基于3维数字模型的显著性度量和显著域处理技术，提出一种模型显著域上的形状调控和处理方法。该方法首先基于曲面上采样顶点处局部投影高度的Gaussian加权平均双边滤波定义数字模型的表面显著性；然后利用定义在模型显著域上的形状调控函数——显著域低通形状调控函数、显著域高通形状调控函数和显著域增强形状调控函数，使模型的显著特征得到有效抑制、提升和增强，实现了针对模型表面显著特征的形状调控和处理。实验结果表明，该方法能够方便快速地实现3维数字模型的不同形状造型效果。

Owing to the perceptual-saliency measure and saliency-domain shape modeling techniques, a novel shape manipulation scheme is presented to adjust the visually salient features of 3D models. The perceptual-saliency measure for 3D models is introduced, which is defined by a center-surround bilateral filter operator on Gaussian-weighted averages of local projection heights between mesh vertices and their neighbors. The geometric features of the underlying shapes can then be filtered by low-pass filters, high-pass filters, and other enhancements due to the user specified shape manipulation functions defined on the saliency-domain, that is, the low-pass shape manipulation, the high-pass shape manipulation and the enhancement shape manipulation. The experimental results show that it is easy and efficient to achieve different shape modeling results with our proposed technique.