2018 IEEE International Conference on Multimedia and Expo (ICME)
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Abstract

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.
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