1. Multi-Hypothesis Disparity-Compensated Light Field Compression
Prashant Ramanathan
EE368B Final Project
December 6, 2000

2. Overview Light fields Light field compression
Multi-hypothesis techniques
Results
Prashant Ramanathan

3. Light Fields I
Represents the appearance of a scene or object from all viewing positions and directions
Planar
Light Field
University of Erlangen
Computer Graphics Group
Prashant Ramanathan

4. Light Fields II Problems with light fields: Difficult to acquire
Very large
Buddha
200 MB uncompressed
Night
95 GB uncompressed
Stanford University Computer Graphics Laboratory
Prashant Ramanathan

5. Light Field Compression
Disparity-compensation (Magnor, Girod 2000)
target image
reference images
reference images
Prashant Ramanathan

6. Multiple Hypothesis
Specify reference views to use and independent disparity values
reference
view 1
reference
view 3
Prashant Ramanathan

7. Experimental Data Two sets of images from Flieger light field
target image
reference images
reference images
Prashant Ramanathan

8. Experiments Three schemes tested: STD: one disparity H1:
reference index
H2:
two disparities +
reference indices
Prashant Ramanathan

9. Results I
4x4 blocks H2 H1
STD
Prashant Ramanathan

10. Results II
32x32 blocks H2 H1
STD
Prashant Ramanathan

11. Conclusions and Future Work
Multi-hypothesis prediction reduces residual error
Overall compression gain?
Theoretical analysis?
Prashant Ramanathan