Chain Code-Based Occupancy Map Coding for Video-Based Point Cloud Compression

被引:2
作者
Yang, Runyu [1 ]
Yan, Ning [1 ]
Li, Li [1 ]
Liu, Dong [1 ]
Wu, Feng [1 ]
机构
[1] Univ Sci & Technol China, CAS Key Lab Technol Geospatial Informat Proc & Ap, Hefei 230027, Peoples R China
来源
2020 IEEE INTERNATIONAL CONFERENCE ON VISUAL COMMUNICATIONS AND IMAGE PROCESSING (VCIP) | 2020年
关键词
arithmetic coding; chain coding; occupancy map; quadtree-based partition; semantic map; video-based point cloud compression;
D O I
10.1109/vcip49819.2020.9301867
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In video-based point cloud compression (V-PCC), occupancy map video is utilized to indicate whether a 2-D pixel corresponds to a valid 3-D point or not. In the current design of V-PCC, the occupancy map video is directly compressed losslessly with High Efficiency Video Coding (HEVC). However, the coding tools in HEVC are specifically designed for natural images, thus unsuitable for the occupancy map. In this paper, we present a novel quadtree-based scheme for lossless occupancy map coding. In this scheme, the occupancy map is firstly divided into several coding tree units (CTUs). Then, the CTU is divided into coding units (CUs) recursively using a quadtree. The quadtree partition is terminated when one of the three conditions is satisfied. Firstly, all the pixels have the same value. Secondly, the pixels in the CU only have two kinds of values and they can be separated by a continuous edge whose endpoints lie on the side of the CU. The continuous edge is then coded using chain code. Thirdly, the CU reaches the minimum size. This scheme simplifies the design of block partitioning in HEVC and designs simpler yet more effective coding tools. Experimental results show significant reduction of bit-rate and complexity compared with the occupancy map coding scheme in V-PCC. In addition, this scheme is also very efficient to compress the semantic map.
引用
收藏
页码:479 / 482
页数:4
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