Geometric Blur Descriptors for Point Correspondence

Nisarg VyasComputational Photography

(15862) Final Project,

Carnegie Mellon University

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

Point Correspondence

Basic Approaches: SSD, NCC

,Do not work well under affine transfoms

Blurred Descriptors

MOPS

Geometric Blur

Geometric Blur: Introduction

A “Spatially varying” Kernel which smoothes

Instead of Kx(y) = Gσ(y), Kx(y) = Gα|x|(y)

Comparison: Geometric Blur & Gaussian Blur

Geometric Blur “Descriptor”

Take signed Gradient of input image in both directions, we will now be with 4 channels

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

Results

Results

Results

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

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-2005-035)

Questions and Suggestions?