Abstract

We propose a novel method for detecting mesh saliency, a perceptuallybased
measure of the importance of a local region on a 3D surface mesh.
Our method incorporates global considerations by making use of spectral
attributes of the mesh, unlike most existing methods which are typically
based on local geometric cues. We first consider the properties of the log-
Laplacian spectrum of the mesh. Those frequencies which show differences
from expected behaviour capture saliency in the frequency domain. Information
about these frequencies is considered in the spatial domain at multiple
spatial scales to localise the salient features and give the final salient
areas. The effectiveness and robustness of our approach are demonstrated
by comparisons to previous approaches on a range of test models. The benefits
of the proposed method are further evaluated in applications such as
mesh simplification, mesh segmentation and scan integration, where we
show how incorporating mesh saliency can provide improved results.