1. Geometric Blur Descriptors for Point Correspondence
Nisarg Vyas
Computational Photography (15862) Final Project,
Carnegie Mellon University

2. Motivation Point Correspondences are used in many vision applications
Image Alignment
3D reconstruction of scene from multiple views
Object Recognition
Vehicle path Navigation
Structure from Motion

3. Point Correspondence Basic Approaches: SSD, NCC
 ,Do not work well under affine transfoms

4. Blurred Descriptors
MOPS
Geometric Blur

5. Geometric Blur: Introduction
A “Spatially varying” Kernel which smoothes
Instead of Kx(y) = Gσ(y), Kx(y) = Gα|x|(y)

6. Comparison: Geometric Blur & Gaussian Blur

7. Geometric Blur “Descriptor”
Take signed Gradient of input image in both directions, we will now be with 4 channels

8. Geometric Blur “Descriptor”
Take a feature point, calculate Blur Descriptor for all 4 gradient channels,
Subsampled in concentric circles

9. Results

10. Results

11. Results

12. Status so far & Plans for final submission
Done implementing Geometric Blur Descriptor
Results are not as good as expected, sometimes simple SSD does even better !!
Have to try changing the thresholds which varies the sigma
Trying Other interesting descriptors (SIFT,C1), If time permits

13. References [1] Geometric Blur for Template Matching
A.C. Berg and J. Malik, CVPR, 2001
[2] Shape Matching and Object Recognition using Low-distortion Correspondences,
A.C. Berg, T.L. Berg and J. Malik, CVPR, 2005
[3] Comparing Visual Features for Morphing Based Recognition, J.J. Wu, MIT CSAIL Technical report, 2005 (TR )

14. Questions and Suggestions?