Robust Motion Watermarking based on Multiresolution Analysis

1. Robust Motion Watermarkingbased onMultiresolution Analysis Tae-hoon Kim Jehee Lee Sung Yong Shin Korea Advanced Institute of Science and Technology

2. Introduction • Watermarking • Embedding signature into the media data • Applications of watermarking • Ownership protection (robust watermarking ) • Data authentication • Fingerprinting • Secret data hiding ………

3. Objectives • Robust watermarking for motion data • Imperceptible • Non-invertible • Robust to attacks • smoothing, cropping, scaling, type conversion, quantization, adding noise, adding another watermark, …

4. registered suspect motion suspect motion Ownership Protection with Watermark insertion + watermarked motion original motion watermark analysis of similarity - extraction extracted watermark registration

5. Previous Work • [Schyndel et al. 1994] • Modifying the least significant bits • [Tanaka et al. 1990] • Embedding noise-like watermarks • [Cox et al. 1997] • Introducing spread-spectrum for images • [Praun et al. 1999] • Employing spread-spectrum for 3D meshes

6. insertion insertion + + watermarked signal watermarked signal original signal original signal watermark signal watermark signal Spread Spectrum Watermarking • Embedding a watermark with redundancy Properties of spread spectrum:  JR (jam resistance)  LPI (low probability of intercept)

7. image watermarked image Spread Spectrum Approaches • Images [Cox et al. 1997] • Discrete cosine transform • Modifying the most important coefficients frequency domain

8. 3D mesh basis functions watermarked mesh basis function Spread Spectrum Approaches • 3D meshes [Praun et al. 1999] • Multiresolution analysis

9. … … motion data motion signal Our Approach • Spread spectrum watermarking for motion Motion data = bundle of motion signals of position or orientation

10. Our Approach Problem: Difficult to obtain frequency information from the motion data due to complication caused by orientations Solution: Extracting frequency information from multiresolution representation

11. Multiresolution Representation • Representing at multiple resolutions • Hierarchy of successive smoother and coarser signals • Hierarchy of displacement maps

12. Reduction Reduction Reduction Expansion Expansion Expansion Decomposition Reduction : smoothing, followed by down-sampling Expansion : up-sampling, followed by smoothing • Both of them can be realized by spatial masking [Lee2000]

13. … … • Reconstruction … Representation and Reconstruction • Representation …

14. Motion Watermarking Based on multiresolution analysis • Watermark insertion • Watermark extraction • Analysis of similarity between inserted and extracted watermarks

15. coarse base signal original signal … Multiresolution Representation detail coefficients Watermark Insertion • Decomposing motion signal

16. watermark coefficient coarse base signal coarse base signal scaling parameter original signal … … the i-th largest coefficient altered coefficient detail coefficients detail coefficients Watermark Insertion • Perturbing the largest coefficients

17. coarse base signal original signal watermarked signal … detail coefficients Watermark Insertion • Reconstructing the motion signal

18. watermark signal watermarked motion + original motion Watermark Insertion • Perturbation of coefficient  Embedding watermark into wide range

19. original signal original signal registered suspect signal suspect signal dynamic time warping resampling Watermark Extraction • Registering original and suspect motion • Using dynamic time warping [Bruderlin1995]

20. coarse base signal coarse base signal original signal suspect signal … … detail coefficients detail coefficients Watermark Extraction • Decomposing motion signals

21. coarse base signal coarse base signal comparing … … detail coefficients detail coefficients Watermark Extraction • Comparing watermarked coefficients

22. scaling parameter Watermark Extraction • Extracting suspect watermark • Obtaining from

23. Analysis of Similarity • Computing false-positive probability • False-positive probability (Pfp ): Probability of incorrectly asserting that the data is watermarked when it is not • Using Student’s t-test • From correlation

24. Data A Data B Data C Data D Experimental Results

25. Experimental Results • Original Motion and Watermarked Motion • Fly Spin Kick

26. Experimental Results • Original Motion and Watermarked Motion • Blown Back

27. Experimental Results • Results for various attacks • Adding noise attack on Fly Spin Kick

28. Experimental Results • Results for various attacks • Adding the second watermark on Fly Spin Kick

29. Experimental Results • Results for various attacks • Smoothing attack on Blown Back

30. Experimental Results • Results for various attacks • Time warping attack on Blown Back

31. Experimental Results

32. Conclusion and Future Works • Watermarking schemes for motion data • Spread spectrum approach • Using multiresolution motion analysis • Robust to attacks • Future works • Consideration for other attacks • Blind detection • Watermark extraction from rendered images

34. Q/A : False-negative Probability • False-negative Probability Probability of failing to detect watermarked data • lesser important than false-positive probability • More difficult to analyze since it depends on the type and magnitude of attacks

35. random numbers original data hashed value owner’s key Q/A : Non-invertible Watermark • Generating non-invertible watermark randomly selected from • seeded by cryptographic hash function with (original data + owner’s key)