robust motion watermarking based on multiresolution analysis tae-hoon kim jehee lee sung yong shin...
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Robust Motion Watermarkingbased onMultiresolution Analysis
Tae-hoon KimJehee Lee
Sung Yong Shin
Korea Advanced Institute of Science and Technology
Introduction
Watermarking Embedding signature into the media data
Applications of watermarking Ownership protection (robust
watermarking ) Data authentication Fingerprinting Secret data hiding
………
Objectives
Robust watermarking for motion data Imperceptible Non-invertible Robust to attacks
smoothing, cropping, scaling, type conversion, quantization, adding noise, adding another watermark, …
Ownership Protection with Watermark
insertion
watermark
registration
extractedwatermark
extraction
+
-
analysis ofsimilarity
original motion watermarked motion
registeredsuspect motion suspect motion
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
Spread Spectrum Watermarking
Embedding a watermark with redundancy
original signal
insertion+
watermarked signal
watermark signal
original signal
insertion+
watermarked signal
watermark signal
Properties of spread spectrum: JR (jam resistance) LPI (low probability of intercept)
Spread Spectrum Approaches
Images [Cox et al. 1997] Discrete cosine transform Modifying the most important coefficients
image watermarkedimage
frequencydomain
Spread Spectrum Approaches
3D meshes [Praun et al. 1999] Multiresolution analysis
3D mesh basis functions watermarkedmesh
basis function
Our Approach
Spread spectrum watermarking for motion
motion signal
…
motion data
…
Motion data = bundle of motion signals of position or orientation
Our Approach
Problem:Difficult to obtain frequency information from the motion data due to complicati
on caused by orientations
Solution:Extracting frequency information frommultiresolution representation
Multiresolution Representation
Representing at multiple resolutions Hierarchy of successive smoother and
coarser signals Hierarchy of displacement maps
(3)m (2)m (1)m (0)m
Decomposition
Reduction : smoothing, followed by down-samplingExpansion : up-sampling, followed by smoothing
Both of them can be realized by spatial masking [Lee2000]
)(nm
)1( nm
Reduction Expansion
)1( nd)(nm
)1( nm
Reduction Expansion
)1( nd)(nm
)1( nm
Reduction Expansion
)1( nd
Representation and Reconstruction
Representation
)(nm )1( nm
)1( nd
)2( nm
)2( nd
)(nm )1( nm (1)m
)0(m
)0(d…
…
)1( nd )1(d
)0(m
)0(d
Reconstruction…
…
Motion Watermarking
Based on multiresolution analysis
Watermark insertion
Watermark extraction Analysis of similarity between
inserted and extracted watermarks
Watermark Insertion
Decomposing motion signal
original signal
MultiresolutionRepresentation
(0)d(1)d
(n-1)d
…
coarse base signal
detail coefficients
(0)m
Watermark Insertion
Perturbing the largest coefficients
original signal
( , )u v
(0)d(1)d
(n-1)d
…
coarse base signal
detail coefficients
(0)m
the i-th largest coefficient
(0)d(1)d
(n-1)d
coarse base signal
detail coefficients
…
(0)m
altered coefficient
( , ) u v
( , ) (1 )( , )iw u v u v
scaling paramete
r
watermark
coefficient
Watermark Insertion
Reconstructing the motion signal
original signal
(0)d(1)d
(n-1)d
coarse base signal
detail coefficients
…
(0)m
watermarked signal
Watermark Insertion
Perturbation of coefficient Embedding watermark into wide
range
original motion
+
watermarksignal
watermarked motion
Watermark Extraction
Registering original and suspect motion Using dynamic time warping
[Bruderlin1995]
dynamic time warping
resampling
originalsignal
suspectsignal
originalsignal
registeredsuspect signal
Watermark Extraction
Decomposing motion signals
original signal
suspect signal
(0)d(1)d
(n-1)d…
coarse base signal
detail coefficients
(0)m
*(0)d*(1)d
*(n-1)d
coarse base signal
detail coefficients
…
*(0)m
Watermark Extraction
Comparing watermarked coefficients
(0)d(1)d
(n-1)d…
coarse base signal
detail coefficients
(0)m
*(0)d*(1)d
*(n-1)d
coarse base signal
detail coefficients
…
*(0)m
( , )u v
),( ** vu
comparing
Watermark Extraction
Extracting suspect watermark
Obtaining from
scaling paramete
r
),)(1(),( *** vuvu iw
) ..., , ,( **2
*1
*mwwww
) ..., , ,( 21 mwwww
Analysis of Similarity
Computing false-positive probability False-positive probability (Pfp ):
Probability of incorrectly asserting that the datais watermarked when it is not
Using Student’s t-test From correlation * ,ww
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
Q/A : False-negative Probability
False-negative ProbabilityProbability 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