Three-dimensional mesh quality metric with reference based on a support vector regression model

Three-dimensional (3-D) meshing has become a commonly used tool in several computer vision applications. As the performance of these applications depends highly on the quality of the meshes, several methods have been proposed in the literature to quantify mesh quality. We propose a 3-D mesh quality measure based on the fusion of some selected features. The goal here is to improve the global performance of the quality assessment process by taking into account the advantages of these features. The fusion step was achieved using a support vector regression model. The method was evaluated in terms of correlation with subjective judgments using two well-known databases. The results obtained show the relevance of the proposed approach. (C) 2018 SPIE and IS&T