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Autori principali: Gilles, Jerome, Alvarez, Francis, Ferrante, Nicholas B., Fortman, Margaret, Tahir, Lena, Tarter, Alex, von Seeger, Anneke
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:https://arxiv.org/abs/2410.21551
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author Gilles, Jerome
Alvarez, Francis
Ferrante, Nicholas B.
Fortman, Margaret
Tahir, Lena
Tarter, Alex
von Seeger, Anneke
author_facet Gilles, Jerome
Alvarez, Francis
Ferrante, Nicholas B.
Fortman, Margaret
Tahir, Lena
Tarter, Alex
von Seeger, Anneke
contents In this paper, we investigate how moving objects can be detected when images are impacted by atmospheric turbulence. We present a geometric spatio-temporal point of view to the problem and show that it is possible to distinguish movement due to the turbulence vs. moving objects. To perform this task, we propose an extension of 2D cartoon+texture decomposition algorithms to 3D vector fields. Our algorithm is based on curvelet spaces which permit to better characterize the movement flow geometry. We present experiments on real data which illustrate the efficiency of the proposed method.
format Preprint
id arxiv_https___arxiv_org_abs_2410_21551
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Detection of moving objects through turbulent media. Decomposition of Oscillatory vs Non-Oscillatory spatio-temporal vector fields
Gilles, Jerome
Alvarez, Francis
Ferrante, Nicholas B.
Fortman, Margaret
Tahir, Lena
Tarter, Alex
von Seeger, Anneke
Computer Vision and Pattern Recognition
In this paper, we investigate how moving objects can be detected when images are impacted by atmospheric turbulence. We present a geometric spatio-temporal point of view to the problem and show that it is possible to distinguish movement due to the turbulence vs. moving objects. To perform this task, we propose an extension of 2D cartoon+texture decomposition algorithms to 3D vector fields. Our algorithm is based on curvelet spaces which permit to better characterize the movement flow geometry. We present experiments on real data which illustrate the efficiency of the proposed method.
title Detection of moving objects through turbulent media. Decomposition of Oscillatory vs Non-Oscillatory spatio-temporal vector fields
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2410.21551