Dynamic 3-D facial compression using low rank and sparse decomposition
SIGGRAPH Asia 2012 Technical Briefs
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Generation and transmission of complex animation sequences can benefit substantially from the availability of tools for handling large amounts of data associated with dynamic three-dimensional (3-D) models. Previous works in 3-D dynamic compression consider only the simplest situation where the connectivity changes do not occur with time. In this paper, we present an approach for compressing 3-D dynamic models in which both the vertex data and the connectivity data can change with time. Using our framework, 3-D animation sequences generated using commercial graphics tools or dynamic range data captured using range scanners can be compressed significantly. We use 3-D registration to identify the changes in the vertex data and the connectivity of the 3-D geometry between successive frames. Next, the interframe motion is encoded using affine motion parameters and the differential pulse coded modulation (DPCM) predictor. Our work is the first to exploit the temporal coherence in the connectivity data between frames and presents a detailed encoding scheme for 3-D dynamic data. We also discuss the issue of inserting I-frames in the compressed data for better performance. We show that our algorithm has a far superior performance when compared with existing techniques for both vertex compression and connectivity compression of 3-D dynamic datasets.