Author:
Daniel Barath
Affiliation:
MTA SZTAKI, Hungary
Keyword(s):
Homography, Minimal Problem, Local Affine Transformation, Stereo Vision.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Stereo Vision and Structure from Motion
Abstract:
We propose an algorithm, called P-HAF, to estimate planar homographies using partially known local affine transformations. This general theory is able to exploit the affine components obtained by the commonly used partially affine covariant detectors, such as SIFT or SURF, in a real time capable way. P-HAF as a minimal solver can estimate the homography using two SIFT correspondences, moreover, it can deal with any number of point pairs as an overdetermined system. It is validated both on synthesized and publicly available datasets that exploiting all information leads to more accurate estimates and makes multi-homography estimation less ambiguous.