Los puntos clave no están disponibles para este artículo en este momento.
Compression of 3D time-varying meshes (TVMs) plays a critical role in the storage and transmission of 3D contents. In this paper, we propose a novel framework for compressing 3D TVMs. In our framework, 3D TVMs are parameterized and represented by the geometry videos (GVs) through polycube parameterization. By considering the low-rank characteristic of dynamic meshes, we decompose GVs into a sequence with small frames namely EigenGV and the computed reconstruction matrix. We further apply 2D video encoder to eliminate spatial and temporal redundancy among the EigenGV. Experimental results demonstrate that the proposed method significantly outperforms the existing compression schemes in terms of both the rate distortion performance and visual quality. Besides, the proposed method naturally achieves progressive form, which is very suitable for error prone channel transmission.
Hou et al. (Sun,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: