Scalable Point Cloud Geometry Coding with Binary Tree Embedded Quadtree

Many applications of point cloud have recently been identified in automobile navigation system, visual communication, and so on. However, the huge data size of point cloud has been a bottleneck for the practical implementations. In this paper, we present a compression scheme that utilizes variable-rate coding of a same point cloud data at different quality. Point cloud is encoded at fixed-rate for highest representation. Encoder, however, can present variable-rate encoded data for any lowest to highest representation to decoder which is then decoded to reconstruct point cloud at different quality. Variable-rate encoding is achieved through the so-called binary tree quadtree (BTQT) scheme. The BTQT scheme made the compression more effective by dividing point cloud frame into blocks using binary-tree and encoding flat surfaces in the blocks by quadtree and non-flat surfaces by octree. Simulation results show that scalable coding solution can efficiently compress point cloud data at variable rate compensating the quality.