1. Affine Motion-compensated Prediction
Dragomir Anguelov
EE368B Final Project
December 8, 2000

2. Motivation Motion models used for prediction
Translation
How about more complex motions: rotation, shear?
Tradeoff – increased expressivity vs. increased number of parameters

3. Motion Models Translation – 2 parameters
Affine – additional 4 parameters
Account for rotation and shear

4. The Motion-compensated Hybrid Coder
Testbed assumptions:
Want very good image reconstruction
Details
Subpixel accuracy
No filtering
DCT Entropy-Minimizing coder with uniform quantization
Error image encoded and transmitted

5. The “Hybrid” MCHC

6. Affine Motion Estimation Overview
Blockmatching techniques
Infeasible, search space in 6 dimensions, optimizations in this space not well studied
Differential techniques
Lucas-Kanade pyramidal tracker (used in this project) [Lucas, Kanade ’81] [Shi, Tomasi, ’94]
Mixture techniques

7. Lucas-Kanade tracker Minimizes
Newton-Raphson minimization using the derivatives of the error function
Issues
Assumes motions between frames are not too large
Hierarchical implementation

8. Hybrid affine tracker
Use blockmatching to determine several minima of the SSD function
Initialize a differential method with those points and pick the best resulting set of affine parameters

9. Experimental results (1)
Setup:
Padded image borders
Affine parameter quantization with step 0.2
DCT error quantization with step 1.0
Block size = 16

10. Experimental Results(2)
Small, translation motion between frames
Hybrid MCHC rates are comparable
Frame
Trate
Hrate
Diff

11. Experimental Results (3)
Relatively large motion, rotation present
Frame
TRate
Hrate
RateDiff

12. Experimental Results (4)
Block Choices
0: translation 1: affine

13. Experimental Results (5)
Block size = 32, param quantization step = 0.1
Frame
Trate
Hrate
Diff

14. Conclusions Not too effective system
Small improvements
Increases running time
Limitation on accuracy of transmission and amount of motion
Improvement (better rate, same quality)
Larger blocksizes
Complex motions