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Estimation de pose de caméra à partir de correspondances ellipse - ellipsoïde

Vincent Gaudillière 1 Gilles Simon 1 Marie-Odile Berger 1
1 MAGRIT-POST - Augmentation visuelle d'environnements complexes
Inria Nancy - Grand Est, LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
Abstract : In computer vision, estimating camera pose from correspondences between 3D geometric entities and their projections into the image is a widely investigated problem. Although most state-of-the-art methods exploit simple primitives such as points or lines, and thus require dense scene models, the appearance of very effective CNN-based object detectors in the recent years has paved the way to the use of much lighter 3D models composed solely of a few semantically relevant features. In that context, we propose a novel model-based camera pose estimation method in which the scene is represented by a set of ellipsoids. We show that the problem can be solved by optimizing only the three camera orientation parameters, and that two correspondences between 2D ellipses and 3D ellipsoids are necessary in practice .
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Submitted on : Wednesday, June 5, 2019 - 4:27:28 PM
Last modification on : Wednesday, March 18, 2020 - 11:11:41 AM

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  • HAL Id : hal-02148633, version 1

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Vincent Gaudillière, Gilles Simon, Marie-Odile Berger. Estimation de pose de caméra à partir de correspondances ellipse - ellipsoïde. ORASIS 2019 - 17ème journées francophones des jeunes chercheurs en vision par ordinateur, May 2019, Saint-Dié-des-Vosges, France. ⟨hal-02148633⟩

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