Communication Dans Un Congrès Année : 2025

3D Object Reconstruction Through Integration of Hyperspectral and RGB-D Imaging

Résumé

This work explores the integration of RGB-D and hyperspectral imaging technologies to enhance the accuracy of 3D reconstructions. We propose a methodology that combines depth maps from an RGB-D camera with spectral data from a hyperspectral camera to develop a detailed 3D hyperspectral point cloud model. Our approach combines feature points detected in spectral bands and captured depth maps to estimate the poses of the multi-camera system moved around objects to reconstruct their overall shape accurately in a dense manner. 3D reconstruction with the hyperspectral data experiments are conducted on commonly used objects in literature and compared with the publicly available ground-truth 3D point clouds of these objects. Results of utilizing full spectral information consistently demonstrate superior reconstruction accuracy both quantitatively and qualitatively compared to reduced spectral representations (i.e. three band selected false-color images or band averaged images).

Fichier principal
Vignette du fichier
2025_Hong_MVA.pdf (4.59 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-05124721 , version 1 (30-07-2025)

Licence

Identifiants

  • HAL Id : hal-05124721 , version 1

Citer

Cheng Hong, Guillaume Caron, Nevrez Imamoglu, Fumio Kanehiro. 3D Object Reconstruction Through Integration of Hyperspectral and RGB-D Imaging. International Conference on Machine Vision Applications, Jul 2025, Kyoto (Japan), Japan. ⟨hal-05124721⟩
474 Consultations
458 Téléchargements

Partager

  • More