Quantitative Affine Feature Detector Comparison based on Real-World Images Taken by a Quadcopter
Zoltán Pusztai, Levente Hajder · 2019
Feature detectors are frequently used in computer vision. Recently, detectors which can extract the affine transformation between the features have become popular. With affine transformations, it is possible to estimate the properties of the camera motion and the 3D scene from significantly fewer feature correspondences. This paper quantitatively compares the affine feature detectors on real-world images captured by a quadcopter. The ground truth (GT) data are calculated from the constrained motion of the cameras. Accurate and very realistic testing data are generated for both the feature locations and the corresponding affine transformations. Based on the generated GT data, many popular affine feature detectors are quantitatively compared.