Exploring The Efficiency Of Image Metric For Assessing The Visual Quality Of 3d Mesh Model

Recent developments in 3D graphics technology have led to extensive processes on 3D meshes (e.g., compression, simplification, transmission and watermarking), these processes unavoidably cause the visual perceptual degradation of the 3D objects. The existing mesh visual quality evaluation metrics either require topology constrain or fail to reflect the perceived visual quality. Meanwhile, for the 3D objects that are observed on 2D screens by the users, it is reasonable to apply image metric to assess the distortion caused by mesh simplification. We attempt to explore the efficiency of image metric for assessing the visual fidelity of the simplified 3D model in this paper. For this purpose, several latest and most effective image metrics, 2D snapshots, number and pooling algorithms are involved in our study, and finally tested on the IEETA simplification database. The statistical data allow the researcher to select the optimal parameter for this image-based mesh visual quality assessment and provide a new perspective for the design and performance assessment of mesh simplification algorithms.