1. Joint Optimization of Data Hiding and Video Compression Jithendra K. Paruchuri & Sen-ching S. Cheung Department of Electrical and Computer Engineering Center for Visualization and Virtual Environments University of Kentucky, Lexington, KY 40507 ISCAS - May 21, 2008

2. Overview Motivation and Problem Data Hiding Framework Rate-Distortion Optimized Data Hiding Results Conclusion & Future Work www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

3. Smart video surveillance Biometric theft Mobile-media processing RFID tracking Signal Privacy

4. Identity Obfuscation Original Pixelation/ Blurring Black Box Object Removal - Segmentation + Video In-painting [Venkatesh 06, 08]

5. Problem with Obfuscation Police: Where were you 9am on Oct 1? A: I was in my office. Police:Do you have any proof? A:…… Obfuscation destroys the authenticity Original needed to legitimize the modification. Accessed with proper authorization.

6. Privacy Data Preservation Separate Files or Meta-data Cryptographic Scrambling [Boult05], [Dufaux06] Data Hiding in DCT [Zhang05] –Works with any obfuscation techniques –High capability and low distortion –Fragile embedding –Eight-fold increase in output bit-rate!

7. Data Hiding with Compression Motion Compensation DCT Entropy Coding DCT Domain Frequency, contrast and luminance masking [Watson] DCT Perceptual Mask Parity Embedding Last decoded frame www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

8. Embedding & Perceptual Distortion To embed x in a quantized DCT coeff. c(i,j,k) Select coefficients to minimize distortion –Contrast masking –Frequency masking –Distortion

9. Causes of Bit-rate Explosion Disturbing the ‘favorable characteristics’ (zero blocks & long run-lengths) for entropy coding Data embedding inserts noise into motion compensation loop www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257 Proposed solution: Identify specific DCT coefficients for data hiding that minimizes both the output rate and distortion

10. R-D optimized Data Hiding Motion Compensation DCT Entropy Coding DCT Domain Frequency, contrast and luminance masking [Watson] H.263 DCT Perceptual Mask Parity Embedding R-D Optimization Positions of the “optimal’ DCT coeff for embedding Last decoded frame www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257 Parity Embedding

11. Constrained Optimization Let R k ( M k ) and D k ( M k ) be the rate and distortion after hiding M k bits into the k-th DCT block. δ is a user-defined weight Optimization Problem:

12. Calculations of R k ( M k ) and D k ( M k ) Two Issues: –Parity embedding depends on hidden data –Need to find optimal selection as well “Worst-case” embedding on previous frame Optimal selection –D k ( M k ) is additive (easy) –R k ( M k ) is not: R k ( N ) and R k ( N+1 ) may use very different coefficients

13. Dynamic Programming Greedy Approximation –Pick next coefficient to minimize cost –Fast implementation Dynamic Programming versus Greedy approach Embedding K-th bit Embedding K+1-st bit i+1 i i+2 i+1 i+2 i+3

14. Performance Comparison For CIF, Greedy needs 26 second/frame vs. DP needs 22 minutes/frame

15. Dual of the optimization Lower bounded by unconstrained opt: Search λ to meet constraint –Start at 2 nd order approximation of C k ( M k ) 3-5 seconds per one CIF frame

16. Experiment 1: Hall Monitor

17. Hall Monitor (QP=10) Weight δ Rate In kbps Perceptual Distortion Rate Increase Separate Files 119.5+81= 200.5 00% 032821.6563.8% 0.53022750.9% 128710243.4% www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257

18. Hall Monitor (QP=10) Original Distortion Optimized Weight = 0.5 Rate Optimized

19. Surveillance Video

20. Surveillance (QP=10) www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257 Weight δ Rate In kbps Perceptual Distortion Rate Increase Separate Files 153.97+77.34 =231.31 00% 0379.7317.5564.2% 0.5359.7621.5855.5% 1341.7274.7947.7%

21. Surveillance (QP=10) Original Distortion Optimized Rate Optimized Weight=0.5

22. Conclusions Privacy Data Preservation with Data Hiding R-D Optimization Framework for Data Hiding Current work –Reversible Data Embedding: ICIP 2008 –Privacy Data Management: ICIP 2008 –Incorporate temporal dimension in perceptual and rate model –Joint encryption and data hiding www.vis.uky.edu | Dedicated to Research, Education and Industrial Outreach | 859.257.1257