Fast Video-Based Point Cloud Compression Based on Early Termination and Transformer Model

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Abstract
Video-based Point Cloud Compression (V-PCC) was proposed by the Moving Picture Experts Group (MPEG) to standardize Point Cloud Compression (PCC). The main idea of V-PCC is to project the Dynamic Point Cloud (DPC) into auxiliary information, occupancy, geometry, and attribute videos for encoding utilizing High Efficiency Video Coding (HEVC), Versatile Video Coding (VVC), etc. Compared with the previous PCC algorithms, V-PCC has achieved a significant improvement in compression efficiency. However, it is accompanied by substantial computational complexity. To solve this problem, this paper proposes a fast V-PCC method to decrease the coding complexity. Taking into account the coding characteristic of V-PCC, the geometry and attribute maps are first classified into occupied and unoccupied blocks. Moreover, we analyze Coding Unit (CU) splitting for geometry and attribute map. Finally, we propose fast V-PCC algorithms based on early termination algorithm and transformer model, in which the early termination method is proposed for low complexity blocks in the geometry and attribute map, and the transformer model-based fast method is designed to predict the optimal CU splitting modes for the occupied block of the attribute map. The proposed algorithms are implemented with typical DPC sequences on the Test Model Category 2 (TMC2). The experimental results imply that the average time of the proposed method can significantly reduce 56.39% and 55.10% in the geometry and attribute map, respectively, with negligible Bjontegaard-Delta bitrate (BD-rate) compared with the anchor method.
Funding Information
  • National Natural Science Foundation of China (61671283, U2033218)

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