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Communication Dans Un Congrès Année : 2022

Projective multitexturing of current 3D city models and point clouds with many historical images

Résumé

Iconographic image collections are a cultural heritage that could reach a larger audience by proposing their immersive presentation in a 3D web application. Proposing a historical street view application, based on these historical images, raises issues such as the unavailability of historical 3D models of the scene and the heterogeneity and sparsity of these photographs. We propose to use the 3D city and terrain models of the current scene, as well as a 3D point cloud if available, to simultaneously reproject and blend many historical images using an image-based rendering approach. Our contributions raise significantly the number of projective textures blended per rendering pass (typically from 8 to 40) on triangular meshes (of the 3D city and terrain models) and on point clouds. As a first step to tackle diachrony artifacts, we also propose a simple point cloud classification to filter in the shader the points corresponding to building or terrain details from the points corresponding to transient objects.

Dates et versions

hal-03684813 , version 1 (01-06-2022)

Identifiants

Citer

Maria Scarlleth Gomes de Castro, Mathieu Brédif. Projective multitexturing of current 3D city models and point clouds with many historical images. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Jun 2022, Nice, France. pp.213-218, ⟨10.5194/isprs-annals-V-4-2022-213-2022⟩. ⟨hal-03684813⟩
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