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CamMark : a camcorder copy simulation as watermarking benchmark for digital video
Schaber, Philipp
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Kopf, Stephan
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Wesch, Christoph
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Effelsberg, Wolfgang
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DOI:
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https://doi.org/10.1145/2557642.2557644
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URL:
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http://dl.acm.org/citation.cfm?doid=2557642.255764...
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Weitere URL:
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https://www.researchgate.net/publication/261960749...
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Dokumenttyp:
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Konferenzveröffentlichung
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Erscheinungsjahr:
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2014
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Buchtitel:
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Proceedings of the 5th ACM Multimedia Systems Conference (MMSys '14) : Singapore, March 19 - 21, 2014
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Seitenbereich:
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91-102
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Veranstaltungstitel:
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ACM Multimedia Systems 2014
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Veranstaltungsort:
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Singapore
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Veranstaltungsdatum:
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19.03.2014
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Ort der Veröffentlichung:
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New York, NY
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Verlag:
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ACM
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ISBN:
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978-1-4503-2705-3
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Sprache der Veröffentlichung:
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Englisch
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Einrichtung:
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Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik > Praktische Informatik IV (Effelsberg 1989-2017)
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Fachgebiet:
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004 Informatik
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Freie Schlagwörter (Englisch):
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Digital watermarking , camcorder copy , video watermarking benchmark , geometric distortion , frame blending , automatic gain control , automatic white balance , BayerCFA
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Abstract:
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In 1998, Petitcolas et al. proposed StirMark as a benchmark for image watermarking schemes. The main idea was to introduce a re-sampling process that mimics the analog process of printing and scanning a watermarked image. For digital video, the corresponding concept is a camcorder copy, where a video displayed on a screen is (digitally) recorded using a video camera. As most commercial video streaming systems (VOD, IPTV) and offline distribution (Blu-ray, HDDs for cinemas) are strongly protected by means of DRM, filming a display is actually a relevant use case and a requirement for robust video watermarking systems to survive.
We therefore present a tool to simulate content re-acquisition with a camcorder. Our goal is to support watermark development by enabling automated test cases for such camcorder copy attacks, as well as to provide a benchmark for robust video watermarking. Manually creating camcorder copies is a cumbersome process, and even more problematic, it is hardly reproducible with the same setup.
By re-sampling each video frame, we simulate the typical artifacts of a camcorder copy: geometric modifications (aspect ratio changes, cropping, perspective and lens distortion), temporal modifications (unsynchronized frame rates and the resulting frame blending), sub-sampling (rescaling, filtering, Bayer color array filter), and histogram changes (AGC, AWB). We also support simulating camera movement (e.g., a hand-held camera) and background insertion.
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