Robust Video Coding. Heechan Park. Signal and Image Processing Group Computer Science Department University of Warwick. for CS403
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1 Robust Video Coding for CS403 Heechan Park Signal and Image Processing Group Computer Science Department University of Warwick
2 Standard Video Coding Scalable Video Coding Distributed Video Coding
3 Video Coding Compression! Video recording with 1M pixel cam [ 1 Mega pixel x 1Byte x 30frame ] / sec
4 frame 1 frame 2 frame 7 JPEG coding for each frame? Not efficient way, only slight change frame to frame
5 How to compress video Motion estimation / compensation Residual Coding
6 Sender ----> Receiver Encoding Channel Decoding
7 Sender ----> Receiver Encoding Channel Decoding current frame
8 Sender ----> Receiver Encoding Channel Decoding current frame
9 Sender ----> Receiver Encoding Previous frame Channel Decoding current frame
10 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation current frame
11 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation current frame
12 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation current frame
13 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation Prediction current frame
14 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation Prediction current frame
15 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation Prediction current frame
16 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation Prediction current frame
17 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation Prediction current frame
18 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation Prediction current frame Closed loop system
19 Sender ----> Receiver Encoding Previous frame Channel Decoding Motion Estimation / Compensation Prediction current frame Closed loop system
20 Motion Estimation Previous Frame sender/receiver Current Frame sender
21 Motion Estimation Previous Frame sender/receiver Current Frame sender
22 Motion Estimation Previous Frame sender/receiver Current Frame sender
23 Motion Estimation Previous Frame sender/receiver Current Frame sender
24 Motion Estimation Previous Frame sender/receiver Current Frame sender
25 Motion Estimation Mean Absolute Difference Previous Frame sender/receiver Current Frame sender
26 Motion Estimation Mean Absolute Difference Previous Frame sender/receiver Current Frame sender
27 Motion Estimation Mean Absolute Difference copy & paste Previous Frame sender/receiver Current Frame sender
28 Mesh-Based ME
29 Mesh-Based ME Triangle deformation is expressed by Affine Transform
30 Residual Coding
31 Residual Coding w/o ME with ME
32 Residual Coding w/o ME with ME (DCT Wavelet) > Quantisation > Entropy
33 H.264 / MPEG-4 AVC Latest Standard, Finely tuned over decades succeeding H263 and MPEG4 Offers 50:1 compression ratio (J2K 40:1) Bluray / HD-DVD H264 = great so what is next now?
34 Compactness
35 Robustness Compactness
36 Compactness Robustness Scalability
37 What is problem in this system? Encoding Decoding
38 What is problem in this system? Encoding Decoding Wireless Noisy Channel
39 What is problem in this system? Encoding Decoding Wireless Noisy Channel
40 What is problem in this system? Encoding Decoding Wireless Noisy Channel
41 What is problem in this system? Encoding Decoding Wireless Noisy Channel
42 What is problem in this system? Encoding Decoding Wireless Noisy Channel
43 What is problem in this system? Encoding Decoding Wireless Noisy Channel
44 What is problem in this system? Encoding Decoding Wireless Noisy Channel Drifting Error Accumulates
45 What is problem in this system? Encoding Decoding Wireless Noisy Channel Drifting Error Accumulates Target bitrate is fixed; not flexible to cope with variable connection
46 Scalable Video Coding
47 Wavelet Temporal Filtering
48 Wavelet Temporal Filtering
49 Wavelet Temporal Filtering
50 Wavelet Temporal Filtering
51 Wavelet Temporal Filtering End-user can choose right resolution for his connection
52 Wavelet Temporal Filtering End-user can choose right resolution for his connection alleviates drifting errors
53 Wavelet Temporal Filtering End-user can choose right resolution for his connection alleviates drifting errors but not a perfect solution for channel noise
54 Distributed Video Coding
55 1970 Slepian and Wolf Independent encoding Joint decoding Girod IEEE Video Coding and Delivery 2005
56 1970 Slepian and Wolf Independent encoding Joint decoding X and Y are correlated Girod IEEE Video Coding and Delivery 2005
57 1970 Slepian-Wolf Theorem RX H(X Y) RY H(Y X) (RX + RY) H(X, Y) Girod IEEE Video Coding and Delivery 2005
58 1970 Slepian-Wolf Theorem RX H(X Y) RY H(Y X) (RX + RY) H(X, Y) Girod IEEE Video Coding and Delivery 2005
59 1970 Slepian-Wolf Theorem RX H(X Y) RY H(Y X) (RX + RY) H(X, Y) Girod IEEE Video Coding and Delivery 2005
60 Later, Wyner and Ziv established the min rate to encode X guaranteeing its recon. when Y is already known to decoder but not to encoder decoder aware of the correlation between X and Y No rate increase when X and Y are jointly Gaussian Girod IEEE Video Coding and Delivery 2005
61 Later, Wyner and Ziv established the min rate to encode X guaranteeing its recon. when Y is already known to decoder but not to encoder decoder aware of the correlation between X and Y No rate increase when X and Y are jointly Gaussian Girod IEEE Video Coding and Delivery 2005
62 Later, Wyner and Ziv X, Y correlated established the min rate to encode X guaranteeing its recon. when Y is already known to decoder but not to encoder decoder aware of the correlation between X and Y No rate increase when X and Y are jointly Gaussian Girod IEEE Video Coding and Delivery 2005
63 Later, Wyner and Ziv X, Y correlated X=Y established the min rate to encode X guaranteeing its recon. when Y is already known to decoder but not to encoder decoder aware of the correlation between X and Y No rate increase when X and Y are jointly Gaussian Girod IEEE Video Coding and Delivery 2005
64 Later, Wyner and Ziv X, Y correlated Channel coding X=Y established the min rate to encode X guaranteeing its recon. when Y is already known to decoder but not to encoder decoder aware of the correlation between X and Y No rate increase when X and Y are jointly Gaussian Girod IEEE Video Coding and Delivery 2005
65 Later, Wyner and Ziv X, Y correlated X=Y Error Correction Channel coding established the min rate to encode X guaranteeing its recon. when Y is already known to decoder but not to encoder decoder aware of the correlation between X and Y No rate increase when X and Y are jointly Gaussian Girod IEEE Video Coding and Delivery 2005
66 Example standard video coding Correlation = hamming distance is at most 1 Given Y = [ ] Encode X = [ ]
67 Example standard video coding Correlation = hamming distance is at most 1 Given Y = [ ] Encode X = [ ] X = [ ] or [ ] or [ ] or [ ]
68 Example standard video coding Correlation = hamming distance is at most 1 Given Y = [ ] Encode X = [ ] X = [ ] or [ ] or [ ] or [ ] 4 possibilities; Need 2 bits to encode
69 Example distributed video coding Correlation = hamming distance is at most 1 Given Y = [ ] Encode X = [ ]
70 Example distributed video coding Correlation = hamming distance is at most 1 Given Y = [ ] Encode X = [ ]
71 Example distributed video coding Correlation = hamming distance is at most 1 Given Y = [ ] Encode X = [ ]
72 Example distributed video coding Correlation = hamming distance is at most 1 Given Y = [ ] Encode X = [ ] Coset 1 Coset 2 Coset 3 Coset 4 [ ] [ ] [ ] [ ] [ ] [ ] [ ] [ ]
73 Example distributed video coding Correlation = hamming distance is at most 1 Given Y = [ ] Encode X = [ ] Coset 1 Coset 2 Coset 3 Coset 4 [ ] [ ] [ ] [ ] [ ] [ ] [ ] [ ] 4 possibilities; Need 2 bits to encode
74 Distributed Video Coding Encoding Channel Decoding
75 Distributed Video Coding Encoding Channel Decoding
76 Distributed Video Coding Encoding Channel Decoding partial info for each block
77 Distributed Video Coding Encoding Channel Decoding partial info for each block
78 Distributed Video Coding Encoding Channel Decoding partial info for each block refresh each block with partial info -> no drift error
79 Distributed Video Coding Encoding Channel Decoding partial info for each block refresh each block with partial info -> no drift error
80 Distributed Video Coding Encoding Channel Decoding partial info for each block refresh each block with partial info -> no drift error
81 Coset code and Side info(y) Source Side Info Ramchandran ICIP 2005
82 Coset code and Side info(y) Source Side Info Ramchandran ICIP 2005
83 Coset code and Side info(y) Source Side Info Ramchandran ICIP 2005
84 Coset code and Side info(y) Source Side Info Ramchandran ICIP 2005
85 Coset code and Side info(y) Source Side Info Ramchandran ICIP 2005
86 Coset code and Side info(y) Source Side Info Ramchandran ICIP 2005
87 Coset code and Side info(y) Source Side Info Ramchandran ICIP 2005
88 Quantised DCT coefficient Generating Cosets
89 Generating Cosets Quantised DCT coefficient x
90 Generating Cosets Quantised DCT coefficient x
91 Generating Cosets Quantised DCT coefficient x
92 Generating Cosets Quantised DCT coefficient x
93 Generating Cosets Quantised DCT coefficient x coset 1 coset 2
94 Generating Cosets Quantised DCT coefficient x coset 1 coset 2
95 Generating Cosets Quantised DCT coefficient x coset 1 coset 2 y
96 Generating Cosets Quantised DCT coefficient x coset 1 coset 2 y
97 Motion Estimation Previous Frame Current Frame
98 Motion Estimation Previous Frame Current Frame
99 Motion Estimation Previous Frame Current Frame
100 Motion Estimation Previous Frame Current Frame
101 Motion Estimation Too many side info(y) Previous Frame Current Frame
102 Motion Estimation Too many side info(y) Previous Frame Current Frame
103 Motion Estimation Too many side info(y) CRC or Hash Previous Frame Current Frame
104 Motion Estimation Too many side info(y) copy & paste CRC or Hash Previous Frame Current Frame
105 Packet Loss Experiment H FEC SVC + DVC Ramchandran PCS 2004
106 Packet Loss Experiment H FEC SVC + DVC Separate source coding and channel coding Ramchandran PCS 2004
107 Packet Loss Experiment H FEC SVC + DVC Separate source coding and channel coding Joint source / channel coding Ramchandran PCS 2004
108 Pereira, MPEG Future Video Coding Workshop, Nice, France 2005
109 Standard Video Coding Distributed Video Coding Encoding Slow Very Fast Decoding Fast Slow Power Consumption High in encoder / Low in decoder Low in encoder / High in encoder Motion Estimation in encoder in decoder Compression ratio 50:1 (60:1) ~30:1 Noise resilient No Yes Applications DVD, Streaming from server,... Streaming from mobile, Sensor Network,...
110 References Girod, A. Aaron, S. Rane and D. Rebollo-Monedero, "Distributed video coding," Proceedings of the IEEE, Special Issue on Video Coding and Delivery, vol. 93, no. 1, pp , January 2005 R. Puri and K. Ramchandran, PRISM: A new robust video coding architecture based on distriubted compression principles, in Proc. Allerton Conference on Communication, Contro, and Computing, Allerton, IL, Oct S. S. Pradhan and K. Ramchandran, Generalized Coset Codes for Distributed Binning, IEEE Trans. Information Theory, Vol. 51, No. 10, Oct M. Tagliasacchi, A. Majumdar and K. Ramchandran, A Distributed- Source-Coding Based Robust Spatio-Temporal Scalable Video Codec, Picture Coding Symposium 2004
111 References Girod, A. Aaron, S. Rane and D. Rebollo-Monedero, "Distributed video coding," Proceedings of the IEEE, Special Issue on Video Coding and Delivery, vol. 93, no. 1, pp , January 2005 R. Puri and K. Ramchandran, PRISM: A new robust video coding architecture based on distriubted compression principles, in Proc. Allerton Conference on Communication, Contro, and Computing, Allerton, IL, Oct S. S. Pradhan and K. Ramchandran, Generalized Coset Codes for Distributed Binning, IEEE Trans. Information Theory, Vol. 51, No. 10, Oct M. Tagliasacchi, A. Majumdar and K. Ramchandran, A Distributed- Source-Coding Based Robust Spatio-Temporal Scalable Video Codec, Picture Coding Symposium 2004 This slide is available at
112 Conclusion Conventional video coding structure and its problem Scalable Video Coding Distributed Video Coding Joint source-channel coding : Wyner - Ziv coding Still very early stage and more works to be done for better coding efficiency
113 Questions?
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