Combining visual relevance criteria into adaptive mesh simplification techniques

A wide range of simplification techniques for 3D meshes may take advantage of the limitations of the human visual system by concentrating computational resources in those regions where the user´s attention will focus most often. Some of those visually outstanding regions may be extracted by means of an automatic visual attention model. Additionally, there are some features that are known to have a high impact in the quality perceived by our visual system, as for example the silhouettes. The goal of this paper is to present the feasibility of combining different perceptual criteria into a set of labels that encode the importance of mesh elements according to their distance to relevant regions. These regions may have been independently extracted by applying different criteria in preprocessing time. The combination of the perceptual criteria is parameterizable, allowing to vary their relative importance. Moreover, the possibility of performing this combination in real time allows to adapt the regions of attention to the visualization conditions.