1. Rate-distortion Optimized Mode Selection Based on Multi-channel Realizations Markus Gärtner Davide Bertozzi Classroom Presentation 13 th March 2001

2. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 2 Overview Hybrid Video Coding Proposed Architecture Multi-channel realizations Performance Measurements: Concealment Techniques Number of Channel Realization Error Propagation Conclusions

3. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 3 Motion-compensated hybrid coder Intraframe DCT coder Motion compensated predictor Intraframe Decoder Mode Control XORXOR Decoder Encoder

4. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 4 Proposed Improvements over H.263 H.263 Hybrid Video Coder: Error propagation in the decoder loop neglected Error-free transmission assumed Threshold based mode selection Goals of our approach: Simulation of several channel conditions Prediction of the error incurred at the receiver Rate-Distortion optimized mode selection

5. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 5 Multiple Channel Realizations Coder Frame Buffer Decoder Inter Intra Channel n Decoder Conceal- ment & Mode Decision Original Encoder n th Channel Realization input output

6. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 6 Channel Realizations Randomly generated error patterns for each channel Capture different sensitivity of macro-blocks to errors Channel 1 Channel 2 Channel n X X X X X Group of blocks (GOB) Estimate of the real channel conditions (on the average)

7. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 7 Bit error causes loss of macro block Synchronization markers before each GOB Macro block concealment GOB concealment Concealment of rest of GOB Error Concealment X X X X X X Erroneous macro- blocks are replaced by respective macro-block of previously reconstructed frame

8. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 8 Distortion Measure Channel 1 Channel N For each Macro-block:

9. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 9 Mode Selection Decision takes place for each macro-block  selection table Computational complexity Input Frame > < Mode Selection

10. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 10 Channel Decoder Selection table Coder Mode input Intra: quantized frame Inter: difference signal, motion vectors For each channel : Inter: previous frame buffer content + difference signal Intra: quantized frame Reconstructed Frame

11. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 11 Experimental Setup Encoder Decoder Channel Quantizer Frame Buffer Dequantizer Distortion Rate

12. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 12 Performance Measurement (I)

13. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 13 Performance Measurement (II)

14. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 14 Number of Realizations

15. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 15 Error Propagation (I) First I-Frame received in error

16. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 16 Error Propagation (II) First I-Frame received correctly

17. Markus Gärtner, Davide Bertozzi: Robust Video coding Stanford University, 13 th March 2001 17 Conclusions Suitability for error-prone environments Better performance than H.263 Reduction of error propagation Limitations Advanced modes of H.263 not considered Computational complexity Application for downloadable multimedia Future work: Sophisticated channel models Implementation of advanced features