Fighting movie piracy often requires automatic content identification. The most common technique to achieve this uses
watermarking, but not all copyrighted content is watermarked. Video fingerprinting is an efficient alternative solution to
identify content, to manage multimedia files in UGC sites or P2P networks and to register pirated copies with master
content. When registering by matching copy fingerprints with master ones, a model of distortion can be estimated. In
case of in-theater piracy, the model of geometric distortion allows the estimation of the capture location. A step even
further is to determine, from passive image analysis only, whether different pirated versions were captured with the same
camcorder. In this paper we present three such fingerprinting-based forensic applications: UGC filtering, estimation of
capture location and source identification.
Pirate copies of feature films are proliferating on the Internet. DVD rip or screener recording methods involve the
duplication of officially distributed media whereas 'cam' versions are illicitly captured with handheld camcorders in
movie theaters. Several, complementary, multimedia forensic techniques such as copy identification, forensic tracking
marks or sensor forensics can deter those clandestine recordings. In the case of camcorder capture in a theater, the image
is often geometrically distorted, the main artifact being the trapezoidal effect, also known as 'keystoning', due to a
capture viewing axis not being perpendicular to the screen. In this paper we propose to analyze the geometric distortions
in a pirate copy to determine the camcorder viewing angle to the screen perpendicular and derive the approximate
position of the pirate in the theater. The problem is first of all geometrically defined, by describing the general projection
and capture setup, and by identifying unknown parameters and estimates. The estimation approach based on the
identification of an eight-parameter homographic model of the 'keystoning' effect is then presented. A validation
experiment based on ground truth collected in a real movie theater is reported, and the accuracy of the proposed method
is assessed.
The proliferation of pirate copies of feature films on peer-to-peer networks arouses a great interest to countermeasures
such as the insertion of (invisible) forensic marks in projected movies, to deter their illegal capture. The registration of
pirate copies with the original content is however a prerequisite to the recovery of such embedded messages, as severe
geometric distortions often occur in illegally camcorded contents. After a brief state-of-the-art in image registration, the
paper details an algorithm for video registration, focusing on the compensation of geometric distortions. Control points
are automatically extracted in original and copy pictures, followed by pre- and post-matching filtering steps to discard
not relevant control points and erroneous matched pairs of control points respectively. This enables the accurate
numerical estimation of an 8-parameter homographic distortion model, used to register the copy frames with the original
reference grid. Such an image registration algorithm is inserted into a general video registration scheme. Results are
presented on both natural and synthetic test material.
KEYWORDS: Distortion, 3D modeling, 3D image processing, Digital watermarking, 3D metrology, Visualization, Image quality, Distance measurement, Head, 3D acquisition
Three-dimensional image quality assessment causes new challenges for a wide set of applications and particularly for emerging 3-D watermarking schemes. First, new metrics have to be drawn for the distortion measurement from an original 3-D surface to its deformed version: this metric is necessary to address distortions that are acceptable and to which a 3-D watermarking algorithm should resist. In this paper, we focus on distortion energy evaluation extending works on distortion minimization for planar and spherical parameterization. Secondly, a key perceptual assessment of 3-D geometrical transforms is their impact on the various 2-D views that can be extracted from the object. As a matter of fact, most of the applications (games, avatars, …) are targeting users owning 2-D screens. In this paper we restrict our study to 3-D shape distortion analysis, assuming standard lighting conditions and we do not address the textures distortion issues. We analyze how to automatically select relevant pairs of 2D projections which needs an initial registration between both shapes to compare. We use a mutual information criterion to assess the distortion for each projection pair and eventually derive a global score by weighting the contributions of each view.
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