Abstract
This paper provides an overview of the state-of-the-art techniques recently developed within the emerging field of dynamic mesh compression. Static encoders, wavelet-based schemes, PCA-based approaches, differential temporal and spatio-temporal predictive techniques, and clustering-based representations are considered, presented, analyzed, and objectively compared in terms of compression efficiency, algorithmic and computational aspects and offered functionalities (such as progressive transmission, scalable rendering, computational and algorithmic aspects, field of applicability...).
The proposed comparative study reveals that: (1) clustering-based approaches offer the best compromise between compression performances and computational complexity; (2) PCA-based representations are highly efficient on long animated sequences (i.e. with number of mesh vertices much smaller than the number of frames) at the price of prohibitive computational complexity of the encoding process; (3) Spatio-temporal Dynapack predictors provides simple yet effective predictive schemes that outperforms simple predictors such as those considered within the interpolator compression node adopted by the MPEG-4 within the AFX standard; (4) Wavelet-based approaches, which provide the best compression performances for static meshes show here again good results, with the additional advantage of a fully progressive representation, but suffer from an applicability limited to large meshes with at least several thousands of vertices per connected component.
