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Visual Sensor Networks and Related Applications
Open AccessArticle

Rotation Estimation: A Closed-Form Solution Using Spherical Moments

IBISC lab. EA 4526, University of Evry-Val-d’Essonne-Paris Saclay, 91000 Evry, France
INSA Centre Val de Loire, PRISME lab. EA 4229, University of Orleans, 18000 Bourges, France
MIS lab. EA 4290, University of Picardie Jules Verne, 80039 Amiens, France
Authors to whom correspondence should be addressed.
This paper is an extended version of our paper published in Hadj-Abdelkader, H.; Tahri, O.; Benseddik, H.E. Closed form solution for Rotation Estimation using Photometric Spherical Moments. In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 1–5 October 2018; pp. 627–634.
Sensors 2019, 19(22), 4958;
Received: 30 September 2019 / Revised: 22 October 2019 / Accepted: 24 October 2019 / Published: 14 November 2019
(This article belongs to the Section Intelligent Sensors)
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. View Full-Text
Keywords: geometric moments; spherical image; motion estimation geometric moments; spherical image; motion estimation
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Hadj-Abdelkader, H.; Tahri, O.; Benseddik, H.-E. Rotation Estimation: A Closed-Form Solution Using Spherical Moments. Sensors 2019, 19, 4958.

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