Mesh saliency is a measure that attempts to capture the importance of a point or local region on a 3D surface mesh in a similar way to human visual perception. The human perceptual system is able to detect visual saliency extraordinarily quickly and reliably, even for novel scenes. The term “saliency” is often considered in the context of bottom-up computations. However, development of bottom-up computational models which simulate this basic intelligent behaviour remains a profound challenge in computer vision and graphics.
Mesh saliency detection methods usually merge perceptual criteria inspired by low-level human visual cues with mathematical measures based on discrete differential geometry, such as curvatures. Overall, however, saliency must efficiently and effectively reflect perceptually important regions on a 3Dmesh, which curvature alone may not capture. While mesh saliency may not outperform mesh curvature as a surface analysis tool in all applications, it provides an alternative approach when processing 3D meshes, based on perceptual mechanisms rather than purely local geometric measures of shape.