全规整重网格化三维模型的压缩

Mesh Compression by Uniform Resampling

通过保形自适应重采样,可将三维网格模型转化为规则排列的二维几何图像,从而可借鉴成熟的图像压缩技术对其进行压缩.提出了保形自适应采样算法,根据网格模型表面的有效顶点分布密度自适应地调整采样网格,并可最大限度地通过原始网格顶点进行采样.在不增加采样率的前提下,该压缩方法所得解压模型具有更小的失真度.通过大量实例对文中方法进行了验证,并与同类方法进行对比.实验结果表明该方法是切实可行的,且具有更好的压缩效果.

The 3D mesh model is transformed into geometric image by adaptive shape-preserving resampling, and compressed using the image processing technique. An adaptive shape-preserving resampling algorithm is presented, which adaptively optimizes the sampling planar mesh according to the valid vertex density of the original mesh surface, and the sampling points get across the original vertex to the greatest extent. The compression result achieves high fidelity without increasing the sampling rate. Some examples are used to compare the proposed and the similar method, which shows that our method is feasible and has excellent performance.