Full-Reference Objective Quality Metric for Three-Dimensional Deformed Models

Abstract

Three-dimensional data are generally represented by triangular meshes. The 3D data are used in several fields including remote 3D games, 3D medical application, 3D virtual worlds and 3D augmented reality application. These applications require displaying, printing or exchanging the 3D models through the network to optimize the rendering of the 3D models and 3D applications, which include different treatments, for example, smoothing, compression, re-meshing, simplification, watermarking, etc. However, these processes generate distortions that affect the quality of the rendered 3D data. Thus, subjective or objective metrics are required for assessing the visual quality of the deformed models to evaluate the efficiency of the applied algorithms. In this context, we introduce a new perceptual full-reference metric that compare two 3D meshes based on their 3D content information. The proposed metric integrates the relativity and selectivity properties of the Human visual system (HVS) independent of the mesh type and connectivity (e.g. Triangular, Quadrilateral, Tetrahedron, Hexahedron), which represent a limit in the existing method, in order to capture the perceptual quantity of the distortion by the observer. The results of the proposed approach outperform the existing metrics and have a high correlation with the subjective measures. We use the two correlation coefficients Spearman Rank ([Formula: see text]) and Pearson Rank (Rp) in order to assess the performance of the proposed metric.