Multi-view Shape and Texture Learning for Stereo Finite-Element Digital Image Correlation - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2020

Multi-view Shape and Texture Learning for Stereo Finite-Element Digital Image Correlation

Résumé

In order to make use of a Stereo Finite-Element Digital Image Correlation framework, one has first to perform a calibration procedure that encompasses the calibration of the cameras and of the specimen shape. This last step is not always straightforward and often requires some kind of regularisation. In the current work, we propose to measure the shape and the texture attached to the specimen and show that it allows to drastically reduce the ill-posedness of the shape measurement problem.
Fichier non déposé

Dates et versions

hal-02982170 , version 1 (28-10-2020)

Identifiants

  • HAL Id : hal-02982170 , version 1

Citer

Raphaël Fouque, Robin Bouclier, Jean-Charles Passieux, Jean-Noël Périé. Multi-view Shape and Texture Learning for Stereo Finite-Element Digital Image Correlation. International Digital Image Correlation Society Virtual Conference 2020, Oct 2020, Virtual Conference, France. ⟨hal-02982170⟩
72 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More