3D GEOMETRY REPRESENTATION USING MULTIVIEW CODING OF IMAGE TILES

Compression of dynamic 3D geometry obtained from depth sensors is challenging, because noise and temporal inconsis-tency inherent in acquisition of depth data means there is no one-to-one correspondence between sets of 3D points in con-secutive time instants. In this paper, instead of coding 3D points (or meshes) directly, we propose to represent an ob-ject’s 3D geometry as a collection of tile images. Specifically, we first place a set of image tiles around an object. Then, we project the object’s 3D geometry onto the tiles that are inter-preted as 2D depth images, which we subsequently encode using a modified multiview image codec tuned for piecewise smooth signals. The crux of the tile image framework is the “optimal ” placement of image tiles—one that yields the best tradeoff in rate and distortion. We show that if only planar and cylindrical tiles are considered, then the optimal place-ment problem for K tiles can be mapped to a tractable piece-wise linear approximation problem. We propose an efficient dynamic programming algorithm to find an optimal solution to the piecewise linear approximation problem. Experimen-tal results show that optimal tiling outperforms naı̈ve tiling by up to 35 % in rate reduction, and graph transform can further exploit the smoothness of the tile images for coding gain. Index Terms — 3D geometry compression, multiview im-age coding 1