SIFT Vs SURF: Quantifying the Variation in Transformations

TL;DR

This paper provides a detailed empirical comparison of SIFT and SURF algorithms, analyzing their robustness to various image transformations and aiding in selecting the appropriate technique for specific applications.

Contribution

It offers an exhaustive quantitative analysis of how SIFT and SURF handle different transformation deformations, which was lacking in prior comparative studies.

Findings

SIFT and SURF exhibit different robustness levels to various transformations.

Matching performance varies significantly with parameter adjustments.

The study guides optimal use case selection for SIFT and SURF.

Abstract

This paper studies the robustness of SIFT and SURF against different image transforms (rigid body, similarity, affine and projective) by quantitatively analyzing the variations in the extent of transformations. Previous studies have been comparing the two techniques on absolute transformations rather than the specific amount of deformation caused by the transformation. The paper establishes an exhaustive empirical analysis of such deformations and matching capability of SIFT and SURF with variations in matching parameters and the amount of tolerance. This is helpful in choosing the specific use case for applying these techniques.