1. Smoothly Varying Affine Stitching [CVPR 2011]
Ph.D. Student, Chang-Ryeol Lee
February 10, 2013

2. Contents Introduction Related works Proposed method Expeirments
Motivation
Problem
Related works
Dynamosaics: Video Mosaics with Non-Chronological Time [CVPR 2005]
Proposed method
Smoothly Varying Affine Stitching [CVPR 2011]
Expeirments

3. Introduction
Motivation
Typical camera FOV: 50˚ X 35˚

4. Introduction Motivation Typical camera FOV: 50˚ X 35˚
Human FOV: 200˚ X 135˚

5. Introduction Motivation Typical camera FOV: 50˚ X 35˚
Human FOV: 200˚ X 135˚
Panoramic view: 360˚ X 180˚

6. Introduction
Impressive

7. Introduction
Problem
Usually generating using rotating the camera around the center of projection:
The mosaic has a natural interpretation in 3D
The images are reprojected onto a common plane
The mosaic is formed on this plane

8. Introduction
Problem: Changing Camera Center
synthetic PP
PP1
PP2

9. Introduction
Problem: Changing Camera Center
Pics from Internet

10. Related works
Dynamosaics: Video Mosaics with Non-Chronological Time [CVPR 2005]
Shmuel Peleg (Hebrew University, Israel)
Motivation
Satellites create panoramas by scanning
1D sensor
Rotation & Translation
How can this idea be utilized?

11. Related works
Push broom stitching t
t+1
t+2

12. Related works Time-Space Cube Align the images
Create Push-broom mosaics by combining the image pieces
Different Cuts can create different mosaics

13. Related works Push broom distortion Experimental result
x-axis: Orthographic Projection
y-axis: Perspective Projection
y shrinks as Z increases, x doesn’t
Experimental result

14. Proposed method Smoothly Varying Affine Stitching [CVPR 2011]
Loong-Fah Cheong (NUS)
Work Assumption
Most scenes can be modeled as having smoothly varying depth
A global affine has general shape preservation

15. Proposed method
System overview

16. Proposed method
The affine stitching field

17. Proposed method Algorithm to compute stitching field Input: Output:
M Base image features
N Target image features
Global affine matrix
Output:
Converged affine matrix

18. Proposed method Algorithm to compute stitching field Cost function
Notation
Affine parameters
Stitched feature points by

19. Proposed method Algorithm to compute stitching field Cost function
Notation
Robust Gaussian mixture
Smoothness regularization
: Fourier transform of
: Fourier transform of Gaussian

20. Proposed method Algorithm to compute stitching field Cost function
Minimization by EM style optimization
Estimated stitching field map

21. Applications
Re-shoot

22. Applications
Re-shoot

23. Experiments
Panoramic stitching

24. Experiments
Matching

25. Thank you!
* This material is based on Raz Nossek‘s Image Registration & Mosaicing.