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No-Reference 3D Mesh Quality Assessment Based on Dihedral Angles Model and Support Vector Regression

Abstract : 3D meshes are subject to various visual distortions during their transmission and geometrical processing. Several works have tried to evaluate the visual quality using either full reference or reduced reference approaches. However, these approaches require the presence of the reference mesh which is not available in such practical situations. In this paper, the main contribution lies in the design of a computational method to automatically predict the perceived mesh quality without reference and without knowing beforehand the distortion type. Following the no-reference (NR) quality assessment principle, the proposed method focuses only on the distorted mesh. Specifically, the dihedral angles are firstly computed as a surface roughness indexes and so a structural information descriptors. Then, a visual masking modulation is applied to this angles according to the main characteristics of the human visual system. The well known statistical Gamma model is used to fit the dihedral angles distribution. Finally, the estimated parameters of the model are learned to the support vector regression (SVR) in order to predict the quality score. Experimental results demonstrate the highly competitive performance of the proposed no-reference method relative to the most influential methods for mesh quality assessment.
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Contributeur : LE2I - université de Bourgogne Connectez-vous pour contacter le contributeur
Soumis le : lundi 9 janvier 2017 - 18:31:15
Dernière modification le : jeudi 11 août 2022 - 13:10:06



Ilyass Abouelaziz,, Mohammed El Hassouni, Hocine Cherifi. No-Reference 3D Mesh Quality Assessment Based on Dihedral Angles Model and Support Vector Regression. 7th International Conference on Image and Signal Processing (ICISP 2016) , May 2016, Trois Rivières, Canada. pp.369-377, ⟨10.1007/978-3-319-33618-3_37⟩. ⟨hal-01430400⟩



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