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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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Barath, D. (2017). P-HAF: Homography Estimation using Partial Local Affine Frames. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 6: VISAPP; ISBN 978-989-758-227-1; ISSN 2184-4321, SciTePress, pages 227-235. DOI: 10.5220/0006130302270235

@conference{visapp17,
author={Daniel Barath.},
title={P-HAF: Homography Estimation using Partial Local Affine Frames},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 6: VISAPP},
year={2017},
pages={227-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006130302270235},
isbn={978-989-758-227-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 6: VISAPP
TI - P-HAF: Homography Estimation using Partial Local Affine Frames
SN - 978-989-758-227-1
IS - 2184-4321
AU - Barath, D.
PY - 2017
SP - 227
EP - 235
DO - 10.5220/0006130302270235
PB - SciTePress