Camcorder piracy refers to the process of using a camcorder to record a screen that displays copyrighted content. In contrast to the previous works that aimed at detecting the occurrence of camcorder piracy, this paper conducts an in-depth study of the luminance flicker that is naturally present in camcorded videos due to the interplay between a liquid-crystal-display (LCD) screen and a camcorder. We first model the flicker signal and show that its parameters are tied to such internal characteristics of the pirate devices as the back-light frequency of the LCD screen and the read-out time of the camcorder. We then present new estimation techniques to recover these hidden parameters directly from camcorded videos and demonstrate that such forensic cues could provide intelligence on the pirate devices. We also discuss how to recover the shape of the low-power flicker signal itself and show that it could be used to infer which back-light technology employed in the pirate LCD screen.

Spatio-temporal desynchronization remains a major challenge for watermarking system as it could impair the detection of the hidden payload. Over the years, several (non-blind) registration techniques have been proposed to realign the analyzed content prior to watermark detection and thereby achieve robustness against severe attacks such as display-and-camcord. Such techniques rely on assumptions that may be invalidated by new attacks that had not been accounted for. In the case of video, for instance, best-in-class resynchronization techniques may have difficulties to cope with screencasting. In this paper, we report findings after an experimental study that involved five popular screencasting tools. The impact of screencasting can indeed be characterized in terms of frame drops and repeats. Moreover, the on-the-fly encoding process occurring during screen recapture inherently introduces dependencies between the likelihood of drop/repeat and the frame encoding type.

Cryptography-based content protection is an efficient means to protect multimedia content during transport. Nevertheless, content is eventually decrypted at rendering time, leaving it vulnerable to piracy e.g. using a camcorder to record movies displayed on an LCD screen. Such type of piracy naturally imprints a visible flicker signal in the pirate video due to the interplay between the rendering and acquisition devices. The parameters of such flicker are inherently tied to the characteristics of the pirate devices such as the back-light of the LCD screen and the read-out time of the camcorder. In this article, we introduce a forensic methodology to estimate such parameters by analyzing the flicker signal present in pirate recordings. Experimental results clearly showcase that the accuracy of these estimation techniques offers efficient means to tell-tale which devices have been used for piracy thanks to the variety of factory settings used by consumer electronics manufacturers.

Despite the academic focus on blind detection, many forensic watermarking systems actually operate in a non-blind fashion to accommodate for real-life desynchronization attacks. In other words, the original content is needed to perform watermark detection e.g. to re-align the pirate sample with the original content prior to watermark decoding. A somehow intermediate strategy, that could be coined `semi-blind', only requires access to a condensed representation of the original content i.e. content fingerprints. In this paper, we combined a variant of the dynamic time warping algorithm together with multi-dimensional temporal fingerprints to realign pirate video samples. Reported experimental results clearly demonstrate improved accuracy compared to state-of-the-art registration methods for a number of synthetic and real-life attack scenarios.

3D video content has been receiving increasing interest over the last few months and created challenges regarding how to protect such high valued items. For instance, depth-image-based rendering techniques allowing for the creation of virtual views may impair underlying watermarks embedded within individual views. In contrast with previous works, this article focus on defining a view-independent watermark embedding domain rather than a watermarking system coherent with the disparity across several views, thus permitting blind detection. More specifically, based on the fact that pixel displacements across views most often reduce to horizontal shifts, the average luminance value along the rows of the video frames have been selected for watermark embedding. Experimental results clearly prove the robustness of the watermark against virtual views generation.

Designing watermarks that can withstand geometric and temporal attacks is a notoriously difficult problem. The registration of a pirate content with the reference content, prior to the decoding of an embedded forensic mark, is therefore preferred. Semi-automatic registration systems, requiring the expert user to manually select and match control points through a suitable user interface, are not acceptable for content owners and do not usually provide very accurate results. A fully automated registration scheme is therefore chosen to synchronize pirate and master contents. By extracting robust and unique features, digital fingerprinting provides a relevant framework for automatic semi-blind content registration. In this paper we focus on temporal registration. In order to guarantee an accurate alignment while keeping the fingerprint size as small as possible, we propose a temporally adaptive approach. The registration scheme is designed around an adaptive motion description based on hierarchical encoding of the wavelet coefficients computed on the difference of successive frames.

In this industrial exhibit, Technicolor will showcase various technologies developed to protect digital audio-visual material all along the media value chain, from production to distribution, including forensics services in case pirated content is detected. The exhibit will be organized around Technicolor's proprietary technologies in video fingerprinting and audio/video watermarking.

This paper presents a framework for the forensic analysis of video content, for example those illegal copies of feature films proliferating in peer-to-peer networks or on bootleg DVDs. Compact and discriminant feature vectors, so called ¿fingerprints¿, are computed for a catalog of master contents. They combine global (image-based) and local (keypoint-based) signal properties extracted on representative keyframes, together with a one-dimensional signature capturing the temporal evolution of the video. We demonstrate that the extracted fingerprints not only allow accurate copy detection but also enable precise temporal and geometric alignment of candidate videos with master content. Besides making possible watermark decoding in the presence of geometric distortion, this opens the door to the reconstruction of the history of signal manipulations. The performance of the proposed scheme is assessed through a realistic copy detection and registration scenario.

Watermarking can be modeled as transmission through a steganographic channel. Up to now, most of the channels studied in the literature have been additive or substitutive channels where noise modifies the data values. However, other modifications occur frequently during the life of a watermark, namely geometric distortions: images may be cropped, scaled and even non-linearly distorted by digital/analog conversion or by an attacker. We model geometric transformations by a geometric channel and introduce a random variable, the index variable, to model geometric deformations. We propose to use a synchronisation pattern to estimate geometric distortions caused by jitter attack, and describe two estimation algorithms (Viterbi and forward-backward).

Watermarking can be modeled as a transmission through a steganographic channel. Most of the channel studied up to now in the literature were additive or substitutive channels where the noise modifies the data values. But other modifications occur frequently during the watermark life, namely geometric distortions: images may be cropped, scaled and even non-linearly distorted by digital/analog conversion or by an attacker. We model here the geometric transformations by a geometric channel, and compute the expression of capacity for a channel with shift and for a channel with jitter. We also compare the theoretic bounds obtained to the rate achieved by some watermarking methods.

Watermarking is often modeled as the transmission of a message over a very noisy channel. Indeed, the watermark power must be very low to ensure invisibility, and the modifications suffered by an image can be rather strong (JPEG or MPEG compression for instance), leading to a high noise level. To ensure a reliable transmission on a channel with such a low SNR, channel coding is thus mandatory. However, as standard codes are not adapted to such noisy channels, we propose a coding scheme based on concatenated codes. We show that, for these codes, optimal decoding is far too complex, and that hard decoding algorithms used in practice lead to poor performance. As soft decoding enables to approach optimal decoding at lower cost, we adapt the classical Chase (1972) decoding algorithm to the watermarking context, and propose a new soft decoding algorithm based on tree exploration.