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Rotation Estimation: A Closed-Form Solution Using Spherical Moments †
Photometric moments are global descriptors of an image that can be used to recover motion information. This paper uses spherical photometric moments for a closed form estimation of 3D rotations from images. Since the used descriptors are global and not of the geometrical kind, they allow to avoid im...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891670/ https://www.ncbi.nlm.nih.gov/pubmed/31739484 http://dx.doi.org/10.3390/s19224958 |
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author | Hadj-Abdelkader, Hicham Tahri, Omar Benseddik, Houssem-Eddine |
author_facet | Hadj-Abdelkader, Hicham Tahri, Omar Benseddik, Houssem-Eddine |
author_sort | Hadj-Abdelkader, Hicham |
collection | PubMed |
description | Photometric moments are global descriptors of an image that can be used to recover motion information. This paper uses spherical photometric moments for a closed form estimation of 3D rotations from images. Since the used descriptors are global and not of the geometrical kind, they allow to avoid image processing as features extraction, matching, and tracking. The proposed scheme based on spherical projection can be used for the different vision sensors obeying the central unified model: conventional, fisheye, and catadioptric. Experimental results using both synthetic data and real images in different scenarios are provided to show the efficiency of the proposed method. |
format | Online Article Text |
id | pubmed-6891670 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68916702019-12-12 Rotation Estimation: A Closed-Form Solution Using Spherical Moments † Hadj-Abdelkader, Hicham Tahri, Omar Benseddik, Houssem-Eddine Sensors (Basel) Article Photometric moments are global descriptors of an image that can be used to recover motion information. This paper uses spherical photometric moments for a closed form estimation of 3D rotations from images. Since the used descriptors are global and not of the geometrical kind, they allow to avoid image processing as features extraction, matching, and tracking. The proposed scheme based on spherical projection can be used for the different vision sensors obeying the central unified model: conventional, fisheye, and catadioptric. Experimental results using both synthetic data and real images in different scenarios are provided to show the efficiency of the proposed method. MDPI 2019-11-14 /pmc/articles/PMC6891670/ /pubmed/31739484 http://dx.doi.org/10.3390/s19224958 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hadj-Abdelkader, Hicham Tahri, Omar Benseddik, Houssem-Eddine Rotation Estimation: A Closed-Form Solution Using Spherical Moments † |
title | Rotation Estimation: A Closed-Form Solution Using Spherical Moments † |
title_full | Rotation Estimation: A Closed-Form Solution Using Spherical Moments † |
title_fullStr | Rotation Estimation: A Closed-Form Solution Using Spherical Moments † |
title_full_unstemmed | Rotation Estimation: A Closed-Form Solution Using Spherical Moments † |
title_short | Rotation Estimation: A Closed-Form Solution Using Spherical Moments † |
title_sort | rotation estimation: a closed-form solution using spherical moments † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891670/ https://www.ncbi.nlm.nih.gov/pubmed/31739484 http://dx.doi.org/10.3390/s19224958 |
work_keys_str_mv | AT hadjabdelkaderhicham rotationestimationaclosedformsolutionusingsphericalmoments AT tahriomar rotationestimationaclosedformsolutionusingsphericalmoments AT benseddikhoussemeddine rotationestimationaclosedformsolutionusingsphericalmoments |