A curvature-tensor-based perceptual quality metric for 3D triangular meshes

Fakhri Torkhani 1 Kai Wang 1 Jean-Marc Chassery 1
1 GIPSA-AGPIG - AGPIG
GIPSA-DIS - Département Images et Signal
Abstract : Perceptual quality assessment of 3D triangular meshes is crucial for a variety of applications. In this paper, we present a new objective metric for assessing the visual difference between a reference triangular mesh and its distorted version produced by lossy operations such as noise addition, simplification, compression and watermarking. The proposed metric is based on the measurement of a distance between curvature tensors of the two meshes under comparison. Our algorithm uses not only tensor eigenvalues (i.e., curvature amplitudes) but also tensor eigenvectors (i.e., principal curvature directions) to derive a perceptually-oriented tensor distance. The proposed metric also accounts for the visual masking effect of the human visual system, through a roughness-based weighting of the local tensor distance. A final score that reflects the visual difference between two meshes is obtained via a Minkowski pooling of the weighted local tensor distances over the mesh surface. We validate the performance of our algorithm on four subjectively-rated mesh visual quality databases, and compare the proposed method with state-of-the-art objective metrics. Experimental results show that our approach achieves high correlation between objective scores and subjective assessments.
Type de document :
Article dans une revue
Machine Graphics & Vision, 2014, pp.1-25
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https://hal.archives-ouvertes.fr/hal-00995716
Contributeur : Kai Wang <>
Soumis le : vendredi 23 mai 2014 - 16:39:55
Dernière modification le : mercredi 17 juin 2015 - 01:14:35

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  • HAL Id : hal-00995716, version 1

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Fakhri Torkhani, Kai Wang, Jean-Marc Chassery. A curvature-tensor-based perceptual quality metric for 3D triangular meshes. Machine Graphics & Vision, 2014, pp.1-25. <hal-00995716>

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