018

2018 25th IEEE International Conference on Image Processing (ICIP)

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The recent development of multimedia has made video editing accessible to everyone. Unfortunately, forensic analysis tools capable of detecting traces left by video processing operations in a blind fashion are still at their beginnings. One of the reasons is that videos are customary stored and distributed in a compressed format, and codec-related traces tends to mask previous processing operations. In this paper, we propose to capture video codec traces through convolutional neural networks (CNNs) and exploit them as an asset. Specifically, we train two CNNs to extract information about the used video codec and coding quality, respectively. Building upon these CNNs, we propose a system to detect and localize temporal splicing for video sequences generated from the concatenation of different video segments, which are characterized by inconsistent coding schemes and / or parameters (e.g., video compilations from different sources or broadcasting channels). The proposed solution is validated using videos at different resolutions (i.e., CIF, 4CIF, PAL and 720p) encoded with four common codecs (i.e., MPEG2, MPEG4, H264 and H265) at different qualities (i.e., different constant and variable bitrates, as well as constant quantization parameters).

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Flicker Forensics for Camcorder Piracy

Cited by 18 publications

References 28 publications

Camcording-Resistant Forensic Watermarking Fallback System Using Secondary Watermark Signal

Camcording-Resistant Forensic Watermarking Fallback System Using Secondary Watermark Signal

A Survey on Piracy Protection Techniques in Digital Cinema Watermarking Schemes

Video Codec Forensics Based on Convolutional Neural Networks

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