Dirichlet Harmonic Shape Compression with Feature Preservation for Parameterized Surfaces

With the rapid advancement of 3D scanning devices, large and complicated 3D shapes are becoming ubiquitous, and require large amount of resources to store and transmit them efficiently. This makes shape compression a demanding technique in order for the user to reduce the data transmission latency. Existing shape compression methods could achieve very low bit-rates by sacrificing shape quality. But none of them guarantees the preservation of salient feature lines that users care. In addition, many 3D shapes come with parametric information for texture mapping purposes. In this paper we describe a spectral method to compress the geometric shapes equipped with arbitrary valid parametric information. It guarantees to preserve user-specified feature lines while achieving a high compression ratio. By applying the spectral shape analysis – Dirichlet Manifold Harmonics, in the 2D parametric domain, this method provides a progressive compression mechanism to trade-off between bit-rate and shape quality. Experiments show that this method provides very low bit-rate with high shape-quality and still guarantees the preservation of user-specified feature lines.