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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...

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Detalles Bibliográficos
Autores principales: Hadj-Abdelkader, Hicham, Tahri, Omar, Benseddik, Houssem-Eddine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
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
Descripción
Sumario: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.