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Detecting Re-captured Videos using Shot-Based Photo Response Non-Uniformity

Detecting Re-captured Videos using Shot-Based Photo Response Non-Uniformity. Dae -Jin Jung. Introduction. Recent digital camcorders Advantages High quality Low price Easy usage Abuse Camcorder theft. Introduction. Camcorder theft (illegally re-captured videos)

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Detecting Re-captured Videos using Shot-Based Photo Response Non-Uniformity

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  1. Detecting Re-captured Videos using Shot-Based Photo Response Non-Uniformity Dae-Jin Jung

  2. Introduction • Recent digital camcorders • Advantages • High quality • Low price • Easy usage • Abuse • Camcorder theft

  3. Introduction • Camcorder theft (illegally re-captured videos) • Single largest source of [1] • Fake DVDs • Unauthorized copies • Causes a great loss on movie industry Original Recaptured [1] Motion Picture Association Of America (http://www.mpaa.org)

  4. Previous Works • Lee et al.[2] • Watermarking scheme • Robust against camcorder theft • Estimates the position of the pirate • Good results • Needs embedding process [2] Digital cinema watermarking for estimating the position of the pirate (2010)

  5. Previous Works • Cao et al.[3] • Identifies recaptured images on LCD screens • Good results (EER lower than 0.5%) • Used SVM • Not suitable for videos [3] Identification of recaptured photographs on LCD screens (2010)

  6. Previous Works • Wang et al.[4] • Detects re-projected video • Skew estimating • Can achieve low false positive • Using many feature points • Feature points not on the right position • Manual pre-processing is needed [4] Detecting Re-Projected Video (2008)

  7. Differences (Original/Recaptured) • Recording device • Original • Analog cameras • Mainly used in movie industry • High quality, soft shades of colors • Recaptured • Digital cameras • Small, light, easy to handle • Recapturing without being observed

  8. Differences (Original/Recaptured) • Number of cameras used in recording • Original • Many cameras • Conversation scenes • Different purposes • Shots have different source cameras • Recaptured • Only 1 camera for recapturing

  9. Differences (Original/Recaptured) • Different post-processing • Original • Heavy post-processing • Harmonize shots from different cameras • CGs, visual effects • Recaptured • Minimum post-processing • Resizing • Re-compression

  10. Resulting characteristics • Shot based PRNU estimated from an original video • Has low correlation with each other • Analog camera • Many cameras in recording • Heavy post-processing • Shot based PRNU estimated from a recaptured video • Has high correlation with each other • Digital camcorder (PRNU) • 1 recording camera • Light post-processing

  11. Proposed method • Overview • Divide a video into shots • Estimate PRNU • PCE based recaptured video detection

  12. Proposed method • Shot change detection [5] • Calculate absolute histogram difference • Good performance and fast : Maximum gray level : Histogram of th frame [5] Automatic partitioning of full-motion video (1993)

  13. Proposed method • PRNU estimation[6] • PRNU model • MLE method • Codec noise removal [6] Source digital camcorder identification using sensor photo response non-uniformity (2008)

  14. Proposed method • Detecting re-captured videos • PCE • NxN PCE value matrix from N shots • NxNboolean matrix by thresholding

  15. Proposed method • Detecting re-captured videos • False negative correction • No fine reference pattern from sky view • Warshall’s algorithm 1 2 3 1 2 3

  16. Experimental results • Test set • 10 original videos • 20 shots were extracted • Full HD ~ HD • 4 Digital camcorders • Samsung : 1 (H205BD) • Sony : 3 (CX500, CX550, SR10) • 40 recaptured videos

  17. Experimental results • Test set

  18. Experimental results • Re-captured video detection test • (number of true values/total) ratio in boolean matrix • ‘1.00’ indicates a recaptured video Recaptured videos

  19. Experimental results • Compression test • Quality factor(QF) : 100~60 • MPEG4 (AVC/H.264)

  20. Experimental results • Resize test • Scaling factor (SF) : 0.9~0.3 • MPEG4 (AVC/H.264)

  21. Experimental results • Combinational test • Common setting for re-compression • Quality factor (QF) : 80 • Scaling factor (SF) : 0.5 • MPEG4 (AVC/H.264) • 100% detected

  22. Conclusion • Automatic recaptured video detection • Uses the shot based PRNU • Good results • Recompressed • Resized • Still weak against severe attacks

  23. Thank you

  24. Appendix • Threshold setting • 2400 pairs of PRNU from same camcorders • 2400 pairs of PRNU from different camcorders • Threshold : 80

  25. Appendix • Un-correctable False negative

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