Full-reference saliency-based 3D mesh quality assessment index

Anass Nouri (1) , Christophe Charrier (2) , Olivier Lézoray (1)

1 Equipe Image - Laboratoire GREYC - UMR6072
2 Equipe SAFE - Laboratoire GREYC - UMR6072

We propose in this paper a novel perceptual viewpoint-independent metric for the quality assessment of 3D meshes. This full-reference objective metric relies on the method proposed by Wang et al.[1] that compares the structural in-formations between an original signal and a distorted one. In order to extract the structural informations of a 3D mesh, we use a multi-scale visual saliency map on which we compute the local statistics. The experimental results attest the strong correlation between the objective scores provided by our metric and the human judgments. Also, comparisons with the state-of-the-art prove that our metric is very competitive.

Mots clés: Objective quality assessment; 3D mesh; Visual Saliency; graph

Domaines: Informatique [cs]; Mathématiques [math]

Anass Nouri, Christophe Charrier, Olivier Lézoray. Full-reference saliency-based 3D mesh quality assessment index. IEEE International Conference on Image Processing, IEEE, Sep 2016, Phoenix, United States. pp.1007 - 1011, ⟨10.1109/ICIP.2016.7532509⟩. ⟨hal-01413778⟩