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Communication Dans Un Congrès Année : 2023

3D surface Approximation of the Entire Bayeux Tapestry for Improved Pedagogical Access

Résumé

The Bayeux Tapestry is an exceptional cultural heritage masterpiece by its size and the finesse of its details. Digitizing it raises a challenge, knowing that it is extremely fragile and thus lasers or invasive techniques are out of scope. In this work, we address this 3D-reconstruction challenge by introducing a pipeline to generate a high-resolution panorama of the Tapestry's geometry. It is based on a deep learning architecture that converts the RGB images of a pre-existing 2D panorama into a 2.5D normal map panorama. With a view to facilitating the Tapestry inclusive accessibility, we further show that coupling our 3D-reconstruction pipeline with a segmentation method allows the affordable and rapid creation of 3D-printed bas-reliefs, which can be explored tactilely by visually impaired people.
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Dates et versions

hal-04196665 , version 1 (05-09-2023)

Identifiants

  • HAL Id : hal-04196665 , version 1

Citer

Marjorie Redon, Matthieu Pizenberg, Yvain Quéau, Abderrahim Elmoataz. 3D surface Approximation of the Entire Bayeux Tapestry for Improved Pedagogical Access. 4th ICCV Workshop on Electronic Cultural Heritage, Oct 2023, Paris, France. pp.1593-1602. ⟨hal-04196665⟩
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