Abstract
Digital cameras are being integrated in a large number of mobile devices. These devices may be used to record illegal activities, or the recordings themselves may be illegal. Due to the tight integration of these mobile devices with the internet, these recordings may quickly find their way to internet video-sharing sites such as YouTube. In criminal casework it is advantageous to reliably establish the source of the video. Although this was shown to be doable for relatively high quality video, it is unknown how these systems perform for low quality transcoded videos. The CAMCOM2010 contest is organized to create a benchmark for source video identification, where the videos originate from YouTube. Despite the number of participants was satisfactory initially, only two participants submitted results, mostly due to a lack of time. Judging by the performance of the contestants, this is certainly not a trivial problem.
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References
Geradts, Z., Bijhold, J., Kieft, M., Kurosawa, K., Kuroki, K., Saitoh, N.: Methods for identification of images acquired with digital cameras. In: Proc. of SPIE: Enabling Technologies for Law Enforcement and Security, vol. 4232, pp. 505–512 (2001)
Lukáš, J., Fridrich, J., Goljan, M.: Determining digital image origin using sensor imperfections. In: Proc. of SPIE, vol. 5685, p. 249 (2005)
Chen, M., Fridrich, J., Goljan, M., Lukáš, J.: Determining Image Origin and Integrity Using Sensor Noise. IEEE Trans. on Information Forensics and Security 3(1), 74–90 (2008)
Alles, E.J., Geradts, Z.J.M.H., Veenman, C.J.: Source camera identification for heavily JPEG compressed low resolution still images. Journal of Forensic Sciences 54(3), 628–638 (2009)
van Houten, W., Geradts, Z.: Source video camera identification for multiply compressed videos originating from YouTube. Digital Investigation 6(1-2), 48–60 (2009)
Goljan, M., Fridrich, J., Filler, T.: Large Scale Test of Sensor Fingerprint Camera Identification. In: Proc. of SPIE, vol. 7254, pp. 72540I–72540I-12 (2009)
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van Houten, W., Geradts, Z., Franke, K., Veenman, C. (2010). Verification of Video Source Camera Competition (CAMCOM 2010). In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds) Recognizing Patterns in Signals, Speech, Images and Videos. ICPR 2010. Lecture Notes in Computer Science, vol 6388. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17711-8_3
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DOI: https://doi.org/10.1007/978-3-642-17711-8_3
Publisher Name: Springer, Berlin, Heidelberg
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