A No Reference Deep Quality Assessment Index for 3D Colored Meshes - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen (GREYC)
Communication Dans Un Congrès Année : 2024

A No Reference Deep Quality Assessment Index for 3D Colored Meshes

Résumé

The advent of 3D data has revolutionized various industries, from architecture and engineering to healthcare and entertainment, enabling more precise simulations and realistic visualizations. However, 3D data is susceptible to noise and loss during generation and transmission, making quality assessment crucial for ensuring accuracy and usability. While existing literature addresses quality assessment for 3D point clouds and meshes separately, a gap exists in assessing the quality of 3D colored meshes due to the lack of reference datasets. This paper proposes an approach for No Reference 3D Colored Mesh Visual Quality Assessment (CMVQA), based on previous work related to quality assessment of 3D non colored meshes quality assessment. Our approach combines geometric and color features with spatial domain features extracted from mesh projections. Through extensive experiments and comparisons with full-reference metrics, including image quality metrics, our proposed approach demonstrates superior performance.
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Dates et versions

hal-04775149 , version 1 (09-11-2024)

Identifiants

  • HAL Id : hal-04775149 , version 1

Citer

Zaineb Ibork, Anass Nouri, Olivier Lézoray, Christophe Charrier, Raja Touahni. A No Reference Deep Quality Assessment Index for 3D Colored Meshes. IEEE International Conference on Systems, Man, and Cybernetics (SMC2024), IEEE, Oct 2024, Sarawak, Malaysia. ⟨hal-04775149⟩
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